The paper studies a nonlinear model based on time series neural network system (TSNN) to improve the highly nonlinear dynamic model of an automotive lead acid cell battery. Artificial neural network (ANN) take into consideration the dynamic behavior of both input-output variables of the battery charge-discharge processes. The ANN works as a benchmark, its inputs include delays and charging/discharging current values. To train our neural network, we performed a pulse discharge on a lead acid battery to collect experimental data. Results are presented and compared with a nonlinear Hammerstein-Wiener model. The ANN and nonlinear autoregressive exogenous model (NARX) models achieved satisfying results.
A robust state of charge estimation for multiple models of lead acid battery ...journalBEEI
An accurate estimation technique of the state of charge (SOC) of batteries is an essential task of the battery management system. The adaptive Kalman filter (AEKF) has been used as an obsever to investigate the SOC estimation effectiveness. Therefore, The SOC is a reflexion of the chemistry of the cell which it is the key parameter for the battery management system. It is very complex to monitor the SOC and control the internal states of the cell. Three battery models are proposed and their state space models have been established, their parameters were identified by applying the least square method. However, the SOC estimation accuracy of the battery depends on the model and the efficiency of the algorithm. In this paper, AEKF technique is presented to estimate the SOC of Lead acid battery. The experimental data is used to identify the parameters of the three models and used to build different open circuit voltage–state of charge (OCV-SOC) functions relationship. The results shows that the SOC estimation based-model which has been built by hight order RC model can effectively limit the error, hence guaranty the accuracy and robustness.
Comparison of one and two time constant models for lithium ion battery IJECEIAES
The fast and accurate modeling topologies are very much essential for power train electrification. The importance of thermal effect is very important in any electrochemical systems and must be considered in battery models because temperature factor has highest importance in transport phenomena and chemical kinetics. The dynamic performance of the lithium ion battery is discussed here and a suitable electrical equivalent circuit is developed to study its response for sudden changes in the output. An effective lithium cell simulation model with thermal dependence is presented in this paper. One series resistor, one voltage source and a single RC block form the proposed equivalent circuit model. The 1 RC and 2 RC Lithium ion battery models are commonly used in the literature are studied and compared. The simulation of Lithium-ion battery 1RC and 2 RC Models are performed by using Matlab/Simulink Software. The simulation results in his paper shows that Lithium-ion battery 1 RC model has more maximum output error of 0.42% than 2 RC Lithium-ion battery model in constant current condition and the maximum output error of 1 RC Lithium-ion battery model is 0.18% more than 2 RC Lithium-ion battery model in UDDS Cycle condition. The simulation results also show that in both simple and complex discharging modes, the error in output is much improved in 2 RC lithium ion battery model when compared to 1 RC Lithium-ion battery model. Thus the paper shows for general applications like in portable electronic design like laptops, Lithium-ion battery 1 RC model is the preferred choice and for automotive and space design applications, Lithium-ion 2 RC model is the preferred choice. In this paper, these simulation results for 1 RC and 2 RC Lithium-ion battery models will be very much useful in the application of practical Lithium-ion battery management systems for electric vehicle applications.
An electric circuit model for a lithium-ion battery cell based on automotive ...IJECEIAES
The on-board energy storage system plays a key role in electric vehicles since it directly affects their performance and autonomy. The lithium-ion battery offers satisfactory characteristics that make electric vehicles competitive with conventional ones. This article focuses on modeling and estimating the parameters of the lithium-ion battery cell when used in different electric vehicle drive cycles and styles. The model consists of an equivalent electrical circuit based on a second-order Thevenin model. To identify the parameters of the model, two algorithms were tested: TrustRegion-Reflective and Levenberg-Marquardt. To account for the dynamic behavior of the battery cell in an electric vehicle, this identification is based on measurement data that represents the actual use of the battery in different conditions and driving styles. Finally, the model is validated by comparing simulation results to measurements using the mean square error (MSE) as model performance criteria for the driving cycles (UDDS, LA-92, US06, neural network (NN), and HWFET). The results demonstrate interesting performance mostly for the driving cycles (UDDS and LA-92). This confirms that the model developed is the best solution to be integrated in a battery management system of an electric vehicle.
Performance Evaluation of Modelling and Simulation of Lead Acid Batteries for...IJPEDS-IAES
Lead-acid batteries have been the most widely used energy storage units in
stand-alone photovoltaic (PV) applications. To make a full use of those
batteries and to improve their lifecycle, high performance charger is often
required. The implementation of an advanced charger needs accurate
information on the batteries internal parameters. In this work, we selected
CIEMAT model because of its good performance to deal with the widest
range of lead acid batteries. The performance evaluation of this model is
based on the co-simulation LabVIEW/Multisim. With the intention of
determining the impact of the charging process on batteries, the behaviour of
different internal parameters of the batteries was simulated. During the
charging mode, the value of the current must decrease when the batteries’
state of charge is close to be fully charged.
A robust state of charge estimation for multiple models of lead acid battery ...journalBEEI
An accurate estimation technique of the state of charge (SOC) of batteries is an essential task of the battery management system. The adaptive Kalman filter (AEKF) has been used as an obsever to investigate the SOC estimation effectiveness. Therefore, The SOC is a reflexion of the chemistry of the cell which it is the key parameter for the battery management system. It is very complex to monitor the SOC and control the internal states of the cell. Three battery models are proposed and their state space models have been established, their parameters were identified by applying the least square method. However, the SOC estimation accuracy of the battery depends on the model and the efficiency of the algorithm. In this paper, AEKF technique is presented to estimate the SOC of Lead acid battery. The experimental data is used to identify the parameters of the three models and used to build different open circuit voltage–state of charge (OCV-SOC) functions relationship. The results shows that the SOC estimation based-model which has been built by hight order RC model can effectively limit the error, hence guaranty the accuracy and robustness.
Comparison of one and two time constant models for lithium ion battery IJECEIAES
The fast and accurate modeling topologies are very much essential for power train electrification. The importance of thermal effect is very important in any electrochemical systems and must be considered in battery models because temperature factor has highest importance in transport phenomena and chemical kinetics. The dynamic performance of the lithium ion battery is discussed here and a suitable electrical equivalent circuit is developed to study its response for sudden changes in the output. An effective lithium cell simulation model with thermal dependence is presented in this paper. One series resistor, one voltage source and a single RC block form the proposed equivalent circuit model. The 1 RC and 2 RC Lithium ion battery models are commonly used in the literature are studied and compared. The simulation of Lithium-ion battery 1RC and 2 RC Models are performed by using Matlab/Simulink Software. The simulation results in his paper shows that Lithium-ion battery 1 RC model has more maximum output error of 0.42% than 2 RC Lithium-ion battery model in constant current condition and the maximum output error of 1 RC Lithium-ion battery model is 0.18% more than 2 RC Lithium-ion battery model in UDDS Cycle condition. The simulation results also show that in both simple and complex discharging modes, the error in output is much improved in 2 RC lithium ion battery model when compared to 1 RC Lithium-ion battery model. Thus the paper shows for general applications like in portable electronic design like laptops, Lithium-ion battery 1 RC model is the preferred choice and for automotive and space design applications, Lithium-ion 2 RC model is the preferred choice. In this paper, these simulation results for 1 RC and 2 RC Lithium-ion battery models will be very much useful in the application of practical Lithium-ion battery management systems for electric vehicle applications.
An electric circuit model for a lithium-ion battery cell based on automotive ...IJECEIAES
The on-board energy storage system plays a key role in electric vehicles since it directly affects their performance and autonomy. The lithium-ion battery offers satisfactory characteristics that make electric vehicles competitive with conventional ones. This article focuses on modeling and estimating the parameters of the lithium-ion battery cell when used in different electric vehicle drive cycles and styles. The model consists of an equivalent electrical circuit based on a second-order Thevenin model. To identify the parameters of the model, two algorithms were tested: TrustRegion-Reflective and Levenberg-Marquardt. To account for the dynamic behavior of the battery cell in an electric vehicle, this identification is based on measurement data that represents the actual use of the battery in different conditions and driving styles. Finally, the model is validated by comparing simulation results to measurements using the mean square error (MSE) as model performance criteria for the driving cycles (UDDS, LA-92, US06, neural network (NN), and HWFET). The results demonstrate interesting performance mostly for the driving cycles (UDDS and LA-92). This confirms that the model developed is the best solution to be integrated in a battery management system of an electric vehicle.
