汽车工程 ›› 2021, Vol. 43 ›› Issue (2): 204-209.doi: 10.19562/j.chinasae.qcgc.2021.02.007

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锂离子电池多因素动态生热率模型

潘海鸿1,2,李熠婧1,张沫1,梁刚1,陈琳1,2()   

  1. 1.广西大学机械工程学院,南宁 530004
    2.广西电化学能源材料重点实验室,南宁 530004
  • 收稿日期:2020-04-29 修回日期:2020-07-25 出版日期:2021-02-25 发布日期:2021-03-04
  • 通讯作者: 陈琳 E-mail:gxdxcl@163.com
  • 基金资助:
    国家自然科学基金(51667006)

Multiple Factors Dynamic Heat Generation Rate Model of Lithium‑ion Battery

Haihong Pan1,2,Yijing Li1,Mo Zhang1,Gang Liang1,Lin Chen1,2()   

  1. 1.School of Mechanical Engineering,Guangxi University,Nanning 530004
    2.Guangxi Key Laboratory of Electrochemical Energy Materials,Nanning 530004
  • Received:2020-04-29 Revised:2020-07-25 Online:2021-02-25 Published:2021-03-04
  • Contact: Lin Chen E-mail:gxdxcl@163.com

摘要:

为提高生热率模型的仿真精度,基于Bernardi生热率模型车用锂电池实际应用,提出建立多因素动态生热率模型。首先,综合考虑温度、荷电状态和充放电倍率对Bernardi生热率模型的参数动态影响;其次,利用实验数据建立融合多种影响因素的动态内阻和动态温熵系数的数学模型,将这两个数学模型代入Bernardi生热率模型构建多因素动态生热率模型;然后,开发该模型充电、放电和充放电循环3种工况的仿真程序并仿真电池的动态温度;最后,将电池温度的仿真值与实验值对比验证,结果表明所建立的动态生热率模型能够准确仿真电池在不同工况下的动态温度,其误差小于3.25 ℃。

关键词: 锂离子电池, 多因素, 动态生热率, 动态内阻, 动态温熵系数

Abstract:

In order to improve the simulation accuracy of the heat generation rate model, a multiple factors dynamic heat generation rate model is proposed based on the practical application of the Bernardi heat generation rate model for vehicle lithium?ion battery. First, the model integrates the dynamic effects of temperature, state of charge and charge?discharge rate on the parameters of Bernardi heat generation rate model. The mathematical models of dynamic internal resistance and dynamic entropy coefficient integrating multiple influencing factors are established based on the experimental data, which are substituted into Bernardi heat generation rate model to construct a multiple factors dynamic heat generation rate model. Then, the simulation program of charge, discharge and charge?discharge cycle is developed and the dynamic temperature of the battery is simulated. Finally, the simulation value of the battery temperature is verified by the experimental value. The results show that the dynamic heat generation rate model can accurately simulate the dynamic temperature of the battery under different working conditions, with the error less than 3.25 ℃.

Key words: lithium?ion battery, multiple factors, dynamic heat generation rate, dynamic internal resistance, dynamic entropy coefficient