This document describes the model-based development process for hybrid control unit software for a parallel hybrid vehicle with a compressed natural gas engine. It involves multiple stages of testing using simulation and hardware-in-the-loop testing before implementation in the prototype vehicle. The development process emphasizes modular modeling of the vehicle and environment and uses automatic code generation to enable testing at different stages.
A portable hardware in-the-loop device for automotive diagnostic control systemsISA Interchange
In-vehicle driving tests for evaluating the performance and diagnostic functionalities of engine control systems are often time consuming, expensive, and not reproducible. Using a hardware-in-the-loop (HIL) simulation approach, new control strategies and diagnostic functions on a controller area network (CAN) line can be easily tested in real time, in order to reduce the effort and the cost of the testing phase. Nowadays, spark ignition engines are controlled by an electronic control unit (ECU) with a large number of embedded sensors and actuators. In order to meet the rising demand of lower emissions and fuel consumption, an increasing number of control functions are added into such a unit. This work aims at presenting a portable electronic environment system, suited for HIL simulations, in order to test the engine control software and the diagnostic functionality on a CAN line, respectively, through non-regression and diagnostic tests. The performances of the proposed electronic device, called a micro hardware-in-the-loop system, are presented through the testing of the engine management system software of a 1.6 l Fiat gasoline engine with variable valve actuation for the ECU development version.
For Induction motor is a system that works at their speed, nevertheless there are applications at which the speed operations are needed. The control of range of speed of induction motor techniques is available. The robust control is used with induction motor and the performance of the system with the controller will be improved. The mathematical model to the controller, which were coded in MATLAB. The modeling and controller will be shown by the conditions of robustness of be less than one.
Parallel distribution compensation PID based on Takagi-Sugeno fuzzy model app...IJECEIAES
This paper presents a new technique for a Takagi-Sugeno (TS) fuzzy parallels distribution compensation-PID'S (TSF-PDC-PID'S) to improve the performance of egyptian load frequency control (ELFC). In this technique, the inputs to a TS fuzzy model are the parameters of the change of operating points. The TS fuzzy model can definite the suitable PID control for a certain operating point. The parameters of PID'S controllers are obtained by ant colony optimization (ACO) technique in each operating point based on an effective cost function. The system controlled by the proposed TSF-PDCPID’S is investigated under different types of disturbances, uncertainty and parameters variations. The simulation results ensure that the TSF-PDC-PID'S can update the suitable PID controller at several operating points so, it has a good dynamic response under many types of disturbances compared to fixed optimal PID controller.
Towards Rapid Implementation of Adaptive Robotic SystemsMeshDynamics
Current automation design practice produces expensive one-of-a-kind installations where the system cannot be easily modified to
meet changing demands or advancements in technology. It is imperative that we design robot systems to be modular, portable and
easily re-configurable in order to reduce the design lead times and life cycle costs of providing automation alternatives.
The Unified Tele-robotics Architecture Program (UTAP) was developed under the sponsorship of the US Air Force Robotics and
Automation Center of Excellence. A goal of the program was to define and develop prototypes of commonly used software building
blocks for sensor guided real time embedded control of telerobotic devices. Standard building blocks and a non-proprietary
communication protocols would provide the Air Force and specifically the Logistic Centers with a support infrastructure designed to
rapidly and efficiently build and maintain mission critical automation systems.
An Integrated Prototyping Environment For Programmable AutomationMeshDynamics
We are implementing a rapid prototyping environment for robotic systems, based on tenets of modularity,
reconfigurability and extendibility that may help build robot systems "faster, better and cheaper". Given a task
specification, (e.g. repair brake assembly), the user browses through a library of building blocks that include both
hardware and software components. Software advisors or critics recommend how blocks may be "snapped" together to
speedily construct alternative ways to satisfy task requirements. Mechanisms to allow "swapping" competing modules
for comparative test and evaluation studies are also included in the prototyping environment. After some iterations, a
stable configuration or "wiring diagram" emerges. This customized version of the general prototyping environment still
contains all the hooks needed to incorporate future improvements in component technologies and to obviate unplanned obsolescence...
