Title: A real-time energy management strategy based on fuzzy control and ECMS for PHEVs

Authors: Shuhan Wang; Kun Yao; Peng Dong; Xiangyang Xu; Weiqiang Li; Wei Guo; Shipeng Li; Zhengrui Niu; Yajun Huang; Yi Liu

Addresses: Department of Automotive Engineering, School of Transportation Science and Engineering, Beihang University, Beijing, 100191, China; Ningbo Institute of Technology, Beihang University, Ningbo, 315832, China; National Engineering and Technology Research Center of Automatic Transmission for Passenger Vehicles, 261205, China; China FAW Group Co. Ltd., Jilin, 130000, China ' Department of Automotive Engineering, School of Transportation Science and Engineering, Beihang University, Beijing, 100191, China ' Department of Automotive Engineering, School of Transportation Science and Engineering, Beihang University, Beijing, 100191, China; Ningbo Institute of Technology, Beihang University, Ningbo, 315832, China ' Department of Automotive Engineering, School of Transportation Science and Engineering, Beihang University, Beijing, 100191, China; Ningbo Institute of Technology, Beihang University, Ningbo, 315832, China; National Engineering and Technology Research Center of Automatic Transmission for Passenger Vehicles, 261205, China; China FAW Group Co. Ltd., Jilin, 130000, China ' China FAW Group Co. Ltd., Jilin, 130000, China ' Ningbo Institute of Technology, Beihang University, Ningbo, 315832, China ' Guizhou Kaixing Hydraulic Transmission Machinery Co. Ltd., Zunyi, 563003, China ' Physis New Energy Technology (Ningbo) Ltd., Ningbo, 315336, China ' Shantui Mechanical Engineering Co. Ltd., Jining, 272073, China ' Shaanxi Fast Gear Co. Ltd., Xi'an, 710199, China

Abstract: Hybrid electric vehicles (HEVs) have the advantages of strong dynamic, low fuel consumption, and low emission. The energy management strategy (EMS) is the key to giving full play to these advantages. In this context, an online adaptive EMS for plug-in hybrid electric vehicle (PHEV) with P2 architecture is proposed, including a fuzzy control-based working mode decision method (F-WMDM) and an adaptive equivalent consumption minimisation strategy (A-ECMS)-based torque distribution strategy. Furthermore, a mileage-based state of charge (SOC) reference curve is established, which is provided by internet information, GNSS, and navigation map. The SOC reference curve is an important basis for working mode decisions, and also a reference for adjusting the equivalent factor (EF) of ECMS. Finally, the simulation results show that under two driving cycles, the EMS based on F-WMDM and A-ECMS can reduce the engine start and stop times and fuel consumption compared with the rule-based EMS effectively.

Keywords: equivalent consumption minimisation strategy; energy management strategy; fuzzy control; plug-in hybrid electric vehicle; PHEV.

DOI: 10.1504/IJPT.2024.140136

International Journal of Powertrains, 2024 Vol.13 No.2, pp.178 - 200

Received: 23 Oct 2022
Accepted: 20 Jan 2024
Published online: 24 Jul 2024 *

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