Network Flow Problems with Electric Vehicles

TL;DR

This paper develops a new theoretical and computational framework for routing electric vehicles in charging networks, addressing range limits and charging dynamics to optimize logistics and infrastructure planning.

Contribution

It introduces a novel EV network flow model with range and nonlinear charging constraints, and identifies conditions for polynomial-time solutions to key routing problems.

Findings

Polynomial-time solutions for single EV routing under certain conditions

Insights into optimizing EV flow and infrastructure capacity

Framework applicable to sustainable long-distance logistics

Abstract

Electric vehicle (EV) adoption in long-distance logistics faces challenges such as range anxiety and uneven distribution of charging stations. Two pivotal questions emerge: How can EVs be efficiently routed in a charging network considering range limits, charging speeds and prices? And, can the existing charging infrastructure sustain the increasing demand for EVs in long-distance logistics? This paper addresses these questions by introducing a novel theoretical and computational framework to study the EV network flow problems. We present an EV network flow model that incorporates range constraints and nonlinear charging rates, and identify conditions under which polynomial-time solutions can be obtained for optimal single EV routing, maximum flow, and minimum-cost flow problems. Our findings provide insights for optimizing EV routing in logistics, ensuring an efficient and sustainable future.