Energy-Efficient Routing for Electric Vehicles under Acceleration and Load Effects

TL;DR

This paper introduces a new routing problem for electric vehicles that considers acceleration and load effects to optimize energy consumption, using advanced models and algorithms validated with real-world data.

Contribution

It develops a generalized time-dependent speed model and a novel meta-heuristic algorithm for energy-efficient EV routing considering acceleration and load effects.

Findings

Meta-heuristic outperforms exact solver on large problems

Model accurately captures real traffic and load effects

Validated with real data from Singapore

Abstract

This paper proposes an Acceleration and Load-Dependent Electric Vehicle Routing Problem (ALD-EVRP), to optimize the energy consumption (EC) while capturing the effects of changing traffic conditions between peak and off-peak periods. We generalize the time-dependent speed model by replacing step functions with piecewise linear functions. The EC of each vehicle is influenced by its speed, acceleration, and real-time load. A mathematical model is developed and solved using BonMin, and a custom meta-heuristic algorithm is proposed for large-scale problems, yielding the same results as BonMin on small problems and performing better on larger ones. This is validated with real data from Singapore.