锂电池二阶RC等效电路模型参数辨识

Parameters identification of second order RC equivalent circuit model for lithium batteries

以锂电池二阶RC等效电路模型为研究对象,将电池模型RC参数的辨识问题归结为非线性最优化问题,建立非.线性最小二乘优化模型,采用Levenberg-Marquard(LM)算法对其进行求解.该优化问题不仅是非线性的,而且非凸,因此需要对优化算法中的初始值进行选取,同时放电电流大小的变化也会影响参数求解结果的稳健性.为解决这两个问.题,首次提出一种简单有效的RC参数初始值的选取方法和调整最优化模型中的目标函数的方法,保证该算法在不同放电电流情况下均能得到正确的解.仿真结果表明:在选定合适的初始值的情况下,该算法能够快速准确求解模型中的RC参数值.

The establishment of an accurate battery model is critical for the estimation of SOC(state of charge)and SOH(state of health).The accuracy of model mainly depends on two aspects:the determination of the model kind and the identification of model parameters.The research shows that the second-order dynamic lithium-ion battery model can effectively simulate charging and discharging process.So this paper mainly focus on the second-order model of lithium battery.The problem of parameters identification of the model can be reduced to a nonlinear optimization problem.Firstly,a corresponding nonlinear least squares optimization model is established.Then the optimal identification results of the parameters are obtained by the Levenberg-Marquard algorithm.However the optimization problem is not only non-linear,but also non-convex.So the selection of the initial value of RC parameters is important to the outcome of the algorithm.At the same time,the variation of the discharge current will also affect the identification results.In order to solve these two problems,this paper first proposes a simple and effective method for selecting the initial value of RC parameters and a method for adjusting the objective function in the optimization model to ensure the algorithm can obtain correct solutions under different discharge current conditions.Parameters under different soc are identified by this method.The simulation results show that the algorithm can quickly and accurately obtain the RC parameter values in the model when a suitable initial value is selected.