Real-Time Energy Management Strategy for Fuel Cell Vehicles Based on DP and Rule Extraction

Yanwei Liu, Mingda Wang, Jialuo Tan, Jie Ye () and Jiansheng Liang
Additional contact information
Yanwei Liu: School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China
Mingda Wang: School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China
Jialuo Tan: School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China
Jie Ye: School of Mechatronics Engineering, Foshan University, Foshan 528225, China
Jiansheng Liang: Automotive Engineering Research Institute, BYD Co., Ltd., Shenzhen 518118, China

Energies, 2024, vol. 17, issue 14, 1-20

Abstract: Energy management strategy (EMS), as a core technology in fuel cell vehicles (FCVs), profoundly influences the lifespan of fuel cells and the economy of the vehicle. Aiming at the problem of the EMS of FCVs based on a global optimization algorithm not being applicable in real-time, a rule extraction-based EMS is proposed for fuel cell commercial vehicles. Based on the results of the dynamic programming (DP) algorithm in the CLTC-C cycle, the deep learning approach is employed to extract output power rules for fuel cell, leading to the establishment of a rule library. Using this library, a real-time applicable rule-based EMS is designed. The simulated driving platform is built in a CARLA, SUMO, and MATLAB/Simulink joint simulation environment. Simulation results indicate that the proposed strategy yields savings ranging from 3.64% to 8.96% in total costs when compared to the state machine-based strategy.

Keywords: energy management strategy; fuel cell vehicles; rule extraction; dynamic programming (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/14/3465/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/14/3465/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:14:p:3465-:d:1434948

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().