Reliability assessment for traction power supply system based on Quantification of Margins and Uncertainties. (September 2018)

• Record Type: Journal Article
• Authors: Feng, Ding; Lin, Sheng; Sun, Xiaojun; He, Zhengyou
• Is Part Of: Microelectronics and reliability. Volume 88/90(2018)
• Page Start: 1195
• Page End: 1200
• Publication Date: 2018-09
• Subjects: Reliability assessment -- Quantification of Margins and Uncertainties -- Traction power supply system -- Traction power supply equipment; Electronic apparatus and appliances -- Reliability -- Periodicals; Miniature electronic equipment -- Periodicals; Appareils électroniques -- Fiabilité -- Périodiques; Équipement électronique miniaturisé -- Périodiques; Electronic apparatus and appliances -- Reliability; Miniature electronic equipment; Periodicals; 621.3815
• DOI: 10.1016/j.microrel.2018.06.032
• Languages: English
• ISSNs: 0026-2714

Abstract

Abstract: The traction power supply is a crucial part of high-speed rail network. A failure of the traction power supply system may lead to delay or outage of high-speed trains that will not only have direct impact on the entire operation schedule but will also cause tremendous losses. Therefore, the reliability assessment of the traction power supply system is extremely important to ensure the transportation quality of high-speed trains and improve the economy. This paper presents a reliability evaluation method for the traction power supply system based on Quantification of Margins and Uncertainties (QMU). Firstly, the characteristics of the traction power supply equipment and system are combined to establish the observation list and then the performance channel for the equipment and system is determined. Finally, the confidence factor is calculated and the reliability of the equipment and system quantified by the quantification of the performance margin and uncertainty. In order to validate the effectiveness of the proposed method, simulations are conducted using practical operation data from a China traction power supply system. The simulation results demonstrate that the proposed reliability assessment method can account for the uncertainty and quantify the system reliability index. The proposed method has good applicability and can be used to effectively evaluate the reliability of the traction power supply system.