Power distribution optimization for hybrid power source integrated with battery and super-capacitor considering vehicle energy consumption

Abstract

The enhancement of energy utilization of battery/super-capacitor hybrid power source can improve the driving economy of electric vehicle. Introducing optimization algorithms to achieve optimal power distribution for battery/super-capacitor hybrid power source is an important means of effectively reducing energy consumption and is worth further exploration. This article takes the energy consumption rate as the optimization objective and establishes a fitness function based on the relationship between energy consumption rate and battery current, while achieving the minimum energy consumption rate, the optimal battery current can also be obtained. The established algorithm simulation models for power distribution strategies based on particle swarm optimization algorithm, seeker optimization algorithm, and whale optimization algorithm are integrated with circuit model of the hybrid power source-based driving system of vehicle, respectively, simulations are conducted based on the New European Driving Cycle working condition. The three control strategies can achieve average energy efficiency of about 87.5%, 85.5% and 86.0%, respectively, and average energy consumption rate of approximately 0.146 kWh/km, 0.147 kWh/km and 0.146 kWh/km. In addition, the simulation results of three control strategies are compared and analyzed in terms of simulation time, optimization iteration times, and solution stability. This work can provide reference for related research on power distribution optimization of hybrid power source.