A trajectory-based energy consumption estimation method considering battery degradation for an urban electric vehicle network. (September 2019)

• Record Type: Journal Article
• Authors: Wang, Hua; Zhao, De; Cai, Yutong; Meng, Qiang; Ong, Ghim Ping
• Is Part Of: Transportation research. Volume 74(2019)
• Page Start: 142
• Page End: 153
• Publication Date: 2019-09
• Subjects: Electric vehicle -- Energy consumption estimation -- Battery degradation -- Quadratic regression -- EV trajectory; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2019.07.021
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: Incorporate battery degradation into EV network-level energy consumption estimation. Estimate unit energy consumption functions using quadratic regression models. Propose an easy-to-implement trajectory-based energy consumption estimation method. Validate the proposed method based on real taxi trajectories on Singapore's road network. Abstract: As a cost-effective and environmental-friendly transport means, electric vehicle (EV) has received widespread attention in the recent decade. The increasing market share and wider adoption of EV in transportation systems also bring about the energy use issues. In this paper, we propose a method to estimate network-wide EV energy consumption by taking into account battery degradation. We first derive unit energy consumption functions with respect to the battery degradation rate by quadratic regression method using EV operational data in the US. We then put forward an easy-to-implement and tangible method to estimate EV network energy consumption based on EV trajectories and the derived unit energy consumption function. In detail, EVs' battery degradation rates are assumed to follow a given and known probability distribution and daily travel mileage of each EV is derived from EV trajectories. Based on these, we can get the expected total energy consumption in the network. We also propose a prorated assignment approach to determine the expected energy consumed by EVs through each EV charging point based on the estimated temporal-spatial charging demand distribution from EVs' trajectories. A case study in Singapore is demonstrated in the end and the importance of incorporating battery degradation is highlighted. The results reveal that overlooking battery degradation would lead to more than 10% of estimation error in energy consumption estimation.