Performance Evaluation of Modelling and Simulation of Lead Acid Batteries for...IJPEDS-IAES
Lead-acid batteries have been the most widely used energy storage units in
stand-alone photovoltaic (PV) applications. To make a full use of those
batteries and to improve their lifecycle, high performance charger is often
required. The implementation of an advanced charger needs accurate
information on the batteries internal parameters. In this work, we selected
CIEMAT model because of its good performance to deal with the widest
range of lead acid batteries. The performance evaluation of this model is
based on the co-simulation LabVIEW/Multisim. With the intention of
determining the impact of the charging process on batteries, the behaviour of
different internal parameters of the batteries was simulated. During the
charging mode, the value of the current must decrease when the batteries’
state of charge is close to be fully charged.
Optimization of EDM Process Parameters using Response Surface Methodology for...ijtsrd
The present work demonstrates the optimization process of material removal rate MRR of electrical discharge machining EDM by RSM Response Surface Methodology . The work piece material was EN31 tool steel. The pulse on time, pulse off time, pulse current and voltage were the control parameters of EDM. RSM method was used to design the experiment using rotatable central composite design as this is the most widely used experimental design for modeling a second–order response surface. The process has been successfully modeled using response surface methodology RSM and model adequacy checking is also carried out using Minitab software. The second order response models have been validated with analysis of variance. Finally, an attempt has been made to estimate the optimum machining conditions to produce the best possible responses within the experimental constraints. Dr. N. Mahesh Kumar | Mr. P. Chinna Rao ""Optimization of EDM Process Parameters using Response Surface Methodology for AISI D3 Steel"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23535.pdf
Paper URL: https://www.ijtsrd.com/engineering/mechanical-engineering/23535/optimization-of-edm-process-parameters-using-response-surface-methodology-for-aisi-d3-steel/dr-n-mahesh-kumar
Hybrid energy storage system optimal sizing for urban electrical bus regardin...IJECEIAES
This paper proposes an algorithm for sizing the hybrid energy storage system of an urban electrical bus regarding battery thermal behavior. The aim of this study is to get the supercapacitors optimal contribution part in the hybrid energy storage system to keep the battery temperature within its allowable limit. A semi-active parallel topology that uses supercapacitors as a main source of energy is considered. According to the bus mechanical parameters and the ARTEMIS driving cycle, the power and energy demand are calculated. Using mathematical models for the battery, supercapacitors and DC-DC converter, several simulations are performed for different hybridization percentages. While observing the evolution of battery temperature, the most favorable hybridization percentage is defined.
This paper demonstrates a mathematical representation of Photovoltaic (PV) solar cells and hence panels performance. One-diode solar cell model is implemented to simulate the cell and extract the performance indications. The tested PV modules are BP Solar (60 Watt) and Synthesis Power (50 Watts), which are operating in a PV generation system in the University of Anbar - Iraq, College of Applied Sciences. The math model demonstrates Power versus Voltage (P-V) characteristic curves to depict and study various parameters with affecting variations in the PV array performance. The parameters include ambient and cell temperature degrees and solar irradiance (G) level which are the main elements to dictate the productivity of a solar system. G is represented by sun unit (1 sun=1 kW/m2). The outcomes of the simulation model characteristics curves have been compared with curves provided by the tested modules data sheets. MATLAB software has been used to simulate the model and extract the results. This paper also investigated photovoltaic simulation with maximum power point tracking (MPPT) converter to evaluate hence predict the behaviors of the whole photovoltaic DC current generation using PSIM Power Electronics program. The model focuses on the basic components in PV systems; The panel and the DC-DC converter. The modeling outcome data will be used as a reference verifying the performance of the tested modules during the year seasons under the dominating dusty hot weather in western Iraq.
Prediction of li ion battery discharge characteristics at different temperatu...eSAT Journals
Abstract State of charge (SOC) is an important battery parameter which provides a good indication of the useful capacity that can be derived out of a battery system at any given point of time. Li-ion has become state of the art technology for commercial and aerospace applications due to the various advantages that they offer. For spacecrafts requiring long lifetime, SOC estimation is crucial for on-orbit as well as offline data analysis. On-orbit estimation of SOC should be carefully addressed, as this provides information on survivability of battery and also serves as input to Battery Management System (BMS). In addition, detailed offline data analysis of battery electrical characteristics, which indicate the SOC-Voltage relationship is important to assess the performance of the battery under various mission scenarios at both Beginning of life (BOL) and End of Life (EOL) of a spacecraft system. In this work, a hybrid SOC estimation method, incorporating coulomb counting and Unscented Kalman Filter (UKF) is used, to predict the BOL discharge behaviour of an 18650 commercial Li-ion cell at different temperatures and discharge rates. The experimental results are encouraging and the approach gives a prediction error of less than 10%. The study will serve as basis for life assessment of Li-ion cells and batteries used for GEO and LEO missions. Key Words: Li-ion, State of Charge, Unscented Kalman Filter etc…
There is need for an energy storage device capable of transferring high power in transient situations
aboard naval vessels. Currently, batteries are used to accomplish this task, but previous research has
shown that when utilized at high power rates, these devices deteriorate over time causing a loss in lifespan.
It has been shown that a hybrid energy storage configuration is capable of meeting such a demand while
reducing the strain placed on individual components. While designing a custom converter capable of
controlling the power to and from a battery would be ideal for this application, it can be costly to develop
when compared to purchasing commercially available products. Commercially available products offer
limited controllability in exchange for their proven performance and lower cost point - often times only
allowing a system level control input without any way to interface with low level controls that are
frequently used in controller design. This paper proposes the use of fuzzy logic control in order to provide
a system level control to the converters responsible for limiting power to and from the battery. A system
will be described mathematically, modeled in MATLAB/Simulink, and a fuzzy logic controller will be
compared with a typical controller.
One of the common methods that developed to predict state of charge is open circuit voltage (OCV) method. The problem which commonly occurs is to find the correction parameter between open circuit voltage and loaded voltage of the battery. In this research, correlation between state of charge measurement at loaded condition of a Panasonic LC-VA1212NA1, which is a valve-regulated lead acid (VRLA) battery, and open circuit voltage had been analyzed. Based on the results of research, correlation between battery’s measured voltage under loaded condition and open circuit voltage could be approached by two linearization area. It caused by K v ’s values tend to increase when measured voltage under loaded condition V M < 11.64 volt. However, K v values would be relatively stable for every V M ≥ 11.64 volts. Therefore, estimated state of charge value, in respect to loaded battery voltage, would increase slower on V M < 11.64 volts and faster on other range.
Solar Module Modeling, Simulation And Validation Under Matlab / SimulinkIJERA Editor
Solar modules are systems which convert sunlight into electricity using the physics of semiconductors. Mathematical modeling of these systems uses weather data such as irradiance and temperature as inputs. It provides the current, voltage or power as outputs, which allows plot the characteristic giving the intensity I as a function of voltage V for photovoltaic cells. In this work, we have developed a model for a diode of a Photovoltaic module under the Matlab / Simulink environment. From this model, we have plotted the characteristic curves I-V and P-V of solar cell for different values of temperature and sunlight. The validation has been done by comparing the experimental curve with power from a solar panel HORONYA 20W type with that obtained by the model.
