Multi-Objective Optimal Sizing Hybrid Power System in a Solar Electric Vehicle Using Particle Swarm Optimization Algorithm

Abstract

In a solar electric vehicle, the optimal sizing of hybrid power system can be considered as a multi-objective optimization problem. The two conflicting goals are to maximize the Loss of Peak Power Probability (LPPP) and minimize the system cost. And the former is related to the reliability of the system while the latter relates to whether production prototype so the two optimization objectives are important. An improved particle swarm algorithm was presented to optimal size the hybrid power system. Here the mutation operator of genetic algorithm was introduced and the acceleration factor could change with time. The optimization results show that: the improved particle swarm algorithm can well solve the hybrid power system for multi-objective optimization problems.

A Systematic Review of Energy Management Systems for Battery/Supercapacitor Electric Vehicle Applications

“…On the downside, their reliability is lower than those in Figure 3a,c-e; if one of the converters is damaged, the vehicle might be inoperative. To control the energy and power of the battery and SC, a multi-converter is proposed by scholars, as shown in Figure 3h [26][27][28][29]. This configuration presents a steady DC bus voltage and protects the battery from high repetitive power.…”