Title: Study on the fuel economy of fuel cell electric vehicle based on rule-based energy management strategies

Authors: Yu Song; Kai Han; Xiaolong Li

Addresses: Engineering and Research Institute, Wanbao Mining Limited, Beijing, China ' School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China ' School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China

Abstract: This paper designed a fuel cell power system statically to meet the dynamic requirement, with the fuel cell's model and the vehicle model built by GT-Suite. The influence mechanism of different rule-based energy management strategies on the fuel economy was studied. The results revealed that fuel cell worked more efficiently with fuzzy logic control strategy than with power-follower strategy, given an average efficiency increase of 13.27%. Compared with the on/off control strategy, the heat dissipation was reduced by 79.67% with the fuzzy control strategy. Considering the feasibility of real-time implementation, robustness, and low computational burden, the on/off control strategy was optimised by a non-dominated sorting genetic algorithm (NSGA-II), based on ModeFRONTIER (MF). Compared with the original strategy, the fuel consumption was reduced by 17.9%.

Keywords: powertrain; rule-based energy management strategy; NSGA-II; electric vehicle; fuel cell; optimisation method; fuzzy logic controller; energy balance.

DOI: 10.1504/IJPT.2021.120331

International Journal of Powertrains, 2021 Vol.10 No.3, pp.266 - 292

Accepted: 02 Sep 2021
Published online: 11 Jan 2022 *

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