Fuzzy Logic Assisted Resource-Based Energy Management Strategy For Hybrid Electrical Vehicles

It has been demonstrated that hybrid electric vehicles (HEVs) are a promising solution to environmental pollution and fuel savings. Typically, the benefit of a solution is measured by the quantity of fuel saved, which poses a challenge for the development of energy management strategies (EMSs) for HEVs. Moreover, meeting the design requirements is essential for optimal power distribution, even though this necessitates sacrificing competing goals. To this end, many EMSs have been proposed in the literature, necessitating a better categorization method to classify the design and control contributions, focusing on fuel economy, power demand, and real-time application. In this project, a HEV Simulink model is modified to be integrated with in EMS controller. A fuzzy logic control (FLC) for series-parallel HEV is developed to effectively control the torque distribution between the internal combustion engine (ICE) and electrical motor (EM) by taking the vehicle speed, state-of-charge (SOC) of the battery and trip distance as inputs. The vehicle and controller performance are evaluated regarding fuel consumption to verify the model. The original HEV model is updated by virtually installing the EMS FLC. The proposed EMS is implemented, and the performance of vehicle is evaluated through simulation on standard drive cycles. Show that the proposed EMS is outperforming the conventional rule-based EMS by up to 40.82 % in terms of fuel consumption in selected certain conditions while maintaining battery SOC within it’s over the set lower threshold range