Design of rule-based controller and parameter optimization using a genetic algorithm for a dual motor heavy duty battery electric vehicle
2022-01-0489
03/29/2022
- Event
- Content
- This paper designs a configuration and controller for dual motor battery electric vehicles (BEVs) using Assisted Model Building with Energy Refinement (AMBER). A model with two electric motors is designed based on literature and current market search, where one is on the front axle and the other is on the rear axle. Based on the model, a rule-based control algorithm is designed for the new dual motor BEV and the control parameters are optimized by using a genetic algorithm (GA). The vehicle model is simulated in different driving cycles and grade-ability tests. The results have shown that there is a good agreement between the speed profile simulated by the model and that of the driving cycles. In addition, it is able to satisfy the grade-ability performance requirements of trucks. The simulation results are then compared with different model that use a single motor, which shows that the dual motor BEV model consumes less energy under the same load
- Citation
- yu, K., Vijayagopal, R., and Kim, N., "Design of rule-based controller and parameter optimization using a genetic algorithm for a dual motor heavy duty battery electric vehicle," SAE Technical Paper 2022-01-0489, 2022, .