In this paper, a complete description of dynamic modeling of proton exchange membrane fuel cell (PEMFC) and solid oxide fuel cell (SOFC) is given. For modeling of fuel cell for software based study, calculation of all voltage drops during chemical reaction of fuel is required. Additionally a flow chart of fuel cell output voltage calculation is also explained which includes fuel cell voltage, double layer charging effect, thermodynamic response and terminal voltage of fuel cell. By using ac to dc converter, the fuel cell power can be connected to load or grid. Based on this study, a mathematical model of fuel cell is developed in simulink software MATLAB to obtain output characteristic of fuel cell. Pratik Mochi | Mihir Bhatt"Dynamic Modeling of PEMFC and SOFC" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11087.pdf http://www.ijtsrd.com/engineering/electrical-engineering/11087/dynamic-modeling-of-pemfc-and-sofc/pratik-mochi
Modeling and validation of lithium-ion battery with initial state of charge ...nooriasukmaningtyas
The modeling of lithium-ion battery is an important element to the management of batteries in industrial applications. Various models have been studied and investigated, ranging from simple to complex. The second-order equivalent circuit model was studied and investigated since the dynamic behavior of the battery is fully characterized. The simulation model was built in Matlab Simulink using the Kirchhoff Laws principle in mathematical equations, while the battery's internal parameters were identified by using the BTS4000 (battery tester) device. To estimate the full state of charge (SOC), the initial state of charge (SOC0) must be identified or measured. Hence, this paper seeks for the SOC estimation by using experimental terminal voltage data and SOC with Matlab lookup table. Then, the simulated terminal voltage, as well as the SOC of the battery are compared and validated against measured data. The maximum relative error of 0.015V and 2% for terminal voltage and SOC respectively shows that the proposed model is accurate and relevant based on the error analysis.
Electrical battery modeling for applications in wireless sensor networks and ...journalBEEI
Modeling the behavior of the battery is non-trivial. Nevertheless, an accurate battery model is required in the design and testing of systems such wireless sensor network (WSN) and internet of things (IoT). This paper presents the one resistive-capacitance (1RC) battery model with simple parameterization technique for nickel metal hydride (NiMH). This model offers a good trade-off between accuracy and parameterization effort. The model’s parameters are extracted through the pulse measurement technique and implemented in a physical and dynamic simulator. Finally, the performance of the model is validated with the real-life NiMH battery by applying current pulses and real wireless sensor node current profiles. The results of the voltage response obtained from both the model and experiments showed excellent accuracy, with difference of less than 2%.
Optimization of EDM Process Parameters using Response Surface Methodology for...ijtsrd
The present work demonstrates the optimization process of material removal rate MRR of electrical discharge machining EDM by RSM Response Surface Methodology . The work piece material was EN31 tool steel. The pulse on time, pulse off time, pulse current and voltage were the control parameters of EDM. RSM method was used to design the experiment using rotatable central composite design as this is the most widely used experimental design for modeling a second–order response surface. The process has been successfully modeled using response surface methodology RSM and model adequacy checking is also carried out using Minitab software. The second order response models have been validated with analysis of variance. Finally, an attempt has been made to estimate the optimum machining conditions to produce the best possible responses within the experimental constraints. Dr. N. Mahesh Kumar | Mr. P. Chinna Rao ""Optimization of EDM Process Parameters using Response Surface Methodology for AISI D3 Steel"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23535.pdf
Paper URL: https://www.ijtsrd.com/engineering/mechanical-engineering/23535/optimization-of-edm-process-parameters-using-response-surface-methodology-for-aisi-d3-steel/dr-n-mahesh-kumar
Hybrid energy storage system optimal sizing for urban electrical bus regardin...IJECEIAES
This paper proposes an algorithm for sizing the hybrid energy storage system of an urban electrical bus regarding battery thermal behavior. The aim of this study is to get the supercapacitors optimal contribution part in the hybrid energy storage system to keep the battery temperature within its allowable limit. A semi-active parallel topology that uses supercapacitors as a main source of energy is considered. According to the bus mechanical parameters and the ARTEMIS driving cycle, the power and energy demand are calculated. Using mathematical models for the battery, supercapacitors and DC-DC converter, several simulations are performed for different hybridization percentages. While observing the evolution of battery temperature, the most favorable hybridization percentage is defined.
This paper demonstrates a mathematical representation of Photovoltaic (PV) solar cells and hence panels performance. One-diode solar cell model is implemented to simulate the cell and extract the performance indications. The tested PV modules are BP Solar (60 Watt) and Synthesis Power (50 Watts), which are operating in a PV generation system in the University of Anbar - Iraq, College of Applied Sciences. The math model demonstrates Power versus Voltage (P-V) characteristic curves to depict and study various parameters with affecting variations in the PV array performance. The parameters include ambient and cell temperature degrees and solar irradiance (G) level which are the main elements to dictate the productivity of a solar system. G is represented by sun unit (1 sun=1 kW/m2). The outcomes of the simulation model characteristics curves have been compared with curves provided by the tested modules data sheets. MATLAB software has been used to simulate the model and extract the results. This paper also investigated photovoltaic simulation with maximum power point tracking (MPPT) converter to evaluate hence predict the behaviors of the whole photovoltaic DC current generation using PSIM Power Electronics program. The model focuses on the basic components in PV systems; The panel and the DC-DC converter. The modeling outcome data will be used as a reference verifying the performance of the tested modules during the year seasons under the dominating dusty hot weather in western Iraq.
Prediction of li ion battery discharge characteristics at different temperatu...eSAT Journals
Abstract State of charge (SOC) is an important battery parameter which provides a good indication of the useful capacity that can be derived out of a battery system at any given point of time. Li-ion has become state of the art technology for commercial and aerospace applications due to the various advantages that they offer. For spacecrafts requiring long lifetime, SOC estimation is crucial for on-orbit as well as offline data analysis. On-orbit estimation of SOC should be carefully addressed, as this provides information on survivability of battery and also serves as input to Battery Management System (BMS). In addition, detailed offline data analysis of battery electrical characteristics, which indicate the SOC-Voltage relationship is important to assess the performance of the battery under various mission scenarios at both Beginning of life (BOL) and End of Life (EOL) of a spacecraft system. In this work, a hybrid SOC estimation method, incorporating coulomb counting and Unscented Kalman Filter (UKF) is used, to predict the BOL discharge behaviour of an 18650 commercial Li-ion cell at different temperatures and discharge rates. The experimental results are encouraging and the approach gives a prediction error of less than 10%. The study will serve as basis for life assessment of Li-ion cells and batteries used for GEO and LEO missions. Key Words: Li-ion, State of Charge, Unscented Kalman Filter etc…
There is need for an energy storage device capable of transferring high power in transient situations
aboard naval vessels. Currently, batteries are used to accomplish this task, but previous research has
shown that when utilized at high power rates, these devices deteriorate over time causing a loss in lifespan.
It has been shown that a hybrid energy storage configuration is capable of meeting such a demand while
reducing the strain placed on individual components. While designing a custom converter capable of
controlling the power to and from a battery would be ideal for this application, it can be costly to develop
when compared to purchasing commercially available products. Commercially available products offer
limited controllability in exchange for their proven performance and lower cost point - often times only
allowing a system level control input without any way to interface with low level controls that are
frequently used in controller design. This paper proposes the use of fuzzy logic control in order to provide
a system level control to the converters responsible for limiting power to and from the battery. A system
will be described mathematically, modeled in MATLAB/Simulink, and a fuzzy logic controller will be
compared with a typical controller.
One of the common methods that developed to predict state of charge is open circuit voltage (OCV) method. The problem which commonly occurs is to find the correction parameter between open circuit voltage and loaded voltage of the battery. In this research, correlation between state of charge measurement at loaded condition of a Panasonic LC-VA1212NA1, which is a valve-regulated lead acid (VRLA) battery, and open circuit voltage had been analyzed. Based on the results of research, correlation between battery’s measured voltage under loaded condition and open circuit voltage could be approached by two linearization area. It caused by K v ’s values tend to increase when measured voltage under loaded condition V M < 11.64 volt. However, K v values would be relatively stable for every V M ≥ 11.64 volts. Therefore, estimated state of charge value, in respect to loaded battery voltage, would increase slower on V M < 11.64 volts and faster on other range.
