This paper presents an analysis and design of linear quadratic regulator for reduced order full car suspension model incorporating the dynamics of the actuator to improve system performance, aims at benefiting: Ride comfort, long life of vehicle, and stability of vehicle. Vehicleโs road holding or handling and braking for good active safety and driving pleasure and keeping vehicle occupants comfortable and reasonably well isolated from road noise, bumps, and vibrations are become a key research area conducted by many researchers around the globe. Different researchers were tested effectiveness of different controllers for different vehicle model without considering the actuator dynamics. In this paper full vehicle model was reduced to a minimal order using minimal realization technique. The entire system responses were simulated in MATLAB/Simulink environment. The effectiveness of linear quadratic regulator controller was compared for the system model with and without actuator dynamics for different road profiles. The simulation results were indicated that percentage reduction in the peak value of vertical and horizontal velocity for the linear quadratic regulator with actuator dynamics relative to linear quadratic regulator without actuator dynamics was 28.57%. Overall simulation results were demonstrated that proposed control scheme has able to improve the effectiveness of the car model for both ride comfort and stability.
Linear Control Technique for Anti-Lock Braking SystemIJERA Editor
ย
Antilock braking systems are used in modern cars to prevent the wheels from locking after brakes are applied. The dynamics of the controller needed for antilock braking system depends on various factors. The vehicle model often is in nonlinear form. Controller needs to provide a controlled torque necessary to maintain optimum value of the wheel slip ratio. The slip ratio is represented in terms of vehicle speed and wheel rotation.
In present work first of all system dynamic equations are explained and a slip ratio is expressed in terms of system variables namely vehicle linear velocity and angular velocity of the wheel. By applying a bias braking force system, response is obtained using Simulink models. Using the linear control strategies like PI-type the effectiveness of maintaining desired slip ratio is tested. It is always observed that a steady state error of 10% occurring in all the control system models.
Fuzzy rules incorporated skyhook theory based vehicular suspension design for...IJERA Editor
ย
The vehicle suspension system supports and isolate the vehicle body and payload from road vibrations due to surface roughness by maintaining a controllable damping traction force between tires and road surface. In modern luxury vehicles semi active suspension system are offering both the reliability and accuracy that has enhanced the passenger ride comfort with less power demand. In this paper we have proposed the design of a hybrid control system having a combination of skyhook theory with fuzzy logic control and applied on a semi-active vehicle suspension system for its ride comfort enhancement. A two degree of freedom dynamic model is simulated using Matlab/Simulink for a vehicle equipped with semi-active suspension system with focused on the passengerโs ride comfort performance.
This document discusses the development of an Active Idle Stop (AIS) system for vehicles to improve performance when driving uphill. The AIS system is intended to address issues with deceleration and rollback that occur when vehicles stop and restart on inclines. A proportional-integral-derivative (PID) controller is used with a nonlinear vehicle longitudinal model and genetic algorithm to optimize controller parameters. Simulation results show the AIS system can significantly reduce deceleration and minimize rollback when driving uphill.
This document summarizes a study on developing a wheel slip control system for an electric vehicle to improve traction and energy efficiency during acceleration. The study proposes a sliding mode controller and vehicle velocity estimator. Simulations using CarSim software and experiments on a test electric vehicle equipped with in-wheel motors validate that the control system enhances traction performance and reduces energy consumption compared to uncontrolled acceleration. The robust wheel slip controller and practical vehicle velocity estimation approach make use of the advantages of electric vehicle drivetrains for improved acceleration control.
The document proposes a wheel slip control system using a sliding mode controller to improve traction and energy efficiency for electric vehicles. It describes developing a sliding mode controller and vehicle velocity estimator to actively control driving wheels and prevent wheel spin. Simulation and experimental results using an electric vehicle with in-wheel motors demonstrate the effectiveness of the proposed traction control system in improving performance and reducing energy consumption during acceleration.
Effect of Rack Friction, Column Friction and Vehicle Speed on Electric Power ...IRJET Journal
ย
This document describes a study on the effect of rack friction, column friction, and vehicle speed on the electric power steering (EPS) system of a vehicle. A complete wheel-to-wheel steering model is developed in Amesim simulation software, including all associated components. With the validated model, the variation of total torque required at the pinion gear is plotted at different vehicle speeds from 0 to 160 kmph. The friction torque at the column, steering rack, and motor is also plotted to understand how it changes over time for a given steering angle input and vehicle speed. The results are analyzed to develop an understanding of how the components in the steering system interact so that the necessary power can be requested from the system without compromising
Control systems project report (180501008)(180501016)(180501018)(180501020)khang31
ย
A cruise control system for an electric vehicle has been modeled in MATLAB Simulink. A PI controller controls torque and a PID controller controls speed. The effect of the controllers and different inputs were analyzed. With both controllers, the system became stable, while it was unstable with no controllers. Step, ramp, and sine wave inputs all stabilized. Key parameters like peak time, rise time, and settling time were calculated from the output.
IRJET- Vibration and Suspension Deflection Controlling of Half Car Model usin...IRJET Journal
ย
This document summarizes a study on controlling vibration and suspension deflection of a half car model using ANSYS and MATLAB. A half car model with independent front and rear passive suspensions is implemented in MATLAB Simulink to simulate the reaction forces from the front and rear wheels. Vibration analysis is performed with and without a tune mass damper. The objectives are to analyze the ride characteristics, natural frequency, and harmonic response of the half car model, and reduce vibration using tune mass dampers. Simulation results show that vehicle displacement and pitch decrease with increasing vehicle speed. Natural frequency is identified as 1.955 Hz and vibration is reduced by 11% with the addition of tune mass dampers.
Linear Control Technique for Anti-Lock Braking SystemIJERA Editor
ย
Antilock braking systems are used in modern cars to prevent the wheels from locking after brakes are applied. The dynamics of the controller needed for antilock braking system depends on various factors. The vehicle model often is in nonlinear form. Controller needs to provide a controlled torque necessary to maintain optimum value of the wheel slip ratio. The slip ratio is represented in terms of vehicle speed and wheel rotation.
In present work first of all system dynamic equations are explained and a slip ratio is expressed in terms of system variables namely vehicle linear velocity and angular velocity of the wheel. By applying a bias braking force system, response is obtained using Simulink models. Using the linear control strategies like PI-type the effectiveness of maintaining desired slip ratio is tested. It is always observed that a steady state error of 10% occurring in all the control system models.
Fuzzy rules incorporated skyhook theory based vehicular suspension design for...IJERA Editor
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The vehicle suspension system supports and isolate the vehicle body and payload from road vibrations due to surface roughness by maintaining a controllable damping traction force between tires and road surface. In modern luxury vehicles semi active suspension system are offering both the reliability and accuracy that has enhanced the passenger ride comfort with less power demand. In this paper we have proposed the design of a hybrid control system having a combination of skyhook theory with fuzzy logic control and applied on a semi-active vehicle suspension system for its ride comfort enhancement. A two degree of freedom dynamic model is simulated using Matlab/Simulink for a vehicle equipped with semi-active suspension system with focused on the passengerโs ride comfort performance.
This document discusses the development of an Active Idle Stop (AIS) system for vehicles to improve performance when driving uphill. The AIS system is intended to address issues with deceleration and rollback that occur when vehicles stop and restart on inclines. A proportional-integral-derivative (PID) controller is used with a nonlinear vehicle longitudinal model and genetic algorithm to optimize controller parameters. Simulation results show the AIS system can significantly reduce deceleration and minimize rollback when driving uphill.
This document summarizes a study on developing a wheel slip control system for an electric vehicle to improve traction and energy efficiency during acceleration. The study proposes a sliding mode controller and vehicle velocity estimator. Simulations using CarSim software and experiments on a test electric vehicle equipped with in-wheel motors validate that the control system enhances traction performance and reduces energy consumption compared to uncontrolled acceleration. The robust wheel slip controller and practical vehicle velocity estimation approach make use of the advantages of electric vehicle drivetrains for improved acceleration control.
The document proposes a wheel slip control system using a sliding mode controller to improve traction and energy efficiency for electric vehicles. It describes developing a sliding mode controller and vehicle velocity estimator to actively control driving wheels and prevent wheel spin. Simulation and experimental results using an electric vehicle with in-wheel motors demonstrate the effectiveness of the proposed traction control system in improving performance and reducing energy consumption during acceleration.
