Battery System Modeling provides advances on the modeling of lithium-ion batteries. Offering step-by-step explanations, the book systematically guides the reader through the modeling of state of charge estimation, energy prediction, power evaluation, health estimation, and active control strategies. Using applications alongside practical case studies, each chapter shows the reader how to use the modeling tools provided. Moreover, the chemistry and characteristics are described in detail, with algorithms provided in every chapter. Providing a technical reference on the design and application of Li-ion battery management systems, this book is an ideal reference for researchers involved in batteries and energy storage. Moreover, the step-by-step guidance and comprehensive introduction to the topic makes it accessible to audiences of all levels, from experienced engineers to graduates. - Explains how to model battery systems, including equivalent, electrical circuit and electrochemical nernst modeling - Includes comprehensive coverage of battery state estimation methods, including state of charge estimation, energy prediction, power evaluation and health estimation - Provides a dedicated chapter on active control strategies

Shunli Wang Ph.D is a leading expert on new energy research, DTlab head, New energy measurement & control research team leader. Measurement & control processing is conducted on the needs of the high power Li-ion battery field for its modeling and state estimation strategy. More than 40 projects & 20 patents have been undertaken, publishing over 60 papers on world-famous journals such as Journal of Power Sources, obtaining 20 awards named as Science and Technology Progress Award and University & Enterprise Innovation Talent Team et al. Multiple generation systems have been developed for battery packs, improving the aircraft reliability and expanding its application fields with significant social and economic benefits.

Battery System Modeling provides advances on the modeling of lithium-ion batteries. Offering step-by-step explanations, the book systematically guides the reader through the modeling of state of charge estimation, energy prediction, power evaluation, health estimation, and active control strategies. Using applications alongside practical case studies, each chapter shows the reader how to use the modeling tools provided. Moreover, the chemistry and characteristics are described in detail, with algorithms provided in every chapter. Providing a technical reference on the design and application of Li-ion battery management systems, this book is an ideal reference for researchers involved in batteries and energy storage.

Moreover, the step-by-step guidance and comprehensive introduction to the topic makes it accessible to audiences of all levels, from experienced engineers to graduates.

• Explains how to model battery systems, including equivalent, electrical circuit and electrochemical nernst modeling
• Includes comprehensive coverage of battery state estimation methods, including state of charge estimation, energy prediction, power evaluation and health estimation
• Provides a dedicated chapter on active control strategies

1. Li-ion Battery Characteristics and Applications 2. Electrical Equivalent Circuit Modeling 3. Electrochemical Nernst Modeling 4. Battery State Estimation Methods 5. Battery State-of-charge Estimation Methods 6. Battery State-of-energy Prediction Methods 7. Battery State-of-power Evaluation Methods 8. Battery State-of-health Estimation Methods 9. Battery System Active Control Strategies