HEV Component Sizing and Design Optimization
Chris Chunting Mi, M. Abul Masrur, Wenzhong Gao · 2011
In this chapter, four global optimization algorithms are applied in the design optimization of Hybrid Electric Vehicles (HEV). These four algorithms are: DIRECT, Simulated Annealing, Genetic Algorithm, and Particle Swarm Optimization. The principles of the optimization algorithms are thoroughly discussed together with programming flow charts. The four algorithms are used for component sizing of an example parallel HEV. The design goal is to achieve maximum fuel economy subject to constraints of desired vehicle performance. 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 optimization results and the performance of the four optimization algorithms are compared. Our initial study shows that DIRECT and Simulated Annealing algorithms are efficient for the complex HEV engineering design problem. In addition, Non-dominated Sorting Genetic Algorithm (NSGA-II) is used for multi-objective design optimization of a series HEV.