Effect of Rack Friction, Column Friction and Vehicle Speed on Electric Power ...IRJET Journal
ย
This document describes a study on the effect of rack friction, column friction, and vehicle speed on the electric power steering (EPS) system of a vehicle. A complete wheel-to-wheel steering model is developed in Amesim simulation software, including all associated components. With the validated model, the variation of total torque required at the pinion gear is plotted at different vehicle speeds from 0 to 160 kmph. The friction torque at the column, steering rack, and motor is also plotted to understand how it changes over time for a given steering angle input and vehicle speed. The results are analyzed to develop an understanding of how the components in the steering system interact so that the necessary power can be requested from the system without compromising
Control systems project report (180501008)(180501016)(180501018)(180501020)khang31
ย
A cruise control system for an electric vehicle has been modeled in MATLAB Simulink. A PI controller controls torque and a PID controller controls speed. The effect of the controllers and different inputs were analyzed. With both controllers, the system became stable, while it was unstable with no controllers. Step, ramp, and sine wave inputs all stabilized. Key parameters like peak time, rise time, and settling time were calculated from the output.
IRJET- Vibration and Suspension Deflection Controlling of Half Car Model usin...IRJET Journal
ย
This document summarizes a study on controlling vibration and suspension deflection of a half car model using ANSYS and MATLAB. A half car model with independent front and rear passive suspensions is implemented in MATLAB Simulink to simulate the reaction forces from the front and rear wheels. Vibration analysis is performed with and without a tune mass damper. The objectives are to analyze the ride characteristics, natural frequency, and harmonic response of the half car model, and reduce vibration using tune mass dampers. Simulation results show that vehicle displacement and pitch decrease with increasing vehicle speed. Natural frequency is identified as 1.955 Hz and vibration is reduced by 11% with the addition of tune mass dampers.
Modeling, Simulation and Body Height Adjustment Control of Full Car Laterally...IRJESJOURNAL
ย
Abstract:- In this paper, the working principles, the dynamic performance, and the static characteristics of full car interconnected air suspension are investigated and verified using established real physical test benches and simulations. Also, the physical and mathematical models of the suspension are established to help study the vehicleโs roll, pitch, bounce and other relevant motions. PID and Fuzzy controllers are built using matlab/simulink to simulate and control the body vertical height adjustment of the interconnected air suspension. Two two-dimensional fuzzy controllers are applied respectively to control the front and rear air springs. To improve height adjustment precision, a target height of 20 mm is used as input to the front controller; while the actual body height in front air spring is used as an input to the rear controller. The results of the simulation clearly demonstrate that compared with the open-loop switch control, PID and fuzzy controllers are found to effectively suppress the overshoot during the process of body height adjustment. Again, by setting the front wheels as the target height, the designed controllers quickly and accurately adjust body height to the target height and significantly stabilized and improved the performance of the system as compared to the openloop switch control.
This document summarizes a report on an active suspension system for a vehicle using fuzzy logic control. It begins with an abstract describing the goals of improving ride comfort while maintaining road handling ability. It then provides an introduction describing typical suspension systems and the limitations of passive systems. The literature review summarizes several papers on using fuzzy logic control and other control methods to model and simulate active suspension systems with the aim of improving ride quality and stability. Finally, a case study problem statement outlines using an active force control strategy with a quarter car model to reduce sprung mass motion and improve comfort and road handling capability.
MODELLING SIMULATION AND CONTROL OF AN ACTIVE SUSPENSION SYSTEM IAEME Publication
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Conventional passive suspension systems lag in providing the optimum level of performance. Passive suspensions are a trade-off between the conflicting demands of comfort and control. An active suspension system provides both comfort and control along with active roll and pitch control during cornering and braking. Thus it gives a ride that is level and bump free over an incredibly rough terrain. This paper is a review the active suspension system and the modelling, simulation and control of an active suspension system in MATLAB/Simulink. The performance of the system is
determined by computer simulation in MATLAB/Simulink. The performance of the system can be controlled and improved by proper tuning a proportional-integral-derivative (PID) controller.
Modelling simulation and control of an active suspension systemIAEME Publication
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The document discusses modeling, simulation, and control of an active suspension system in MATLAB/Simulink. An active suspension system provides both comfort and control during driving maneuvers through the use of linear electromagnetic motors (LEMs), sensors, and a power amplifier. The performance of the active suspension system is determined through computer simulation in MATLAB/Simulink. A proportional-integral-derivative (PID) controller is used to control and improve the system performance. The simulation shows the effectiveness of this control approach and that the active suspension system provides better performance than a conventional passive suspension system.
IRJET- Experimental Analysis of Passive/Active Suspension SystemIRJET Journal
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This document presents an experimental analysis comparing the performance of passive and active suspension systems using a quarter car model. A quarter car model with two degrees of freedom was created using masses, springs, and dampers to simulate the sprung and unsprung components of a vehicle. Experimental tests were conducted using this physical model, with and without active control via a PID controller. The results showed that with active control, displacements were reduced to 600-900 ฮผm and accelerations were reduced to 1-3 m/s2, compared to 5-10 mm and 14-20 m/s2 respectively for the passive system. Graphs of the experimental data further demonstrated that the active suspension provided better vibration isolation than the passive system. In
This document presents an adaptive sliding-mode (ASM) controller for a vehicle steer-by-wire (SbW) system. It models the SbW system as a second-order system and regards self-aligning torque and friction as external disturbances. An ASM controller is designed that can estimate the coefficient of self-aligning torque and handle parametric uncertainties. Experiments show the ASM controller achieves better tracking of a slalom path and circular path than a sliding-mode controller or H-infinity controller under various road conditions.
Mathematical Modeling and Simulation of Two Degree of Freedom Quarter Car Modelijsrd.com
ย
The proposed study is to develop an active suspension system to increase the comfort for the passenger by reducing the body acceleration. The dynamic quarter car suspension system is considered for mathematical modelling and simulation is carried using MATLAB SIMULINK. The present suspension system is controlled by Proportional- Integral -Derivative controller. The system performance is analysed using the single speed bump road surface and the effectiveness is evaluated with active and passive controlled systems.
Modelling simulation and control of an active suspension systemIAEME Publication
ย
This document discusses the modeling, simulation, and control of an active suspension system in MATLAB/Simulink. It begins by describing conventional passive and semi-active suspension systems, noting their tradeoffs between comfort and control. It then introduces active suspension systems, which can adjust their dynamics in real-time to provide both comfort and control. The document outlines modeling an active suspension system using a quarter car test setup and sensors to measure displacement, acceleration, and velocity. It describes using a linear electromagnetic motor actuated by a power amplifier and controlled via a PID controller to counteract road forces and keep the vehicle stable. The performance of the active suspension is simulated in MATLAB/Simulink and compared to a passive system.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Latest Transmission Technologies In Passenger Cars- A ReviewIRJET Journal
ย
This document reviews latest transmission technologies in passenger cars. It discusses the history and purpose of transmission systems, including manual and automatic transmissions. The key points covered include:
- Automatic transmissions provide more convenience than manual transmissions by shifting gears automatically, but are less fuel efficient due to losses in the torque converter and hydraulic actuators.
- Electronic control transmissions (ECT) use sensors and an electronic control unit to control shifting instead of a hydraulic system. This allows for smoother gear changes.
- The electronic control unit programs optimal shift patterns and controls transmission components like solenoid valves, shift valves, and the lock-up clutch based on vehicle speed and throttle position sensor inputs.
- Dri
IRJET- Experimental Analysis and Topology Optimization of Lower Suspension Ar...IRJET Journal
ย
This document presents an analysis of the lower control arm of a car's suspension system. It begins with an introduction to suspension systems and the role of the lower control arm. Finite element analysis is then used to model and analyze the stresses and deformation on the original lower control arm design. Topology optimization is performed to reduce the weight by 15% while maintaining structural integrity. Modal analysis shows the optimized design has slightly higher stresses but a reduced weight of 2.2kg compared to the original 2.6kg. Experimental testing of the optimized part validated the finite element analysis results.
This paper present a speed hybrid fuzzy-sliding mode control (HFSMC) of a permanent magnet synchronous motor (PMSM) to ensure the traction of an electric vehicle; at the first we applied the sliding mode control (SMC) with three surfaces on the PMSM by taking into account the dynamics of the vehicle; And afterwards we applied the fuzzy-sliding mode in which the surface of the speed is replaced by a Fuzzy-PI controller; Simulation under Matlab/Simulink has been carried out to evaluate the efficiency and robustness of the proposed control on a system drive. It should be noted that the reference speed is the European urban driving schedule ECE-15 cycle.
Presentation on Modeling and Simulation of (1).pptxMBSIXTEEN
ย
This presentation summarizes a project on modeling and simulating a semi-active suspension system. The project aims to design a suspension that can electronically adjust damping forces in response to road conditions to enhance stability, safety, and ride comfort. The team will develop a mathematical model, run simulations in MATLAB Simulink, and iterate on the design to optimize performance. A literature review covered research on using magnetorheological dampers and PID controllers to improve suspension. The methodology outlines forming models, parameters, simulations, analysis, and iterations. Tasks are scheduled on a Gantt chart. In conclusion, suspension systems have advanced significantly and this project will demonstrate and refine the performance of a semi-active system.