Solar Module Modeling, Simulation And Validation Under Matlab / SimulinkIJERA Editor
Solar modules are systems which convert sunlight into electricity using the physics of semiconductors. Mathematical modeling of these systems uses weather data such as irradiance and temperature as inputs. It provides the current, voltage or power as outputs, which allows plot the characteristic giving the intensity I as a function of voltage V for photovoltaic cells. In this work, we have developed a model for a diode of a Photovoltaic module under the Matlab / Simulink environment. From this model, we have plotted the characteristic curves I-V and P-V of solar cell for different values of temperature and sunlight. The validation has been done by comparing the experimental curve with power from a solar panel HORONYA 20W type with that obtained by the model.
In this paper, a complete description of dynamic modeling of proton exchange membrane fuel cell (PEMFC) and solid oxide fuel cell (SOFC) is given. For modeling of fuel cell for software based study, calculation of all voltage drops during chemical reaction of fuel is required. Additionally a flow chart of fuel cell output voltage calculation is also explained which includes fuel cell voltage, double layer charging effect, thermodynamic response and terminal voltage of fuel cell. By using ac to dc converter, the fuel cell power can be connected to load or grid. Based on this study, a mathematical model of fuel cell is developed in simulink software MATLAB to obtain output characteristic of fuel cell. Pratik Mochi | Mihir Bhatt"Dynamic Modeling of PEMFC and SOFC" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11087.pdf http://www.ijtsrd.com/engineering/electrical-engineering/11087/dynamic-modeling-of-pemfc-and-sofc/pratik-mochi
Modeling and validation of lithium-ion battery with initial state of charge ...nooriasukmaningtyas
The modeling of lithium-ion battery is an important element to the management of batteries in industrial applications. Various models have been studied and investigated, ranging from simple to complex. The second-order equivalent circuit model was studied and investigated since the dynamic behavior of the battery is fully characterized. The simulation model was built in Matlab Simulink using the Kirchhoff Laws principle in mathematical equations, while the battery's internal parameters were identified by using the BTS4000 (battery tester) device. To estimate the full state of charge (SOC), the initial state of charge (SOC0) must be identified or measured. Hence, this paper seeks for the SOC estimation by using experimental terminal voltage data and SOC with Matlab lookup table. Then, the simulated terminal voltage, as well as the SOC of the battery are compared and validated against measured data. The maximum relative error of 0.015V and 2% for terminal voltage and SOC respectively shows that the proposed model is accurate and relevant based on the error analysis.
Electrical battery modeling for applications in wireless sensor networks and ...journalBEEI
Modeling the behavior of the battery is non-trivial. Nevertheless, an accurate battery model is required in the design and testing of systems such wireless sensor network (WSN) and internet of things (IoT). This paper presents the one resistive-capacitance (1RC) battery model with simple parameterization technique for nickel metal hydride (NiMH). This model offers a good trade-off between accuracy and parameterization effort. The model’s parameters are extracted through the pulse measurement technique and implemented in a physical and dynamic simulator. Finally, the performance of the model is validated with the real-life NiMH battery by applying current pulses and real wireless sensor node current profiles. The results of the voltage response obtained from both the model and experiments showed excellent accuracy, with difference of less than 2%.
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.
Today power electronics play an important role in the electric industry. Power electronic converters are an inseparable component in power systems. One of these converters is DC/AC inverter that is widely used in power systems, industrial applications, electric motor drive and electric vehicles. Due to the tense situation with the complexity that exists in these applications, inverters are exposed to failure. The fault occurring in inverter can cause disturbance and damaging harmonics, cut some industrial processes to in the power system or in the case of electric vehicles, causing irreparable damage. For this reason, detecting faults in the inverter is very important. In this paper, open circuit fault of IGBT in an electric vehicle has been examined. We use three-phase current and wavelet transform to identify the state of the system and we can extract current waveform characteristics. We use neural network algorithm for fault detection and classification. An electric vehicle in 5 different speeds and 5 different torque and a total of 220 failure modes have been studied and tested. The results show the method has been succeeded to detection all forms of defined faults.
A new exact equivalent circuit of the medium voltage three-phase induction m...IJECEIAES
This paper proposes a new equivalent circuit for medium voltage and great power induction motors considering the more complete information given by the manufacturer. A methodology for obtaining the parameters of the equivalent circuit is presented, having this circuit the advantage of allowing the electrical calculation of all the power losses and the realization of the power balance. It is an achievement of this work a new way of calculating and representing the additional losses using a resistance located in the rotor circuit. Then, three types of losses are considered as a part of a power balance: the conventional or joule effect variable losses, the constant losses, and the additional losses. The proposed method is straight and non-iterative. It was applied to a case study motor of 6000 V and 2500 kW located at the Maximo Gomez Power Plant in Cuba.
Electric Vehicles Battery Charging by Estimating SOC using Modified Coulomb C...ijtsrd
Quick and effective battery charging is critical for battery powered vehicles. This paper describes a multilevel charging technique for Li ion batteries used in electric vehicle applications. Instead of a single constant current level, five constant current levels are used to quickly charge the battery. A DC DC converter is used as a current source in the charging circuit for safe and efficient charging. The precise calculation of state of charge SoC is used as an input to enforce the above optimal battery charging technique. The SoC is calculated using a hybrid method that incorporates both the Open Circuit Voltage OCV and Coulomb integral methods. To estimate battery parameters, the Simulink Design Optimization SDO tool is used. The simulations are performed using MATLAB. The difference between the inbuilt battery SoC estimation method and the updated coulomb counting system in terms of SoC estimation is less than 2 . A 3.7 V, 1.1 Ah Li ion battery was used for all of the tests. A. Srilatha | A. Pandian "Electric Vehicles Battery Charging by Estimating SOC using Modified Coulomb Counting" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-2 , February 2022, URL: https://www.ijtsrd.com/papers/ijtsrd49153.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/49153/electric-vehicles-battery-charging-by-estimating-soc-using-modified-coulomb-counting/a-srilatha
Batteries are one of the main elements in Uninterruptable Power Supply (UPSs). To maintain good operation during power failure, UPSs must have adequate energy for their operation. It depends on the reliability and performance of batteries. Owing to low capital cost and wide availability, lead-acid batteries have been used extensively as the main energy source in UPSs. Nevertheless, as batteries technology grown, Nickel Metal Hydride (NiMH) batteries have offered more promising performance than lead-acid batteries; they are installed in various portable electronic devices. This paper provides an overview of the performance of lead-acid and NiMH batteries during the operation of a single-phase UPS. Their performances are studied based on 2 characteristics which are discharge curve and State of Charge (SOC). Based on those characteristics, both batteries have shown different performances. Simulation results have shown that the NiMH battery exhibits better discharge curve with higher voltage capacity and constant discharge current, and it is more reliable to obtain 12V at minimum percentage of SOC than the lead-acid battery.
The Application of Artificial Intelligence Techniques for Modeling and Simula...MohammadMomani26
Abstract— This paper accurately models photovoltaic (PV) arrays based on genetic and Cuckoo Optimization algorithms. These algorithms are used to obtain the parameters of the array model based on a PV cell datasheet information. In this work, a comparison between the two-diode model and the single-diode model is presented. The adopted model is implemented on simulation platforms using MATLAB 2020a environment and it is designed to be of use to power electronics specialists. The mathematical analysis of the model is presented in detail where different cases of different temperature and solar irradiance are adopted. The model was tested and validated with experimental data. Validation and comparison data are taken from the Mutah university PV power plant. The results show that the two-diode model is more accurate than the single diode model, Cuckoo optimization algorithm handles the problem with low iterations and better fitness value as compared with the genetic algorithm. The work in paper is useful for power electronics designers and researchers who need an effective and more accurate way to model and simulate photovoltaic arrays.
A battery charging system & appended zcs (pwm) resonant converter dc dc buck ...hunypink
This paper presents technique for battery charger to achieve efficient performance in charging shaping,
minimum low switching losses and reduction in circuit volume .The operation of circuit charger is switched
with the technique of zero-current-switching, resonant components and append the topology of dc-dc buck.
