基于改进奇异值分解的新能源汽车串联型电弧故障检测方法  

Detection Method for a Series Arc Fault of New Energy Vehicles Based on Improved Singular Value Decomposition

作　　者：崔亚楠 李强 Cui Ya'nan;Li Qiang

机构地区：[1]广州华夏职业学院,广东广州510935

出　　处：《时代汽车》2024年第19期168-170,共3页Auto Time

摘　　要：在电动汽车充电时,通常会遇到一些问题,比如高压线路连接不牢固和线路绝缘老化破损等。这些问题往往会导致电弧故障,严重威胁到充电线路的安全性。由此本文提出基于改进奇异值分解的新能源汽车串联型电弧故障检测方法的研究,该研究旨在快速、准确地检测电动汽车电气系统中的电弧故障。该研究搭建了电动汽车故障电弧实验平台,采集不同工况下干路电流时间序列并建立了样本库。通过使用串联型锂离子电池系统的等效电路模型,构建基于二阶RC模型。最终,通过仿真分析来验证该模型的准确性。When charging electric vehicles,some problems are usually encountered,such as the weak connection of high-voltage lines and the aging and damage of line insulation.These problems often lead to arc failures,which seriously threaten the safety of the charging line.Therefore,this paper proposes research on the tandem arc fault detection method of new energy vehicles based on improved singular value decomposition,which aims to quickly and accurately detect arc faults in the electrical system of electric vehicles.In this study,an experimental platform for fault arcing of electric vehicles was built,and the time series of trunk circuit currents under different working conditions were collected and a sample library was established.A second-order RC model is constructed by using an equivalent circuit model for a series lithium-ion battery system.Finally,the accuracy of the model was verified by simulation analysis.

关 键 词：改进奇异值分解 故障检测 新能源汽车 串联型电弧 

分 类 号：U46[机械工程—车辆工程]