Effects of eco-driving on energy consumption and battery degradation for electric vehicles at signalized intersections

TL;DR

This paper demonstrates that eco-driving strategies for electric vehicles at signalized intersections can significantly reduce energy consumption and battery degradation, with potential benefits validated through simulations and field tests.

Contribution

It introduces a novel eco-driving algorithm incorporating battery degradation models and validates its effectiveness through simulations and real-world field tests.

Findings

Eco-driving can save up to 49% in costs due to energy and battery life benefits.

Larger batteries significantly increase EV lifetime, enhancing V2G applications.

Field tests with a phone app confirmed simulation results and showed practical adoption potential.

Abstract

Eco-driving has been shown to reduce energy consumption for electric vehicles (EVs). Such strategies can also be implemented to both reduce energy consumption and improve battery lifetime. This study considers the eco-driving of a connected electric vehicle equipped with vehicle-to-infrastructure (V2I) communication passing through two signalized intersections. Dynamic programming is employed to construct an eco-driving algorithm that incorporates a battery degradation model in addition to minimizing energy consumption to optimize the vehicle's speed trajectory while transiting the control zone. A parametric study is conducted for various signal timings and distances between the two intersections. It is found that eco-driving can provide up to 49\% in cost benefits over regular driving due to energy savings and improved battery life which could boost consumers' interests on EVs. This study also considered different battery capacity decay rates based on battery chemistry. Although a higher decay rate affects the optimal speed trajectories only slightly, it amplifies the benefits of eco-driving on battery life. Two battery sizes were also studied to show that the larger battery is associated with a drastically increased lifetime, thus creating opportunities for electric vehicles in other applications such as vehicle-to-grid (V2G) integration. Field tests were also conducted using a simplified rule-based version of the eco-driving algorithm implemented as a phone app which issues audio speed recommendations to the driver. The field test results were promising and validated the results from simulations. The phone app implementation is convenient and could facilitate broader adoption and widespread use of eco-driving which helps to improve transportation efficiency and protect the environment.