Hierarchical Energy Management and Energy Saving Potential Analysis for Fuel Cell Hybrid Electric Tractors

Shenghui Lei, Yanying Li, Mengnan Liu (), Wenshuo Li, Tenglong Zhao, Shuailong Hou and Liyou Xu ()
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Shenghui Lei: College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China
Yanying Li: College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China
Mengnan Liu: College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China
Wenshuo Li: College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China
Tenglong Zhao: College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China
Shuailong Hou: College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China
Liyou Xu: College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China

Energies, 2025, vol. 18, issue 2, 1-27

Abstract: To address the challenges faced by fuel cell hybrid electric tractors (FCHETs) equipped with a battery and supercapacitor, including the complex coordination of multiple energy sources, low power allocation efficiency, and unclear optimal energy consumption, this paper proposes two energy management strategies (EMSs): one based on hierarchical instantaneous optimization (HIO) and the other based on multi-dimensional dynamic programming with final state constraints (MDDP-FSC). The proposed HIO-based EMS utilizes a low-pass filter and fuzzy logic correction in its upper-level strategy to manage high-frequency dynamic power using the supercapacitor. The lower-level strategy optimizes fuel cell efficiency by allocating low-frequency stable power based on the principle of minimizing equivalent consumption. Validation using a hardware-in-the-loop (HIL) simulation platform and comparative analysis demonstrate that the HIO-based EMS effectively improves the transient operating conditions of the battery and fuel cell, extending their lifespan and enhancing system efficiency. Furthermore, the HIO-based EMS achieves a 95.20% level of hydrogen consumption compared to the MDDP-FSC-based EMS, validating its superiority. The MDDP-FSC-based EMS effectively avoids the extensive debugging efforts required to achieve a final state equilibrium, while providing valuable insights into the global optimal energy consumption potential of multi-energy source FCHETs.

Keywords: fuel cell; hybrid electric tractors; energy management strategy; hierarchical instantaneous optimization; dynamic programming; optimal energy consumption (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: 2025
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