The proposed novel dc-dc battery charger has advantages with the simplicity, low cost, high efficiency and
with the behaviour of easy control under the ZCS condition accordingly reducing the switching losses. The
detailed study of operating principle and design consideration is performed. A short survey of battery
charging system, capacity demand & its topologies is also presented. In order to compute LC resonant pair
values in conventional converter, the method of characteristic curve is used and electric function equations
are derived from the prototype configuration. The efficient performance of charging shaping is confirmed
through the practical examines and verification of the results is revealed by the MATLAB simulation. The
efficiency is ensured about 89% which is substantially considered being satisfactory performance as
achieved in this paper.
ELECTRIC AND SOLAR VEHICLE-DESIGN AND DEVELOPMENT.pptxsrinivasarao8004
By this training I have learnt So much about Electric Vehicles, advantages, disadvantages, and its Components. Also, I have learnt more about MATLAB, like how to design battery circuit, how to give required amount of current to the battery circuit and how to Identify the resultant Voltage etc. Modeling and simulation of electric vehicle’s battery is done on MATLAB/Simulink. Designed a battery circuit with 9 batteries with a voltage of 3.7V each and we have noticed that state of charge is decreases with respective to the Time. This model can be used to estimate how long the battery can be used in electric vehicles. From the plot of State of Charge is observed that after the vehicle has started running, after some time the graph has decreased in terms of charge stored in the battery. Further from the engine speed and Motor Speed, shows smooth functioning of vehicle without any distortions. This means the graph of SOC with respective to the time shown above decreases with increase in acceleration of the vehicle. Here the current is constant throughout the process because of we have connected the circuit in series, so the voltage and SOC decrease with increase in acceleration of Vehicle.
Fuel Cell Impedance Model Parameters Optimization using a Genetic Algorithm Yayah Zakaria
The objective of this paper is the PEM fuel cell impedance model parameters identification. This work is a part of a larger work which is the diagnosis of the fuel cell which deals with the optimization and the parameters identification of the impedance complex model of the Nexa Ballard 1200 PEM fuel cell. The method used for the identification is a sample genetic algorithm and the proposed impedance model is based on electric parameters, which will be found from a sweeping of well determined frequency bands. In fact, the frequency spectrum is divided into bands according to the behavior of the fuel cell. So, this work is considered a first in the field of impedance spectroscopy So, this work is considered a first in the field of impedance spectroscopy. Indeed, the identification using genetic algorithm requires experimental measures of the fuel cell impedance to optimize and identify the impedance model parameters values. This method is characterized by a good precision compared to the numeric methods. The obtained results prove the effectiveness of this approach.
Fuel Cell Impedance Model Parameters Optimization using a Genetic AlgorithmIJECEIAES
The objective of this paper is the PEM fuel cell impedance model parameters identification. This work is a part of a larger work which is the diagnosis of the fuel cell which deals with the optimization and the parameters identification of the impedance complex model of the Nexa Ballard 1200 W PEM fuel cell. The method used for the identification is a sample genetic algorithm and the proposed impedance model is based on electric parameters, which will be found from a sweeping of well determined frequency bands. In fact, the frequency spectrum is divided into bands according to the behavior of the fuel cell. So, this work is considered a first in the field of impedance spectroscopy So, this work is considered a first in the field of impedance spectroscopy. Indeed, the identification using genetic algorithm requires experimental measures of the fuel cell impedance to optimize and identify the impedance model parameters values. This method is characterized by a good precision compared to the numeric methods. The obtained results prove the effectiveness of this approach.
Similar to A Nonlinear TSNN Based Model of a Lead Acid Battery (20)
Square transposition: an approach to the transposition process in block cipherjournalBEEI
The transposition process is needed in cryptography to create a diffusion effect on data encryption standard (DES) and advanced encryption standard (AES) algorithms as standard information security algorithms by the National Institute of Standards and Technology. The problem with DES and AES algorithms is that their transposition index values form patterns and do not form random values. This condition will certainly make it easier for a cryptanalyst to look for a relationship between ciphertexts because some processes are predictable. This research designs a transposition algorithm called square transposition. Each process uses square 8 × 8 as a place to insert and retrieve 64-bits. The determination of the pairing of the input scheme and the retrieval scheme that have unequal flow is an important factor in producing a good transposition. The square transposition can generate random and non-pattern indices so that transposition can be done better than DES and AES.
Hyper-parameter optimization of convolutional neural network based on particl...journalBEEI
Deep neural networks have accomplished enormous progress in tackling many problems. More specifically, convolutional neural network (CNN) is a category of deep networks that have been a dominant technique in computer vision tasks. Despite that these deep neural networks are highly effective; the ideal structure is still an issue that needs a lot of investigation. Deep Convolutional Neural Network model is usually designed manually by trials and repeated tests which enormously constrain its application. Many hyper-parameters of the CNN can affect the model performance. These parameters are depth of the network, numbers of convolutional layers, and numbers of kernels with their sizes. Therefore, it may be a huge challenge to design an appropriate CNN model that uses optimized hyper-parameters and reduces the reliance on manual involvement and domain expertise. In this paper, a design architecture method for CNNs is proposed by utilization of particle swarm optimization (PSO) algorithm to learn the optimal CNN hyper-parameters values. In the experiment, we used Modified National Institute of Standards and Technology (MNIST) database of handwritten digit recognition. The experiments showed that our proposed approach can find an architecture that is competitive to the state-of-the-art models with a testing error of 0.87%.
Supervised machine learning based liver disease prediction approach with LASS...journalBEEI
In this contemporary era, the uses of machine learning techniques are increasing rapidly in the field of medical science for detecting various diseases such as liver disease (LD). Around the globe, a large number of people die because of this deadly disease. By diagnosing the disease in a primary stage, early treatment can be helpful to cure the patient. In this research paper, a method is proposed to diagnose the LD using supervised machine learning classification algorithms, namely logistic regression, decision tree, random forest, AdaBoost, KNN, linear discriminant analysis, gradient boosting and support vector machine (SVM). We also deployed a least absolute shrinkage and selection operator (LASSO) feature selection technique on our taken dataset to suggest the most highly correlated attributes of LD. The predictions with 10 fold cross-validation (CV) made by the algorithms are tested in terms of accuracy, sensitivity, precision and f1-score values to forecast the disease. It is observed that the decision tree algorithm has the best performance score where accuracy, precision, sensitivity and f1-score values are 94.295%, 92%, 99% and 96% respectively with the inclusion of LASSO. Furthermore, a comparison with recent studies is shown to prove the significance of the proposed system.
A secure and energy saving protocol for wireless sensor networksjournalBEEI
The research domain for wireless sensor networks (WSN) has been extensively conducted due to innovative technologies and research directions that have come up addressing the usability of WSN under various schemes. This domain permits dependable tracking of a diversity of environments for both military and civil applications. The key management mechanism is a primary protocol for keeping the privacy and confidentiality of the data transmitted among different sensor nodes in WSNs. Since node's size is small; they are intrinsically limited by inadequate resources such as battery life-time and memory capacity. The proposed secure and energy saving protocol (SESP) for wireless sensor networks) has a significant impact on the overall network life-time and energy dissipation. To encrypt sent messsages, the SESP uses the public-key cryptography’s concept. It depends on sensor nodes' identities (IDs) to prevent the messages repeated; making security goals- authentication, confidentiality, integrity, availability, and freshness to be achieved. Finally, simulation results show that the proposed approach produced better energy consumption and network life-time compared to LEACH protocol; sensors are dead after 900 rounds in the proposed SESP protocol. While, in the low-energy adaptive clustering hierarchy (LEACH) scheme, the sensors are dead after 750 rounds.
Plant leaf identification system using convolutional neural networkjournalBEEI
This paper proposes a leaf identification system using convolutional neural network (CNN). This proposed system can identify five types of local Malaysia leaf which were acacia, papaya, cherry, mango and rambutan. By using CNN from deep learning, the network is trained from the database that acquired from leaf images captured by mobile phone for image classification. ResNet-50 was the architecture has been used for neural networks image classification and training the network for leaf identification. The recognition of photographs leaves requested several numbers of steps, starting with image pre-processing, feature extraction, plant identification, matching and testing, and finally extracting the results achieved in MATLAB. Testing sets of the system consists of 3 types of images which were white background, and noise added and random background images. Finally, interfaces for the leaf identification system have developed as the end software product using MATLAB app designer. As a result, the accuracy achieved for each training sets on five leaf classes are recorded above 98%, thus recognition process was successfully implemented.
