Paper
22 December 2021 How do driving preference and throttle operation impact electric vehicle’s energy consumption? A case study in Beijing, China
Dawei Zhang, Hongwei Guo, Xiaobei Jiang, Wuhong Wang
Author Affiliations +
Proceedings Volume 12058, Fifth International Conference on Traffic Engineering and Transportation System (ICTETS 2021); 120584G (2021) https://doi.org/10.1117/12.2619980
Event: 5th International Conference on Traffic Engineering and Transportation System (ICTETS 2021), 2021, Chongqing, China
Abstract
Driving behavior has a great impact on vehicle energy consumption and emissions, and also has a direct impact on the driving range of electric vehicles. This article uses the driver's direct input, that is, the pedal operation, combined with vehicle motion state parameters to interpret and define driving behavior. This study uses the real-world vehicle operation data of representative cities in China as the research basis. By obtaining the vehicle operation information and driving operation information collected by on-board diagnostic system (OBD), the relationship between driving performance and vehicle energy consumption is established combined with vehicle kinematics equations. The Multivariate Composite Contour Map (MCCM) drawn according to this relationship can better express the influence relationship between vehicle energy consumption and driving behavior. This study analyzes the influence of driving preference and throttle operation on the energy consumption of electric vehicles in a continuous driving state and gives the recommended driving pattern and relevant research conclusions can also be used in areas such as driving assistance design and energy-saving driving training.
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Dawei Zhang, Hongwei Guo, Xiaobei Jiang, and Wuhong Wang "How do driving preference and throttle operation impact electric vehicle’s energy consumption? A case study in Beijing, China", Proc. SPIE 12058, Fifth International Conference on Traffic Engineering and Transportation System (ICTETS 2021), 120584G (22 December 2021); https://doi.org/10.1117/12.2619980
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KEYWORDS
Analytical research

Composites

Kinematics

Resistance

Data modeling

Information operations

Statistical analysis

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