Novel Electric Bus Energy Consumption Model Based on Probabilistic Synthetic Speed Profile Integrated With HVAC

被引:27
|
作者
El-Taweel, Nader A. [1 ]
Zidan, Aboelsood [1 ]
Farag, Hany E. Z. [1 ]
机构
[1] York Univ, Dept Elect Engn & Comp Sci, Toronto, ON M3J 1P3, Canada
关键词
Data models; Energy consumption; Load modeling; Heating systems; Atmospheric modeling; Acceleration; Meteorology; Electric buses; energy consumption; heat ventilation and air conditioning; route topography; speed profile; transportation electrification; weather conditions; BATTERY; HYBRID; WELL;
D O I
10.1109/TITS.2020.2971686
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This paper proposes a novel and generic model to calculate the Electric Bus Energy Consumption (EBEC) without the need for a high-resolution speed profile data. The proposed model generates a set of speed profiles using the basic information of the bus trip: trip time, trip length, and distances between successive bus stops. The generated speed profiles could accurately reflect the various traffic conditions and speed behaviors of real-world situations. Roadway Level of Service (LoS) is incorporated in the proposed model to simulate different traffic conditions. Further, a stochastic model for the bus speed profile is adopted to simulate the probability of the bus to stop at each on-route designated stop. The generated speed profiles are then inputted to an accurate EBEC model that considers the route topography, auxiliary loads (lighting, sound, and radio systems) and the impact of the weather conditions. The operation of the heat, ventilation and air conditioning system (HVAC) is also incorporated in the model using the thermal mass balance principle. Using the proposed model, the characteristics of EBEC on a given route can be evaluated through generating a set of speed profiles for the studied route. The proposed model provides transit network planners with a useful tool to appropriately design electric-based transit networks when there is a lack or unavailability of real-time and high resolution data.
引用
收藏
页码:1517 / 1531
页数:15
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