IRJET- Generation of Alternative Solutions for Differential-Less Drive Sys...IRJET Journal
ย
1) The document discusses potential alternative solutions to differentials in vehicle drive systems to address limitations like getting stuck when one wheel encounters an obstacle.
2) It presents 4 conceptual designs for differential-less drive systems, including ones using separate engines for each front wheel, hydraulic motors for each rear wheel, program-controlled variable speed motors for all wheels, and a mechanical system that can disengage one wheel during turns.
3) The concepts are evaluated against criteria like reliability, speed range, cost, versatility, and sensitivity, and the mechanical system is identified as the highest ranking concept warranting further development as a differential-less drive system.
Comparison of active and semi active suspension systems using robust controllerMustefa Jibril
ย
1. The document compares active and semi-active suspension systems using robust H-infinity controllers. Mathematical models of quarter car active and semi-active suspension systems are developed.
2. Simulation results show that the active suspension system with H-infinity controller decreases body acceleration and maintains suspension deflection and body travel outputs, proving its effectiveness over the semi-active system.
3. Numerical results confirm that the active suspension system provides minimum body travel and acceleration amplitudes, while matching the suspension deflection to the road profile, achieving the control targets.
Comparison of active and semi active suspension systems using robust controllerMustefa Jibril
ย
1) The document compares active and semi-active suspension systems for a quarter car model using robust H-infinity control.
2) Mathematical models are developed and simulations are run with random and sine road disturbances to evaluate body travel, acceleration, and suspension deflection.
3) The results show that the active suspension system with H-infinity controller is most effective at decreasing body acceleration and maintaining suspension deflection matching the road profile, proving its advantages over the semi-active system.
This document describes a simulation study of a vehicle model with four independent electric motors and active anti-roll bars on both axles. The vehicle model is composed of sub-models for the vertical dynamics, horizontal dynamics, and tire model. Simulation results show that coordinated control of the electric drive train and active suspension components can improve the vehicle's ride, stability, and handling. A complex cascade controller using PID and fuzzy logic techniques governs the integrated system based on sensor data from the virtual vehicle model.
This document describes a computational model called the Vehicle Dynamic Model (VDM) that was developed to analyze the dynamic behavior of vehicles. The VDM allows users to define vehicle parameters and evaluate the vehicle's vertical response when traversing different track profiles. It provides four types of results: 1) steady state response, 2) frequency response curves, 3) animation of the vehicle running on a track profile, and 4) natural frequencies and vibration modes. The model accounts for components like tires, springs, dampers and vehicle geometry. It was tested using literature data and allows analyzing ride performance by changing parameters and checking the vehicle's response over different tracks.
SIMULTANEOUS OPTIMIZATION OF SEMIACTIVE QUARTER CAR SUSPENSION PARAMETERS USI...ijmech
ย
In present paper, a methodology is presented related to the optimization of semi-active quarter car model
suspension parameters having three degrees of freedom, subjected to bump type of road excitation.
Influence of primary suspension stiffness, primary suspension damping, secondary suspension stiffness and
secondary suspension damping are studied on the passenger ride comfort, taking root mean square (RMS)
values of passenger seat displacement and settling time into account. Semi-active quarter car model
assembled with magneto-rheological (MR) shock absorber is selected for optimization of suspension
parameters using Taguchi method in combination with Grey relational analysis. Confirmatory results with
simulation run indicates that the optimized results of suspension parameters are helpful in achieving the
best ride comfort to travelling passengers in terms of minimization of passenger seat displacement and
settling time values.
This paper presents the modeling and simulation of
a magnetorheological damper based semiactive suspension using
variable structure controllers. Passive suspension systems tend to
limit the trade-off between passenger comfort and road handling.
But Semiactive suspensions can reduce this trade-off margin and
dynamically respond to the damping requirements. Active
suspensions provide the best response since they can add damping
force in any direction, but are prone to higher power consumption.
Semiactive suspensions just change the damping coefficient by
simply applying a control voltage as and when required. The
performance of three controllers- sigma 1, sigma 2 and sigma 3,
are measured and analyzed using nine parameters using peak,
root mean square and normalized approaches. The road
excitations considered are a single road hump and random road
disturbance. The control system is applied to a 2-degree of
freedom quarter car model of a passenger car. A modified BoucWen
model of MR damper is used to cater to the system responses
at near zero velocities. The performance of these controllers is
superior to the uncontrolled case, which is similar to passive
suspension system. Sigma 3 controller is superior to the
uncontrolled system by 63% while sigma 1 and sigma 2 are
superior by 53% when it comes to peak suspension deflection for
a random road disturbance. Both sigma 2 and sigma 3 controllers
are better in terms of performance. The validation of the
semiactive suspension leads to selection of sigma 2 controller over
sigma 3 controller because of its simplicity in implementation in
real-time systems.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
ย
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the modelโs competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
ย
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
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Modeling, Simulation and Body Height Adjustment Control of Full Car Laterally...IRJESJOURNAL
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Abstract:- In this paper, the working principles, the dynamic performance, and the static characteristics of full car interconnected air suspension are investigated and verified using established real physical test benches and simulations. Also, the physical and mathematical models of the suspension are established to help study the vehicleโs roll, pitch, bounce and other relevant motions. PID and Fuzzy controllers are built using matlab/simulink to simulate and control the body vertical height adjustment of the interconnected air suspension. Two two-dimensional fuzzy controllers are applied respectively to control the front and rear air springs. To improve height adjustment precision, a target height of 20 mm is used as input to the front controller; while the actual body height in front air spring is used as an input to the rear controller. The results of the simulation clearly demonstrate that compared with the open-loop switch control, PID and fuzzy controllers are found to effectively suppress the overshoot during the process of body height adjustment. Again, by setting the front wheels as the target height, the designed controllers quickly and accurately adjust body height to the target height and significantly stabilized and improved the performance of the system as compared to the openloop switch control.
This document summarizes a report on an active suspension system for a vehicle using fuzzy logic control. It begins with an abstract describing the goals of improving ride comfort while maintaining road handling ability. It then provides an introduction describing typical suspension systems and the limitations of passive systems. The literature review summarizes several papers on using fuzzy logic control and other control methods to model and simulate active suspension systems with the aim of improving ride quality and stability. Finally, a case study problem statement outlines using an active force control strategy with a quarter car model to reduce sprung mass motion and improve comfort and road handling capability.
MODELLING SIMULATION AND CONTROL OF AN ACTIVE SUSPENSION SYSTEM IAEME Publication
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Conventional passive suspension systems lag in providing the optimum level of performance. Passive suspensions are a trade-off between the conflicting demands of comfort and control. An active suspension system provides both comfort and control along with active roll and pitch control during cornering and braking. Thus it gives a ride that is level and bump free over an incredibly rough terrain. This paper is a review the active suspension system and the modelling, simulation and control of an active suspension system in MATLAB/Simulink. The performance of the system is
determined by computer simulation in MATLAB/Simulink. The performance of the system can be controlled and improved by proper tuning a proportional-integral-derivative (PID) controller.
Modelling simulation and control of an active suspension systemIAEME Publication
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The document discusses modeling, simulation, and control of an active suspension system in MATLAB/Simulink. An active suspension system provides both comfort and control during driving maneuvers through the use of linear electromagnetic motors (LEMs), sensors, and a power amplifier. The performance of the active suspension system is determined through computer simulation in MATLAB/Simulink. A proportional-integral-derivative (PID) controller is used to control and improve the system performance. The simulation shows the effectiveness of this control approach and that the active suspension system provides better performance than a conventional passive suspension system.
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This document presents an experimental analysis comparing the performance of passive and active suspension systems using a quarter car model. A quarter car model with two degrees of freedom was created using masses, springs, and dampers to simulate the sprung and unsprung components of a vehicle. Experimental tests were conducted using this physical model, with and without active control via a PID controller. The results showed that with active control, displacements were reduced to 600-900 ฮผm and accelerations were reduced to 1-3 m/s2, compared to 5-10 mm and 14-20 m/s2 respectively for the passive system. Graphs of the experimental data further demonstrated that the active suspension provided better vibration isolation than the passive system. In
This document presents an adaptive sliding-mode (ASM) controller for a vehicle steer-by-wire (SbW) system. It models the SbW system as a second-order system and regards self-aligning torque and friction as external disturbances. An ASM controller is designed that can estimate the coefficient of self-aligning torque and handle parametric uncertainties. Experiments show the ASM controller achieves better tracking of a slalom path and circular path than a sliding-mode controller or H-infinity controller under various road conditions.
