基于概率模型和数据驱动的动力总成悬置系统可靠性优化  

Reliability Optimization for the Powertrain Mounting System Based on Probability Model and Data-Driven Model

作　　者：吕辉 张家明 黄晓婷 上官文斌[2] LüHui;Zhang Jiaming;Huang Xiaoting;Shangguan Wenbin(School of Automobile and Traffic Engineering,Guangzhou City University of Technology,Guangzhou 510800;School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510641)

机构地区：[1]广州城市理工学院汽车与交通工程学院,广州510800 [2]华南理工大学机械与汽车工程学院,广州510641

出　　处：《汽车工程》2024年第3期456-463,488,共9页Automotive Engineering

基　　金：国家自然科学基金(51975217,52375093);广东省自然科学基金(2023A1515011585)资助。

摘　　要：针对电动汽车动力总成悬置系统(PMS)一部分参数为概率变量,一部分参数为离散数据的复杂不确定情形,开展了基于概率模型和数据驱动的电动汽车PMS可靠性优化设计研究。首先,基于任意多项式混沌(APC)展开和广义最大熵原理推导了一种求解该复杂不确定情形下PMS响应不确定性和可靠性的高效方法;然后,基于蒙特卡洛抽样,给出了该复杂不确定情形下求解PMS响应不确定性和可靠性的参考方法;接着,提出了一种基于APC展开法的灵敏度分析方法,进一步提出了一种考虑响应不确定性和可靠性的PMS优化设计方法;最后,通过应用算例验证方法的有效性,并对系统进行了灵敏度分析和可靠性优化。结果表明,所提出的方法可有效地处理电动汽车PMS一部分参数为概率变量、一部分参数为离散数据的复杂不确定情形,并能可靠地优化该情形下的系统固有特性,且方法具有较高的计算精度和计算效率。For complex and uncertain situations related to the powertrain mounting system(PMS)of electric vehicle where some parameters are probabilistic variables,and some parameters are discrete data,a study on the reliability optimization design for the PMS of electric vehicles is conducted based on the probabilistic model and data-driven model.Firstly,based on the arbitrary polynomial chaos(APC)expansion and generalized maximum entropy principle,an efficient method is derived for solving the uncertainty and reliability of the PMS response under the aforementioned complex uncertain situation.Then,based on the Monte Carlo sampling,a reference method is proposed for performing the uncertainty and reliability analysis of PMS.Next,a sensitivity analysis method based on APC expansion method is proposed,and an optimization method of PMS is further put forward considering the uncertainty and reliability of responses.Finally,a numerical example is used to verify the effectiveness of the proposed method,and the sensitivity analysis and reliability optimization of the system are carried out.The results show that the proposed method can effectively handle the complex and uncertain situations where some parameters of the electric vehicle PMS are probability variables and some parameters are discrete data and can optimize the PMS inherent characteristics reliably with good computational accuracy and efficiency.

关 键 词：电动汽车动力总成悬置系统 任意多项式混沌展开 最大熵原理 数据驱动 不确定性 

分 类 号：U464.13[机械工程—车辆工程]