电动汽车动力电池SOH估计方法探讨

doi:10.16731/j.cnki.1671-3133.2018.05.009

摘要/Abstract

摘要： 实时估计电动汽车动力电池健康状态(State of Health,SOH),对于充分保证每个电池组的充/放电性能,延长整个电池组的寿命具有重要意义。作为电池管理系统的重要组成部分,相比于电池荷电状态(State of Charge,SOC)和电池均衡系统的研究,SOH估计方法的研究明显落后。简单介绍了SOH的定义及影响因素,按照离线估计方法和在线估计方法进行分类,探讨了常见的SOH估计方法。最后展望了SOH估计方法的发展趋势,指出基于卡尔曼滤波的在线估计和智能学习神经网络的方法将是未来的主流方法。

关键词: 电动汽车, 动力电池, 健康状态, 估计方法

Abstract: Real-time estimation of battery State of Health (SOH)for electric vehicleis has very important significance for guaranteeing charging and discharging performance of each battery pack and extending the life of entire battery pack.As an important part of battery management system,compared to the battery State of Charge (SOC)and battery equalization system,research on SOH obviously falls behind.The definition of battery SOH and its main influencing factors are introduced,the online and offline estimation methods are classified,and the common SOH estimation methods are discussed.Finally,the trend of SOH estimation method is looked forward,moreover the Kalman filtering online estimation and intelligent learning neural network online estimation methods are pointed out to be the future mainstream method

Key words: electric vehicle, power battery, State of Health(SOH), estimation method

中图分类号:

TM912

邓涛, 罗卫兴. 电动汽车动力电池SOH估计方法探讨[J]. 现代制造工程, 2018, 452(5): 43-49.

Deng Tao, Luo Weixing. Research on estimation methods of battery SOH for electric vehicle[J]. Modern Manufacturing Engineering, 2018, 452(5): 43-49.

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