基于斑鬣狗优化器的扩展卡尔曼滤波动力电池荷电状态估计

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中图分类号：TM912.9 文献标志码：A DOI：10.20104/j.cnki.1674-6546.20250227

Extended Kalman Filter for SOC Estimation Based on Spotted Hyena Optimizer

Chen Yandong，Zhang Qiao，Chen Fuhui，He Jian （LiaoningUniversity of Technology，Jinzhou 122001）

【Abstract]Accurate estimationofthe Stateof Charge （SOC）in lithium-ion power batteries is crucial fortherange and batterylifeof new energyvehicles.However，inpracticaloperatingconditions，processnoiseandobservationnoiseoften exhibitsignificanttime-varyingcharacteristics，causingtraditional ExtendedKalmanFilter（EKF）methodsbasedonfixed gainsto suffrfromgainmismatchanddificultyinmaintainingstableaccuracy.Toenhance SOCestimationperformance，this paperproposesan Extended Kalman Filter methodbased on the Spoted Hyena Optimizer （SHO-EKF）.This method first employs theRecursiveLeastSquares withForgetingFactortoachieveonlineidentificationof theparametersof thesecondorderequivalentcircuit model.Subsequently，the Spotted Hyena Optimizer （SHO）isused to establishamapping relationship betweenEKFgainand SOCestimation error，enablingoflineoptimizationtoobtaintheoptimal gain，therebydynamically improving filtering performanceunder time-varying noiseconditions.Experimental validation wasconducted under FUDS conditions，andcomparisonsaremadewiththeParticle SwarmOptimizationEKF（PSO-EKF）algorithm.Theresultsindicate that SHO-EKFdemonstrates higher estimation stabilityandaccuracythroughoutthedischargecycle，with a Mean Absolute Error（MAE）ofonly0.O0637，significantlyoutperforming PSO-EKF’s0.01317;theRoot MeanSquareError（RMSE）also decreasedfromO.O1532to0.Oo751.Particularlyinthebateryvoltageplateauregion，SHO-EKFefectivelysuppresssoise disturbances，significantly improving the accuracy degradation issue of EKF in strongly nonlinear segments.

Key words：Lithium-ion power battery，State of Charge （SOC） estimation，Extended Kalman Filter （EKF），Spotted Hyena Optimizer （SHO）

【引用格式】陈艳东，张乔，陈福辉，等.基于斑鬣狗优化器的扩展卡尔曼滤波动力电池荷电状态估计[J].汽车工程师， 2026（1）： 8-16.

CHENYD，ZHANGQ，CHENFH，etal.Extended KalmanFilter for SOC Estimation Basedon Spotted Hyena Optimizer[J]. Automotive Engineer， 2026（1）： 8-16.

1前言

当前，动力电池荷电状态（StateofCharge，SOC）估计算法主要分为安时积分法、卡尔曼滤波类方法和智能优化算法。（剩余11502字）