On the modular platoon-based vehicle-to-vehicle electric charging problem

TL;DR

This paper introduces a novel vehicle-to-vehicle charging system for modular electric vehicles, formulated as a MILP and optimized with a genetic algorithm, demonstrating significant energy and cost savings in simulated scenarios.

Contribution

It presents a new MILP formulation and a genetic algorithm solution for the PV2VC technology, improving efficiency over traditional methods.

Findings

PV2VC saves up to 11.07% energy

Reduces travel time by 11.65%

Lowers total costs by 11.26%

Abstract

We formulate a mixed integer linear program (MILP) for a platoon-based vehicle-to-vehicle charging (PV2VC) technology designed for modular vehicles (MVs) and solve it with a genetic algorithm (GA). A set of numerical experiments with five scenarios are tested and the computational performance between the commercial software applied to the MILP model and the proposed GA are compared on a modified Sioux Falls network. By comparison with the optimal benchmark scenario, the results show that the PV2VC technology can save up to 11.07% in energy consumption, 11.65% in travel time, and 11.26% in total cost. For the PV2VC operational scenario, it would be more beneficial for long-distance vehicle routes with low initial state of charge, sparse charging facilities, and where travel time is perceived to be higher than energy consumption costs.