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Intelligent Battery Management Systems for Electric Vehicle Applications
Modeling, Simulation, and Control
- 1st Edition - May 1, 2029
- Editors: Cheng Siong Chin, Caizhi Zhang
- Language: English
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 5 5 6 7 - 3
The future success of electric vehicles relies nearly entirely on the design, modelling and simulation of the vehicle battery management systems. Intelligent Battery Management… Read more
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Request a sales quoteThe future success of electric vehicles relies nearly entirely on the design, modelling and simulation of the vehicle battery management systems. Intelligent Battery Management Systems for Electric Vehicle Applications describes the step-by-step methods for designing successful simulation models for battery management systems (BMS). With a strong emphasis on practical applications and model uncertainties, this title incorporates AI and ML techniques to improve BMS design.
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Guides readers through the process of designing and creating working simulation models using AI and ML approaches
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Provides different smart estimation methods on battery management systems (BMS), including the state of charge and state of health
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Consider thermal modeling of battery cells and multiple energy systems management under different parametric conditions
Postgraduate students, researchers, engineers and software-hardware developers, interested in automotive engineering, energy engineering, renewable energy and energy systems
1. Introduction to Lithium-ion battery
2. Overview of electric vehicle and charging
3. Overview of battery management system
4. Intelligent estimation of battery parameters
4.1. Neural network
4.2. Deep learning
4.3. Optimized machine learning techniques
4.4. Fuzzy neural network and particle swarm optimization algorithm
4.5. Extreme learning machine
4.6. Random forest regression
5. Other battery modelling and simulation with AI
6. Cells balancing of battery
6.1 Fixed shunt resistor method
6.2 Switching shunt resistor method
6.3 Capacitor based active balancing method
6.4 Inductor and transformer based active balancing method
7. Thermal Modelling of battery
7.1. Electro-thermal model
7.2. Parametrization of electro-thermal model
7.3. Model uncertainties
8. Fault diagnosis and degradation of lithium-ion battery
8.1 Battery degradation and RUL prediction
8.2 Uncertainties during degradation
8.3 Quantifying uncertainties
8.4 Real-time fault diagnosis using Improved RBF Neural Network
9. Modelling and control of battery powered underwater vehicle using MATLAB/Simulink
10. Modelling and control of electric vehicle using MATLAB/Simulink
11. Modelling and control of hybrid vehicle with fuel cell using MATLAB/Simulink
12. Modeling and simulating battery for electric vehicle using Modelica
13. Modelling of Lithium–Ion Battery for Aerospace Applications using MATLAB/Simulink
14. Modelling of a Small Unmanned Battery Powered Tailsitter Drone using MATLAB/Simulink
15. References
16. Appendices
- Language: English
- Edition: 1
- Published: May 1, 2029
- Imprint: Elsevier
- eBook ISBN: 9780443155673
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Cheng Siong Chin
Cheng Siong Chin is an Associate Professor at Newcastle University. He received his Ph.D. in Applied Control Engineering at Research Robotics Centre in Nanyang Technological University in 2008 and M.Sc. (Distinction) in Advanced Control and Systems Engineering from The University of Manchester in 2001. He worked in the consumer electronics industry for a few years before moving into academia. He currently holds 3 U.S. Patents in electronics test systems. His research interests include intelligent systems modeling and designing complex systems under uncertain environments such as marine electric vehicles, energy storage systems, and acoustic systems. He is an author/co-author of over 100 peer-reviewed papers on journals and conference proceedings. He was an elected Vice-Chairman for the IEEE Oceanic Engineering Society Singapore Section, Associate Editor for IEEE Access Journal, and IEEE Transportation Electrification Community (TEC) eNewsletter. He has served as General Chair, Session Chair, and Technical Committee in various international conferences.
CZ
Caizhi Zhang
Caizhi Zhang received their Ph.D. degree in thermal dynamics and fuel cells from the School of Mechanical and Aerospace Engineering, Nanyang Technological University (NTU), Singapore, in 2016. He joined as a Professor with Chongqing University (CQU), Chongqing, China, in September 2016. Before that, he was a Research Associate and a Research Fellow with NTU. He is currently a supervisor of doctoral students and the Leader of the Fuel Cell Vehicle Laboratory, School of Automotive Engineering, CQU. He is also a Researcher with the State Key Laboratory of Mechanical Transmissions and the Chongqing Automotive Collaborative Innovation Centre, CQU. He has extensive experience in fuel cell and fuel cell system since September 2008. He participated and oversaw more than 10 national-, provincial-, and ministerial-level projects, such as 2 new energy vehicle projects of the National Key Research and Development Program in 2018 and 1 project of the Youth National Foundation of China.