储能科学与技术2025，Vol.14Issue(9)：3567-3580,14.DOI:10.19799/j.cnki.2095-4239.2025.0192
基于数字孪生的高精度SOC和温度联合估计方法
A high-precision SOC and temperature joint estimation method based on rapid prototype modeling
摘要
Abstract
Mining lithium-ion batteries face severe safety and reliability challenges under extreme working conditions in coal mines.Although high-precision physical modeling is a potential solution,traditional experimental methods are limited by high cost and risk,while mechanism-based models struggle to adapt to actual complex working conditions.To address this,a collaborative estimation framework based on digital twins is proposed.Taking a 228 Ah mining lithium-ion battery as the object,a battery characteristic characterization system considering multi-factor coupling of temperature,multiplicity,state of charge(SOC),and aging is established by improving the first-order RC equivalent circuit model.Based on the Simulink/Simscape multiphysics field co-simulation platform,a digital twin system integrating electrochemical,thermodynamic,and state estimation algorithms is constructed.The convective heat transfer,unscented Kalman filter(UKF),and extended Kalman filter(EKF)modules are integrated to perform comparative analyses of SOC and temperature joint estimation.The experimental results of UKF show that the maximum permissible errors(MPE)of SOC estimation under BBDST conditions are 0.3937%,0.4347%,and 0.5067%at 25℃,45℃,and 60℃,respectively,while the MPE of temperature estimation are 0.74℃,1℃,and 0.9613℃.Under DST conditions,the MPE of SOC estimation are 0.1829%,0.0034%,and 0.0035%at 25℃,45℃,and 60℃,respectively,and the MPE of temperature estimation are 0.6℃,0.9992℃,and 0.9740℃.The results confirm that the model possesses excellent temperature adaptability and generalization capability,serving as a reliable digital twin verification platform for next-generation intelligent battery management system(BMS)development.This provides significant theoretical value and broad engineering application prospects.关键词
矿用锂离子电池/数字孪生/SOC与温度联合估计/Simulink/SimscapeKey words
mining lithium-ion battery/digital twin/SOC and temperature joint estimation/Simulink/Simscape分类
信息技术与安全科学引用本文复制引用
封居强,张成知,陈雨杭..基于数字孪生的高精度SOC和温度联合估计方法[J].储能科学与技术,2025,14(9):3567-3580,14.基金项目
安徽省高校中青年教师培养行动项目(YQYB2023030),淮南师范学院校级科研项目、重点教育教学改革研究项目(2024XJZD012、2024hsjyxm14). （YQYB2023030）
