Energy Aware Driving: Optimal Electric Vehicle Speed Profiles for Sustainability in Transportation

This paper investigates the benefits of exploiting weather conditions for energy optimal driving. Optimization approaches are introduced that are based on the fact that weather-dependent speed profiles can save transportation energy, especially for electric transportation systems. Optimization models for both minimum transportation energy with travel time constraints and minimum travel time with transportation energy constraints are introduced and the resulting speed profiles are analyzed. Infinite dimensional optimization models are proposed for exact problem descriptions and approximate discretized convex models are derived for highly efficient solutions. The optimization tasks are formulated as a deterministic as well as a robust optimization problem, where weather conditions such as wind speed and rolling resistance effects are assumed to be known exactly or within uncertainty bounds. Simulations illustrate the utility of the proposed optimization models and demonstrate achievable efficiency improvements.

I. Introduction

Sustainability is rooted in the growing awareness that human activities have a significant environmental impact that can impose substantial ecological, social and economic costs [1]. Transportation systems are known to significantly contribute to this cost [1]–[3]. Electric and hybrid drive systems are electrifying the modern transportation system and have often been seen as a significant positive development for its sustainability [2], [4]–[7]. While the net contribution of these systems to sustainability is sometimes questioned and depends on many factors [1], the positive effects towards sustainability will become more dominant with the arrival of more clean and renewable power generation systems.