Design and Implementation of High Resolution Data Acquisition Systemijsrd.com
Fuel cell stacks containing hundreds of individual cells are capable of generating high voltage and current values needed for transportation, commercial, residential, portable and industrial power applications. Although majority of hydrogen produced today comes from reformulated natural gas generated through a process that creates a significant amount of carbon dioxide, fuel cell is still a viable energy source for the future electrical power applications. One of the hard cases of the fuel-cell power systems is proper monitoring, instrumentation and data acquisition of system parameters such as fuel flow into the system, AC and DC voltage values, load current, humidity, power, pressure, temperature, fuel utilization, overall system efficiency, noise, etc. Fuel cell test systems must precisely monitor and control the aforementioned hundreds of measurements in real-time. It is necessary to have an instrumentation system which is able to monitor and control fuel cell operation under varying conditions and accurately get information relating to real-time performance and operational characteristics to calculate fuel cell efficiency correctly. Instrumentation and interface systems must also provide flexible data acquisition, monitoring, and control capability to precisely control fuel cell operation. Therefore, a typical fuel cell test system requires high-resolution, high-voltage input, isolation, and waveform acquisition capability. The objective of this applied research project is design and implementation of a high-resolution data acquisition and interface module for a 500 W Hydrogen fuel cell power station using LabVIEW ™ PDS v8.20 software and field point based data acquisition modules.
A portable hardware in-the-loop device for automotive diagnostic control systemsISA Interchange
In-vehicle driving tests for evaluating the performance and diagnostic functionalities of engine control systems are often time consuming, expensive, and not reproducible. Using a hardware-in-the-loop (HIL) simulation approach, new control strategies and diagnostic functions on a controller area network (CAN) line can be easily tested in real time, in order to reduce the effort and the cost of the testing phase. Nowadays, spark ignition engines are controlled by an electronic control unit (ECU) with a large number of embedded sensors and actuators. In order to meet the rising demand of lower emissions and fuel consumption, an increasing number of control functions are added into such a unit. This work aims at presenting a portable electronic environment system, suited for HIL simulations, in order to test the engine control software and the diagnostic functionality on a CAN line, respectively, through non-regression and diagnostic tests. The performances of the proposed electronic device, called a micro hardware-in-the-loop system, are presented through the testing of the engine management system software of a 1.6 l Fiat gasoline engine with variable valve actuation for the ECU development version.
For Induction motor is a system that works at their speed, nevertheless there are applications at which the speed operations are needed. The control of range of speed of induction motor techniques is available. The robust control is used with induction motor and the performance of the system with the controller will be improved. The mathematical model to the controller, which were coded in MATLAB. The modeling and controller will be shown by the conditions of robustness of be less than one.
Parallel distribution compensation PID based on Takagi-Sugeno fuzzy model app...IJECEIAES
This paper presents a new technique for a Takagi-Sugeno (TS) fuzzy parallels distribution compensation-PID'S (TSF-PDC-PID'S) to improve the performance of egyptian load frequency control (ELFC). In this technique, the inputs to a TS fuzzy model are the parameters of the change of operating points. The TS fuzzy model can definite the suitable PID control for a certain operating point. The parameters of PID'S controllers are obtained by ant colony optimization (ACO) technique in each operating point based on an effective cost function. The system controlled by the proposed TSF-PDCPID’S is investigated under different types of disturbances, uncertainty and parameters variations. The simulation results ensure that the TSF-PDC-PID'S can update the suitable PID controller at several operating points so, it has a good dynamic response under many types of disturbances compared to fixed optimal PID controller.
Towards Rapid Implementation of Adaptive Robotic SystemsMeshDynamics
Current automation design practice produces expensive one-of-a-kind installations where the system cannot be easily modified to
meet changing demands or advancements in technology. It is imperative that we design robot systems to be modular, portable and
easily re-configurable in order to reduce the design lead times and life cycle costs of providing automation alternatives.
The Unified Tele-robotics Architecture Program (UTAP) was developed under the sponsorship of the US Air Force Robotics and
Automation Center of Excellence. A goal of the program was to define and develop prototypes of commonly used software building
blocks for sensor guided real time embedded control of telerobotic devices. Standard building blocks and a non-proprietary
communication protocols would provide the Air Force and specifically the Logistic Centers with a support infrastructure designed to
rapidly and efficiently build and maintain mission critical automation systems.
An Integrated Prototyping Environment For Programmable AutomationMeshDynamics
We are implementing a rapid prototyping environment for robotic systems, based on tenets of modularity,
reconfigurability and extendibility that may help build robot systems "faster, better and cheaper". Given a task
specification, (e.g. repair brake assembly), the user browses through a library of building blocks that include both
hardware and software components. Software advisors or critics recommend how blocks may be "snapped" together to
speedily construct alternative ways to satisfy task requirements. Mechanisms to allow "swapping" competing modules
for comparative test and evaluation studies are also included in the prototyping environment. After some iterations, a
stable configuration or "wiring diagram" emerges. This customized version of the general prototyping environment still
contains all the hooks needed to incorporate future improvements in component technologies and to obviate unplanned obsolescence...