Mathematical Modeling and Simulation of Two Degree of Freedom Quarter Car Modelijsrd.com
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The proposed study is to develop an active suspension system to increase the comfort for the passenger by reducing the body acceleration. The dynamic quarter car suspension system is considered for mathematical modelling and simulation is carried using MATLAB SIMULINK. The present suspension system is controlled by Proportional- Integral -Derivative controller. The system performance is analysed using the single speed bump road surface and the effectiveness is evaluated with active and passive controlled systems.
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This document discusses the modeling, simulation, and control of an active suspension system in MATLAB/Simulink. It begins by describing conventional passive and semi-active suspension systems, noting their tradeoffs between comfort and control. It then introduces active suspension systems, which can adjust their dynamics in real-time to provide both comfort and control. The document outlines modeling an active suspension system using a quarter car test setup and sensors to measure displacement, acceleration, and velocity. It describes using a linear electromagnetic motor actuated by a power amplifier and controlled via a PID controller to counteract road forces and keep the vehicle stable. The performance of the active suspension is simulated in MATLAB/Simulink and compared to a passive system.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Latest Transmission Technologies In Passenger Cars- A ReviewIRJET Journal
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This document reviews latest transmission technologies in passenger cars. It discusses the history and purpose of transmission systems, including manual and automatic transmissions. The key points covered include:
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- Electronic control transmissions (ECT) use sensors and an electronic control unit to control shifting instead of a hydraulic system. This allows for smoother gear changes.
- The electronic control unit programs optimal shift patterns and controls transmission components like solenoid valves, shift valves, and the lock-up clutch based on vehicle speed and throttle position sensor inputs.
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This document presents an analysis of the lower control arm of a car's suspension system. It begins with an introduction to suspension systems and the role of the lower control arm. Finite element analysis is then used to model and analyze the stresses and deformation on the original lower control arm design. Topology optimization is performed to reduce the weight by 15% while maintaining structural integrity. Modal analysis shows the optimized design has slightly higher stresses but a reduced weight of 2.2kg compared to the original 2.6kg. Experimental testing of the optimized part validated the finite element analysis results.
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Presentation on Modeling and Simulation of (1).pptxMBSIXTEEN
ย
This presentation summarizes a project on modeling and simulating a semi-active suspension system. The project aims to design a suspension that can electronically adjust damping forces in response to road conditions to enhance stability, safety, and ride comfort. The team will develop a mathematical model, run simulations in MATLAB Simulink, and iterate on the design to optimize performance. A literature review covered research on using magnetorheological dampers and PID controllers to improve suspension. The methodology outlines forming models, parameters, simulations, analysis, and iterations. Tasks are scheduled on a Gantt chart. In conclusion, suspension systems have advanced significantly and this project will demonstrate and refine the performance of a semi-active system.
IRJET- Generation of Alternative Solutions for Differential-Less Drive Sys...IRJET Journal
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1) The document discusses potential alternative solutions to differentials in vehicle drive systems to address limitations like getting stuck when one wheel encounters an obstacle.
2) It presents 4 conceptual designs for differential-less drive systems, including ones using separate engines for each front wheel, hydraulic motors for each rear wheel, program-controlled variable speed motors for all wheels, and a mechanical system that can disengage one wheel during turns.
3) The concepts are evaluated against criteria like reliability, speed range, cost, versatility, and sensitivity, and the mechanical system is identified as the highest ranking concept warranting further development as a differential-less drive system.
Comparison of active and semi active suspension systems using robust controllerMustefa Jibril
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1. The document compares active and semi-active suspension systems using robust H-infinity controllers. Mathematical models of quarter car active and semi-active suspension systems are developed.
2. Simulation results show that the active suspension system with H-infinity controller decreases body acceleration and maintains suspension deflection and body travel outputs, proving its effectiveness over the semi-active system.
3. Numerical results confirm that the active suspension system provides minimum body travel and acceleration amplitudes, while matching the suspension deflection to the road profile, achieving the control targets.
Comparison of active and semi active suspension systems using robust controllerMustefa Jibril
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1) The document compares active and semi-active suspension systems for a quarter car model using robust H-infinity control.
2) Mathematical models are developed and simulations are run with random and sine road disturbances to evaluate body travel, acceleration, and suspension deflection.
3) The results show that the active suspension system with H-infinity controller is most effective at decreasing body acceleration and maintaining suspension deflection matching the road profile, proving its advantages over the semi-active system.
This document describes a simulation study of a vehicle model with four independent electric motors and active anti-roll bars on both axles. The vehicle model is composed of sub-models for the vertical dynamics, horizontal dynamics, and tire model. Simulation results show that coordinated control of the electric drive train and active suspension components can improve the vehicle's ride, stability, and handling. A complex cascade controller using PID and fuzzy logic techniques governs the integrated system based on sensor data from the virtual vehicle model.
This document describes a computational model called the Vehicle Dynamic Model (VDM) that was developed to analyze the dynamic behavior of vehicles. The VDM allows users to define vehicle parameters and evaluate the vehicle's vertical response when traversing different track profiles. It provides four types of results: 1) steady state response, 2) frequency response curves, 3) animation of the vehicle running on a track profile, and 4) natural frequencies and vibration modes. The model accounts for components like tires, springs, dampers and vehicle geometry. It was tested using literature data and allows analyzing ride performance by changing parameters and checking the vehicle's response over different tracks.
SIMULTANEOUS OPTIMIZATION OF SEMIACTIVE QUARTER CAR SUSPENSION PARAMETERS USI...ijmech
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In present paper, a methodology is presented related to the optimization of semi-active quarter car model
suspension parameters having three degrees of freedom, subjected to bump type of road excitation.
Influence of primary suspension stiffness, primary suspension damping, secondary suspension stiffness and
secondary suspension damping are studied on the passenger ride comfort, taking root mean square (RMS)
values of passenger seat displacement and settling time into account. Semi-active quarter car model
assembled with magneto-rheological (MR) shock absorber is selected for optimization of suspension
parameters using Taguchi method in combination with Grey relational analysis. Confirmatory results with
simulation run indicates that the optimized results of suspension parameters are helpful in achieving the
best ride comfort to travelling passengers in terms of minimization of passenger seat displacement and
settling time values.
This paper presents the modeling and simulation of
a magnetorheological damper based semiactive suspension using
variable structure controllers. Passive suspension systems tend to
limit the trade-off between passenger comfort and road handling.
But Semiactive suspensions can reduce this trade-off margin and
dynamically respond to the damping requirements. Active
suspensions provide the best response since they can add damping
force in any direction, but are prone to higher power consumption.
Semiactive suspensions just change the damping coefficient by
simply applying a control voltage as and when required. The
performance of three controllers- sigma 1, sigma 2 and sigma 3,
are measured and analyzed using nine parameters using peak,
root mean square and normalized approaches. The road
excitations considered are a single road hump and random road
disturbance. The control system is applied to a 2-degree of
freedom quarter car model of a passenger car. A modified BoucWen
model of MR damper is used to cater to the system responses
at near zero velocities. The performance of these controllers is
superior to the uncontrolled case, which is similar to passive
suspension system. Sigma 3 controller is superior to the
uncontrolled system by 63% while sigma 1 and sigma 2 are
superior by 53% when it comes to peak suspension deflection for
a random road disturbance. Both sigma 2 and sigma 3 controllers
are better in terms of performance. The validation of the
semiactive suspension leads to selection of sigma 2 controller over
sigma 3 controller because of its simplicity in implementation in
real-time systems.
Similar to Optimization of automobile active suspension system using minimal order (20)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
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Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the modelโs competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
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Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
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This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Neural network optimizer of proportional-integral-differential controller par...IJECEIAES
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Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
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This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
A review on features and methods of potential fishing zoneIJECEIAES
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This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naรฏve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.
Electrical signal interference minimization using appropriate core material f...IJECEIAES
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As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
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Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
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Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
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The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
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Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
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Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
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One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
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The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
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Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
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Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
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A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances studentsโ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
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Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
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Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
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Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Tools & Techniques for Commissioning and Maintaining PV Systems W-Animations ...Transcat
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Join us for this solutions-based webinar on the tools and techniques for commissioning and maintaining PV Systems. In this session, we'll review the process of building and maintaining a solar array, starting with installation and commissioning, then reviewing operations and maintenance of the system. This course will review insulation resistance testing, I-V curve testing, earth-bond continuity, ground resistance testing, performance tests, visual inspections, ground and arc fault testing procedures, and power quality analysis.
