基于自产热和外传热的锂离子电池热学模型参数辨识方法

doi:10.19595/j.cnki.1000-6753.tces.222104

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摘要

锂离子电池热学模型参数（热容和热阻）的准确辨识对电池热电耦合建模及状态参数估计至关重要。然而传统测量方法成本高且测试周期长,如何利用充放电工况结合产热和传热机理研究快速热参数辨识方法具有重要意义。以8A•h软包锂离子电池为研究对象,建立分布式热路模型;设计双向脉冲工况实验,采用自适应粒子群算法（APSO）进行辨识;同时采用其它工况进行验证,实验和仿真温度误差小于0.1℃。另外,将热容和热阻转换为比热容和导热系数并与其它文献中同类电池的参数进行比对,量级接近。研究结果表明,该方法可以有效解决层叠式软包锂离子电池热学模型参数辨识难的问题,且简便易行、成本低。

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关键词 ：层叠式软包, 锂离子电池, 分布式热路模型, 热容和热阻, 自产热和外传热

Abstract：

Accurate identification of thermal model parameters (heat capacity and thermal resistance) of lithium ion batteries is crucial for thermoelectric coupling modeling and state parameter estimation of batteries. There is a certain conversion formula between the thermal model parameters and the thermophysical parameters (specific heat capacity and thermal conductivity) of lithium ion batteries, so the two sets of parameters have an equivalent relationship. The study of thermal model parameters can refer to the research methods of thermophysical parameters.
Accurate measurement of battery specific heat capacity and thermal conductivity requires the use of expensive testing equipment, which is costly and takes longer to test. Using optimization algorithms to identify thermal model parameters not only has low cost, but also has short calculation cycle. In this paper, a fast method for identifying the thermal model parameters of NCM laminated soft packaged lithium-ion batteries is proposed based on the charging and discharging conditions combined with the battery heat generation and heat transfer mechanisms.
By establishing a distributed thermal equivalent circuit model to simulate the temperature distribution along the thickness direction of the battery, the reversible heat can be ignored and the calculation of battery heat generation can be simplified by designing a bidirectional pulse operating condition; The temperature was discretized and the thermal model parameters of 0℃, 10℃, and 20℃ were identified using APSO algorithm. The identified parameters are equivalently treated as specific heat capacity and thermal conductivity, with an average specific heat capacity of 0.996J/(g·K) and an average thermal conductivity of 0.377W/(m·K). Comparing the specific heat capacity and thermal conductivity of batteries from different literature, they are within a reasonable range, and the difference is not more than 8%. Temperature sensitivity analysis was conducted. When the thermal model parameters changed by ±5%, the temperature error of the model simulation results was less than 0.08℃. Therefore, in the range of 0 to 20℃, the thermal model parameters are not sensitive to temperature. Finally, the identified parameters are brought into the model and simulated using a different strategy than the parameter identification experiment. The measured and simulated battery surface temperatures agree well with a temperature error of less than 0.1℃, which proves that the proposed thermal model parameter identification method has a high accuracy. Moreover, the proposed method has the advantage of simplicity and simplicity, requiring only two batteries of the same specification, without the need for other devices, and having a short test cycle. It can provide technical support for the identification of thermal model parameters for stacked soft packaged lithium ion batteries.

Key words： laminated flexible lithium-ion battery distributed thermal circuit model heat capacity and thermal resistance self-generated heat and external heat transfer

收稿日期: 2022-11-04

PACS:

TM911

通讯作者: 孙丙香, 女,1979年生,教授,博士生导师,研究方向为锂离子动力电池高效集成及智能管控技术。包括建模与仿真、热特性与低温加热策略、优化充电、储能电池性能评估与经济性分析等。E-mail：bxsun@bjtu.edu.cn

作者简介: 宋东林, 男,1996年生,硕士研究生,研究方向为锂离子电池低温加热、电池热特性建模。E-mail：20121484@bjtu.edu.cn

引用本文:

孙丙香, 宋东林, 阮海军, 张维戈, 郑凯元. 基于自产热和外传热的锂离子电池热学模型参数辨识方法[J]. 电工技术学报, 0, (): 8915-. Sun Bingxiang, Song Donglin, Ruan Haijun, Zhang Weige, Zheng Kaiyuan. Parameter Identification Method of Thermal Model of Lithium-Ion Battery Based on Self-Generated Heat and External Heat Transfer. Transactions of China Electrotechnical Society, 0, (): 8915-.

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