针对电动车辆的复杂行驶工况,提出一种基于雨流计数原理的实时预估钴酸锂电池健康状态(state of health,SOH)的建模方法。首先,开发了一种改进的实时雨流计数法,实现对不同放电深度(depth of discharge,DOD)下循环次数的统计分析;在此...针对电动车辆的复杂行驶工况,提出一种基于雨流计数原理的实时预估钴酸锂电池健康状态(state of health,SOH)的建模方法。首先,开发了一种改进的实时雨流计数法,实现对不同放电深度(depth of discharge,DOD)下循环次数的统计分析;在此基础上,提出一种利用等效充放电电流–荷电状态(state of charge,SOC)的包络面积,来评估每次循环中衰减因子的计算方法,并以不同循环次数下衰减因子的累加和来刻画电池的寿命衰减;最后,设计电池循环老化实验,验证了所提出方法可实现对随机充放电电流、DOD和循环次数下的电池SOH实时估计。展开更多
The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of...The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of soil.In order to save computing time during parameter inversion,a new procedure to compute the calculated strains is presented by multi-linear simplification approach instead of finite element method(FEM).The real-coded hybrid genetic algorithm is developed by combining normal genetic algorithm with gradient-based optimization algorithm.The numerical and experimental results for conditioned soil are compared.The forecast strains based on identified nonlinear constitutive model of soil agree well with observed ones.The effectiveness and accuracy of proposed parameter estimation approach are validated.展开更多
文摘针对电动车辆的复杂行驶工况,提出一种基于雨流计数原理的实时预估钴酸锂电池健康状态(state of health,SOH)的建模方法。首先,开发了一种改进的实时雨流计数法,实现对不同放电深度(depth of discharge,DOD)下循环次数的统计分析;在此基础上,提出一种利用等效充放电电流–荷电状态(state of charge,SOC)的包络面积,来评估每次循环中衰减因子的计算方法,并以不同循环次数下衰减因子的累加和来刻画电池的寿命衰减;最后,设计电池循环老化实验,验证了所提出方法可实现对随机充放电电流、DOD和循环次数下的电池SOH实时估计。
基金Project(2007CB714006) supported by the National Basic Research Program of China Project(90815023) supported by the National Natural Science Foundation of China
文摘The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of soil.In order to save computing time during parameter inversion,a new procedure to compute the calculated strains is presented by multi-linear simplification approach instead of finite element method(FEM).The real-coded hybrid genetic algorithm is developed by combining normal genetic algorithm with gradient-based optimization algorithm.The numerical and experimental results for conditioned soil are compared.The forecast strains based on identified nonlinear constitutive model of soil agree well with observed ones.The effectiveness and accuracy of proposed parameter estimation approach are validated.
