Energy Management Improvement of Hybrid Electric Vehicles via Combined GPS/Rule-Based Methodology

This paper aims at proposing an efficient and versatile application of Petri nets (PNs) either alone without global positioning system (GPS) as in (GPS-free) system or together with the navigation system (GPS-registered) to conveniently provide a proper energy management strategy for hybrid electric vehicles (HEVs) of high hybridization level and serial architecture. A comparison between the PN strategy and two fuzzy logic strategies is performed in terms of fuel consumption and convergence time. In this paper, short and long trip types of 30 km mainly urban and 240 km mostly highway are considered with an initial state of charge (SoC) of 50% and different daily driving cycles or various standard the New York City Cycle, the New European Driving Cycle, US06 driving cycles. Both kinds of battery management strategies, GPS-free and GPS registered, are demonstrated and compared through simulation studies using the MTCsim software. Dealing with both types of trips, the simulation results significantly illustrate the superiority of the novel GPS-registered methodology's efficiency toward improving the HEV's energy management and reducing its fuel consumption besides the relative economic feasibility and structural simplicity features. Over one week duration, the GPS allows reaching the desired final SoC with acceptable errors and reducing the fuel consumption for both daily short and weekend long trips. The originality of this paper is proposing a hybrid GPS/rule-based approach to reduce the fuel consumption during daily driving trips that present about half of the professional travels in 2008 according to the French Sustainable Development Division. This novel strategy is developed on the basis of the recorded GPS data from past trips and the batteries' final recharging capacities.