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author:

Lin, X.-Y. (Lin, X.-Y..) [1] | Su, L. (Su, L..) [2] | Zheng, Q.-X. (Zheng, Q.-X..) [3]

Indexed by:

Scopus PKU CSCD

Abstract:

Employing traditional coordination control strategy or model predictive control (MPC) to solve the ride comfort problem during mode transition, however, there are disadvantages such as the non-significant effect of the improvement and the lack of in-depth detailed research. In this paper, a dynamic coordination control strategy involving the clutch mode transition process based on MPC is formulated to ameliorate the ride comfort of the mode transition process with clutch engagement for hybrid electric vehicles. On the basis of simplifying mode transition model with clutch in hybrid system, the principle description of MPC on mode transition coordination control is carried out to reduce the jerk of mode transition with clutch which is employed to perform the design of dynamic coordination control strategy based on MPC, and then the comparison of jerk under different weighting factors is performed. Through experimental verification, the results show that the maximum jerk of mode transition coordination control using MPC was declined from 26.3 m/s3 to 9.26 m/s3, and 64.8% decreased, which effectively suppresses the jerk in the process of the mode transition and improves the ride comfort. © 2020, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.

Keyword:

Coordination control strategy; Hybrid vehicle; Mode transition; Model predictive control (MPC)

Community:

  • [ 1 ] [Lin, X.-Y.]College of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, Fujian 350002, China
  • [ 2 ] [Lin, X.-Y.]Key Laboratory of Fluid Power and Intelligent Electro-Hydraulic Control (Fuzhou University), Fuzhou, Fujian 350002, China
  • [ 3 ] [Su, L.]College of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, Fujian 350002, China
  • [ 4 ] [Zheng, Q.-X.]College of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, Fujian 350002, China

Reprint 's Address:

  • [Lin, X.-Y.]College of Mechanical Engineering and Automation, Fuzhou UniversityChina

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Source :

Control Theory and Applications

ISSN: 1000-8152

Year: 2020

Issue: 4

Volume: 37

Page: 897-906

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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