Eco-Driving Control for Electric Vehicles with Multi-Speed Transmission: Optimizing Vehicle Speed and Powertrain Operation in Dynamic Environments

TL;DR

This paper introduces an eco-driving control algorithm for electric vehicles with multi-speed transmissions that optimizes speed and powertrain operation to reduce energy consumption in dynamic traffic environments.

Contribution

It formulates a real-time, co-optimization controller that enhances energy efficiency by integrating vehicle speed, powertrain management, and traffic prediction constraints.

Findings

Energy consumption reduced by up to 11.36% in simulations and real-world tests.

The controller operates efficiently in real-time despite complex problem formulation.

Demonstrates effectiveness in dynamic urban traffic scenarios.

Abstract

This article presents an eco-driving algorithm for electric vehicles featuring multi-speed transmissions. The proposed controller is formulated as a co-optimization problem, simultaneously optimizing both vehicle longitudinal speed and powertrain operation to maximize energy efficiency. Constraints derived from a connected vehicle based traffic prediction algorithm are used to ensure traffic safety and smooth traffic flow in dynamic environments with multiple signalized intersections and mixed traffic. By simplifying the complex, nonlinear mixed integer problem, the proposed controller achieves computational efficiency, enabling real-time implementation. To evaluate its performance, traffic scenarios from both Simulation of Urban MObility (SUMO) and real-world road tests are employed. The results demonstrate a notable reduction in energy consumption by up to 11.36\% over an \SI{18}{\km} drive.