Digital twin modeling method for lithium-ion batteries based on data-mechanism fusion driving  

作　　者：Chao Lyu Shaochun Xu Junfu Li Michael Pecht 

机构地区：[1]School of Electrical Engineering and Automation,Harbin Institute of Technology,Harbin 150001,Heilongjiang,China [2]School of Automotive Engineering,Harbin Institute of Technology,Weihai 264209,Shandong,China [3]Center for Advanced Life Cycle Engineering(CALCE),University of Maryland,College Park,MD 20742,USA

出　　处：《Green Energy and Intelligent Transportation》2024年第5期52-69,共18页新能源与智能载运（英文）

基　　金：support by Shandong Province National Natural Science Foundation of China(No.ZR2023QE036).

摘　　要：Lithium-ion batteries have been rapidly developed as clean energy sources in many industrial fields,such as new energy vehicles and energy storage.The core issues hindering their further promotion and application are reliability and safety.A digital twin model that maps onto the physical entity of the battery with high simulation accuracy helps to monitor internal states and improve battery safety.This work focuses on developing a digital twin model via a mechanism-data-driven parameter updating algorithm to increase the simulation accuracy of the internal and external characteristics of the full-time domain battery under complex working conditions.An electrochemical model is first developed with the consideration of how electrode particle size impacts battery characteristics.By adding the descriptions of temperature distribution and particle-level stress,a multi-particle size electrochemical-thermal-mechanical coupling model is established.Then,considering the different electrical and thermal effect among individual cells,a model for the battery pack is constructed.A digital twin model construction method is finally developed and verified with battery operating data.

关 键 词：Lithium-ion battery Multi-particle size electrochemical-thermalmechanical coupling model Online model parameter updating algorithm Digital twin 

分 类 号：TM912[电气工程—电力电子与电力传动]