EM-TFL identification for Particle Swarm Optimization of HEV powertrain

The feasibility of developing a design optimization environment utilizing an Electromagnetic-Team Fuzzy Logic, EM-TFL, robust identifier for use with Particle Swarm Optimization, PSO, technique is investigated. The developed environment is applied in a case study to increase the efficiency and fuel economy of a prototype Hybrid Electric Vehicle, HEV, powertrain in series configuration. This optimization necessitates the characterization of the key electromechanical components of the HEV powertrain system which includes a generator, an electric motor drive system, and a battery pack in addition to an Internal Combustion Engine, ICE. The basic objective of improving the fuel economy while maintaining the performance of the vehicle is met through the implementation of a PSO algorithm.