Joint Optimization of Configuration, Component Sizing, and Energy Management for Input-Split Hybrid Powertrains

Abstract

Configuration design, component sizing, and energy management are intertwined. However, the full potential of hybrid powertrains has not yet been thoroughly investigated due to the multi-dimensional design space. Therefore, in this paper, a joint optimization method combining particle swarm optimization (PSO) and convex programming (CP) is proposed for the first time. In the outer loop, the PSO algorithm searches for the optimal design for the powertrain configuration. In contrast, the component size and power management are simultaneously optimized by the CP algorithm in the inner loop. A combined driving cycle is designed to integrate both acceleration and energy-saving performance, where an extreme acceleration driving process is intended to act as the acceleration constraint. The results show that, compared to Prius 1st, the acceleration and total cost-saving of the optimal 1-PG (planetary gear) powertrain are improved by 13.09% and 11.08%, respectively. In particular, the acceleration and total cost-saving of the optimal 2-PG powertrain (MG2-RSG) are upgraded by 34.23% and 15.18%, respectively. Finally, the effectiveness and efficiency of the proposed method are verified by comparing it with dynamic programming (DP) and multi-objective evolutionary algorithm based on the decomposition (MOEA/D) method.