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

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.

Figures (12)

• Figure 1: The iPhone app interface developed to test eco-driving for connected electric vehicles. GPS locations and vehicle speed are obtained using the phone's GPS data. Light timing, recommended actions, and a map are also shown. Audio alerts are issued to provide speed recommendations to the driver.
• Figure 2: An illustrative example of a vehicle trajectory through time and distance. The control zone commences 100 m upstream of the first light and the ends 100 m downstream of the second light. In this example, the distance between the two lights is 400 m, and they have the same signal timing. Both the distance and cycle timing will be varied to evaluate their effect on the benefits of eco-driving. The solid and dashed lines show the trajectories of the eco-driver and regular driver, respectively.
• Figure 3: Results comparing eco-driving with regular driving for signal combination [15 15] when both lights turn red 15 seconds after the vehicle enters the control zone. Eco-driver; Regular driver. (a) Trajectories through time and distance; (b) speed trajectories; (c) energy consumption; and (d) battery capacity decay.
• Figure 4: Results comparing eco-driving with regular driving for signal combination [15 15]. (a) Total cost, Eco-driver, Regular driver; and (b) electricity and battery cost comparison with the overall cost savings denoted as a %.
• Figure 5: Results comparing eco-driving with regular driving for signal combination [-15 15] when the first and second lights turn red 15 seconds before and after the vehicle enters the control zone, respectively. Eco-driver; Regular driver. (a) Trajectories through time and distance; (b) speed trajectories; (c) energy consumption; and (d) battery capacity decay.