摘要
当电动汽车主电路的电气接触点接触不良时,极易产生电弧故障,直接威胁车内人员的生命安全。论文提出了一种基于自定义差分阈值滤波-分段最大值标准化-统计数值规律的电弧故障检测方法。首先围绕真实电动汽车吉利帝豪EV450搭建了电动汽车电弧故障实验平台,开展了电动汽车在不同工作模式下的电弧故障实验。然后以电源端电压为对象,对信号进行小波分解,对小波分解得到的低频系数进行自定义差分阈值滤波和分段最大值标准化。最后统计标准化后数据相同值个数,并通过阈值法检测串联型电弧故障。论文对模型样本长度、差分阈值比例、最大值标准化分段数、预处理方法选择等进行了深入分析,并对参数进行了优化设置,进一步提升模型性能。结果表明,所建模型对电动汽车电弧故障检测准确率为98.35%,且实时性较好。通过对模型进行泛化性分析、算法时间复杂度分析及与其他电弧故障检测模型对比分析,证明论文所建模型对电动汽车电弧故障检测具有较好的适用性。
When the electrical contact points of the main circuit of an electric vehicle have poor contact,it is extremely easy to generate arc faults,directly threatening the life safety of the occupants.This paper proposes an arc fault detection method based on Customized differential threshold filtering,segmented maximum standardization,and statistical numerical rules.Firstly,an electric vehicle arc fault experimental platform was built around the real electric vehicle Geely Emgrand EV450,to conduct arc fault experiments under different working modes.Then,taking the power supply terminal voltage as the object,the signal is subjected to wavelet decomposition.The low-frequency coefficients obtained from wavelet decomposition were subjected to Customized differential threshold filtering and segmented maximum value standardization.Finally,the number of identical values in the normalized data was counted,and series arc faults were detected using a threshold method.The paper conducted in-depth analysis of the model′s on the target function of sample length,differential threshold ratio,number of segments in maximum normalization,and preprocessing method selection,optimizing the parameters to further improve the model performance.The results show that the accuracy of the constructed model for detecting electric vehicle arc faults is 98.35%,with good real-time performance.Through generalization analysis,algorithm time complexity analysis,and comparative analysis with other arc fault detection models,it is proven that the proposed model has good applicability for arc fault detection in electric vehicles.
作者
刘艳丽
杨贺允
刘乙雁
崔诗淼
王浩
Liu Yanli;Yang Heyun;Liu Yiyan;Cui Shimiao;Wang Hao(Faculty of Electrical and Control Engineering,Liaoning Technical University,Huludao 125105,China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2024年第5期262-270,共9页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(52104160)
2022年度葫芦岛市科技指导计划重点研发项目(2022JH2/07b)资助。
关键词
电动汽车
电弧故障
自定义差分阈值滤波
分段最大值标准化
统计数值规律
electric vehicles
arc faults
customized differential threshold filtering
segmented maximum value standardization
statistical numerical laws
