Hybrid approach for energy management strategy and energy management strategy for plug-in hybrid electric vehicles using GTO-DRN approach

This manuscript presents a hybrid approach to energy management strategy for plug-in-hybrid electric vehicles (PHEV). The proposed hybrid technique is the joint execution of the Gorilla Troops Optimization Algorithm (GTO) and dilated residual convolutional neural networks (DRN). Hence it is named as GTO-DRN system. The proposed method's main objective is to minimise the energy loss and reduces the cost. The GTO method is utilised to optimise the battery by developing an interaction among the independent operating parameters, voltage and current, using response surface methodology. The GTO method is optimised to charge or discharge the battery, and other control decisions to minimise energy consumption or emissions. The DRN technique is used to model and predict the vehicle's power demand.