• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2021, Vol. 57 ›› Issue (14): 10-22.doi: 10.3901/JME.2021.14.010

• 特邀专栏:电源系统设计、管理与大数据 • 上一篇    下一篇

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车用锂离子电池电化学-热耦合高效建模方法

匡柯1, 孙跃东1, 任东生2,3, 韩雪冰2, 郑岳久1, 耿兆杰4   

  1. 1. 上海理工大学机械工程学院 上海 200093;
    2. 清华大学汽车安全与节能国家重点实验室 北京 100084;
    3. 清华大学核能与新能源技术研究院 北京 100084;
    4. 北京新能源汽车股份有限公司 北京 100176
  • 收稿日期:2020-07-24 修回日期:2021-03-22 出版日期:2021-09-15 发布日期:2021-09-15
  • 通讯作者: 韩雪冰(通信作者),男,1987年出生,博士,助理研究员。主要研究方向为智能电池管理与智慧能源系统。E-mail:hanxuebing@tsinghua.edu.cn
  • 作者简介:匡柯,男,1997年出生。主要研究方向为电动汽车动力锂离子电池建模与安全快充。E-mail:kekuang2018@163.com
  • 基金资助:
    国家重点研发计划(2018YFB0104000)、国家自然科学基金(51807108,51877138)和上海市青年科技启明星计划(19QA1406200)资助项目

Efficient Approach for Electrochemical-thermal Coupled Modeling of Large-format Lithium-ion Power Battery

KUANG Ke1, SUN Yuedong1, REN Dongsheng2,3, HAN Xuebing2, ZHENG Yuejiu1, GENG Zhaojie4   

  1. 1. School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093;
    2. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084;
    3. Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084;
    4. Beijing New Energy Automobile Co., Ltd., Beijing 100176
  • Received:2020-07-24 Revised:2021-03-22 Online:2021-09-15 Published:2021-09-15

摘要: 精确的电池模型是车用锂离子电池系统状态估计和能量管理的基础。电化学机理模型用途广、精度高,是下一代电池管理系统的重点研究对象。然而,目前电池电化学机理模型建立过程中存在参数获取困难、依赖后期参数标定等问题。为此,提出一种大容量车用锂离子电池电化学-热耦合高效建模方法。将电化学机理模型的参数进行分类,对可测量/辨识参数(几何尺寸、正负极初始化学计量比和固相颗粒最大嵌锂浓度等)进行精确的测量和参数辨识。利用不同温度下的脉冲充电试验来标定固相扩散系数Ds和反应速率常数k。进一步地,建立电池产热模型,搭建考虑温度影响的电池电化学-热耦合模型。不同倍率充放电、不同温度下的脉冲放电和动态应力工况测试下试验验证结果显示,所搭建的模型具有很好的精度和适应性,电压平均误差小于10 mV,温度平均误差小于1.1℃。参数敏感性分析结果显示固相扩散系数Ds的减小会导致电极颗粒内部锂离子浓度差变大,从而使得颗粒表面电势提前达到截止电压,降低电池容量;反应速率常数k的减少主要影响电池阻抗,将造成放电电压曲线整体下移和产热增加。所提出的建模方法可以快速高效地建立精度高、普适性好,成本低的电池电化学-热耦合模型。

关键词: 锂离子电池, 电池管理, 电化学-热耦合模型, 参数辨识, 参数敏感性分析

Abstract: Accurate battery model is the basis for the state estimation and energy management of lithium-ion power battery systems. Benefit from its wide application and high accuracy, the electrochemical mode is urgently needed for the next generation battery management systems. However, as the electrochemical model has many parameters that are difficult to acquired, calibration of the electrochemical model has large influence on model accuracy. To solve this problem, an efficient approach for electrochemical-thermal coupled modeling of large-format lithium-ion battery is proposed. First of all, the parameters of the electrochemical model are classified into several categories. The measurable/identifiable parameters (geometric dimensions, initial stoichiometry coefficient of cathode and anode, and maximum lithium intercalation concentration of solid particles) are accurately measured and identified through tests and post-mortem analysis. Furthermore, the pulsed-charge tests at different temperatures are performed to calibrate the solid-phase diffusion coefficient Ds and the reaction rate constant k of the electrodes. Battery thermal model is also built to simulate battery heat generation, and the electrochemical-thermal coupled model is finally established with the consideration of temperature effects. Also, the electrochemical-thermal coupled model is validated by the following three tests:charging and discharging tests at different rates, pulse-discharge tests at different temperatures and dynamic stress test(DST). The results show that the model has high accuracy and adaptability at different C-rates and temperature, with the average error of voltage is less than 10 mV, and the average error of temperature is lower than 1.1℃. Finally, the modeling analysis results show that the decrease of the solid-phase diffusion coefficient Ds will increase the difference of lithium ion concentration inside the electrode particles, leading to the higher particle surface potential and thus earlier termination of discharge process and lower capacity. Besides, the reduction of reaction rate constant k mainly affects battery resistance, which will cause a overall downward movement of the battery discharge voltage curve and also an increase of heat generation. The modeling method proposed can efficiently establish an electrochemical-thermal model coupled with high-accuracy, easy-applicability, and fair-economy.

Key words: lithium-ion battery, battery management, electrochemical-thermal coupled model, parameter identification, sensitivity analysis of parameter

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