Customized moodle-based learning management system for socially disadvantaged...journalBEEI
This study aims to develop Moodle-based LMS with customized learning content and modified user interface to facilitate pedagogical processes during covid-19 pandemic and investigate how teachers of socially disadvantaged schools perceived usability and technology acceptance. Co-design process was conducted with two activities: 1) need assessment phase using an online survey and interview session with the teachers and 2) the development phase of the LMS. The system was evaluated by 30 teachers from socially disadvantaged schools for relevance to their distance learning activities. We employed computer software usability questionnaire (CSUQ) to measure perceived usability and the technology acceptance model (TAM) with insertion of 3 original variables (i.e., perceived usefulness, perceived ease of use, and intention to use) and 5 external variables (i.e., attitude toward the system, perceived interaction, self-efficacy, user interface design, and course design). The average CSUQ rating exceeded 5.0 of 7 point-scale, indicated that teachers agreed that the information quality, interaction quality, and user interface quality were clear and easy to understand. TAM results concluded that the LMS design was judged to be usable, interactive, and well-developed. Teachers reported an effective user interface that allows effective teaching operations and lead to the system adoption in immediate time.
Understanding the role of individual learner in adaptive and personalized e-l...journalBEEI
Dynamic learning environment has emerged as a powerful platform in a modern e-learning system. The learning situation that constantly changing has forced the learning platform to adapt and personalize its learning resources for students. Evidence suggested that adaptation and personalization of e-learning systems (APLS) can be achieved by utilizing learner modeling, domain modeling, and instructional modeling. In the literature of APLS, questions have been raised about the role of individual characteristics that are relevant for adaptation. With several options, a new problem has been raised where the attributes of students in APLS often overlap and are not related between studies. Therefore, this study proposed a list of learner model attributes in dynamic learning to support adaptation and personalization. The study was conducted by exploring concepts from the literature selected based on the best criteria. Then, we described the results of important concepts in student modeling and provided definitions and examples of data values that researchers have used. Besides, we also discussed the implementation of the selected learner model in providing adaptation in dynamic learning.
Prototype mobile contactless transaction system in traditional markets to sup...journalBEEI
One way to prevent and reduce the spread of the covid-19 pandemic is through physical distancing program. This research aims to develop a prototype contactless transaction system using digital payment mechanisms and QR code technology that will be applied in traditional markets. The method used in the development of electronic market systems is a prototype approach. The application of QR code and digital payments are used as a solution to minimize money exchange contacts that are common in traditional markets. The results showed that the system built was able to accelerate and facilitate the buying and selling transaction process in traditional market environment. Alpha testing shows that all functional systems are running well. Meanwhile, beta testing shows that the user can very well accept the system that was built. The results of the study also show acceptance of the usefulness of the system being built, as well as the optimism of its users to be able to take advantage of this system both technologically and functionally, so its can be a part of the digital transformation of the traditional market to the electronic market and has become one of the solutions in reducing the spread of the current covid-19 pandemic.
Wireless HART stack using multiprocessor technique with laxity algorithmjournalBEEI
The use of a real-time operating system is required for the demarcation of industrial wireless sensor network (IWSN) stacks (RTOS). In the industrial world, a vast number of sensors are utilised to gather various types of data. The data gathered by the sensors cannot be prioritised ahead of time. Because all of the information is equally essential. As a result, a protocol stack is employed to guarantee that data is acquired and processed fairly. In IWSN, the protocol stack is implemented using RTOS. The data collected from IWSN sensor nodes is processed using non-preemptive scheduling and the protocol stack, and then sent in parallel to the IWSN's central controller. The real-time operating system (RTOS) is a process that occurs between hardware and software. Packets must be sent at a certain time. It's possible that some packets may collide during transmission. We're going to undertake this project to get around this collision. As a prototype, this project is divided into two parts. The first uses RTOS and the LPC2148 as a master node, while the second serves as a standard data collection node to which sensors are attached. Any controller may be used in the second part, depending on the situation. Wireless HART allows two nodes to communicate with each other.
Implementation of double-layer loaded on octagon microstrip yagi antennajournalBEEI
A double-layer loaded on the octagon microstrip yagi antenna (OMYA) at 5.8 GHz industrial, scientific and medical (ISM) Band is investigated in this paper. The double-layer consist of two double positive (DPS) substrates. The OMYA is overlaid with a double-layer configuration were simulated, fabricated and measured. A good agreement was observed between the computed and measured results of the gain for this antenna. According to comparison results, it shows that 2.5 dB improvement of the OMYA gain can be obtained by applying the double-layer on the top of the OMYA. Meanwhile, the bandwidth of the measured OMYA with the double-layer is 14.6%. It indicates that the double-layer can be used to increase the OMYA performance in term of gain and bandwidth.
The calculation of the field of an antenna located near the human headjournalBEEI
In this work, a numerical calculation was carried out in one of the universal programs for automatic electro-dynamic design. The calculation is aimed at obtaining numerical values for specific absorbed power (SAR). It is the SAR value that can be used to determine the effect of the antenna of a wireless device on biological objects; the dipole parameters will be selected for GSM1800. Investigation of the influence of distance to a cell phone on radiation shows that absorbed in the head of a person the effect of electromagnetic radiation on the brain decreases by three times this is a very important result the SAR value has decreased by almost three times it is acceptable results.
Exact secure outage probability performance of uplinkdownlink multiple access...journalBEEI
In this paper, we study uplink-downlink non-orthogonal multiple access (NOMA) systems by considering the secure performance at the physical layer. In the considered system model, the base station acts a relay to allow two users at the left side communicate with two users at the right side. By considering imperfect channel state information (CSI), the secure performance need be studied since an eavesdropper wants to overhear signals processed at the downlink. To provide secure performance metric, we derive exact expressions of secrecy outage probability (SOP) and and evaluating the impacts of main parameters on SOP metric. The important finding is that we can achieve the higher secrecy performance at high signal to noise ratio (SNR). Moreover, the numerical results demonstrate that the SOP tends to a constant at high SNR. Finally, our results show that the power allocation factors, target rates are main factors affecting to the secrecy performance of considered uplink-downlink NOMA systems.
Design of a dual-band antenna for energy harvesting applicationjournalBEEI
This report presents an investigation on how to improve the current dual-band antenna to enhance the better result of the antenna parameters for energy harvesting application. Besides that, to develop a new design and validate the antenna frequencies that will operate at 2.4 GHz and 5.4 GHz. At 5.4 GHz, more data can be transmitted compare to 2.4 GHz. However, 2.4 GHz has long distance of radiation, so it can be used when far away from the antenna module compare to 5 GHz that has short distance in radiation. The development of this project includes the scope of designing and testing of antenna using computer simulation technology (CST) 2018 software and vector network analyzer (VNA) equipment. In the process of designing, fundamental parameters of antenna are being measured and validated, in purpose to identify the better antenna performance.
Transforming data-centric eXtensible markup language into relational database...journalBEEI
eXtensible markup language (XML) appeared internationally as the format for data representation over the web. Yet, most organizations are still utilising relational databases as their database solutions. As such, it is crucial to provide seamless integration via effective transformation between these database infrastructures. In this paper, we propose XML-REG to bridge these two technologies based on node-based and path-based approaches. The node-based approach is good to annotate each positional node uniquely, while the path-based approach provides summarised path information to join the nodes. On top of that, a new range labelling is also proposed to annotate nodes uniquely by ensuring the structural relationships are maintained between nodes. If a new node is to be added to the document, re-labelling is not required as the new label will be assigned to the node via the new proposed labelling scheme. Experimental evaluations indicated that the performance of XML-REG exceeded XMap, XRecursive, XAncestor and Mini-XML concerning storing time, query retrieval time and scalability. This research produces a core framework for XML to relational databases (RDB) mapping, which could be adopted in various industries.
