Modeling and State Estimation of Automotive Lithium-Ion Batteries [Hardcover]

1.?Introduction? 2.?Working principle and experimental characteristic analysis of power lithium-ion battery? 3.?Dynamic migration modeling of power lithium-ion batteries? 4.?SOC and SOH co-estimation based on the firefly optimization algorithm? 5.?Experimental validation analysis of SOC and SOH co-estimation? 6.?Work summary and outlook

This book aims to evaluate and improve the state of charge (SOC) and state of health (SOH) of automotive lithium-ion batteries.

This book aims to evaluate and improve the state of charge (SOC) and state of health (SOH) of automotive lithium-ion batteries.

 

The authors first introduce the basic working principle and dynamic test characteristics of lithium-ion batteries. They present the dynamic transfer model, compare it with the traditional second-order reserve capacity (RC) model, and demonstrate the advantages of the proposed new model. In addition, they propose the chaotic firefly optimization algorithm and demonstrate its effectiveness in improving the accuracy of SOC and SOH estimation through theoretical and experimental analysis.

 

The book will benefit researchers and engineers in the new energy industry and provide students of science and engineering with some innovative aspects of battery modeling.

Shunli Wang is Professor, Academic Dean, Academic Leader of the National Electrical Safety and Quality Testing Center, Academician of the Russian Academy of Natural Sciences, Senior Overseas Study Talent of Sichuan Province, and Academic and Technical Leader of China Science and Technology City. He is an authoritative expert in renewable energy research and is interested in modeling, state estimation, and safety management for energy storage systems. 

Fan Wu is in the School of Information Engineering at Southwest l+