Sizing of Power Train and Cooling of the Battery Systems of Hybrid Electric Vehicles by using Genetic Algorithm

Nowadays, the development of HEVs is done from three approaches: emission, fuel consumption, and vehicle performance. Due to the expansion of the use of HEVs around the world, optimal performance of the power train and power supply in the vehicle system has become an important issue. In this paper, in the first step, an optimal cooling attempt was made during power transfer in batteries by designing battery modules and their optimal configuration. The optimal design of the components of the transmission system and their optimized sizing have been performed in such a way that, while reducing emissions and fuel consumption, the dynamic performance of the vehicle is maintained at the standard level of passenger ones. The characteristics of class B passenger vehicle were utilized for modeling and simulation of the HEV and its optimization carried out by the constrained multi-objective genetic algorithm. It has been depicted that with the simultaneous sizing of power transmission components and optimal cooling of the battery system, fuel consumption and emission can be reduced by 5% and 8%, respectively, in various cycles of driving and traffic conditions.