Optimal Control Strategies for Maximizing Energy Efficiency in Electric Vehicle Charging Infrastructure
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Abstract
Among the workable technology alternatives to address the escalating climate change challenges is the transition to electrified transportation. The possibility of shared transport systems and intelligent cars accompany this shift. To move forward and keep comfortable driving conditions, an electric car only uses its stored electric energy. Energy management system (EMS) upgrades are crucial to enhancing efficiency, performance, sustainability of electric vehicles (EVs), as demand for EVs rises steadily. This research propose novel technique in enhancing and maximizing the energy efficiency of electric vehicle based on their charging infrastructure. Here the electric vehicle energy management system has been carried out based on ultracapacitor solar fuel cell and the energy optimization has been carried out using Gaussian grey whale Krill Herd optimization method. Experimental analysis is carried out in terms of energy efficiency, power consumption, Mean Absolute Percentage Error (MAPE), accuracy, robustness. proposed technique attained MAPE of 54%, Accuracy of 97%, ROBUSTNESS of 92%, power consumption of 95%, energy efficiency of 98%. A evaluation based on simulation is carried out, confirming the improved efficiency of the suggested techniques in preserving energy under various driving circumstances.
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