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Automotive Engineering ›› 2025, Vol. 47 ›› Issue (4): 746-754.doi: 10.19562/j.chinasae.qcgc.2025.04.015

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Multi-output Sensitivity Analysis for the Powertrain Mounting System of Electric Vehicles

Xiaoting Huang1,Haibiao Zhang1,2,Changyu Li1(),Hui Lü2,Wenbin Shangguan2   

  1. 1.School of Automobile and Traffic Engineering,Guangzhou City University of Technology,Guangzhou 510800
    2.School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510641
  • Received:2024-07-01 Revised:2024-11-21 Online:2025-04-25 Published:2025-04-18
  • Contact: Changyu Li E-mail:licy@gcu.edu.cn

Abstract:

There are many investigated parameters in the powertrain mounting system (PMS) of electric vehicles, and it involves multi-performance design. For the problem that the traditional single-output sensitivity analysis is difficult to accurately evaluate the influence of system parameters on the system comprehensive performance, the multi-output response sensitivity analysis of the PMS of electric vehicle is carried out by considering the uncertainty of system parameters. Firstly, a 13-degree-of-freedom analysis model of PMS is established, and the uncertain parameters of system are described by the random variables. Then, based on the summation of covariance decomposition, the first order index and the global sensitivity index of the multi-output response of system are derived. Next, a method of calculating the sensitivity indexes of multi-output response is proposed based on Monte Carlo analysis. Finally, the effectiveness of the proposed method is verified by the numerical example of the PMS of an electric vehicle. The analysis results show that the single output sensitivity analysis may not be able to accurately evaluate the comprehensive influence of parameters on the system response, and it may produce contradictory results. The proposed multi-output sensitivity analysis method can effectively evaluate the comprehensive influence of system parameters on the system response, and it can obtain more accurate sensitivity ranking for system parameters.

Key words: electric vehicle, powertrain mounting system, uncertainty, sensitivity analysis, multi-output response