TY - JOUR
T1 - Novel Electric Bus Energy Consumption Model Based on Probabilistic Synthetic Speed Profile Integrated with HVAC
AU - El-Taweel, Nader A.
AU - Zidan, Aboelsood
AU - Farag, Hany E.Z.
N1 - Funding Information:
Manuscript received March 25, 2019; revised August 15, 2019 and November 8, 2019; accepted January 24, 2020. Date of publication February 13, 2020; date of current version March 1, 2021. This work was supported by the Early Researcher Award program from Ontario Government and the IESO Conservation Fund Program In Partnership with Alectra Inc. and Metrolinx. The Associate Editor for this article was F. Chu. (Corresponding author: Nader A. El-Taweel.) The authors are with the Department of Electrical Engineering and Computer Science, York University, Toronto, ON M3J 1P3, Canada (e-mail: [email protected]; [email protected]; [email protected]). Digital Object Identifier 10.1109/TITS.2020.2971686
Publisher Copyright:
© 2000-2011 IEEE.
PY - 2021/3
Y1 - 2021/3
N2 - 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.
AB - 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.
KW - Electric buses
KW - energy consumption
KW - heat ventilation and air conditioning
KW - route topography
KW - speed profile
KW - transportation electrification
KW - weather conditions
UR - http://www.scopus.com/inward/record.url?scp=85097458671&partnerID=8YFLogxK
U2 - 10.1109/TITS.2020.2971686
DO - 10.1109/TITS.2020.2971686
M3 - Article
AN - SCOPUS:85097458671
SN - 1524-9050
VL - 22
SP - 1517
EP - 1531
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 3
M1 - 8998578
ER -