Design method of dual-motor electric tractor drive system based on mass constraint algorithm under uncertainty using mass

Junjiang Zhang, Mingyue Shi, Mengnan Liu, Dongqing Wang, Xianghai Yan, Liyou Xu and Yiwei Wu

Energy, 2025, vol. 322, issue C

Abstract: The tractor using mass is uncertain at the beginning of design, which results in the inability to accurately obtain the driving index constraints for the tractor. To solve the above problems, this paper proposes a parameter design method of dual-motor electric tractor drive system under uncertainty using mass. First, to solve the problem of unable to obtain the driving index constraints for the tractor due to uncertainty using mass, a tractor mass constraint algorithm is proposed and then the algorithm convergence is proved by numerical derivation. Next, to optimize the operating efficiency of the power source, an instantaneous optimization algorithm is adopted to optimize the torque distribution of the dual-motor and the power coupling device gear ratio. Finally, a parameter design method is formed by fusing the tractor mass constraint algorithm, the instantaneous optimization algorithm and the genetic algorithm. To verify the effectiveness of the method, the rule design method is used as a comparison method with the simulation and the HIL test are carried out under plowing conditions. The using mass and energy consumption resulting from the parameter design method are reduced by 8.54% and 4.15%, respectively, comparing with the rule design method.

Keywords: Electric tractor; Coupled drive; Tractor mass constraint algorithm; Instantaneous optimization algorithm; Genetic algorithm (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:322:y:2025:i:c:s0360544225007820

DOI: 10.1016/j.energy.2025.135140

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