A New Efficient Fuel Optimization in Blended Charge Depletion/Charge Sustenance Control Strategy for Plug-In Hybrid Electric Vehicles

Abstract

The fuel consumption and pollutant emissions of vehicles can significantly be reduced by adding an electric drivetrain to the internal combustion engine (ICE) without deteriorating the vehicle performance. One of the best suggestions to achieve such a goal is plug-in hybrid electric vehicles (PHEVs). In PHEVs, the design of an efficient energy management strategy plays a significant role. In this paper, a new control strategy is proposed for parallel PHEV to keep the ICE operation points close to the high-efficiency region, while minimizing the fuel consumption over the standardized drive cycles. First, a new high efficiency ICE on / off control strategy is designed. Second, the teaching-learning based optimization algorithm is used to optimize the proposed control strategy and find the optimal ICE operation region. In the rule-based controllers, the ICE operates within predefined constant efficiency region without incorporating the driving pattern. However, the proposed controller can optimally tune the ICE operation points based on each driving scenario to achieve a better fuel economy. Since the control strategy of PHEVs highly depends on the driving patterns, three different drive cycles with three different trip distances and one recharging opportunity during the trip are considered to show the effectiveness of the proposed technique in terms of the fuel economy and the ICE efficiency. The results illustrate that the proposed control strategy could greatly decrease the fuel consumption of the PHEV under all driving scenarios.