A cyber attack detection strategy for plug-in electric vehicles during charging based on CEEMDAN and Broad Learning System

Jianbo Yi; Haopeng An; Yankai Xing; Jian Li; Guangdou Zhang; Olusola Bamisile; Kai Yang; Yihao Xu

Energy Reports (May 2023)

A cyber attack detection strategy for plug-in electric vehicles during charging based on CEEMDAN and Broad Learning System

Jianbo Yi,
Haopeng An,
Yankai Xing,
Jian Li,
Guangdou Zhang,
Olusola Bamisile,
Kai Yang,
Yihao Xu

Affiliations

Jianbo Yi: Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control, School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
Haopeng An: Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control, School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
Yankai Xing: Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control, School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
Jian Li: Corresponding author.; Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control, School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
Guangdou Zhang: Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control, School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
Olusola Bamisile: Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control, School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
Kai Yang: Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control, School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
Yihao Xu: Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control, School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China

Journal volume & issue: Vol. 9
pp. 80 – 88

Abstract

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Cyber attacks targeting the charging process of plug-in electric vehicles (PEVs) have become more frequent with the popularity of PEVs, posing a significant threat to the battery life of PEVs and the stability of the power distribution network system. To mitigate this threat, a cyber attack detection strategy based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Broad Learning System (BLS) is proposed in this paper. The strategy exploits the coupling between PEVs and the power distribution network system during the charging process to achieve the detection of cyber attacks. CEEMDAN is implemented to extract features of system signals, and BLS uses the features extracted by CEEMDAN for feature mapping and enhancement to capture the presence of cyber attacks. Simulation analysis demonstrates that the proposed strategy can achieve more than 85% detection accuracy, with CEEMDAN bringing about 7% improvement in accuracy.

Published in Energy Reports

ISSN: 2352-4847 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: http://www.journals.elsevier.com/energy-reports/

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