Study on Multi-Objective Optimization of Power System Parameters of Battery Electric Vehicles

The optimization of power parameters is the key to design pure electric vehicles. Reasonable matching relationship between various can effectively reduce energy consumption and achieve sustainability. In this paper, several vehicle performance indexes such as maximum speed, acceleration time per 100 km were used target vectors, transmission ratio was variable establish problem parameter matching. Then, feasible domain obtained by taking lowest index constraint condition. domain, multi-objective genetic algorithm solve problem. Pareto optimal solution set for fixed two-gear transmission, which an alternative set. final parameter-matching scheme determined comparing different motors comprehensively. results show that competition multiple optimizable be described solving front. Specifically, motor A + 1.33~1.85; 2 [1.72, 0.98]~[2.99, 1.57], B [2.99, 1.40]~[2.99, 1.57]. does not require clutch designing a shift algorithm. Therefore, after comprehensive consideration, scheme.