Optimization of multi-motor and multi-speed powertrain system for electric vehicles based on efficiency characteristics between motor and inverter

Multi-motor, multi-speed powertrain systems for electric vehicles (EVs) provide superior EV efficiency and performance. The electric efficiency, determined by motor and inverter losses, directly relates to EV efficiency. This study proposes a process for efficiency characteristic analysis between the motor and inverter to analyze the integrated efficiency of the motor and inverter. The results of the motor parameter effects on the motor and inverter efficiencies showed the need to consider both efficiency characteristics to improve EV efficiency. To optimize the EV powertrain system, a multi-objective optimization problem was formulated using design variables of the motor and transmission, such as the stack length, coil turns, motor torque distribution, and gear ratios, to improve both energy efficiency and dynamic performance. To address the computational burden during optimization, an artificial neural network (ANN)-based optimization method was introduced. Optimization was conducted for two cases, considering (i) motor efficiency only and (ii) integrated efficiency, to confirm the importance of including both motor and inverter efficiencies in the optimization of EV powertrain systems. Comparison of EV efficiency and performance results for both cases demonstrated the superiority of the optimal solutions based on the integrated efficiency case. Additionally, a comparison of the calculation times between the EV simulation and ANN prediction models demonstrated the practicality of the ANN-based multi-objective optimization for EV powertrain systems.