Multi-objective robust optimization design for powertrain mount system of electric vehicles

A multi-objective robust optimization scheme for the powertrain mount system of an electric vehicle is proposed in this paper. A permanent magnet synchronous motor model is established by taking account of the effects of magnetic saturation and space harmonics, in which the d–q -axis inductance and...

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Main Authors: Fu-Long Xin, Li-Jun Qian, Hai-Ping Du, Wei-Hua Li
Format: Article
Language:English
Published: SAGE Publishing 2017-09-01
Series:Journal of Low Frequency Noise, Vibration and Active Control
Online Access:https://doi.org/10.1177/0263092317719635
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spelling doaj-bb9c1a40ee84410aa994e64dbcd63bf02020-11-25T01:25:46ZengSAGE PublishingJournal of Low Frequency Noise, Vibration and Active Control1461-34842048-40462017-09-013610.1177/0263092317719635Multi-objective robust optimization design for powertrain mount system of electric vehiclesFu-Long Xin0Li-Jun Qian1Hai-Ping Du2Wei-Hua Li3Department of Vehicle Engineering, Hefei University of Technology, Hefei, ChinaDepartment of Vehicle Engineering, Hefei University of Technology, Hefei, ChinaDepartment of Mechatronic Engineering, School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, Wollongong, NSW, AustraliaDepartment of Mechatronic Engineering, School of Mechanical, Materials & Mechatronic Engineering, University of Wollongong, Wollongong, NSW, AustraliaA multi-objective robust optimization scheme for the powertrain mount system of an electric vehicle is proposed in this paper. A permanent magnet synchronous motor model is established by taking account of the effects of magnetic saturation and space harmonics, in which the d–q -axis inductance and the flux linkage excited by permanent magnet were obtained by finite element method. The rippled output torque of the permanent magnet synchronous motor mixed with harmonic components is obtained with the New European Driving Cycle as the running condition of the electric vehicle. A six degree-of-freedoms (DOFs) powertrain mount system is established and the response of the system is obtained with the rippled torque as the excitation input. A multi-objective optimization model of the powertrain mount system is built with the stiffness’s of the mounts as the design variables, and with the goal of maximizing the decoupling rates and minimizing the dynamic reaction forces of the mounts acting on the car body. Genetic algorithm is used to conduct the global optimization and all the Pareto optimal solutions are found out based on the optimization theory, and the solution with the optimal robustness of dynamic reaction force is obtained by Latin hypercube sampling method. The results show that with the proposed multi-objective robust optimization scheme applied for the parameters optimization of the motor mount system, the decoupling rates increase obviously, the dynamic reaction force decreases apparently, and the optimization result shows good robustness. The optimization results can make the powertrain mount system of electric vehicles processing of optimal dynamic response characteristics correspondingly.https://doi.org/10.1177/0263092317719635
collection DOAJ
language English
format Article
sources DOAJ
author Fu-Long Xin
Li-Jun Qian
Hai-Ping Du
Wei-Hua Li
spellingShingle Fu-Long Xin
Li-Jun Qian
Hai-Ping Du
Wei-Hua Li
Multi-objective robust optimization design for powertrain mount system of electric vehicles
Journal of Low Frequency Noise, Vibration and Active Control
author_facet Fu-Long Xin
Li-Jun Qian
Hai-Ping Du
Wei-Hua Li
author_sort Fu-Long Xin
title Multi-objective robust optimization design for powertrain mount system of electric vehicles
title_short Multi-objective robust optimization design for powertrain mount system of electric vehicles
title_full Multi-objective robust optimization design for powertrain mount system of electric vehicles
title_fullStr Multi-objective robust optimization design for powertrain mount system of electric vehicles
title_full_unstemmed Multi-objective robust optimization design for powertrain mount system of electric vehicles
title_sort multi-objective robust optimization design for powertrain mount system of electric vehicles
publisher SAGE Publishing
series Journal of Low Frequency Noise, Vibration and Active Control
issn 1461-3484
2048-4046
publishDate 2017-09-01
description A multi-objective robust optimization scheme for the powertrain mount system of an electric vehicle is proposed in this paper. A permanent magnet synchronous motor model is established by taking account of the effects of magnetic saturation and space harmonics, in which the d–q -axis inductance and the flux linkage excited by permanent magnet were obtained by finite element method. The rippled output torque of the permanent magnet synchronous motor mixed with harmonic components is obtained with the New European Driving Cycle as the running condition of the electric vehicle. A six degree-of-freedoms (DOFs) powertrain mount system is established and the response of the system is obtained with the rippled torque as the excitation input. A multi-objective optimization model of the powertrain mount system is built with the stiffness’s of the mounts as the design variables, and with the goal of maximizing the decoupling rates and minimizing the dynamic reaction forces of the mounts acting on the car body. Genetic algorithm is used to conduct the global optimization and all the Pareto optimal solutions are found out based on the optimization theory, and the solution with the optimal robustness of dynamic reaction force is obtained by Latin hypercube sampling method. The results show that with the proposed multi-objective robust optimization scheme applied for the parameters optimization of the motor mount system, the decoupling rates increase obviously, the dynamic reaction force decreases apparently, and the optimization result shows good robustness. The optimization results can make the powertrain mount system of electric vehicles processing of optimal dynamic response characteristics correspondingly.
url https://doi.org/10.1177/0263092317719635
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AT lijunqian multiobjectiverobustoptimizationdesignforpowertrainmountsystemofelectricvehicles
AT haipingdu multiobjectiverobustoptimizationdesignforpowertrainmountsystemofelectricvehicles
AT weihuali multiobjectiverobustoptimizationdesignforpowertrainmountsystemofelectricvehicles
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