Combined Eco-Routing and Power-Train Control of Plug-In Hybrid Electric Vehicles in Transportation Networks

TL;DR

This paper presents a combined eco-routing and power-train control algorithm for PHEVs that significantly reduces energy consumption in urban traffic networks, validated through real-world and simulated data.

Contribution

It introduces a novel algorithm that simultaneously optimizes routing and power-train control for PHEVs, demonstrating practical effectiveness with real-time performance.

Findings

Achieves around 12% energy savings for PHEVs.

Validates effectiveness using real traffic data and high-fidelity energy models.

Demonstrates near real-time algorithm execution.

Abstract

We study the problem of eco-routing for Plug-In Hybrid Electric Vehicles (PHEVs) to minimize the overall energy consumption cost. We propose an algorithm which can simultaneously calculate an energy-optimal route (eco-route) for a PHEV and an optimal power-train control strategy over this route. In order to show the effectiveness of our method in practice, we use a HERE Maps API to apply our algorithms based on traffic data in the city of Boston with more than 110,000 links. Moreover, we validate the performance of our eco-routing algorithm using speed profiles collected from a traffic simulator (SUMO) as input to a high-fidelity energy model to calculate energy consumption costs. Our results show significant energy savings (around 12%) for PHEVs with a near real-time execution time for the algorithm.