Multiobjective optimisation of a series hybrid electric vehicle using DIRECT algorithm

Abstract

With the economic development, transportation in the city becomes more crowded. Furthermore, fuel consumption is causing a serious problem of pollution in the urban environment. Hybrid electric vehicles are considered as a good solution compared to conventional internal combustion engine vehicles. In order to solve those problems, the components parameters of a series hybrid electric vehicle are selected and tested with the ADvanced VehIcle SimulatOR (ADVISOR) simulation tool, which is a software-based on Matlab_simulink. Then, an optimisation was done to minimise simultaneous fuel consumption and emissions (HC, CO, and NOx) of the vehicle engine. In addition, the driving performance requirements are also examined during the urban dynamometer driving schedule (UDDS) to fix their optimal control parameters. Finally, the results show that those steps help reduce fuel consumption and emissions while guaranteeing vehicle performance. Hence, the series hybrid electric vehicle greatly improves fuel economy and reduces toxic emissions.