Electrothermally-Aware Multi-objective Modular Design: A Case Study on Series-Parallel Hybrid Propulsion Systems

This paper introduces an effective modular design solution for series-parallel hybrid propulsion systems (HPSs) based on a battery electrothermal model and a temperature-related sub-objective to consider both the battery electrical and thermal behaviors. To ensure that more optimal design options are provided, a Pareto-augmented collaborative optimization (PACO)-based framework is proposed to integrate three multiobjective evolutionary algorithms (MOEAs), aiming to expand the distribution of the Pareto frontier. Furthermore, two real driving cycles obtained from worldwide harmonized light vehicles are utilized to evaluate the performance of the optimized vehicle systems. The results show that the decomposed MOEA (MOEA/D) within PACO is the main contributor to the performance improvement in the modular design of HPSs, which leads to the reduction of generational distance by over 2.7% and the increase of the hypervolume by over 17.6%, in comparison with two state-of-the-art evolutionary algorithms.