Research on Energy Management Strategy for Hybrid Tractors Based on DP-MPC

Yifan Zhao, Liyou Xu, Chenhui Zhao, Haigang Xu and Xianghai Yan ()
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Yifan Zhao: 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
Chenhui Zhao: YTO Belarus Technology Co., Ltd., Luoyang 471004, China
Haigang Xu: Shandong Shifeng (Group) Co., Ltd., Liaocheng 252800, China
Xianghai Yan: College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China

Energies, 2024, vol. 17, issue 16, 1-22

Abstract: To further improve the fuel economy of hybrid tractors, an energy management strategy based on model predictive control (MPC) solved by dynamic programming (DP) is proposed, taking into account the various typical operating conditions of tractors. A coupled dynamics model was constructed for a series diesel–electric hybrid tractor under three typical working conditions: plowing, rotary tillage, and transportation. Using DP to solve for the globally optimal SOC change trajectory under each operating condition of the tractor as the SOC constraint for MPC, we designed an energy management strategy based on DP-MPC. Finally, a hardware-in-the-loop (HIL) test platform was built using components such as Matlab/Simulink, NI-Veristand, PowerCal, HIL test cabinet, and vehicle controller. The designed energy management strategy was then tested using the HIL test platform. The test results show that, compared with the energy management strategy based on power following, the DP-MPC-based energy management strategy reduces fuel consumption by approximately 7.97%, 13.06%, and 11.03%, respectively, under the three operating conditions of plowing, rotary tillage, and transportation. This achieves fuel-saving performances of approximately 91.34%, 94.87%, and 96.69% compared to global dynamic programming. The test results verify the effectiveness of the proposed strategy. This research can provide an important reference for the design of energy management strategies for hybrid tractors.

Keywords: hybrid tractor; energy management strategy; dynamic programming; model predictive control; hardware in the loop (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: View citations in EconPapers (1)

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