Hybrid vehicle design using global optimisation algorithms

Abstract

Four global optimisation algorithms are applied in the design optimisation of a hybrid electric vehicle (HEV). These four algorithms are: DIRECT, Simulated Annealing, Genetic Algorithm, and Particle Swarm Optimisation. The optimisation objective is to achieve maximum fuel economy, subject to the constraints of vehicle performance. The model in the loop methodology is adopted for our design process, in which a vehicle model named PSAT is used as the analysis tool. The design optimisation results and the performance of the four optimisation algorithms are compared. Our initial study shows that DIRECT and Simulated Annealing algorithms are efficient for the complex HEV engineering design problem.