Optimal electric vehicle navigation through smart grid synergy and innovative routing strategies

Abstract

The synergistic integration of the smart grid and smart transportation network presents a wealth of data pertaining to the main grid and transportation infrastructure, offering valuable insights for electric vehicle (EV) owners to navigate their vehicles efficiently. However, the unpredictable nature of traffic conditions, charging prices, and waiting times at charging stations poses a significant challenge to achieving optimal EV navigation. In response to this challenge, a novel navigation system is proposed that strives to minimize both total travel time and charging costs at charging stations. The approach of this paper involves leveraging a unique methodology to determine the shortest path to the optimal charging station, which will be one of the renewable charging station, non-renewable charging station and mobile EV chargers, employing Dijkstra's algorithm for efficient route planning. The system takes into account real-time data on traffic dynamics, charging station availability, and pricing fluctuations to dynamically adjust navigation routes, ensuring that EV owners can make informed decisions on the go. To validate the effectiveness of the proposed approach, a series of experiments are conducted. The results demonstrate the system's ability to optimize both travel time and charging costs, providing a practical solution for EV navigation in the face of unpredictable variables. These findings validate the effectiveness of the proposed system in optimizing EV navigation under dynamic and uncertain conditions, offering practical solutions for diverse EV mobility configurations.