Fluke Solar Application Specialist Will White is presenting on this engaging topic:
Will has worked in the renewable energy industry since 2005, first as an installer for a small east coast solar integrator before adding sales, design, and project management to his skillset. In 2022, Will joined Fluke as a solar application specialist, where he supports their renewable energy testing equipment like IV-curve tracers, electrical meters, and thermal imaging cameras. Experienced in wind power, solar thermal, energy storage, and all scales of PV, Will has primarily focused on residential and small commercial systems. He is passionate about implementing high-quality, code-compliant installation techniques.
Build the Next Generation of Apps with the Einstein 1 Platform.
Rejoignez Philippe Ozil pour une session de workshops qui vous guidera ร travers les dรฉtails de la plateforme Einstein 1, l'importance des donnรฉes pour la crรฉation d'applications d'intelligence artificielle et les diffรฉrents outils et technologies que Salesforce propose pour vous apporter tous les bรฉnรฉfices de l'IA.
Levelised Cost of Hydrogen (LCOH) Calculator ManualMassimo Talia
ย
The aim of this manual is to explain the
methodology behind the Levelized Cost of
Hydrogen (LCOH) calculator. Moreover, this
manual also demonstrates how the calculator
can be used for estimating the expenses associated with hydrogen production in Europe
using low-temperature electrolysis considering different sources of electricity
Supermarket Management System Project Report.pdfKamal Acharya
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Supermarket management is a stand-alone J2EE using Eclipse Juno program.
This project contains all the necessary required information about maintaining
the supermarket billing system.
The core idea of this project to minimize the paper work and centralize the
data. Here all the communication is taken in secure manner. That is, in this
application the information will be stored in client itself. For further security the
data base is stored in the back-end oracle and so no intruders can access it.
Impartiality as per ISO /IEC 17025:2017 StandardMuhammadJazib15
ย
This document provides basic guidelines for imparitallity requirement of ISO 17025. It defines in detial how it is met and wiudhwdih jdhsjdhwudjwkdbjwkdddddddddddkkkkkkkkkkkkkkkkkkkkkkkwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwioiiiiiiiiiiiii uwwwwwwwwwwwwwwwwhe wiqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq gbbbbbbbbbbbbb owdjjjjjjjjjjjjjjjjjjjj widhi owqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq uwdhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhwqiiiiiiiiiiiiiiiiiiiiiiiiiiiiw0pooooojjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjj whhhhhhhhhhh wheeeeeeee wihieiiiiii wihe
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Optimization of automobile active suspension system using minimal order
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 12, No. 3, June 2022, pp. 2378~2392
ISSN: 2088-8708, DOI: 10.11591/ijece.v12i3.pp2378-2392 ๏ฒ 2378
Journal homepage: http://ijece.iaescore.com
Optimization of automobile active suspension system using
minimal order
Sairoel Amertet Finecomes1
, Fisseha L. Gebre2
, Abush M. Mesene3
, Solomon Abebaw4
1
Department of Mechanical Engineering, Mizan Tepi University, Tepi, Ethiopia
2
Department of Mechanical Engineering, Defence Engineering Collage, Bishoftu, Ethiopia
3
Department of Mechanical Engineering, University of Gonder, Ethiopia
4
Department of Statistics, Mizan Tepi University, Tepi, Ethiopia
Article Info ABSTRACT
Article history:
Received Sep 23, 2019
Revised Nov 8, 2021
Accepted Nov 30, 2021
This paper presents an analysis and design of linear quadratic regulator for
reduced order full car suspension model incorporating the dynamics of the
actuator to improve system performance, aims at benefiting: Ride comfort,
long life of vehicle, and stability of vehicle. Vehicleโs road holding or
handling and braking for good active safety and driving pleasure and
keeping vehicle occupants comfortable and reasonably well isolated from
road noise, bumps, and vibrations are become a key research area conducted
by many researchers around the globe. Different researchers were tested
effectiveness of different controllers for different vehicle model without
considering the actuator dynamics. In this paper full vehicle model was
reduced to a minimal order using minimal realization technique. The entire
system responses were simulated in MATLAB/Simulink environment. The
effectiveness of linear quadratic regulator controller was compared for the
system model with and without actuator dynamics for different road profiles.
The simulation results were indicated that percentage reduction in the peak
value of vertical and horizontal velocity for the linear quadratic regulator
with actuator dynamics relative to linear quadratic regulator without actuator
dynamics was 28.57%. Overall simulation results were demonstrated that
proposed control scheme has able to improve the effectiveness of the car
model for both ride comfort and stability.
Keywords:
Linear actuator
Linear quadratic regulator
control
Minimal realization technique
active suspension system linear
DC motor
This is an open access article under the CC BY-SA license.
Corresponding Author:
Sairoel Amertet Finecomes
Department of Mechanical Engineering, Mizan Tepi University
Tepi, Region of Southern Nations Nationalities and peoples, Ethiopia
Email: sairoel@mtu.edu.et
1. INTRODUCTION
The suspension system is a mechanism that physically separates the car body from the car wheels,
and a complex vibration system having multiple degrees of freedom. It is the most important part of the
vehicle which heavily affects the ride quality and used to isolate the vehicle structure from shocks and
vibration due to irregularities of the road surface [1]. The main purpose of vehicle suspension system is to
minimize the vertical displacement, velocity or acceleration transmitted to the passenger which directly
provides ride comfort [2], [3]. Usually vehicle model could be quarter car, half car and full car models based
on types of suspension system and could be passive, semi active, and active suspension system based on
energy consumptions. In passive suspension system, the good ride quality is mainly achieved by an
appropriate choice of the springs and dampers. The parameters are generally fixed, with values compromised
to achieve a certain level of performance of the suspension system. Since the appropriate choice is depend on
2. Int J Elec & Comp Eng ISSN: 2088-8708 ๏ฒ
Optimization of automobile active suspension system using minimal order (Sairoel Amertet Finecomes)
2379
the road surface, it has a limitation to satisfy to different types of road irregularities [4], [5]. Therefore, a
means of controlling to different types of road surface automatically should be researched. In contrast to
passive systems, active suspension systems can adjust their dynamic characteristics in response to varying
road conditions in real time [6], [7]. In order to design linear quadratic regulator controller, all states should
be measurable and are sensed by its own individual sensor. Fourteen sensors are used to get information from
each state which is bulky and requires high cost [8], [9]. Thus, a means of technique to reduce the number of
states and sensors to a minimal number without affecting the behavior of the original model system is
investigated. To have a good control performance, a good modeling of the system is necessary. As improving
the model from quarter car to half car model, from half car to full car model and including the sensors and
actuator dynamics in the system model, it will be more accurate [10]โ[12]. Most of the researchers were
proven the effectiveness of different controllers for different car suspension system model without
considering the actuator dynamics, without considering the state reachable, and without considering the state
measureable in which the design of state feedback is impossible [13]โ[18]. However, in this research paper, it
is proposed to design linear quadratic regulator (LQR) for active suspension system of automobile vehicles
based on active suspension system of automobile vehicles using reduced order car model by combing a linear
direct control motor actuator to reduce the vehicle body vibration and to settle within short period of time so
that the passengers feel comfort for more specific and concern [19]. At the end of this paper, the controller
performance will be evaluated under full car suspension system reduced order for different road profiles
conditions. The controllerโs dynamic study is performed by evaluating the transient response during the
magnitude variations of road profile reference.
The remaining part of this paper is organized: section 2 describes mathematical model of full car
model with governing equation. The design of linear quadratic regulator controller and system analysis
carried out in section 3. Section 4 presents the results of simulation carried out for different road pro๏ฌle.
Conclusion of the work will present in section 5.
2. MATHEMATICAL MODELING OF SUSPENSION SYSTEM
The vehicle active suspension system model utilized for numerical simulation was developed in the
MATLAB/Simulink environment and the presenters of the vehicle active suspension system are extracted.
The model, as shown in Figure 1 indicates that block diagrams of active suspension system, and its control
mechanism, Figure 2 depicted the schematic diagram of the active suspension system of automobile vehicle,
and Figure 3 utilizes three degree of freedoms for the motion of the car body in the space (pitch, roll, and
bounce), and four degree of freedom for wheel displacement (relative to the vehicle chassis) and rotations.
The mathematical models were developed based on some assumptions (the model considers only linearityโs
region, external factor (aerodynamics resistance) were not consider, and non-linearity properties of tires,
actuators were not considered).