Design and Implementation of High Resolution Data Acquisition Systemijsrd.com
Fuel cell stacks containing hundreds of individual cells are capable of generating high voltage and current values needed for transportation, commercial, residential, portable and industrial power applications. Although majority of hydrogen produced today comes from reformulated natural gas generated through a process that creates a significant amount of carbon dioxide, fuel cell is still a viable energy source for the future electrical power applications. One of the hard cases of the fuel-cell power systems is proper monitoring, instrumentation and data acquisition of system parameters such as fuel flow into the system, AC and DC voltage values, load current, humidity, power, pressure, temperature, fuel utilization, overall system efficiency, noise, etc. Fuel cell test systems must precisely monitor and control the aforementioned hundreds of measurements in real-time. It is necessary to have an instrumentation system which is able to monitor and control fuel cell operation under varying conditions and accurately get information relating to real-time performance and operational characteristics to calculate fuel cell efficiency correctly. Instrumentation and interface systems must also provide flexible data acquisition, monitoring, and control capability to precisely control fuel cell operation. Therefore, a typical fuel cell test system requires high-resolution, high-voltage input, isolation, and waveform acquisition capability. The objective of this applied research project is design and implementation of a high-resolution data acquisition and interface module for a 500 W Hydrogen fuel cell power station using LabVIEW ™ PDS v8.20 software and field point based data acquisition modules.
Tracy–Widom distribution based fault detection approach: Application to aircr...ISA Interchange
The fault detection approach based on the Tracy–Widom distribution is presented and applied to the aircraft flight control system. An operative method of testing the innovation covariance of the Kalman filter is proposed. The maximal eigenvalue of the random Wishart matrix is used as the monitoring statistic, and the testing problem is reduced to determine the asymptotics for the largest eigenvalue of the Wishart matrix. As a result, an algorithm for testing the innovation covariance based on the Tracy–Widom distribution is proposed. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model is considered, and detection of sensor and control surface faults in the flight control system which affect the innovation covariance, are examined.
Analysis and investigation of different advanced control strategies for high-...TELKOMNIKA JOURNAL
Induction motor (IM) drives have received a strong interest from researchers and industry particularly for high-performance AC drives through vector control method. With the advancement in power electronics and digital signal processing(DSP), high capability processors allow the implementation of advanced control techniques for motor drives such as model predictive control (MPC). In this paper, design, analysis and investigation of two different MPC techniques applied to IM drives; themodel predictive torque control (MPTC) and model predictive current control (MPCC) are presented. The two techniques are designed in Matlab/Simulink environment and compared interm of operation in different operating conditions. Moreover, a comparisonof these techniques with field-oriented control (FOC) and direct torque control (DTC) is conducted based on simulation studies with PI speed controller for all control techniques. Based on the analysis, the MPC techniques demonstrates a better result compared with the FOC and DTC in terms of speed, torque and current responses in transient and steady-state conditions.
Dynamic task scheduling on multicore automotive ec usVLSICS Design
Automobile manufacturers are controlled by stringent govt. regulations for safety and fuel emissions and
motivated towards adding more advanced features and sophisticated applications to the existing electronic
system. Ever increasing customer’s demands for high level of comfort also necessitate providing even more
sophistication in vehicle electronics system. All these, directly make the vehicle software system more
complex and computationally more intensive. In turn, this demands very high computational capability of
the microprocessor used in electronic control unit (ECU). In this regard, multicore processors have
already been implemented in some of the task rigorous ECUs like, power train, image processing and
infotainment. To achieve greater performance from these multicore processors, parallelized ECU software
needs to be efficiently scheduled by the underlaying operating system for execution to utilize all the
computational cores to the maximum extent possible and meet the real time constraint. In this paper, we
propose a dynamic task scheduler for multicore engine control ECU that provides maximum CPU
utilization, minimized preemption overhead, minimum average waiting time and all the tasks meet their
real time deadlines while compared to the static priority scheduling suggested by Automotive Open Systems
Architecture (AUTOSAR).
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.
Low Speed Estimation in Sensorless Direct Torque Controlled Induction Motor D...IJPEDS-IAES
Sensorless Direct Torque Control (DTC) is a powerful control scheme for
high performance control of induction motor (IM) drives, which provides
very quick dynamic response with simple structure and a decoupled control
of torque and flux. The performance of the DTC drive greatly depends on the
accuracy of the estimated flux components, torque and speed, using
monitored stator voltages and currents. Low speed estimation is a great
challenge because of the presence of transient offset, drift and domination of
ohmic voltage drop.Extended Kalman filter (EKF) is a non linear adaptive
filter which performs the process of finding the best estimate from the noisy
data based on state space technique and recursive algorithm.This paper
mainly focuses on the accurate estimation of speed ranging from very low
speed to rated speed using the equation of motion. A new state space model
of the IM is developed for estimation in EKF, with load torque as an input
variable and not as an estimated quantity which is the case in most previous
studies.The developed algorithm is validated using MATLAB-Simulink
platform for speeds ranging from low speed to rated speed at rated torque and
at various torque conditions. An exhaustive analysis is carried out to validate
the performance of DTC Induction motor drive especially at the low speeds.
