Co-Estimation of State of Charge and Capacity for Lithium-Ion Batteries with Multi-Stage Model Fusion Method  

作　　者：Rui Xiong Ju Wang Weixiang Shen Jinpeng Tian Hao Mu 

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

出　　处：《Engineering》2021年第10期1469-1482,共14页工程（英文）

基　　金：This work was supported by the National Key Research and Development Program of China(2017YFB0103802);the National Natural Science Foundation of China(51922006 and 51707011).

摘　　要：Lithium-ion batteries(LIBs)have emerged as the preferred energy storage systems for various types of electric transports,including electric vehicles,electric boats,electric trains,and electric airplanes.The energy management of LIBs in electric transports for all-climate and long-life operation requires the accurate estimation of state of charge(SOC)and capacity in real-time.This study proposes a multistage model fusion algorithm to co-estimate SOC and capacity.Firstly,based on the assumption of a normal distribution,the mean and variance of the residual error from the model at different ageing levels are used to calculate the weight for the establishment of a fusion model with stable parameters.Secondly,a differential error gain with forward-looking ability is introduced into a proportional–integral observer(PIO)to accelerate convergence speed.Thirdly,a fusion algorithm is developed by combining a multistage model and proportional–integral–differential observer(PIDO)to co-estimate SOC and capacity under a complex application environment.Fourthly,the convergence and anti-noise performance of the fusion algorithm are discussed.Finally,the hardware-in-the-loop platform is set up to verify the performance of the fusion algorithm.The validation results of different aged LIBs over a wide range of temperature show that the presented fusion algorithm can realize a high-accuracy estimation of SOC and capacity with the relative errors within 2%and 3.3%,respectively.

关 键 词：State of charge Capacity estimation Model fusion Proportional-integral-differential observer HARDWARE-IN-THE-LOOP 

分 类 号：TM912[电气工程—电力电子与电力传动]