Research on Multi-Source Heterogeneous Data Fusion Technology of New Energy Vehicles Under the New Four Modernizations. Issue 2 (April 2021)

• Record Type: Journal Article
• Authors: Zhang, Fan; Yang, Jing; Sun, Chuan; Guo, Xin; Wan, Tiantian
• Is Part Of: Journal of physics. Volume 1865:Issue 2(2021)
• Publication Date: 2021-04
• Subjects: Multi-source heterogeneous data technology -- new energy vehicle -- data model processing -- new energy vehicle fault diagnosis; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1865/2/022034
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In order to better adapt to the development trend of the city, new energy vehicles are widely used to fit the development concept of green transportation. As the focus of smart city development, big data is indispensable for its application in new energy vehicle guarantees, especially in maintenance and machinery guarantees. In the operation and maintenance of new energy vehicles, the application of multi-source heterogeneous data technology is extremely important. Based on this research background, the paper introduces and constructs the new energy vehicle fault feature vector of the new energy vehicle, gives a multi-source time domain frequency domain data fusion new energy vehicle fault diagnosis method, and uses the neural network to give the basic probability distribution. The evidence theory fuses the signals of each sensor to get the diagnosis result.