Figure 1. Block diagram representation of the active suspension system [10]
2.1. Basic structure of active suspension system
Active suspension systems are mechatronics systems that control the vertical movement of the
vehicle body or chassis relative to the wheels. The active suspension systems considered in this paper is
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applied for enhancing the ride comfort of automobile vehicles. Therefore, they are placed in between the
chassis and the wheels through attachment of their two ends to the car body and the wheels. In active
suspension system the vehicleโs up and down motion is controlled by linear quadratic regulator feedback
controller according to the road conditions; the controller output controls the actuator to compensate the road
oscillations and increases the vehicle stability as well as ride comfort. As a result of the road disturbance, the
vehicle body has been oscillated for some time. The sensors measure the amplitude of the vibration from the
equilibrium position. The linear quadratic regulator controller processed the electrical signal information
obtained from the sensors and it provides a control signal which controls the action of the actuator for fine
response in real time. The passive elements and linear direct control motor actuator generate forces which
counteract vertical, pitch and roll motions. Gradually, the purpose of the active suspension system is to
replace the classical passive elements by a controlled system, which can supply a regulated force to the
system. The active suspension system dynamically responds to the changing road surface due to its ability to
supply energy, which is used to achieve the relative motion between the body and wheel [9]. As shown in
Figure 2 the main purpose of suspension is supporting both roads holding and ride quality. Moreover,
suspension system affects on the vehicle handling too. Furthermore, it is very important to keep the road
wheel in contact with the road surface, for the suspension. There are different ways of attaching the wheels of
the car so that they can move up and down on their springs and dampers. The design of front suspension and
design rear suspension have some differences to the ability of opposite wheels to move independently of each
other. For front-wheel drive cars, rear suspension has few constraints and a variety of beam axles and
independent suspensions are used. For rear-wheel drive cars, rear suspension has many constraints and the
development of the superior but more expensive independent suspension layout has been difficult. Four-
wheel drive cars often have suspensions that are similar for both the front and rear wheels.
Figure 2. Schematic diagram of the active suspension system of automobile vehicle [10]
2.2. Mathematical models
Various types of car models such as quarter car model, half car model and full car model have been
used to simulate the performance of suspension systems. In the research studies the quarter car model is
frequently used because of its simplicity, however, the half car model shows more appropriate vertical
motion, including either the pitch or the roll effects. The full car model is the best accurate one, but it
requires more computation than the others as a result very few studies have been carried out based on it [20].
Lot of common vehicles today uses passive suspension system to control the dynamics of a vehicleโs vertical
motion as well as spinning (pitch) and tilting (roll) [21]. The design of a vehicle suspension is an issue that
needs a series of mathematical calculations. To study the vibrational characteristics of the vehicle and to
design the controller appropriately, a mathematical model of a dynamic system is defined as a set of various
equations that represents dynamics of the system accurately or at least, well. By applying Newtonโs second
law motion and using the static equilibrium position as the origin, for the linear vertical displacement, pitch
angular displacement, and roll angular displacement of the vehicle body Y0, ฮธ, and ฯ respectively from the
center of gravity the equations of motion for the system can be formulated. Once a mathematical model of
the system is obtained, various analytical and computer tool, MATLAB, can be used for design of linear
quadratic regulator controller and analysis.
2.3. Equations of motion
The free body diagram of the passive and active suspension systems is shown in Figure 3. While
modeling the system components the spring and the damper are assumed linear, i.e. the model is based on
elements of linear dynamic systems theory. Therefore, the overall equations are linear.
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The values of are obtained by back substitution into the equation from the (1) to (8). After obtained the state
equation, we put into state matrix:
๐ฅฬ = |
๐ด11 ๐ด12
๐ด21 ๐ด21
|๐ฅ(๐ก) + ๐ต๐ข(๐ก) + ๐น(๐ก)
where
๐ด = |
๐ด11 ๐ด12
๐ด21 ๐ด21
|๐ฅ(๐ก) = [14 ร 1],๐ข(๐ก) = [4 ร 1],
๐ต = [14 ร 1], ๐น = [14 ร 4],๐ถ = [๐๐ฆ๐2 ร 14], ๐ท = [๐ง๐๐๐๐ 2 ร 4]
3. SYSTEMANALYSIS AND CONTROLLER DESIGN
The active suspension system model has been developed in section two. As derived and stated in
section two, the model has fourteen (14) state variables. The state matrix (A) of the state space representation
of the system is fourteen by fourteen (14ร14). Therefore, it needs 14 sensors to measure each state which is
not feasible practically. This is costly, so the system should be described with a minimal number of states and
this is achieved using a minimal realization principle. In addition, it is difficult to manipulate the system.
Therefore, to handle the system, the order of the system state space representation is reduced to eighth (8th)
by using minimal realization technique without affecting the characteristics of the original model system.
This is proved to be true by checking the response of the 14th order system and the 8th order system for the
same input disturbance of single bump as shown in the Figures 4(a) and 4(b). Due to the more state variables
are used to describe the system (redundancy of state variables), too much symmetry the system and the
system has physically uncontrollable components. It is difficult (not feasible) to implement the system
physically in real time application. Therefore, these problems are reduced using minimal realization
technique. A minimal realization principle is a means of describing the system with a small number of states.
Therefore, the system is implemented with a minimal number of components. Minimal realization technique
eliminates uncontrollable or unobservable state in state-space models, or cancels pole-zero pairs in transfer
functions. It describes the system with the minimum number of states. Thus, the obtained minimal realization
model has minimal order and the same response characteristics as the original model system. A minimal
realized system is both controllable and observable [22], [23]. When we split out the Figure 4(a) it looks as
displayed in the Figure 4(b). So, our conclusion was that there is no any deviation between the original
system and Minimal realization system. This implies that we can use the realization system instead of
original system.
As it can be observed in Figures 4(a) and 4(b) the simulation results of both the original model
system (14ร14 matrixes) and minimal realized system (8ร8 matrix) are the same. Therefore, this shows that
minimal realization technique doesnโt alter the behavior of the original model system. The six states
(velocities of the four wheels, and positions of coupling wheels) were removed, since they were not affect the
entire suspension system model due to velocities of the wheels are the same to the vehicle suspension system,
and the position of the coupling wheels (both front wheels, and rear wheels) are the same. The difference of
relative motion between them are zero. Therefore, the new state space model becomes as follow. A=[8ร8],
B=[8ร4], C=[2ร8], D=[zeros(2)ร8]. In order to design a linear quadratic regulator controller, the system must
be fully controllable. This is verified by determining the rank of the controllability matrix (A, B). Therefore,
the controllability matrix (A, B) of the active suspension system as shown in the appendix B has full rank (8),
which makes it fully controllable. It is also known that if the system is minimal realized, then it is fully
accessible and observable. Stability is an important property that a system is required to have. It is usually not
desirable that a small change in the input, initial condition, or parameters of the system produces a very large
change in the response of the system. If the response increases indefinitely with time, the system is said to be
unstable. The open-loop response of the system to a road profile 1 can be used to verify stability of the
system.
From the Figure 5(a) it can be observed that the response of the suspension system without feedback
controller is bounded. This shows that the system is stable because, for the bounded input the system is
producing bounded output. Furthermore, Figure 5(a) displayed that open-loop body displacement of the
suspension system model for road single bump road profile Figure 5(b), and open-loop body, pitch, roll, and
yaw displacement of the suspension system model for road single bump road profile. As it is observed in
Figures 5(a) and 5(b), the suspension system without active controller is stable, however, it needs an
improvement to be more comfort for passengers. Therefore, in order to enhance the performance a suitable
6. Int J Elec & Comp Eng ISSN: 2088-8708 ๏ฒ
Optimization of automobile active suspension system using minimal order (Sairoel Amertet Finecomes)
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controller must be designed. The controller generates an appropriate control signal to maintain the car body
at the desired equilibrium position in response to road disturbances. The controller designed will help the
system to be insensitive to the road disturbances. Therefore, the controller will try to make the system stable
and perform well regardless of the disturbance. The linear quadratic regulator is the extension of pole
placement technique that tends to find the control input so as to place the poles of the system at a desired
optimal position. The main idea in linear quadratic regulator control design is to minimize the quadratic cost
function of J given in (9) [24], [25].
๐ฝ =
1
2
โซ [๐ฅ๐
(๐ก)๐(๐ก)๐ฅ(๐ก) + ๐ข๐
(๐ก)๐ (๐ก)๐ข(๐ก)]
๐ก๐
๐ก0
๐๐ก (9)
The LQR should minimize this cost function (performance index) while obtaining the state feedback
gains K that drives the system to the desired operating point. It turns out that regardless of the values of Q
and R, the cost function has a unique minimum that can be obtained by solving the following Algebraic
Riccati equation [25].
