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Varesi, Kazem; Radan, Ahmad; Hosseini, Seyed H.; Sabahi, Mehran
Automatika, 20/1/1/, Volume: 56, Issue: 1Journal Article
In this paper, a simple but efficient Non-dominated Sorting Genetic Algorithm (NSGA) II based technique is proposed for optimizing the Degree of Hybridization (DOH) in parallel passenger hybrid cars. The authors' objective is to improve performance, maximize fuel economy and at the same time, minimize mass and emissions as much as possible, by optimal selection of DOH. The NSGA-II, which is a multi-objective optimization algorithm, is applied to optimize this multiple objective problem. The ADvanced VehIcle SimulatOR (ADVISOR) software is used as simulation tool. To validate high efficiency of proposed methodology, necessary simulations have been carried out on a small-size test car. The results indicates that the proposed methodology is very fast and efficient and can be well applied to any other types of Hybrid Electric Vehicles (HEVs).
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