The results are promising for accurate estimation of speed ranging from low
speed to rated speed using EKF.
The second presentation in applying VDI 2206 in design of mechatronics methodology. In this presentation my colleagues and I are defining the product and specifications.
In this paper, the optimal control problem of a nonlinear robot manipulator in absence of holonomic constraint force based on the point of view of adaptive dynamic programming (ADP) is presented. To begin with, the manipulator was intervened by exact linearization. Then the framework of ADP and Robust Integral of the Sign of the Error (RISE) was developed. The ADP algorithm employs Neural Network technique to tune simultaneously the actor-critic network to approximate the control policy and the cost function, respectively. The convergence of weight as well as position tracking control problem was considered by theoretical analysis. Finally, the numerical example is considered to illustrate the effectiveness of proposed control design.
This is a first of a series of presentations illustrating implementation of VDI 2206 guidelines into a five weeks project carried with my colleagues in post graduate course lectured by Dr. Mohamed Abdelaziz.
Tracy–Widom distribution based fault detection approach: Application to aircr...ISA Interchange
The fault detection approach based on the Tracy–Widom distribution is presented and applied to the aircraft flight control system. An operative method of testing the innovation covariance of the Kalman filter is proposed. The maximal eigenvalue of the random Wishart matrix is used as the monitoring statistic, and the testing problem is reduced to determine the asymptotics for the largest eigenvalue of the Wishart matrix. As a result, an algorithm for testing the innovation covariance based on the Tracy–Widom distribution is proposed. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model is considered, and detection of sensor and control surface faults in the flight control system which affect the innovation covariance, are examined.
Analysis and investigation of different advanced control strategies for high-...TELKOMNIKA JOURNAL
Induction motor (IM) drives have received a strong interest from researchers and industry particularly for high-performance AC drives through vector control method. With the advancement in power electronics and digital signal processing(DSP), high capability processors allow the implementation of advanced control techniques for motor drives such as model predictive control (MPC). In this paper, design, analysis and investigation of two different MPC techniques applied to IM drives; themodel predictive torque control (MPTC) and model predictive current control (MPCC) are presented. The two techniques are designed in Matlab/Simulink environment and compared interm of operation in different operating conditions. Moreover, a comparisonof these techniques with field-oriented control (FOC) and direct torque control (DTC) is conducted based on simulation studies with PI speed controller for all control techniques. Based on the analysis, the MPC techniques demonstrates a better result compared with the FOC and DTC in terms of speed, torque and current responses in transient and steady-state conditions.
Dynamic task scheduling on multicore automotive ec usVLSICS Design
Automobile manufacturers are controlled by stringent govt. regulations for safety and fuel emissions and
motivated towards adding more advanced features and sophisticated applications to the existing electronic
system. Ever increasing customer’s demands for high level of comfort also necessitate providing even more
sophistication in vehicle electronics system. All these, directly make the vehicle software system more
complex and computationally more intensive. In turn, this demands very high computational capability of
the microprocessor used in electronic control unit (ECU). In this regard, multicore processors have
already been implemented in some of the task rigorous ECUs like, power train, image processing and
infotainment. To achieve greater performance from these multicore processors, parallelized ECU software
needs to be efficiently scheduled by the underlaying operating system for execution to utilize all the
computational cores to the maximum extent possible and meet the real time constraint. In this paper, we
propose a dynamic task scheduler for multicore engine control ECU that provides maximum CPU
utilization, minimized preemption overhead, minimum average waiting time and all the tasks meet their
real time deadlines while compared to the static priority scheduling suggested by Automotive Open Systems
Architecture (AUTOSAR).
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.
Low Speed Estimation in Sensorless Direct Torque Controlled Induction Motor D...IJPEDS-IAES
Sensorless Direct Torque Control (DTC) is a powerful control scheme for
high performance control of induction motor (IM) drives, which provides
very quick dynamic response with simple structure and a decoupled control
of torque and flux. The performance of the DTC drive greatly depends on the
accuracy of the estimated flux components, torque and speed, using
monitored stator voltages and currents. Low speed estimation is a great
challenge because of the presence of transient offset, drift and domination of
ohmic voltage drop.Extended Kalman filter (EKF) is a non linear adaptive
filter which performs the process of finding the best estimate from the noisy
data based on state space technique and recursive algorithm.This paper
mainly focuses on the accurate estimation of speed ranging from very low
speed to rated speed using the equation of motion. A new state space model
of the IM is developed for estimation in EKF, with load torque as an input
variable and not as an estimated quantity which is the case in most previous
studies.The developed algorithm is validated using MATLAB-Simulink
platform for speeds ranging from low speed to rated speed at rated torque and
at various torque conditions. An exhaustive analysis is carried out to validate
the performance of DTC Induction motor drive especially at the low speeds.
