2018 Vol.1 Oct. No.5

• Title: Fusion Positioning of Sensor Network Nodes in Electric Vehicle Charging Station under Cloud Computing
• Name: Patrick Gavin
• Company: The University of Nottingham, Malaysia Campus
• Abstract:

  In the cloud computing environment, by designing the sensor network model of electric vehicle charging station, the fusion positioning algorithm of the sensor network node of charging station is studied. Further, the mobile terminal can be used to quickly locate and search the electric vehicle charging station, thereby improving the service function of the charging station. A fusion localization algorithm for sensor network nodes based on strong tracking filter distance estimation is proposed. The channel estimation and modulation model of the sensor network of electric vehicle charging station is constructed. In the cloud computing environment, the sensor network node is accurately positioned and data fusion realized by stochastic resonance fusion technology. The multi-sensor data fusion filtering structure model of electric vehicle charging station is obtained to perform noise. The information amount of the state estimation information is suppressed, and the method of tracking and filtering distance estimation is adopted to realize the fusion positioning of the charging station node. The experimental results show that the distance estimation and fusion positioning of the sensor network nodes of the electric vehicle charging station are accurate and the performance is superior.

• Keyword: Electric Vehicle; Charging Station; Sensor Network; Positioning
• DOI: 10.12250/jpciams2018050113
• Citation form: Patrick Gavin.Fusion Positioning of Sensor Network Nodes in Electric Vehicle Charging Station under Cloud Computing[J]. Computer Informatization and Mechanical System, 2018, vol. 1, pp. 36-41.

[1]Ki Young Kim, Changwook Yoon,et al. Magnetic Resonance Wireless Power Transfer System for Practical Mid-Range Distance Powering Scenario References[C]. 2013 IEEE International Conference on Consumer Electronics (ICCE)],2013:175-176.  

[2]Kim K.Y，Choi J，Kim  C.W.Adaptive frequency with power level tracking system for efficient magnetic resonance wireless power transfer[J] Electronics Letters,2012,48(8):452-454.

[3]Soljačić M，Kurs A，Karalis A，et al．Wireless power transfer via strongly coupled magnetic resonances[J]．Science press，2007，112(6)：1-10．

[4]Zhu Zhen. Support vector machine classification algorithm based on neural network integrated classifier preprocessing [J]. Science bulletin, 2013, 29(4): 26-30.

[5]Liu Hui, Wang Boxiong, Ren Huaiyi, et al. Application of ICP algorithm in point cloud matching of binocular structure optical system[J]. Journal of Tsinghua University: Natural Science Edition.2012,52(7): 946-950.

[6]Zhu Yansong, Dou Guiqin. A WSN Security Data Fusion Method Based on Multi-Dimensional Trust[J].Journal of Wuhan University(Science Edition), 2013, 59(2): 193-197.