Dynamic Programming-Based Energy Management Strategy Optimization for PV System Hybrid Electric Vehicles

Energy efficiency and the decrease of harmful emissions are two major topics of study in the car industry. That's why people are flocking to hybrid electric vehicles. If you want to increase the efficiency of your car's system, you may want to think about a vehicle electrical hybrid (VEH). This vehicle consumes less fuel and produces fewer harmful byproducts than its thermal counterpart. The challenge then becomes determining the optimal power distribution between the hybrid system's two sources, the internal combustion engine (ICE) and the electrical machines (EM), to achieve optimal efficiency. Improving fuel economy and optimising HEV performance are the primary goals of the energy management systems that implement instantaneous split power between the two sources in a hybrid electric vehicle (HEV) through regulation of the battery state of charge (SOC). In this work, we offer the results of a parametric analysis of the effect of optimising the energy management strategy has on the most efficient functioning of the vehicle. Modeling a hybrid car and presenting a rules-based energy management system are discussed Afterwards, a Grey Wolf optimizer-based optimization technique is used to fine-tune these rules (GWO). It's a novel meta-heuristic that takes into account the whole population. The ideal energy management strategy's effect on fuel consumption and CO2 emissions may be deduced from the simulation's findings. Results reveal that the best energy management techniques result in different optimum vehicle operations.