The results are promising for accurate estimation of speed ranging from low
speed to rated speed using EKF.
The second presentation in applying VDI 2206 in design of mechatronics methodology. In this presentation my colleagues and I are defining the product and specifications.
In this paper, the optimal control problem of a nonlinear robot manipulator in absence of holonomic constraint force based on the point of view of adaptive dynamic programming (ADP) is presented. To begin with, the manipulator was intervened by exact linearization. Then the framework of ADP and Robust Integral of the Sign of the Error (RISE) was developed. The ADP algorithm employs Neural Network technique to tune simultaneously the actor-critic network to approximate the control policy and the cost function, respectively. The convergence of weight as well as position tracking control problem was considered by theoretical analysis. Finally, the numerical example is considered to illustrate the effectiveness of proposed control design.
This is a first of a series of presentations illustrating implementation of VDI 2206 guidelines into a five weeks project carried with my colleagues in post graduate course lectured by Dr. Mohamed Abdelaziz.
Automatized testing hil system for agile product-design environmentTritem
The stricter safety requirements in the rail industry – implied by the EN 50128 standard – contribute to an increasing demand for testing rail vehicles and their subsystems, especially vehicle main controllers. Hardware-in-the-Loop method, which is commonly used in automotive and aerospace domains, has proved to be functionally useful. However, such systems would usually exceed the budget of a development project in the railway industry, due to short series manufacturing and multiple vehicle variants. To deal with this problem Tritem Microsystems has designed Virtual-HIL which decreases the overall cost and increases portability of this kind of a system. In this paper, we present both the classic approach and our groundbreaking system, along with a use case from one of our recent projects together with an automated testing framework built on the top of ourVirtual HIL.
SOFTWARE AND HARDWARE DESIGN CHALLENGES IN AUTOMOTIVE EMBEDDED SYSTEMVLSICS Design
Modern automotives integrate large amount of electronic devices to improve the driving safety and comfort. This growing number of Electronic Control Units (ECUs) with sophisticated software escalates the vehicle system design complexity. In this paper we explain the complexity of ECUs in terms of hardware and software and also we explore the possibility of Common Object Request Broker Architecture (CORBA) architecture for the integration of add-on software in ECUs. This reduces the complexity of the embedded system in vehicles and eases the ECU integration by reducing the total number of ECUs in the vehicles.
This paper presents the modeling and real-time simulation of an induction motor. The RT- LAB simulation software enables the parallel simulation of power drives and electric circuits on clusters of a PC running QNX or RT- Linux operating systems at sample time below 10 µs. Using standard Simulink models including SimPowerSystems models, RT-LAB build computation and communication tasks are necessary to make parallel simulation of electrical systems. The code generated by the Real-Time Workshop of RT- LAB is linked to the OP5600 digital real-time simulator. A case study example of real-time simulation of an induction motor system is presented.This paper discusses methods to overcome the challenges of real-time simulation of an induction motor system synchronizing with a real-time clock.
AN EFFICIENT HYBRID SCHEDULER USING DYNAMIC SLACK FOR REAL-TIME CRITICAL TASK...ijesajournal
Task intensive electronic control units (ECUs) in automotive domain, equipped with multicore processors ,
real time operating systems (RTOSs) and various application software, should perform efficiently and time
deterministically. The parallel computational capability offered by this multicore hardware can only be
exploited and utilized if the ECU application software is parallelized. Having provided with such
parallelized software, the real time operating system scheduler component should schedule the time critical
tasks so that, all the computational cores are utilized to a greater extent and the safety critical deadlines
are met. As original equipment manufacturers (OEMs) are always motivated towards adding more
sophisticated features to the existing ECUs, a large number of task sets can be effectively scheduled for
execution within the bounded time limits. In this paper, a hybrid scheduling algorithm has been proposed,
that meticulously calculates the running slack of every task and estimates the probability of meeting
deadline either being in the same partitioned queue or by migrating to another. This algorithm was run and
tested using a scheduling simulator with different real time task models of periodic tasks . This algorithm
was also compared with the existing static priority scheduler, which is suggested by Automotive Open
Systems Architecture (AUTOSAR). The performance parameters considered here are, the % of core
utilization, average response time and task deadline missing rate. It has been verified that, this proposed
algorithm has considerable improvements over the existing partitioned static priority scheduler based on
each performance parameter mentioned above.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
1. Model-based Development of Hybrid-specific ECU Software
for a Hybrid Vehicle with Compressed-Natural-Gas Engine
Dipl.-Ing. Tobias Mauk IVK, Universität Stuttgart
Pfaffenwaldring 12, 70569 Stuttgart
Telephone: +49 711 685 68129, Fax: +49 711 6773216
eMail: Tobias.Mauk@ivk.uni-stuttgart.de
Dr. phil. nat. Dieter Kraft, Robert Bosch GmbH
Dr.-Ing. Joachim Quarg, Adam Opel GmbH
Dipl.-Ing. Michael Böhm, Universität Stuttgart
Prof. Dr.-Ing. Michael Bargende, Universität Stuttgart
Prof. Dr.-Ing. Hans-Christian Reuss, Universität Stuttgart
Abstract
This paper describes the development of hybrid control software for a parallel hybrid vehicle
with compressed-natural-gas engine. The underlying project is shortly introduced. Then the
software development process is presented with emphasis on different stages of testing and
the requirements for the test environment software. Hereafter the tasks of the hybrid control
software are explained. Finally a short description of the control strategy is given.
