Abstract
Compared with conventional vehicles, hybrid electric vehicles (HEVs) carried with tow power systems have a lot of advantages, such as improved fuel consumption and lower emissions. HEV is an extra non-linear system, which performance is greatly influenced by the parameters of drivetrain and control strategy. To improve the performance of HEV, the popular practices are to convert multi-objective optimization problems into a single-objective one by using coefficients, which cannot show the nature of each objective for using unfair coefficients. Aimed at avoiding that limitation and minimizing the fuel consumption and exhaust emissions of parallel hybrid electric vehicles (PHEV), a multi-objective optimization method based on improving strength Pareto evolutionary algorithm is proposed, in which the Pareto dominance principle is employed to separate the sheep from the goats of candidate solutions, and the ADVISOR is adopted to simulate the solution so as to obtain the objective value. The case study shows that the proposed algorithm is capable to reduce the fuel consumption and emissions of PHEV and it also can provide a set of alterative Pareto-optimal solutions for user to satisfy the various requirements.
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© 2011 Springer-Verlag Berlin Heidelberg
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Zhenchao, P., Guanci, Y., Shaobo, L., Jinglei, Q. (2011). Multi-objective Optimization of Parallel Hybrid Electric Vehicles Based on SPEA2. In: Zheng, D. (eds) Advances in Electrical Engineering and Electrical Machines. Lecture Notes in Electrical Engineering, vol 134. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25905-0_63
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DOI: https://doi.org/10.1007/978-3-642-25905-0_63
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