Intelligent power monitoring systems for battery-powered electric vehicles

Yu Heng Lin, Dian Rong Li, Jhih Kai Chuang, Yih-Guang Leu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

An intelligent power monitoring system is studied and implemented in a two-wheeled battery-powered electric vehicle. The power monitoring system utilizes a neural network to estimate the state of charge for the battery-powered electric vehicle. The neural network is trained by the internal loss data of the battery of the vehicle in order to approximate its energy characteristic. The trained neural network is implemented on a tablet computer and provides the real time estimate of remainder energy which denotes the remainder distance. Some experiments are performed to verify the accuracy of the energy estimate for the two-wheeled battery-powered electric vehicle.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages133-137
Number of pages5
ISBN (Electronic)9781467391047
DOIs
Publication statusPublished - 2015 Sep 28
Event2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics - Yunnan, China
Duration: 2015 Aug 82015 Aug 10

Publication series

Name2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics

Other

Other2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics
CountryChina
CityYunnan
Period15/8/815/8/10

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Keywords

  • Two-wheeled balancing vehicle
  • back propagation artificial neural network
  • state of charge

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Human-Computer Interaction
  • Computational Theory and Mathematics
  • Control and Systems Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Cite this

Lin, