Optimization of energy management strategy for fuel cell vehicles based on hybrid genetic algorithm

Abstract

Genetic algorithm is an algorithm that searches for the optimal solution by simulating the natural evolutionary process. The development of fuel cell vehicles is of great significance to the traditional automobile industry as well as the energy industry, and is an important initiative to protect the environment and conserve resources. However, fuel cell vehicles still face the problem of insufficient range. One solution is to form a multi-energy source system by combining fuel cells with secondary charging auxiliary power or other power sources. Therefore, to give full play to the advantages of hybrid power, it is necessary to solve the energy management problems brought about by hybrid power. In this study, the applicability of energy management strategy optimization for fuel cell vehicles is analyzed with the help of hybrid genetic algorithms.

Design and research of energy management strategy for pure electric vehicles based on dynamic programming algorithm

“…The optimization design of energy management strategies aims to enhance the efficiency and performance of the power system by rational allocation and management of battery energy. Currently, energy management strategies can be categorized into rule-based strategies and optimization-based strategies, including logic threshold energy management strategies [3][4] , fuzzy control strategies [5][6] , particle swarm algorithms [7][8] , genetic algorithms [9][10] , and others. However, traditional design methods rely on experience and rules, while genetic algorithms are limited by the computational capabilities of the vehicle's controller and cannot provide an optimal solution.…”