Research on thermal energy management for PHEV based on NSGA-II optimization algorithm

The plug-in hybrid electric vehicle (PHEV) is a new type of energy vehicle that has extremely high demands for vehicle energy consumption management. This study aims to achieve refined energy management of PHEVs, while avoiding high energy consumption associated with independent control of the thermal management system. For this purpose, a reliable co-simulation platform based on a particular PHEV energy and thermal management system architecture is developed. The platform aims to optimize engine fuel consumption and ensure the stability of the coolant temperature. This study introduces the NSGA-II genetic algorithm to the field of vehicle R&D to collaboratively control the rotary speed of the pump and fan, which highly accelerating the vehicle development cycle. The results show that the optimized algorithm for engine thermal management system efficiently improved fuel economy under dynamics driving conditions. Under SFTP-US06 conditions, the fuel consumption of the PHEV reduced by 0.46L/100 km, resulting in a fuel-saving rate of 5.67%, and the average power of low-voltage accessories was reduced by 81.81%.The approach used in this research can increase the accuracy of the virtual calibration and help shorten the automotive development cycle.