NDLI: Data-enhanced machine recognition model of DC serial arc in electric vehicle power system

Content Provider	IET Digital Library
Author	Xia, Kun Zhang, Zihan Liu, Bangzheng Guo, Haotian Yu, Weize Xu, Jingjun Dong, Hui
Abstract	Electric vehicle (EV) power system is the key to the development of EVs. If direct current (DC) arc occurs in the power system, it is difficult to extinguish at zero point. The arc fault will release a huge amount of energy and continuous sparking, which may cause spontaneous combustion or even explosion. In this study, an arc detection algorithm based on the classification of windowed Fourier transform and support vector machine (SVM) model is proposed for DC serial arc detection of EV power system. In order to optimise the arc detection algorithm, the authors use the pre-detection algorithm, which can effectively reduce the false detection rate of DC arc fault and ensure the reliability of detection algorithm. In addition, they propose an arc fault data enhancement model, which can generate arc fault current data. Finally, the experimental results show that the arc detection algorithm has a high accuracy and a false detection rate of 0%. After data enhancement, it has generalisation of the SVM classification model under the condition of high power experiment.
Starting Page	4677
Ending Page	4684
Page Count	8
ISSN	17554535
Volume Number	13
e-ISSN	17554543
Issue Number	Issue 19, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-pel.2020.0923
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-pel/13/19
Journal	IET Power Electronics
Publisher Date	2021-02-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Arc Detection Algorithm Arc Fault Current Data Arc Fault Data Enhancement Model Arcs (electric) Data-enhanced Machine Recognition Model DC Arc Fault DC Serial Arc Detection Direct Current Arc Electric Vehicle Electric Vehicle Power System EV Power System False Detection Rate Fault Current Fault Diagnosis Fourier Transforms High Power Experiment Integral Transforms Power Engineering Computing Pre-detection Algorithm Support Vector Machine Support Vector Machine Model SVM Classification Model Transportation Windowed Fourier Transform Classification
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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