Global Sensitivity Analysis on Powertrain Mounting Systems of Electric Vehicles
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摘要:
针对电动汽车动力总成悬置系统(Powertrain Mounting System,PMS)参数同时存在不确定性和相关性的情形,开展考虑不确定参数相关性的电动汽车PMS固有特性的全局灵敏度分析研究. 采用含相关性的概率变量描述系统的不确定参数,基于方差分解推导考虑概率变量相关性的一阶和总体全局灵敏度公式;基于蒙特卡洛法(Monte Carlo Method,MCM)提出一种求解全局灵敏度指数的方法;推导当概率变量服从正态分布时的全局灵敏度公式,给出采用MCM计算全局灵敏度指数所需样本集的构造方法;以某电动汽车PMS算例验证方法的有效性. 分析结果表明,相关性会影响系统固有频率和解耦率响应对不确定参数的敏感性,考虑不确定参数的相关性可获得更加合理的灵敏度分析结果.
Abstract:
Aiming to handle the complex situation where the parameters of the powertrain mounting system (PMS) of an electric vehicle were both uncertain and correlated, the global sensitivity analysis of the PMS inherent characteristics to system parameters was investigated by considering the correlation of uncertain parameters. Firstly, the PMS uncertain parameters was treated as probabilistic variables with correlation, and the first-and total-order global sensitivity formulas were derived based on variance decomposition. Then, a method for solving the global sensitivity indexes was proposed based on the Monte Carlo Method (MCM). Next, the global sensitivity formulas were further derived for the case where the probabilistic variables are normally distributed, and the required sample sets to calculate the global sensitivity indexes were constructed by using MCM. Finally, the effectiveness of the proposed method was demonstrated by the numerical example of an electric vehicle PMS. The analysis results show that the parametric correlation has some effect on the sensitivities of the intrinsic frequency and decoupling rate responses to uncertain parameters, and the parametric correlation should be taken into account to obtain more reasonable results of sensitivity analysis.