基于锂离子电池简化电化学模型的参数辨识  

Parameter identification based on simplified electrochemical model of lithium ion battery

作　　者：康鑫 时玮[1] 陈洪涛[1] KANG Xin;SHI Wei;CHEN Hongtao(Beijing Jiaotong University,Beijing 100044,China)

机构地区：[1]北京交通大学,北京100044

出　　处：《储能科学与技术》2020年第3期969-978,共10页Energy Storage Science and Technology

基　　金：中央高校基本科研业务费专项资金(2018JBM058)。

摘　　要：本文旨在对一种简化的电化学模型进行参数辨识。首先采用三参数抛物线方程将固相锂离子扩散偏微分方程简化为常微分方程,在单粒子模型的基础上考虑液相浓度和液相电势及SEI膜阻抗引起的过电势对端电压的影响,使用平均体积电流密度取代锂离子流量密度沿电极厚度方向的变化,建立了新的电化学模型。继而采用实验结合仿真的方式获取了电池的正极开路电压表达式。对电化学参数进行参数敏感度分析,并确定了该模型下待辨识电化学参数。最后采用自适应混沌粒子群算法对参数进行辨识,并且通过实验与仿真对比验证了电化学模型的准确性。This paper aims to identify the parameters of a simplified electrochemical model. Firstly, the three-parameter partial differential equations of solid lithium-ion diffusion are simplified to ordinary differential equations. This simplification of the ordinary differential equations is based on the singleparticle model and considers the concentration in liquid phase, liquid-phase electric potential, and the impedance of the solid electrolyte interface film caused by the potential impact on the terminal voltage.The next contribution is a new electrochemical model, which computes the average current density and volume density of the lithium-ion flow along the electrode thickness direction. The expression for positive open-circuit voltage of the battery was formulated through experiment and simulation. The electrochemical parameters of the model were determined in a parameter sensitivity analysis and identified by an adaptive chaotic particle swarm optimization algorithm. The accuracy of the electrochemical model was verified in further experiments and simulations.

关 键 词：锂离子电池 参数辨识 自适应混沌粒子群算法 

分 类 号：TM912[电气工程—电力电子与电力传动]