03616nam a22005415i 4500 978-981-97-4639-2 DE-He213 20251030112912.0 cr nn 008mamaa 240825s2024 si | s |||| 0|eng d 9789819746392 978-981-97-4639-2 10.1007/978-981-97-4639-2 doi TA329-348 TBJ bicssc MAT003000 bisacsh TBJ thema Wei, Zhongbao. author. (orcid)0000-0003-0051-5648 https://orcid.org/0000-0003-0051-5648 aut http://id.loc.gov/vocabulary/relators/aut 82881 Smart Battery Management for Enhanced Safety [electronic resource] / by Zhongbao Wei. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XXI, 230 p. 110 illus., 102 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Key Technologies on New Energy Vehicles, 2662-2939 Overview of battery management -- Modeling -- State Estimation -- Health Diagnostic -- Charging -- Smart battery and management. This book consolidates studies in the rapidly and foreseeably growing field of battery management. The primary focus is to overview the management of batteries (Li-ion batteries and some cases of flow batteries) with the fusion of mechanism and AI-based approaches. The book can be categorized into three groups, i.e., (i) mechanism and AI-based battery modeling and parameterization, (ii) AI-based diagnostic, early warning, and active safety control, and (iii) emerging techniques of smart battery and smart management, combining the emerging areas of embedded sensing and reconfigurable batteries. It is well recognized that the battery safety and management are the kernel of energy storage, renewable utilization, and low-carbon society, which have been highly popular in recent years. The exploration of AI techniques for advanced battery management has been seldom discussed systematically before. Moreover, the combination of AI and mechanism approaches can remarkably enhance the battery management, which however has never been focused on in previous books. Therefore, this book can add new knowledge to the paradigm and attract the attention of academics, scientists, engineers, and practitioners. It is a reference book for researchers and engineers in related fields. The step-by-step guidance, comprehensive introduction, and case studies make it accessible to audiences of different levels, from graduates to experienced engineers. Engineering mathematics. 64145 Electric power production. 65675 Computational intelligence. 64052 Engineering Mathematics. 64145 Electrical Power Engineering. 65867 Computational Intelligence. 64052 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819746385 Printed edition: 9789819746408 Printed edition: 9789819746415 Key Technologies on New Energy Vehicles, 2662-2939 67621 https://doi.org/10.1007/978-981-97-4639-2 ZDB-2-ENE ZDB-2-SXEN 62732 62732