Electrothermal Model Based Remaining Charging Time Prediction of Lithium-Ion Batteries against Wide Temperature Range  

作　　者：Rui Xiong Zian Zhao Cheng Chen Xinggang Li Weixiang Shen 

机构地区：[1]School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081,China [2]School of Science,Computing and Engineering Technologies,Swinburne University of Technology,Hawthorn,VIC 3122,Australia

出　　处：《Chinese Journal of Mechanical Engineering》2024年第2期330-339,共10页中国机械工程学报（英文版）

基　　金：Supported by National Key R&D Program of China(Grant No.2021YFB2402002);Beijing Municipal Natural Science Foundation of China(Grant No.L223013).

摘　　要：Battery remaining charging time(RCT)prediction can facilitate charging management and alleviate mileage anxiety for electric vehicles(EVs).Also,it is of great significance to improve EV users’experience.However,the RCT for a lithiumion battery pack in EVs changes with temperature and other battery parameters.This study proposes an electrothermal model-based method to accurately predict battery RCT.Firstly,a characteristic battery cell is adopted to represent the battery pack,thus an equivalent circuit model(ECM)of the characteristic battery cell is established to describe the electrical behaviors of a battery pack.Secondly,an equivalent thermal model(ETM)of the battery pack is developed by considering the influence of ambient temperature,thermal management,and battery connectors in the battery pack to calculate the temperature which is then fed back to the ECM to realize electrothermal coupling.Finally,the RCT prediction method is proposed based on the electrothermal model and validated in the wide temperature range from-20℃to 45℃.The experimental results show that the prediction error of the RCT in the whole temperature range is less than 1.5%.

关 键 词：Electric vehicles Lithium-ion batteries Remaining charging time Electrothermal model 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] U469.72[自动化与计算机技术—计算机科学与技术]