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On the movement simulations of electric vehicles: A behavioral model-based approach.

Authors :
Xu, Yueru
Zheng, Yuan
Yang, Ying
Source :
Applied Energy. Feb2021, Vol. 283, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

• Scenario-specific electric vehicle behavioral model. • Higher accuracy in representing electric vehicles' movements. • Applicability to timid, aggressive and normal vehicles. • Ability to represent traffic oscillations of electric vehicles. Electric vehicles (EVs) are deemed to be a solution for reducing air pollution and greenhouse gas emissions. As a result, the market share has increased exponentially in recent years. Despite their distinct vehicle dynamics and characteristics, movement simulation models dedicated to EVs are yet to be developed. In this research, a micro-traffic flow model for EVs by considering their unique acceleration/deceleration characteristics is proposed to represent and simulate the movements of EVs in traffic flow, especially in congested traffic. Car-following pairs where second car is an EV were collected from Longpan mid road, Nanjing, China in March 2019 for model calibration and verification. The results show that the proposed EV behavior model outperforms traditional behavior models for both timid and aggressive drivers. In assessing the predictive power of the movement simulation models, we compare their performance for collected car-following pairs. The R-squared values indicate that the performance of the EV behavior model is similar to that of the asymmetric behavior model under free-flow conditions, but substantially better for congested scenarios. With this model, we can better understand and reproduce the trajectories and energy consumption of EVs in complex traffic flow scenarios, and especially in congested traffic. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03062619
Volume :
283
Database :
Academic Search Index
Journal :
Applied Energy
Publication Type :
Academic Journal
Accession number :
148166515
Full Text :
https://doi.org/10.1016/j.apenergy.2020.116356