{"product_id":"fractional-order-intelligent-modeling-for-lithium-ion-batteries-theory-and-practice-hardcover","title":"Fractional Order Intelligent Modeling for Lithium-Ion Batteries: Theory and Practice - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eYanan Wang\u003c\/b\u003e (Author), \u003cb\u003eYangquan Chen\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis book focuses on fractional order (non-integer order) modeling (FOM) techniques coupled with deep neural network-based intelligent modeling methods for lithium-ion batteries (LIBs) and battery management systems (BMS) in general. It provides the first one-stop resource on FOM for LIBs with case studies using real operational data sets.\u003c\/p\u003e\u003cp\u003eWith the rapid growth of electric vehicles and energy storage systems, battery technology has become critical to global energy solutions. \u003cstrong\u003eFractional Order Intelligent Modeling for Lithium-Ion Batteries: Theory and Practice\u003c\/strong\u003e aims to provide several accurate and effective intelligent modeling algorithms for the next generation of advanced BMS. Key topics include intelligent battery modeling, fractional-order modeling, physics-informed machine learning, state estimation, and degradation analysis. By integrating AI and physics-informed machine learning techniques with fractional-order modeling methods, this book presents several innovative solutions for next-generation battery management systems.\u003c\/p\u003e\u003cp\u003eThis title will serve as an invaluable resource for researchers and advanced students in the fields of transportation, energy storage, and power systems, as well as those studying electric vehicles, control theory, machine learning, and fractional calculus-based modeling.\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eYaNan Wang \u003c\/b\u003eis currently an assistant professor and a member of Low-carbon Powertrain Systems Research Lab at Beijing University of Technology, China. Her research focuses on AI-driven battery intelligent management and safety evaluation for power batteries, addressing critical issues such as fast degradation and fault diagnosis.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eYangQuan Chen \u003c\/b\u003eis a professor at the University of California Merced, US. His research interests include mechatronics for sustainability, digital twins, small multi-UAV, applied fractional calculus. His recent publication with CRC Press includes \u003ci\u003eFractional Calculus for Skeptics I: The Fractal Paradigm\u003c\/i\u003e.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 135\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.44 x 10 x 7 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e November 04, 2025\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47337289056505,"sku":"9781041132691","price":187.9,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/bhlJEpsw2U9781041132691.webp?v=1769678728","url":"https:\/\/bookscloud.io\/products\/fractional-order-intelligent-modeling-for-lithium-ion-batteries-theory-and-practice-hardcover","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}