Introduction
In 2006 Adam Opel GmbH, Robert Bosch GmbH and Universität Stuttgart joined forces to
build up a prototypical hybrid vehicle with minimal CO2 emissions [1]. The project is
supported by the Federal Ministry of Economics and Technology (Bundesministerium für
Wirtschaft und Technologie). The concept incorporates a down-sized, highly turbocharged
natural-gas engine [2] combined with an electric motor in a parallel hybrid configuration
[3][4]. The vehicle is based on the Astra Caravan. It is equipped with an automated manual
transmission and two friction clutches.
In addition to the control units of the several aggregates like combustion engine, electric
motor and transmission, a superordinate control unit is necessary. This so-called Hybrid
Control Unit (HCU) coordinates the interaction between the aggregates. More detailed, its
2. most important tasks include the intelligent determination of the appropriate operational
mode, the split-up of the desired driving torque between combustion engine and electric
motor, the selection of the appropriate gear and the consideration of the battery state-of-
charge in all its decisions.
Furthermore, the hybrid control unit receives predictive information about the upcoming road
section from a forward-looking unit. This information includes geographical map data like
curves, slopes and other information. It is used by the hybrid control unit to optimize its
strategy.
Lastly, the hybrid control unit operates as a network gateway, as the control units of the
additional hybrid components cannot be connected to the powertrain CAN bus directly due to
their incompatibility. Therefore a second CAN bus is used.
Figure 1 shows the structure of the prototype vehicle powertrain including the most important
control units and the two CAN busses.
Figure 1: Hybrid powertrain including the most important control units
3. Software Development Process
The following section describes aspects of the software development process for the hybrid
control unit. Being able to test the software already at early development stages is very
important in order to identify and correct software design imperfections as early as possible.
As the software development for the hybrid control unit and the construction and assembly of
the prototype vehicle take place simultaneously in order to save time, the software cannot be
tested in the vehicle at early stages. Even if the vehicle was built up earlier, it would be too
risky to perform early tests of the software on the real vehicle hardware. It is therefore
necessary to model and simulate the environment of the hybrid control unit in order to
perform tests. The environment model consists of a vehicle model, a driver model and a
driving cycle. It ought to provide a virtual environment as it will be perceived by the hybrid
control unit later in the real vehicle. This also enables tests of critical software functions
without danger of damaging the vehicle or injuring people.
Due to these requirements an appropriate software development process is defined. For the
development of the software functions a PC-based environment model is used. This approach
saves a lot of time, as the test simulations can be calculated very fast and do not have to be
slowed down to real-time speed. In the PC-based environment an additional CAN bus model
simulates effects like quantisation, time discretisation and bus latency.
In the vehicle the hybrid control software will be executed on the hybrid control unit, which is
in fact a rapid-prototyping ECU. To verify the real-time capability of the hybrid control
software it is exported to that rapid-prototyping ECU using automatic code generation. A
further real-time computer is used to provide the real-time environment model, which is also
generated from the PC-based environment model using automatic code generation. After
connecting the hybrid control unit and the environment simulator, hardware-in-the-loop (HiL)
tests can be performed. The I/O of the hybrid control unit is identical to the one needed in the
real vehicle. An advantage of using real CAN busses at this stage of testing is that also aspects
as bus load and variable bus latency are taken into account. This approach supports an easier
transfer to the real vehicle. Figure 2 shows the HiL simulation setup.
An even higher level of realistic environment for the hybrid control unit can be achieved
using a test bench. Several parts of the environment model are replaced by real hardware
components, e.g. the combustion engine, the electric motor, the clutch between them and the
battery. All affected signal connections in the environment model must also be replaced by
4. connections to signals from the real components. Those components not present in the
hardware setup have to be further on simulated. Also the driver and the driving cycle remain
part of the environment simulation.
