Memetic algorithm for fuel economy and low emissions parallel hybrid electric vehicles

As the energy crisis and environmental pollution problems become increasingly serious, hybrid electric vehicles (HEVs) have been seen as the world's more fuel-efficient and cleaner vehicles to provide one of the solutions. In this study, we designed the appropriate control strategy parameters use memetic algorithm (MA) with two small population sizes 5 and 10 and iterations 1000 to make the HEV not only reduce the toxic emissions, but also keep the road driving vehicle performance while reducing fuel consumption (FC). In this study, the software ADVISOR was used as a simulation tool and the driving cycle UDDS was used to evaluate FC, emissions and vehicle dynamic performance. Compared with the preset parallel HEV defined in ADVISOR, the results show that MA is a powerful tool for improving the control strategy parameters of the parallel HEV to improve FC and emissions without sacrificing vehicle performance. The method helps to mitigate the energy crisis and environmental pollution problems.