考慮歷史退化信息融合的電池健康狀態(tài)估計研究

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主題詞：鋰離子電池 健康狀態(tài) 特征提取

中圖分類號：U46；TP18；TN303.1 文獻標志碼：A DOI：10.19620/j.cnki.1000-3703.20250111

ResearchonBatteryStateofHealth Estimationwith Historical DegradationInformation Fusion

ZhouDinghual，ZuoPeiwen2，ZhuZhongwen’，QiuXin'，MaQilong1 （1.School of Automotiveand Transportation Engineering，Hefei UniversityofTechnology，Hefei23ooo9;2.China AutomotiveInformation Technology（Tianjin） Co.，Ltd.， Tianjin，3O0000）

【Abstract】Inorder toaccurately estimate the State of Health （SOH）of lithium-ion bateries，this paper proposes an advanced SOHestimation methodthatintegrates Strategic Optimization Algorithm （SOA）with Memory-Enhanced Long ShortTermMemory （MELSTM）neuralnetwork.Firstly，a Variational AutoEncoder（VAE）isutilizedtoprocessrawdata，reducing redundant informationandextracting healthindicators，therebyachievingapreciserepresentationof baterydegradation information.Subsequently，ahybridmodelcombiningSOAandMELSTMisproposedtoestimateSOHoflithium-ionbatteries. Finall，effectivenessofteproposedmethodisvalidatedusing2publicdatasetsforlitium-onbateryaging，amelyACLE andNASA.Experimentalresultsdemonstratethattheproposed method improves RMSE indicators byover30%compared with conventional LSTMalgorithm，ofering new insights and solutionsforaccurateSOHestimationof ithium-ionbattery.

Keywords：Lithium-ionbattery，StateofHealth（SOH），F(xiàn)eatureextraction 【引用格式】周定華，左培文，朱仲文，等.考慮歷史退化信息融合的電池健康狀態(tài)估計研究[J].汽車技術，2025（6）：28-35. ZHOUDH，ZUOPW，ZHUZW，etal.ResearchonBateryStateofHealthEstimation withHistoricalDegradation InformationFusion[J].Automobile Technology，2025（6）：28-35.

1前言

鋰離子電池因具有自放電率低、循環(huán)壽命長、能量密度高、功率密度高、放電平穩(wěn)、工作溫度范圍寬、無記憶效應和環(huán)保等優(yōu)勢[-3]，廣泛應用于電動汽車、大型儲能系統(tǒng)、航空等領域。（剩余11933字）