Proactive Route Planning for Electric Vehicles

TL;DR

This paper introduces a novel route planning approach for electric vehicles that minimizes travel and charging time, significantly improving efficiency and reducing total travel time by up to 50% compared to existing methods.

Contribution

It presents a new graph-based model for EV routing, proves its NP-hardness, and proposes a two-phase heuristic algorithm incorporating an influence factor to optimize charging routes.

Findings

Reduces total EV travel time by 50% compared to state-of-the-art methods.

Effectiveness increases with the number of EVs on the road.

Introduces a new influence factor heuristic for EV route optimization.

Abstract

Due to the limited driving range, inadequate charging facilities, and time-consuming recharging, the process of finding an optimal charging route for electric vehicles (EVs) differs from that of other vehicle types. The time and location of EV charging during a trip impact not only the individual EV's travel time but also the travel time of other EVs, due to the queuing that may arise at the charging station(s). This issue is at large seen as a significant constraint for uplifting EV sales in many countries. In this study, we present a novel Electric Vehicle Route Planning problem, which involves finding the fastest route with recharging for an EV routing request. We model the problem as a new graph problem and present that the problem is NP-hard. We propose a novel two-phase algorithm to traverse the graph to find the best possible charging route for each EV. We also introduce the notion of `influence factor' to propose heuristics to find the best possible route for an EV with the minimum travel time that avoids using charging stations and time to recharge at those stations which can lead to better travel time for other EVs. The results show that our method can decrease total travel time of the EVs by 50\% in comparison with the state-of-the-art on a real dataset, where the benefit of our approach is more significant as the number of EVs on the road increases.