Key performance requirement of future next wireless networks (6G)journalBEEI
Given the massive potentials of 5G communication networks and their foreseeable evolution, what should there be in 6G that is not in 5G or its long-term evolution? 6G communication networks are estimated to integrate the terrestrial, aerial, and maritime communications into a forceful network which would be faster, more reliable, and can support a massive number of devices with ultra-low latency requirements. This article presents a complete overview of potential 6G communication networks. The major contribution of this study is to present a broad overview of key performance indicators (KPIs) of 6G networks that cover the latest manufacturing progress in the environment of the principal areas of research application, and challenges.
Noise resistance territorial intensity-based optical flow using inverse confi...journalBEEI
This paper presents the use of the inverse confidential technique on bilateral function with the territorial intensity-based optical flow to prove the effectiveness in noise resistance environment. In general, the image’s motion vector is coded by the technique called optical flow where the sequences of the image are used to determine the motion vector. But, the accuracy rate of the motion vector is reduced when the source of image sequences is interfered by noises. This work proved that the inverse confidential technique on bilateral function can increase the percentage of accuracy in the motion vector determination by the territorial intensity-based optical flow under the noisy environment. We performed the testing with several kinds of non-Gaussian noises at several patterns of standard image sequences by analyzing the result of the motion vector in a form of the error vector magnitude (EVM) and compared it with several noise resistance techniques in territorial intensity-based optical flow method.
Modeling climate phenomenon with software grids analysis and display system i...journalBEEI
This study aims to model climate change based on rainfall, air temperature, pressure, humidity and wind with grADS software and create a global warming module. This research uses 3D model, define, design, and develop. The results of the modeling of the five climate elements consist of the annual average temperature in Indonesia in 2009-2015 which is between 29oC to 30.1oC, the horizontal distribution of the annual average pressure in Indonesia in 2009-2018 is between 800 mBar to 1000 mBar, the horizontal distribution the average annual humidity in Indonesia in 2009 and 2011 ranged between 27-57, in 2012-2015, 2017 and 2018 it ranged between 30-60, during the East Monsoon, the wind circulation moved from northern Indonesia to the southern region Indonesia. During the west monsoon, the wind circulation moves from the southern part of Indonesia to the northern part of Indonesia. The global warming module for SMA/MA produced is feasible to use, this is in accordance with the value given by the validate of 69 which is in the appropriate category and the response of teachers and students through a 91% questionnaire.
An approach of re-organizing input dataset to enhance the quality of emotion ...journalBEEI
The purpose of this paper is to propose an approach of re-organizing input data to recognize emotion based on short signal segments and increase the quality of emotional recognition using physiological signals. MIT's long physiological signal set was divided into two new datasets, with shorter and overlapped segments. Three different classification methods (support vector machine, random forest, and multilayer perceptron) were implemented to identify eight emotional states based on statistical features of each segment in these two datasets. By re-organizing the input dataset, the quality of recognition results was enhanced. The random forest shows the best classification result among three implemented classification methods, with an accuracy of 97.72% for eight emotional states, on the overlapped dataset. This approach shows that, by re-organizing the input dataset, the high accuracy of recognition results can be achieved without the use of EEG and ECG signals.
Parking detection system using background subtraction and HSV color segmentationjournalBEEI
Manual system vehicle parking makes finding vacant parking lots difficult, so it has to check directly to the vacant space. If many people do parking, then the time needed for it is very much or requires many people to handle it. This research develops a real-time parking system to detect parking. The system is designed using the HSV color segmentation method in determining the background image. In addition, the detection process uses the background subtraction method. Applying these two methods requires image preprocessing using several methods such as grayscaling, blurring (low-pass filter). In addition, it is followed by a thresholding and filtering process to get the best image in the detection process. In the process, there is a determination of the ROI to determine the focus area of the object identified as empty parking. The parking detection process produces the best average accuracy of 95.76%. The minimum threshold value of 255 pixels is 0.4. This value is the best value from 33 test data in several criteria, such as the time of capture, composition and color of the vehicle, the shape of the shadow of the object’s environment, and the intensity of light. This parking detection system can be implemented in real-time to determine the position of an empty place.
Quality of service performances of video and voice transmission in universal ...journalBEEI
The universal mobile telecommunications system (UMTS) has distinct benefits in that it supports a wide range of quality of service (QoS) criteria that users require in order to fulfill their requirements. The transmission of video and audio in real-time applications places a high demand on the cellular network, therefore QoS is a major problem in these applications. The ability to provide QoS in the UMTS backbone network necessitates an active QoS mechanism in order to maintain the necessary level of convenience on UMTS networks. For UMTS networks, investigation models for end-to-end QoS, total transmitted and received data, packet loss, and throughput providing techniques are run and assessed and the simulation results are examined. According to the results, appropriate QoS adaption allows for specific voice and video transmission. Finally, by analyzing existing QoS parameters, the QoS performance of 4G/UMTS networks may be improved.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
2. ISSN: 2302-9285
BEEI, Vol. 7, No. 2, June 2018 : 169 – 175
170
Chemical model is a complex model that considers the typically electrochemical phenomena involved such
as diffusion, polarization and mass transfer within the electrochemical couple [1]-[3]. The chemical model
consists of mathematical models represented by partially differential equations that are difficult to solve
because they require initial and boundary conditions. In addition, these complex models require several
chemical parameters which are difficult to determine. Another model is the empirical model, which is a
classical method based on experimental tests. The performance of the battery is recorded and tabulated. This
type of model does not represent a generic model for all the accumulators because it does not take into
account all the internal parameters, it is necessary to make tests for each type of accumulator.
The simplest and most common model, illustrated in Figure 1, consists of an ideal voltage source V0
(no-load voltage) in series with an internal resistance. Vt(t) is the terminal voltage across the battery. In this
simple model Ri and V0 are considered constant. This model does not consider either the variation of the
internal resistance of the accumulator as a function of the state of charge or of the temperature. This model
can be applied if the dependence of the load state and temperature parameters can be overlooked [4].
However, researchers have arrived at the conclusion that the most accurate battery model is the “Nonlinear
dynamic model”. It is a variant of the Thevenin model that considers the non-linearity of the parameters. In
this model, shown in Figure 2 below, the process of charging and discharging is separated. In addition, all
parameters are dependent on the state of charge of the battery.
Figure 1. Equivalent circuit of Thevenin model Figure 2. Nonlinear model of the battery
The parameters of the model are defined as follows:
C1: Capacity of the accumulator.
R1: Self discharge resistance.
Ric and Rid: Represent the internal resistance due to the electrolyte and the electrodes respectively during
charging and discharging.
The two RC circuits (RCC2 and RdC2) respectively represent the overvoltage at the end of the load
and the sudden drop of the voltage at the end of the discharge. Since all the parameters of this model are
variable (depending on the state of charge or the unloaded voltage), their identification is difficult.
As we have seen, there are different models in the literature [5][6], each of these models has its own
characteristics. The model chosen depends on the application, if we want more precision then we choose a
more detailed model taking into account all the parameters that can affect the performance of the lead acid
battery. The nonlinear dynamic model is very interesting because it has a charge and discharge circuit and all
parameters depend on the state of charge. The Cauer and Foster model [7]-[9] is used much more to represent
the phenomenon of charge transfer and that of diffusion (chemical phenomena).
Extensive comparisons and evaluations with some selected models, generally recognized as reliable
have shown that further efforts are needed to make refinements on the single battery cell model [1]-[12]. The
paper proposes an improved approach based on the time series neural network, in order to obtain an
improved discharge battery modelling using the neuro-procedure processing of the experimental voltage data
using constant current discharge regime. A time series neural network (TSNN) can be usefully exploited to
improve the battery modeling especially at low rate discharge regime. In some operating regimes (Fast
charging/Deep discharging) underestimated and overestimated output values, depending on the simulated
models, lead to failures in cell output voltage prediction. The TSNN model provides more accurate voltage
values compared to the simple mathematical battery cell model, which makes it possible to obtain an
improved low-rate voltage modeling. The main simulation results reported in the paper are compared with
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the experimental and a nonlinear Hammerstein-Wiener based model. The battery modeling was made based
on time series neural network system to simulate it nonlinear behavior.
