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Design of a Rule-Based Controller and Parameter Optimization Using a Genetic Algorithm for a Dual-Motor Heavy-Duty Battery Electric Vehicle
Technical Paper
2022-01-0413
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
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.
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Citation
Yu, K., Vijayagopal, R., and Kim, N., "Design of a Rule-Based Controller and Parameter Optimization Using a Genetic Algorithm for a Dual-Motor Heavy-Duty Battery Electric Vehicle," SAE Technical Paper 2022-01-0413, 2022, https://doi.org/10.4271/2022-01-0413.Also In
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