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A review on charging behavior of electric vehicles: data, model, and control

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Abstract

The adoption and usage of electric vehicles (EVs) have emerged recently due to the increasing concerns on the greenhouse gas issues and energy revolution. As a part of the smart grid, EVs can provide valuable ancillary services beyond consumers of electricity. However, EVs are gradually considered as nonnegligible loads due to their increasing penetration, which may result in negative effects such as voltage deviations, lines saturation, and power losses. Relationship and interaction among EVs, charging stations, and micro grid have to be considered in the next generation of smart grid. Therefore, the topic of smart charging has been the focus of many works where a wide range of control methods have been developed. As one of the bases of simulation, the EV charging behavior and characteristics have also become the focus of many studies. In this work, we review the charging behavior of EVs from the aspects of data, model, and control. We provide the links for most of the data sets reviewed in this work, based on which interested researchers can easily access these data for further investigation.

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Authors and Affiliations

  1. Center for Intelligent and Networked Systems (CFINS), Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, 100084, China

    Qing-Shan Jia & Teng Long

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  1. Qing-Shan Jia
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Correspondence to Qing-Shan Jia.

Additional information

This work was supported in part by the National Key Research and Development Program of China (No. 2016YFB0901900), the National Natural Science Foundation of China under grants (No. 61673229) and the 111 International Collaboration Project of China (No. BP2018006).

Qing-Shan JIA received the B.Sc. degree in Automation and the Ph.D. degree in Control Science and Engineering from Tsinghua University, Beijing, China, in 2002 and 2006, respectively. He was a Visiting Scholar at Harvard University, in 2006, at the Hong Kong University of Science and Technology, in 2010, and at the Massachusetts Institute of Technology, in 2013. He is currently an Associate Professor at the Center for Intelligent and Networked Systems, Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University. His current research interests include theories and applications of cyber physical systems.

Teng LONG received the B.Sc. degree in Department of Automation from Tsinghua University, Beijing, China, in 2017. He is currently pursuing a Ph.D. degree in Control Science and Engineering supervised by Qing-Shan Jia with the Center for Intelligent and Networked Systems (Cfins), Department of Automation, Tsinghua University, Beijing, China. His current research interests include energy management of the smart grid, event-based optimization, and large-scale optimization problem.

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Jia, QS., Long, T. A review on charging behavior of electric vehicles: data, model, and control. Control Theory Technol. 18, 217–230 (2020). https://doi.org/10.1007/s11768-020-0048-8

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  • DOI: https://doi.org/10.1007/s11768-020-0048-8

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