Eco-Routing of Plug-In Hybrid Electric Vehicles in Transportation Networks

TL;DR

This paper introduces a novel eco-routing algorithm for PHEVs that optimizes both route and power-train control to reduce energy consumption, validated on real traffic data, outperforming traditional methods.

Contribution

The paper proposes the CRPTC algorithm that jointly optimizes routing and power-train control for PHEVs, a significant advancement over fixed-strategy approaches.

Findings

CRPTC reduces energy consumption compared to traditional methods.

The algorithm effectively balances energy savings and travel time.

Validation on real traffic data demonstrates practical applicability.

Abstract

We study the problem of eco-routing Plug-In Hybrid Electric Vehicles (PHEVs) to minimize the overall energy consumption costs. Unlike the traditional Charge Depleting First (CDF) approaches in the literature where the power-train control strategy is fixed, we propose a Combined Routing and Power-train Control (CRPTC) algorithm which can simultaneously calculate the optimal energy route as well as the optimal power-train control strategy. To validate our method, we apply our eco-routing algorithm to a subnetwork of the Eastern Massachusetts (EMA) transportation network using actual traffic data provided by the Boston Region Metropolitan Planning Organization. As an alternative benchmark, we also simulate the traffic behavior of the network using the extracted flow data from the aforementioned traffic dataset. We show that the CRPTC approach outperforms the traditional CDF approach and we quantify the trade-off between saving energy and time in using eco-routing algorithms.