基于FFRLS-AUKF算法的锂离子电池SOC估计

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中图分类号：TM912 文献标志码：A 文章编号：2095-2945（2025）28-0070-04

Abstract：AccurateestimationoftheSOCoflithium-ionbateriesisthekeytothesafeandeffcientoperationofelectric vehiclesandenergystoragesystems.Basedonthe Theveninequivalentcircuit model，thispaperusestherecursive leastsquares （FRLS）methodwithforgetingfactortorealizeonlineparameteridentification，andcombinestheadaptiveunscented Kalman filter（AUKF）toestimateSOCinrealtime.InNASAspublicdataset，experimentalresultsshowthatcomparedwithtraditional EKFand UKFalgorithms，AUKFismorerobustundernoiseuncertaintyconditions，andtherot-mean-squareerror（RMSE）and maximum absolute error（MAE）ofSOC estimationare both significantlyreducedand the overallaccuracy ishigher.

Keywords：Lithium-ion battery;SOC；FFRLS;AUKF;estimation

近年来，我国在落实“双碳”自标的背景下，新能源汽车产业得到了高速发展，成为了我国汽车产业转型升级的主要发展方向。（剩余5634字）