Torque-leveling threshold-changing rule-based control for parallel hybrid electric vehicles
File(s)
Accepted version
Author(s)
Li, Xuefang
Evangelou, Simos
Type
Journal Article
Abstract
A novel rule-based control strategy is proposed for the energy management of parallel hybrid electric vehicles (HEVs): the torque-leveling threshold-changing strategy (TTS). In contrast to the most commonly used heuristic electric assist control strategy (EACS) that is designed based on the load following approach, the TTS proposes and applies the new fundamental concept of torque leveling. This mechanism operates the engine with a constant torque when the engine is active, thus ensuring the engine works at an efficient operating point. The TTS additionally extends and uses a design concept that has previously been proposed in the context of series HEVs, the
threshold-changing mechanism, to operate the HEV in a chargesustaining manner. By exploiting this new set of design principles for parallel HEVs, the TTS realizes energy source control sharing behavior that is reminiscent to optimization-based methods. To show its effectiveness, the TTS is implemented to a through-theroad (TTR) HEV and benchmarked against two conventional control strategies: Dynamic Programming (DP) and the EACS. The results show that the TTS, despite its simplicity, is able to deliver comparable fuel economy as the global optimization approach DP and thus achieve significant improvement compared to the EACS. In addition, to facilitate real-time application, a simplified version of the TTS (STTS) is also developed, which is able to deliver similar performance as the TTS but is more simple to implement in practice.
threshold-changing mechanism, to operate the HEV in a chargesustaining manner. By exploiting this new set of design principles for parallel HEVs, the TTS realizes energy source control sharing behavior that is reminiscent to optimization-based methods. To show its effectiveness, the TTS is implemented to a through-theroad (TTR) HEV and benchmarked against two conventional control strategies: Dynamic Programming (DP) and the EACS. The results show that the TTS, despite its simplicity, is able to deliver comparable fuel economy as the global optimization approach DP and thus achieve significant improvement compared to the EACS. In addition, to facilitate real-time application, a simplified version of the TTS (STTS) is also developed, which is able to deliver similar performance as the TTS but is more simple to implement in practice.
Date Issued
2019-07-01
Date Acceptance
2019-05-08
Citation
IEEE Transactions on Vehicular Technology, 2019, 68 (7), pp.6509-6523
ISSN
0018-9545
Publisher
Institute of Electrical and Electronics Engineers
Start Page
6509
End Page
6523
Journal / Book Title
IEEE Transactions on Vehicular Technology
Volume
68
Issue
7
Copyright Statement
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Engineering and Physical Sciences Research Council
Engineering & Physical Science Research Council (E
Identifier
https://ieeexplore.ieee.org/document/8713885
Grant Number
515769103 (EP/N022262/1)
515769103 (EP/N022262/1)
Subjects
Science & Technology
Technology
Engineering, Electrical & Electronic
Telecommunications
Transportation Science & Technology
Engineering
Transportation
Energy management
heuristic control strategy
hybrid electric vehicle (HEV)
supervisory control system (SCS)
PONTRYAGINS MINIMUM PRINCIPLE
ENERGY MANAGEMENT
CONTROL STRATEGY
OPTIMIZATION
ALGORITHM
ECMS
Automobile Design & Engineering
08 Information and Computing Sciences
09 Engineering
10 Technology
Publication Status
Published
Date Publish Online
2019-05-14