锂电池内阻参数的研究

Study on Parameters of Lithium Battery Internal Resistance

随着电池的更新换代,锂电池渐渐地成为了该行业内的主要研究对象;针对内阻是反映锂电池状态的重要参数,对松下18650型号锂电池设计充放电实验;对得到的实验数据,用文中提出的改进灰色关联分析算法进行分析研究;并将该算法用作遗传粒子群算法的适应度函数进行最小二乘支持向量机算法的参数选优,达到了全面分析时间序列参数变化的目的;通过Matlab的建模分析,用变差函数改进的灰色关联分析法能够证明内阻的变化与锂电池的荷电状态变化关联度最高,适合作为荷电状态估计的主要因素;为了进一步分析锂电池内阻的性能,使用改进算法对锂电池内阻与各参数的变化关系进行分析,可得内阻的大小变化受电流、温度等参数变化的影响;因此,正确估计锂电池的状态,必须综合考虑锂电池的各项基本参数。

are becoming the main target of the industry.For the internal resistance is an important parameter reflecting the state of the lithium battery,the charging and discharging experiment for Panasonic 18650 lithium battery is designed.The obtained experimental data are analyzed and studied by the improved grey relational analysis(GRA)algorithm.The algorithm is used as the fitness function of the genetic particle swarm optimization algorithm to optimize the parameters of the least squares support vector machines(LS-SVM),and the purpose to comprehensive analysis the change of time series is achieved.Through the modeling analysis of MATLAB,the GRA method that improved by variogram function,which proved the internal resistance could reflect the state of the lithium battery better.In order to analyze the internal resistance of lithium battery further,the relationship between the internal resistance of lithium battery and its parameters is analyzed by using improved algorithm,it can be seen that the magnitude of internal resistance can be affected by the change of current,temperature and other parameters.So,in order to correctly estimate the state of the battery,the relevant parameters must be considered.