๐ด๐
๐ + ๐๐ด โ ๐๐ต๐ โ1
๐ต๐
๐ + ๐ = 0 (10)
By solving the above Riccati equation the positive-definite matrix P is obtained, thus the optimal gain (K)
and controller (u) are determined as (11):
๐ = ๐ โ1
๐ต๐
๐
๐ข(๐ก) = โ๐๐ฅ(๐ก) (11)
(a)
(b)
Figure 4. Comparing the original and reduced automobile suspension system (a) comparing the original and
minimal realization system and (b) comparison the response of original and minimal realized systems
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2384
(a)
(b)
Figure 5. Observing the effects of (a) open-loop body displacement of the suspension system model for road
profile 1 and (b) open-loop pitch angle response of the suspension system model for road profile 1
From Figure 5, we can observe that the effects of Figure 5(a) open-loop body displacement of the
suspension system model for road profile, and Figure 5(b) open-loop pitch angle response of the suspension
system model for road profile. The control signal given by (11) is the optimal control law. Therefore, if the
matrix K are determined so as to minimize the performance index, J, then (11) is optimal for any initial state
(0). The block diagram of the optimal LQR controller is displayed in the Figure 6.
Figure 6. Block diagram of LQR control scheme
As seen in the cost function, J, given in (8) in addition to the states x(t) and control signals u(t)there
are the weighting matrices Q and R. The parameters Q and R can be used as design parameters to penalize
the state variables and the control signals. The larger these values are, the more you penalize these signals.
The parameter Q penalizes the deviation of system states from the equilibrium. Basically, selecting a large
value for Q means you try to stabilize the system with the least possible changes in the states and large Q
implies less concern about the changes in the states. The parameter R penalizes the use of input control
8. Int J Elec & Comp Eng ISSN: 2088-8708 ๏ฒ
Optimization of automobile active suspension system using minimal order (Sairoel Amertet Finecomes)
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signal. If you choose a large value for R means you try to stabilize the system with less (weighted) energy.
This is usually called expensive control strategy. On the other hand, choosing a small value for R means you
donโt want to penalize the control signal (cheap control strategy). Q and R are weighting matrices and should
be positive semi-definite and positive definite, respectively. They are also symmetric matrices Q=QT; R=RT.
Normally, the Q and R matrices are chosen as diagonal matrices such that the quadratic performance index is
a weighted integral of squared error. The sizes of Q and R matrices depend on the number of state variables
and input variables respectively. If the system A, B is controllable, then we can place the Eigen values of the
closed loop system anywhere we want. That is extremely powerful, but in practice it is sometimes not
usefulness. Therefore, there is problem with placing system Eigen values. The main problem is we do not
have a great sense of the input that is required to accomplish the Eigen values of the closed loop system to
place anywhere. For example, if you try to make your system super-fast (i.e. placing of poles far way to the
left of the s-plane) it can require huge input, which the real physical system could not achieve. So just placing
system Eigen values from this fundamental reason to the appropriate position is required. Since the controller
is a regulator, it tries to drive each state to a constant set point. In this thesis, the controller drives each state
to zero. So, any value bigger than zero weather it is positive or negative is bad in this case. Therefore, the
controller drives each state (t) to zero as time tends to infinity. By choosing the value of Q and R we can
change the relative weightings of one state versus another. Since the number of state variables are eight, the
value of Q can be represented by the following eight by eight (8ร8) matrix Q=10000 โ[eye (8ร8)]; R=0:001
โ[eye (8ร8)]. All the diagonal elements penalize their correspondence state individually. The off diagonal
elements penalize combination of the states. Therefore, since the outputs of the system are combination of
these individual states, by penalize each individual state independently using its respective Q value and
observing the combination effect on the outputs the required performance can be achieved. In fact, penalize
one state has an effect on another but it is small. So, the value of Q is selected carefully and systematically.
The Figure 7(a) demonstrated the responses of four tires for each state variable for the Q and R values,
whereas, the Figure 7(b) showed the responses of roll, pitch, and yaw for each state variable for the Q and R
values respectively.
(a)
(b)
Figure 7. Response of each state variable for the Q and R values, (a) responses of four tires for each
state variable for the Q and R values and (b) responses of roll, pitch, and yaw for each state variable for the Q
and R values
9. ๏ฒ ISSN: 2088-8708
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4. SIMULATION RESULTS AND DISCUSSION
This section discusses about simulation results of passive and active suspension systems for
different scenarios. Performance of the suspension system in terms of ride quality will be observed, where car
body displacement, velocity, pitch angle and angular velocity are considered as output parameters. Using the
vehicle dataโs, the exact physical characteristics of that car can be determined by simulating the mathematical
model with the help of MATLAB software. In order to show the performance of the LQR with actuator
dynamics with tuned values Q and R matrices, different bump disturbances are applied to the system to
observe for different scenarios. In order to study the dynamic behavior of the vehicle and to analysis the
performance of the suspension system an external excitation input for the model is required. In this study, a
different type of sinusoidal function road profiles is used as excitation for simulation purpose. The road bump
profile in Figure 8 is appearing for1:5โคtโค1:75 sec for front right and left wheels and 2:06โคtโค2:31 sec for rear
right and left wheels. The width of each bump โ(t) 0 in this case 0:25 sec indicates the duration of the road
bump at each wheel. From Figure 9, it can be seen that the peak value response of chassis displacement for
passive suspension system is0:06 m: It can be also observed that the peak value response of the chassis
displacement for active suspension excluding actuator dynamics in the system model is 0:055 m while that
for the active suspension with actuator dynamics included in the system model is 0:045 m for the same road
input and the same controller gains. Furthermore, the blue curve indicates the linear quadratic regulator with
actuator dynamics, the rose color showed the passive suspension system, and the black doted curve tells the
linear quadratic regulator without actuator dynamics at single bump road profile. The reduction
(improvement) in percentage for the displacement of the chassis can be calculated as (12), (13):
๐๐ = (
๐๐ฃโ๐๐ฃ
๐๐ฃ
) โ 100% (12)
๐๐ = (
๐๐ฃโ๐๐ฃ
๐๐ฃ
) โ 100% (13)
where rp=reduction in peak value from passive pv=passive value av=active (LQR) with actuator dynamics
value re=reduction in peak value from active excluding actuator dynamics ev=active (LQR) excluding
actuator dynamics value.
๐๐ = (
0.06โ0.045
0.06
) โ 100% = 25%; ๐๐ = (
0.055โ0.045
0.055
) โ 100% = 18.18%
Figure 8. Road input disturbance of a single bump
Thus, the chassis displacement (peak value) is reduced by 25% and 18:18% in case of an active
suspensionsystem with actuator dynamics which is included in the system model. This is a direct indication
of the superiority of active suspension system using LQR with actuator dynamics over passive suspension
system andactive suspension system without actuator dynamics. The settling time, as we can observe from
Figure 9 is 4:95 sec, 3:45 sec and 1:9 secfor passive suspension, active suspension excluding actuator
dynamics and active suspension including actuator dynamics respectively. Thus, reductions (improvements)
in settling time in activesuspension including actuator dynamics in the system model are 61:61% and 44:93%
as compared to passivesuspension and LQR excluding actuator dynamics respectively. Moreover, the Table 1
comparison of passive suspension system, linear quadratic regulator without actuator dynamics, and linear
quadratic regulator with actuator dynamics fordisplacement.
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Figure 9. Simulation result of comparison for body displacement using a single bump
Table 1. Comparison of PSS, LQR without actuator dynamics, and LQR with actuator dynamics
fordisplacement
PS PSS (rpm) LQRA LQRAO % LQRA over PSS % LQRA over LQRAO
PPR(m) 0.06 0.045 0.055 25% 18.18%
Ts(sec) 4.95 1.9 3.45 61.61% 44.93%
VPR(m/s) 0.65 0.4 0.56 38.46% 28.57%
Ts(sec) 4.95 1.7 3.45 65.66% 50.72%
OPR(rad) 0.0388 0.0263 0.0338 32.22% 22.19%
Ts(sec) 3.95 1.57 2.45 62.25% 35.92%
AVPR(rad/s) 0.3375 0.2625 0.2875 22.22% 8.7%
Ts(sec) 3.95 1.57 2.45 60.25% 35.95%
Where PS=performance specifications, PSS=passive suspension system, LQRA=LQR with actuator
dynamics, LQRAO=LQR without actuator dynamics, PPR=position peak response, (amplitude)(m)=Ts(sec)
settling time(sec), VPR(m=sec)=velocity peak response (amplitude)(m=s); OPR(rad) orientation peak
response (amplitude)(rad), AVPR(rad/sec)=angular velocity peak response (amplitude)(rad/s). As observing
from the simulation result of Figure 10, the peak overshoot of sprung mass velocity for passive suspension
system is 0.65 m/s. For the LQR without actuator dynamics and LQR with actuator dynamics are 0.56 m/s
and 0.4 m/s respectively. From these values, it is found that for active suspension system (LQR) with actuator
dynamics the peak value of the velocity of the sprung mass is reduced by 38:46% as compared to passive
suspension system. As compared to active suspension system (LQR) without actuator dynamics the reduction
is 28:57%. The passive suspension system and LQR without actuator dynamics have the same settling time
as of the displacement whereas the settling time for the LQR with actuator dynamics is 1:7 sec. Therefore,
the reduction settling time in active controller (LQR) with actuator dynamics which is included in the system
model is 65:66% as compared with passive system while compared with LQR without actuator dynamics is
50:72%. Furthermore, the blue curve indicates the linear quadratic regulator with actuator dynamics, the rose
color showed the passive suspension system, and the black doted curve tells the linear quadratic regulator
without actuator dynamics at single bump road profile.
