YaNan Wang – författare

This 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.With the rapid growth of electric vehicles and energy storage systems, battery technology has become critical to global energy solutions. Fractional Order Intelligent Modeling for Lithium-Ion Batteries: Theory and Practice 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.This 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.

This 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.With the rapid growth of electric vehicles and energy storage systems, battery technology has become critical to global energy solutions. Fractional Order Intelligent Modeling for Lithium-Ion Batteries: Theory and Practice 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.This 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.

This 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.With the rapid growth of electric vehicles and energy storage systems, battery technology has become critical to global energy solutions. Fractional Order Intelligent Modeling for Lithium-Ion Batteries: Theory and Practice 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.This 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.

Gathering contributions by leading social development scholars, this report offers a comprehensive description of the national development of cultural consumption in China. By comparing the annual growth of cultural consumption, GDP growth, per-capita income growth and savings growth, the authors reveal the disparity between urban and rural areas in terms of cultural consumption, as well as that between provinces. Based on an analysis of the status quo of cultural consumption in China, the book explores the road to a prosperous society and enhancing China’s cultural development.

Gathering contributions by leading social development scholars, this report offers a comprehensive description of the national development of cultural consumption in China. By comparing the annual growth of cultural consumption, GDP growth, per-capita income growth and savings growth, the authors reveal the disparity between urban and rural areas in terms of cultural consumption, as well as that between provinces. Based on an analysis of the status quo of cultural consumption in China, the book explores the road to a prosperous society and enhancing China’s cultural development.

Gathering contributions by leading social development scholars, this report offers a comprehensive description of the national development of cultural consumption in China. By comparing the annual growth of cultural consumption, GDP growth, per-capita income growth and savings growth, the authors reveal the disparity between urban and rural areas in terms of cultural consumption, as well as that between provinces. Based on an analysis of the status quo of cultural consumption in China, the book explores the road to a prosperous society and enhancing China’s cultural development.