Internal Short-Circuit Fault Identification of Lithium-Ion Batteries

Beschreibung

This book focuses on state estimation and internal short-circuit fault identification, two key challenges in ensuring the safe operation and maintenance of lithium-ion batteries. It begins with an overview of lithium-ion batteries and battery management systems, followed by a systematic introduction to data-driven state estimation methods. The book then examines internal short-circuit faults in depth, including their underlying mechanisms, diagnostic requirements, and advanced identification techniques. Particular emphasis is placed on novel data-driven methods for detecting incipient internal short-circuits, as well as model-based approaches for the quantitative estimation of both early-stage and severe faults. Supported by extensive experimental data, tables, and illustrative analyses, the book effectively integrates theoretical foundations with practical applications. It provides researchers and industry professionals with valuable insights and practical tools for battery state monitoring, fault diagnosis, and the development of safer battery systems.

This book focuses on state estimation and internal short-circuit fault identification, two key challenges in ensuring the safe operation and maintenance of lithium-ion batteries. It begins with an overview of lithium-ion batteries and battery management systems, followed by a systematic introduction to data-driven state estimation methods. The book then examines internal short-circuit faults in depth, including their underlying mechanisms, diagnostic requirements, and advanced identification techniques. Particular emphasis is placed on novel data-driven methods for detecting incipient internal short-circuits, as well as model-based approaches for the quantitative estimation of both early-stage and severe faults. Supported by extensive experimental data, tables, and illustrative analyses, the book effectively integrates theoretical foundations with practical applications. It provides researchers and industry professionals with valuable insights and practical tools for battery state monitoring, fault diagnosis, and the development of safer battery systems.

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Bin Li

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Lithium ion Batteries Battery Management Systems (BMS) State Estimation Internal Short Circuit (ISC) Faults Fault Identification

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