2. EXPERIMENTAL SETUP
Data collecting is considered as the first and essential part in identification terminology. In order to
compare the presented methods, some battery data were gathered from a commercial automotive 62Ah, 12V,
540A (TUDOR TB620) lead acid battery. As input, a pulse-discharge test was performed. In this test, the
battery was fully charged using constant current/constant voltage profile, then it was discharged using a -4A
pulse current. A “ADS1299EEG-FE Data Acquisition” was used as data acquisition system (DAQ). The
collected DATA are shown in Figure 3.
Figure 3. Experimental data
3. CURRENT MODELS
The current neural net models for lead acid battery output prediction makes use of the feed forward
multi layered perceptron or back propagation algorithms to train the network [10]. Thus, this model cannot
adequately account for the perturbation of the voltage output and thus provides a prediction with a lower
accuracy. With such a configuration, the training phase of the network is faster, however the results
sometimes show a greater deviation from the target.
4. PROPOSED NARX NEURAL NETWORK MODEL ARCHITECTURE
Nonlinear autoregressive exogenous model (NARX) neural network is a variant of Recurrent
Network [11], [12] that has been successfully utilized in time series prediction problems. The major
difference between recurrent neural network (RNN) and TSNN is that RNN allows a weighted feedback
connection between layers of neurons and thereby making it suitable for time series analysis by allowing
lagged values of variables to be considered in model. Although throughout the literature many time series
methods such Autoregressive (AR), Moving Average (MA), Autoregressive Moving Average (ARMA),
Autoregressive Integrated Moving Average (ARIMA), etc. have been applied in various econometrics
problems, these techniques cannot cope with nonlinear problems. NARX on the contrary can efficiently be
used for modelling non-stationary and nonlinear time series. Mathematically input output representation of
nonlinear discrete time series in NARX network is governed by the following Equation 1.
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Figure 4. Current neural network model architecture
(𝑡)=[𝑢(𝑡-𝐷𝑢),…, 𝑢(𝑡 − 1), 𝑢(𝑡), 𝑦(𝑡 − 𝐷𝑦),.., 𝑦(𝑡 − 1)] (1)
where u(t) and g(t) represent input and output of the network at time t. Du and Dy, are the input and
output order, and the function f is a nonlinear function. The function is approximated by TSNN. It is also
possible to have NARX networks with zero input order and a one-dimensional output. i.e., having feedback
from output only. In such cases operation of NARX network is governed by Equation 2.
(𝑡)=Ψ[𝑢(𝑡), 𝑦(𝑡 − 1), …. (𝑡 − 𝐷)] (2)
where Ψ is the mapping function, approximated by standard TSNN.
4.1. Time Series Modelling
The objective of time series forecasting is to predict future values of a time series, Xn+m based on
the observed data to present, X={Xn, Xn-1,…,X1}. A lot of the time series forecasting model assume Xt to
be stationary.
We have performed time series modeling of a lead acid battery using a NARX model. The used
network is dynamic in nature as it has feedback loops (outputs of a neuron fed back to some previous neuron)
and taps (delay lines that feed the network with past values of inputs). The use of a NARX network helps to
increase the accuracy of prediction as well as can be used for real time prediction of state of charge (SOC)
and state of health (SOF).
The model proposed here has one set of exogenous inputs which are the lead acid battery Current.
The target series comprises of the voltage value of the lead acid battery. The output of the neural network is
predicting the battery output current value over the entire target series along with the next value in the series.
This is a curve-fitting problem which is implemented using MATLAB version 2015a. A parallel NARX
network is created using “narxnet” command which helps in increasing the accuracy of the network. Also,
here we have plotted the time series model of a black-box nonlinear model based on Hammerstein-Wiener of
the same lead acid battery for comparison. For the network training phase, we used the “Levenberg-
Marquardt” algorithm which makes it possible to obtain a numerical solution to the problem of minimizing a
function F(x) Equation (3), often nonlinear and dependent on several variables. The algorithm interpolates
the Gauss-Newton algorithm and the gradient algorithm. More stable than that of Gauss-Newton, it finds a
solution even if it is started very far from a minimum. However, for some very regular functions, it can
converge slightly less quickly. The algorithm was developed by Kenneth Levenberg, then published by
Donald Marquardt.
𝐹(𝑥) =
1
2
∑ [𝑓𝑖(𝑥)]2
𝑚
𝑖=1 (3)
4.2. Results of TSNN Modelling
The following Figure 5 present a sample NARX structure [13]-[15] which will be used in this paper.
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Figure 5. Simple NARX structure
Figure 6 graphically represents the association of the actual and predicted values for all training, test
and validation samples. Magnitude of error expressed as difference between actual and predicted values is
also shown in the same Figure. Although visual representation strongly suggests goodness of fit of NARX
network in predicting output voltage, to quantitatively justify the claim, Mean-squared error (MSE) and
regression (R) values are computed for training and test dataset.
Statistics of MSE and R of predictive modelling performance of NARX network on training and test
dataset for all experimental trials are summarized in following Table 1 and Table 2.
Table 1. Performance on Training Dataset
MSE R
7.91567e-7 9.99985e-1
Table 2. Performance on Test Dataset
MSE R
7.91643e-7 9.99845e-1
It is evident from negligible MSE and high R values that the presented NARX network with 2
delays units has predicted battery output voltage as a nonlinear function quite effectively. Error histogram
with 20 bins is displayed in Figure 7.
Figure 6. Visualization of NARX performance Figure 7. Error histogram of NARX modelling
5. NONLINEAR HAMMERSTEIN-WIENER BASED MODEL
When the output of a system depends nonlinearly on its inputs, sometimes it is possible to
decompose the input-output relationship into two or more interconnected elements. In this case, we can
represent the dynamics by a linear transfer function and capture the nonlinearities using nonlinear functions
of inputs and outputs of the linear system. The Hammerstein-Wiener model achieves this configuration as a
series connection of static nonlinear blocks with a dynamic linear block [16].
The number of units in the wavelet network and the sigmoid network was set to 20. The value of the
delay parameter and the number of units in the networks were purposefully varied in order to find the best
configuration for our nonlinear model.
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The results in Figure 8 are obtained by processing experimental data obtained from the battery. “NL
Model1” is the Hammerstein-Wiener model based on wavelet network as output nonlinearity. “NL Model2”
is the Hammerstein-Wiener model based on sigmoid network as output nonlinearity.
Obviously in Figure 8 and Figure 9, “NL Model1” with a fit of 92.05% outperformed “NL Model2”
with a fit of 82.89% due to their difference in terms of output nonlinearity network structure. However,
although the calculated weight functions for both the wavelet and sigmoid networks are optimal in the sense
that they gave the best possible performance. These models must be able to adapt to changes in the ambient
conditions or battery parameters.
Figure 8. Measured and simulated model battery
output
Figure 9. Measured minus simulated models output
6. CONCLUSION & FUTURE SCOPES
The paper present both TSNN based model and Hammerstein-Wiener models in a multivariate
framework to predict the output voltage of a lead acid battery. The study is based on real collected data.
During the process of generating results, it was observed that both sets of techniques generated useful and
efficient predictions of the voltage value. The application of both Hammerstein-Wiener and NARX including
the use of various backpropagation algorithms is quite unique and the non-linear relationship between the
input battery current and the output voltage have been effectively captured.
From the technique point of view, it is observed that the predictive performance of Hammerstein-
Wiener model does not depend on the number of neurons in the hidden layer (nonlinear output). For the
NARX model, neither the number of neurons, nor the training algorithms, significantly affect the
performance.
The proposed model can be incorporated into complex “Narxnet” models which can be used to
predict the output voltage over a range of time periods or can be used to predict the state of health as well as
the state of charge with high precision. Also, the accuracy of the model can be further increased by allowing
the model to analyze and comprehend the trend of the exogenous input. Also, we can incorporate a fuzzy
system through. The continuation of this work will be the implantation on an FPGA card to build a robust
Battery management system “BMS”.
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