Comparison of Electric Vehicle’s Energy Consumption Factors for Different Road Types
By Enjian Yao, Zhiqiang Yang, Yuanyuan Song, Ting Zuo. 2013
100 citations recorded by the source corpus.
Energy-optimal route planning for electric vehicle (EV) is highly required for the wide-spread use of EV, which is hindered by limited battery capacity and relative short cruising range. Obtaining the cost for each link (i.e., link energy consumption) in road networks plays a key role in energy-optimal route planning process. The link energy consumption depends mainly on energy consumption factor, which is related to not only vehicle speed but also road type. This study aims to analyze the difference of EV’s energy consumption factors for different road types. According to the floating car data (FCD) collected from the road network in Beijing, the vehicle specific power (VSP) distributions under different average travel speeds for different road types are analyzed firstly, and then the EV’s energy consumption rates under different VSP-Bins are calculated. By using VSP as an intermediate variable, EV’s energy consumption factor models for different road types are established and the difference of EV’s energy consumption factors is analyzed. The results show that road type-based energy consumption factor should be used in EV’s energy-optimal route planning process.
Subfields: Automotive Engineering, Electrical and Electronic Engineering, Transportation
View Paper: https://www.semanticscholar.org/paper/749fd9390870f8714133f0a4a881730cee8b4721
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Citations in the corpus
- Data-driven decomposition analysis and estimation of link-level electric vehicle energy consumption under real-world traffic conditions (2017, methodology): “Please note that Model type 1 is proposed in this study and model type 2 & 3 are regarded as baseline models to represent the similar existing models that discussed in (Yao et al., 2013; Grubwinkler et al., 2014).”