Uncertainty Analysis and Application of Temperature Rise Measurement for Traction Motor Winding in Rail Transit

Autor: DENG Min, LU Xiulong, CHENG Hao, CHEN Mingyang, ZOU Xiaoyang, WU Shuangyi
Jazyk: čínština
Rok vydání: 2024
Předmět:
Zdroj: Kongzhi Yu Xinxi Jishu, Iss 1, Pp 121-126 (2024)
Druh dokumentu: article
ISSN: 2096-5427
DOI: 10.13889/j.issn.2096-5427.2024.01.017
Popis: Temperature rise measurement is crucial for evaluating the performance of motors and ensuring their safe operation. In order to more effectively, accurately, and scientifically evaluate temperature rise measurement results for traction motors, the incorporation of the measurement uncertainty concept holds practical significance. This paper proposes a method for evaluating uncertainties in temperature rise measurement of traction motors based on technical specifications outlined in JJF 1059.1-2012 Evaluation and expression of uncertainty in measurement. The current study started with a comprehensive analysis of uncertainty sources in temperature rise measurement results of traction motors using the standard IEC 60349-2:2010 Electric traction-Rotating electrical machines for rail and road vehicles-Part 2: Electronic converter-fed alternating current motors. Subsequently, an uncertainty evaluation model was constructed, and practical examples were used to evaluate measurement uncertainties, specifically involving standard uncertainty evaluation and calculations of uncertainties in synthesis and extension. The results showed that, with a confidence probability of 95%, the motor temperature rise measurement result stood at 79.22 K, containing an extension uncertainty of 1.30 K, which quantitatively characterized the quality of the test results. The proposed method provides a technical basis for determining the confidence level of temperature rise measurement results for rolling stock traction motors, while offering guidance for evaluating uncertainties in temperature rise measurement for motor winding, especially concerning curve fitting using the least squares method.
Databáze: Directory of Open Access Journals