Particle swarm optimization of the fuzzy logic controller for a hybrid energy storage system in an electric car

This paper describes the particle swarm optimization of the fuzzy logic controller for a hybrid energy storage system in an electric vehicle. The Sugeno-type fuzzy inference system has been applied to divide power between the battery and ultracapacitor energy storage systems, as well as to manage the amount of energy stored in ultracapacitors. The two output signals of the described fuzzy logic controller represent power for each energy storage system, and are the weighted sums of all inference rule outputs. The particle swarm optimization has been proposed to determine the weights of rules. A simulation and experimental validation of the power management algorithm is also introduced in this paper.