Shield Reliability Analysis-Based Transfer Impedance Optimization Model for Double Shielded Cable of Electric Vehicle. (8th February 2021)

• Record Type: Journal Article
• Authors: Wu, Xiaoshan; Shi, Xiaohui; Jia, Jin; Zhao, Heming; Li, Xu
• Other Names: Chen Yong Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2021(2021)
• Publication Date: 2021-02-08
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2021/5373094
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Due to the high-voltage and high-current operating characteristics of the electric drive system of electric vehicles, it forms strong electromagnetic interference during the working process. The shielding effectiveness of the high-voltage connection cable that connects the components of the electric drive system is directly related to its electromagnetic interference emissions. Therefore, the modeling and analysis of the shielding effectiveness of the connection cable is very important for the development of a connection cable with good shielding effectiveness. Firstly, the transfer impedance value representing the shielding effectiveness of the shielded cable is analyzed, and the difference between the single-layer shield and the double-layer shield cable is compared. The influence of double-layer shielded high-voltage connection cables commonly used in electric vehicles on the shielding layer DC resistance and keyhole inductance is clarified. Secondly, the transfer impedance optimization model Z T_D -Desmoulins is obtained by combining with the single-layer shielded cable Desmoulins model and considering the influence of shielded layer DC resistance and keyhole inductance. Finally, three double-layer shielded cables of different types were selected for the triaxial test. The error rates of the test data and the Z T _ D -Desmoulin optimization model are all lower than 20% in each frequency band, which verified the correctness, universality, and great engineering application value of the optimization model.