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

Abstract

This paper introduces an effective modular design solution for series-parallel hybrid propulsion systems (HPSs) based on a battery electrothermal model and a sub-objective related to temperature to concurrently consider both the battery electrical and thermal behaviors. To ensure that more optimal design options are provided, a Pareto-augmented collaborative optimization (PACO) framework is proposed to integrate three multi-objective evolutionary algorithms (MOEAs), aiming to extend the range of the Pareto frontier. Furthermore, two real driving cycles taken from worldwide harmonized light vehicles are utilized to evaluate the performance of the optimized vehicle systems. The modelling 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 intergenerational distance by over 2.7% and increase of the hypervolume by over 17.6%, in comparison with two state-of-the-art evolutionary algorithms.