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author:

Yang, Xuelan (Yang, Xuelan.) [1] | Lin, Xinyou (Lin, Xinyou.) [2] | Huang, Qiang (Huang, Qiang.) [3] | Zheng, Qingxiang (Zheng, Qingxiang.) [4] | Wu, Hao (Wu, Hao.) [5]

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EI

Abstract:

Considering the trade-off on the improvement of fuel economy performance and mode transition comfort for multimode hybrid electric vehicles (MMHEV), a bi-objective trade-off control strategy is designed based on the equivalent consumption minimization strategy (ECMS) with Pareto method. Aiming at the problem of optimal economy of multimode working area of vehicles, the equivalent fuel consumption cost and torque distribution MAP in different modes are determined based on ECMS. In order to solve the problem of torque instability caused by engine response lag and demand torque fluctuation, the motor torque optimization coefficient (MTOC) is introduced as the control variable by taking advantage of the motor's fast and accurate response to torque, and the genetic algorithm is used to optimize the MTOC, and a smoother torque distribution is obtained. Because there is a coupling relationship between the economy and ride comfort of the system, the trade-off optimization is carried out using the NSGA-II algorithm based on Pareto principle. The simulation verification conducted in nonslope and slope conditions, as well as hardware-in-the-loop experiments, demonstrates the effectiveness of the proposed control strategy in managing the trade-off between economy and ride comfort for the MMHEV. © 2023 Wiley-VCH GmbH.

Keyword:

Economic and social effects Electric machine control Fuel economy Genetic algorithms Hybrid vehicles Pareto principle Torque Traction motors

Community:

  • [ 1 ] [Yang, Xuelan]Key Laboratory of Conveyance Equipment, East China Jiaotong University, Ministry of Education, Jiangxi, Nanchang; 330013, China
  • [ 2 ] [Lin, Xinyou]College of Mechanical Engineering & Automation, Fuzhou University, Fujian, Fuzhou; 350108, China
  • [ 3 ] [Huang, Qiang]College of Mechanical Engineering & Automation, Fuzhou University, Fujian, Fuzhou; 350108, China
  • [ 4 ] [Zheng, Qingxiang]College of Mechanical Engineering & Automation, Fuzhou University, Fujian, Fuzhou; 350108, China
  • [ 5 ] [Wu, Hao]Key Laboratory of Conveyance Equipment, East China Jiaotong University, Ministry of Education, Jiangxi, Nanchang; 330013, China

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Source :

Energy Technology

ISSN: 2194-4288

Year: 2024

Issue: 1

Volume: 12

3 . 6 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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