Design of a Rule-Based Controller and Parameter Optimization Using a Genetic Algorithm for a Dual-Motor Heavy-Duty Battery Electric Vehicle

This paper describes a configuration and controller, designed using Autonomie,1 for dual-motor battery electric vehicle (BEV) heavy-duty trucks. Based on the literature and current market research, this model was designed with two electric motors, one on the front axle and the other on the rear axle. A rule-based control algorithm was designed for the new dual-motor BEV, based on the model, and the control parameters were optimized by using a genetic algorithm (GA). The model was simulated in diverse driving cycles and gradeability tests. The results show both a good following of the desired cycle and achievement of truck gradeability performance requirements. The simulation results were compared with those of a single-motor BEV and showed reduced energy consumption with the high-efficiency operation of the two motors.

Language

  • English

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Filing Info

  • Accession Number: 01841729
  • Record Type: Publication
  • Source Agency: SAE International
  • Report/Paper Numbers: 2022-01-0413
  • Files: TRIS, SAE
  • Created Date: Apr 6 2022 2:18PM