Figure 2: Hardware-in-the-loop simulation setup
The last level of performing tests will take place in the prototype vehicle, as soon as the
hybrid control unit has passed all previous tests. No further environment simulation is
necessary at this stage. Figure 3 shows the concept of the presented development process. The
steps need to be iterated.
Essential prerequisite for this development process is a strictly modular structure of the
environment model. This includes the consequent separation of function and interface in
every module. Otherwise it would not be possible to easily use the same function in all the
stages of testing, as the modules have to be interchangeable with real hardware components
on the test bench and the interfaces differ from stage to stage (e.g. real bus vs. simulated bus).
The functionality of the environment model software may not be altered between the different
stages of testing. The same holds for transmission rate, resolution and feasible value range of
the signals. This is ensured by using automatic code generation and the use of a library
5. concept. The interface modules for the different stages are stored in separate model libraries
and linked to the respective function modules, which are also stored in libraries. Thus, code
can be automatically generated for all needed configurations (i.e. PC-based, real-time, test
bench configuration).
Figure 3: Development process: several stages of testing
Defining all the module interfaces in an exact manner and at an early stage is essential for the
success of this development process, as later changes would be very time-consuming,
expensive and error-prone. Additionally the compatibility to old software versions would be
lost. It must be distinguished between physical inter-module connections (i.e. physical
couplings of the corresponding hardware components) and communication signals (mostly
CAN signals and messages). Physical connections are mechanical, electrical or thermal
quantities, for example the actual engine speed and torque or the actual current of the electric
motor.
In this project communication signals are mainly CAN signals. As there are several hundred
different signals, a special “helper tool” was developed to automatically generate a module
with I/O blocks for all the CAN signals out of a CAN communication matrix description file.
6. So every signal on the real bus corresponds to a signal in the model. According to the
distinction between physical and communicational signals, the component modules consist of
two parts: one represents the physical part, and the other one the control unit part of the
respective component. Of course it is not possible to exactly replicate the complete control
unit software of all components into these control unit modules – due to the multitude of
functions in today’s control units –, but fortunately it is not necessary to complete this very
complex and expensive task to that extent. Only those signals which are of special interest for
the hybrid control unit have to be modelled in detail. Three levels of detail are distinguished:
• Some signals are not relevant for the hybrid control unit, so it is sufficient to choose a
constant value for those signals. Irrelevant CAN messages (i.e. messages consisting of not
relevant signals only) are not omitted but still transmitted in order to preserve the correct
bus load. An example for such a message is the tire pressure message.
• Another set of signals is relevant for the hybrid control unit, but only for supervising
purposes, for example the airbag activation status signal. The hybrid control unit has to
switch off the high-voltage electrical system in case of an airbag activation. Reasonable
constant values can be used to model these signals. To test the hybrid control unit these
values may be changed manually.
• The remaining signals are especially relevant for the hybrid control unit and must be
carefully modelled, for example the engine speed and torque signals or the battery
voltage. Of course only a simplified model of the real control unit software is practicable.
Environment Model
In the following section the vehicle model (as part of the environment model) will be
described more detailed, since it is a very important element of the development process. Its
structure is strictly modular, which makes it possible to easily exchange interface modules
between different stages of testing, or to replace component modules by real hardware
components at the test bench. The model is limited to the longitudinal dynamics of the
vehicle. The most important modules and their interfaces are shown in Figure 4. The
transmission and the adjacent clutch C2 are handled together in one module, since they are
controlled by a common control unit. The same holds for the electric motor and the inverter.
7. Figure 4: Module structure of the vehicle model
In addition to the modules shown in Figure 4, there is a CAN bus model, which is only
needed to perform the PC-based tests. It simulates time discretisation, quantisation, bus
latency and sampling effects. It is removed in both real-time test stages, since physical CAN
busses are used here. Without the CAN bus model in the PC-based tests, PC simulation
results deviate from the HiL simulation results. This is critical especially when the CAN bus
is part of a closed loop control. When designing closed loop controllers the dead time caused
by the bus must be taken into account. A good example is the necessary communication
between the engine control unit and transmission control unit during a gear shift operation.
