Practical Implementation and Experimental Validation of an Optimal Control based Eco-Driving System

TL;DR

This paper demonstrates the practical implementation and real-world testing of an optimal control-based eco-driving system for electric vehicles, showing energy savings with minimal impact on driving speed.

Contribution

It presents a real-world validation of an eco-driving system using a predictive optimal controller and a visual advisory tool for electric vehicles.

Findings

Eco-driving system reduced energy consumption by 4.6%.

Minimal speed variation of 2% observed during tests.

Field validation confirms practical benefits of the control approach.

Abstract

The main goal of Eco-Driving (ED) is to maximize energy efficiency. This study evaluates the energy gains of an ED system for an electric vehicle, obtained from a predictive optimal controller, in a real-world traffic scenario. To this end, a Visual driver Advisory System (VAS) in the form of a personal tablet is used to advise the driver to follow a target eco-speed via a screen. Two Renault Zoe electric cars, one equipped with the different modules for ED and one without, are used to perform field tests on a route between Rueil-Malmaison and Bougival in France. Overall, the ED consumed, on average, 4.6~$\%$ less energy than the non-eco-driven car with a maximum of 2~$\%$ change in average speed.