Figure 10. Simulation result of comparison for body velocity using a single bump
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Similarly, in Figure 11 we can observe that, the peak values of the pitch angle for sprung mass of
passive suspension, LQR without actuator dynamics and LQR with actuator dynamics are 0.0388 rad,
0.0338 rad and 0.0263 rad respectively. 32.22% and 22.19% are the peak value reductions in LQR with
actuator dynamics as compared to passive suspension system and LQR without actuator dynamics
respectively. From the Figure 11, the settling time for the passive suspension system is 3.95 sec. For the LQR
without actuator dynamics the settling time is 2.45 sec. and for the LQR with actuator dynamics, it is
1.57 sec. Thus, the settling time reductions (improvements) are 60:25% and 35:92% for LQR with actuator
dynamics as compared to the passive and LQR without actuator dynamics respectively. From the Figure 11,
the settling time for the passive suspension system is 3:95 sec. For the LQR without actuator dynamics the
settling time is 2:45 sec and for the LQR with actuator dynamics, it is 1:57 sec: Thus, the settling time
reductions (improvements) are 60:25% and 35:92% for LQR with actuator dynamics as compared to the
passive and LQR without actuator dynamics respectively. The Figure 12(a) showed that the force generated
two wheels from front tires (actuators) in active suspension system at single road profile (bump). Further,
Figure 12(b) demonstrated that the force generated two wheels from front tires (actuators) in active
suspension system at single road profile (bump). Moreover, all the response of the tires is settles about
3.5 second; this showed that the proposed control algorithm is best fitting on the active suspension system.
The time interval 1.7 second to 3.5 second tell us the four tires, and roll, pitch, yaw is in the condition of
unstable. With sometimes later at 3.5 second all the active suspension systems are well settle.
Figure 11. Simulation result of comparison for pitch angular velocity using upward single bump
Figure 13 displayed that the different road profile applied on the front and rear wheels respectively.
The top most indicates that the road profile for the front wheels whereas the bottom most demonstrated that
the rear wheels. Furthermore, it means that Speed humps are in widespread use around the world. Despite
their effective performance in increasing safety, they cause considerable damage to vehicles and discomfort
to drivers and passengers. So, this road profiles are used as input for the system.
As it can be seen in Figures 14 for a two bumps input road profile with different amplitudes, the
amplitude and settling time of the results are different. For the high amplitude input road profile both the
amplitude and settling time of the simulation results are higher than as the input is the low amplitude road
profile which is expected. In addition to, the simulation results indicate that for existence of road disturbances
the vehicle body vibrates up and down from its equilibrium position which is zero whereas for the smooth
(absence) of road input disturbance the vehicle body will be remained in its equilibrium position.
Figure 15(a) displayed that the comparison of suspension system with actuator dynamics, without
actuator dynamics, and passive suspension system for angular position at double road bump profile, whereas
Figure 15(b) indicates that comparison of suspension system with actuator dynamics, without actuator
dynamics, and passive suspension system for angular velocity at double road bump profile. From the
Figures 15 we generalized as the proposed control is best fit for the regulation and optimization of the vehicle
suspension with actuator dynamics, and without actuator dynamics, compared to passive suspension system.
Furthermore, the proposed controller that is linear quadratic regulator is more effective on the suspension
system with actuator dynamics, as we compared to without actuator dynamics. From Figure 16 we infer those
effects of forces on actuators are demonstrated as Force generated from front actuators in active suspension
system using double bumps displayed in Figure 16(a) whereas Figure 16(b) indicated that Force generated
from rear actuators in ASS using double bumps.
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(a)
(b)
Figure 12. Effects of the forces on actuator (a) force generated from front actuators in active suspension
system using a single bump and (b) force generated from rear actuators in active suspension system using a
single bump
Figure 13. Road input disturbance of two road bumps
Figure 14. Comparison of the vehicle suspension system by considering actuator and without considering
actuator dynamics at double bump road profile
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(a)
(b)
Figure 15. Effects of automobile vehicle suspension system on double bump road profile,
(a) simulation result of comparison for pitch angle using two bumps and (b) simulation result of comparison
for pitch angular velocity using two bumps
(a)
(b)
Figure 16. Effects of forces on actuator, (a) force generated from front actuators in ASS using double bumps
and (b) force generated from rear actuatorsin active suspension system using double bumps
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5. CONCLUSION
Active suspension system is one part of the essential mechatronic system of a vehicle system. In this
research paper, with some assumptions, the model of the active suspension system is developed and the state
feedback controller LQR is designed. By comparing the performance of the passive, LQR without actuator
dynamics and LQR with the actuator dynamics, the simulation results clearly indicate that LQR with actuator
dynamics can give lower amplitude and faster settling time. The reduced value of peak response will result in
less sprung-mass travel and hence, the reduced vibrations felt by the passenger. The less settling time will
quickly suspend the oscillations induced in the car body which will ensure better comfort to the passenger.
Therefore, the proposed LQR controller with actuator dynamics which is included in the system model is
more effective in the vibration isolation of the car body than the passive suspension system and LQR without
actuator dynamics. So, the proposed LQR controller with the selected weighting matrices Q and R is
acceptable. The proposed LQR control with actuator dynamics that is included in the system model gives
25% and 18.18% reduction in the peak value of vertical displacement as compared to passive and LQR
controller without actuator dynamics respectively, for the same road input and the same controller gains, thus
improving passenger comfort. It is found that for LQR controller with actuator dynamics, the peak value of
the velocity of the sprung mass is reduced by 38.46% compared to passive suspension system while
compared to LQR without actuator dynamics the reduction is 28.57% which guarantee better ride comfort.
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BIOGRAPHIES OF AUTHORS
Sairoel Amertet Finecomes received a BSc. degree in Electromechanical
Engineering from Hawassa University, Institute of Technology, Hawassa, Ethiopia in 2016,
MSc. degree in Mechatronics Engineering from Addis Ababa Science and Technology
University, Addis Ababa, Ethiopia, in 2019. He is currently Lecturer at Mizan Tepi
University,Tepi, Ethiopia. His professional activities have been focused in Software
developing, emerging technology, Robotic, Autonomous Technology, Mechatronic
systems design, Instrumentation and control. He can be contacted at email:
sairoelamertet23@gmail.com.
Fisseha Legesse Gebre (PhD) Academic Rank: Assistant professor. He has
done his Ph.D degree from Indian Institute of Technology Bombay (IITB) 2018. He
completed his M.Tech from IIT Madras in 2005 and B.Tech from Defence Engineering
College, Ethiopia in 2001. His research interests include additive manufacturing,
functionally gradient objects, welding, robotics, CNC and automation. He can be contacted
at email: fissehal@gmail.com.
Abush M. Mesenewas born in Wolaita, Ethiopia in 1992 G.C. He received his
B.Sc. degrees from Gondar University Institute of Technology in 2016. In 2016, he joined
the School of Mechanical Engineering at Institute of Technology at Gondar, in Ethiopia, as
Assistant Lecturer. He spent the 2016-2017 academic year as a teaching undergraduate
students. He currently has active collaborations with research center at institute of
technology in Gondar. Currently, he has M.sc on mechatronics engineering and working as
service engineer at buhlergroup specifically in Mechatronics activities and Lecturer at
university of Gondar. His activities currently focus on model, control and design of
electromechanical equipments. He can be contacted at email: beyu1216@gmail.com. For
further information on his linkedin homepage: https://www.linkedin.com/in/abush-
mohammed-mesene-2034411a5.
Solomon Abebaw received BSc degree in Statistics from University of Gondar,
Ethiopia. He has received his MSc degree in Biostatistics in 2016 from Jimma University.
Now he is lecturer and Head of StatisticsDepartment at MizanTepi University, College of
Natural and Computational Science. His Professional and Research activities have been
focused on any Statistical Modelling and Data Analysis. He can be contacted at email:
solabew@gmail.com. Further info on his homepage: https://www.mtu.edu.et/about-us.