Another example is the driver model. It is implemented as a controller, which uses the
accelerator and the brake pedal to achieve a desired vehicle speed trajectory. Figure 5 shows
the accelerator position in the HiL simulation (using real busses) and in two different PC-
based simulations (with and without the CAN bus model). The curve shapes of the CAN bus
simulation and the HiL simulation (using real CAN busses) are quite similar, remaining
differences are reducible to the inherent non-determinism of CAN busses. However, the
simulation without the CAN bus model reveals noticeable differences. Especially when
accelerating the vehicle, the resulting accelerator pedal positions are higher when the CAN
latencies are not neglected. This may lead to further discrepancies in the behaviour of both
simulations, for example a gear shift might be triggered in one simulation (but not in the
other) because of different pedal positions. So comparability between PC-based simulation
and HiL simulation (including real busses) can only be preserved by using the CAN bus
model in the PC-based simulation. Again, a special helper tool was developed to
automatically generate the CAN bus model due to the large number of messages.
8. Figure 5: Influence of the CAN bus on simulation results
The Hybrid Control Unit Prototype
Thanks to the very good congruence between PC-based and HiL simulation it is possible to
effectively develop the hybrid control software mainly on the PC. Nonetheless it is necessary
to perform regular HiL tests to validate the real-time capability of the software and the correct
operation of the communication between hybrid control unit and its environment.
Due to incompatibilities between different control units it is not sufficient to use only one
CAN bus for the whole powertrain. The control units from the original Astra vehicle are
directly connected via one CAN bus (“Astra bus”). The other control units, which were
added, e.g. engine, battery and electric motor control units, share another CAN bus (“hybrid
bus”). Both busses are separately connected to the hybrid control unit (see Figure 1), which
works as a gateway. For example, the hybrid control unit acts as a virtual engine control unit
towards the other control units on the Astra bus, since the engine control unit is the only
control unit which was removed from that bus. The hybrid control unit collects all CAN
messages that are supposed to reach the engine control unit and passes them to the real engine
control unit, which is connected to the hybrid bus – after having done all necessary translation
and conversion work. Likewise it receives the messages which the engine control unit sends
to the other powertrain control units (e.g. the transmission control unit or the ABS/ESP
control unit) and translates them to the Astra bus.
Apart from the various tasks already mentioned in the introduction, the hybrid control unit has
another important task which goes beyond a normal gateway function. Not only does it have
9. to translate, re-arrange and requantise signals between both CAN busses, some signals even
need to be re-interpreted, i.e. their meaning is altered in the hybrid context. This fact is
explained by means of the following example. In the series-production vehicle the engine
control unit periodically sends the engine speed in a CAN message. This signal is important
for the transmission control unit (which also controls the adjacent clutch C2), since it needs to
know the input (i.e. engine-sided) speed of the clutch. Engine output speed and clutch input
speed are assumed to be always identical (not only equal) – and rightly so, since the
combustion engine is directly attached to the clutch C2 in the series-production vehicle.
However, these two speeds are not necessarily the same in the hybrid vehicle, as the electric
motor and the other clutch C1 are inserted between the engine and the clutch C2 (and C1 may
be open). In this case it is the speed of the electric motor that is identical to the input speed of
clutch C2. So, although the transmission control unit still expects to receive the combustion
engine speed (it does not know it is being hybridised), it must be told the speed of the electric
motor instead. This implies a change in the meaning of signals. There are a number of signals
that must be likewise “redirected” or even manipulated to make the series aggregates work as
required. Another example is the input torque to clutch C2, which is labelled “engine torque”
in the series car, but in the hybridised car it has to be calculated dependent on the engine
torque, the electric motor torque and the status of clutch C1. This approach makes it possible
to hybridise the car without modifying the series components. Needless to say, it is very
important to test this complex software extensively in the PC-based and HiL simulations.
Hybrid Control Strategy Optimizations
Hybrid vehicle concepts in general offer more degrees of freedom for powertrain control
strategies than conventional vehicles. There are different targets which strategies may pursue
[5], mainly saving fuel, improving driveability or variably weighted mixtures of both. Also
other targets are possible, such as improving comfort or optimizing battery durability. The
strategy in this project focuses on minimizing CO2 emissions (which is quite close to saving
fuel respectively natural gas) while complying current and future emission limits.
Therefore the strategy software is supported by a forward-looking unit which provides
predictive information about the assumed upcoming road section, such as data about curves,
slopes and other information. This data is used for optimization calculations. The strategy
software calculates (approximates) a trajectory of gear shifts, state-of-charge and torque
10. distribution between engine and electric motor (with a variable time horizon of a few
minutes), which is supposed to be optimal in the sense of minimized CO2 emissions.
Summary
A development process for hybrid-specific control software was presented in this paper.
Emphasis was put on the multi-stage testing reaching from PC-based non-real-time simulation
to real-time HiL simulation, and tests including several real aggregates on a test bench.
Important prerequisites were described, especially the exact definition of different interfaces.
Afterwards the tasks of the hybrid control software were explained, especially the extended
gateway function. Finally the hybrid control strategy was shortly presented.
References
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