基于大數(shù)據(jù)的車用鋰電池容量失效預(yù)測

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【摘  要】文章利用大數(shù)據(jù)技術(shù)，搭建LSTM鋰電池容量失效預(yù)測模型。通過對(duì)大量試驗(yàn)數(shù)據(jù)進(jìn)行分析，提取關(guān)鍵特征，對(duì)網(wǎng)絡(luò)進(jìn)行訓(xùn)練，并將訓(xùn)練后的模型與電池模型進(jìn)行融合，利用該模型進(jìn)行試驗(yàn)，通過對(duì)比分析驗(yàn)證該模型可以準(zhǔn)確預(yù)測電池失效，從而為電動(dòng)汽車電池管理提供有效的技術(shù)支持。

【關(guān)鍵詞】鋰電池；容量失效；LSTM；大數(shù)據(jù)

中圖分類號(hào)：U469.72    文獻(xiàn)標(biāo)識(shí)碼：A    文章編號(hào)：1003-8639（ 2024 ）08-0021-03

Failure Prediction of Lithium Battery Capacity Based on Big Data

WANG Wenli，WEI Limei

（Shengrui Transmission Co.，Ltd.，Weifang 261000，China）

【Abstract】This article uses big data technology to build an LSTM lithium battery capacity failure prediction model. By analyzing a large amount of experimental data，extracting key features，training the network，and integrating the trained model with the battery model，the model was used to conduct experiments. Through comparative analysis，it was verified that the model can accurately predict battery failure，thereby providing Provide effective technical support for electric vehicle battery management.

【Key words】lithium battery；capacity failure；LSTM；big data

作者簡介

王文麗，女，工程師，工程碩士，主要從事汽車零部件失效分析及質(zhì)量控制技術(shù)研究工作。（剩余3894字）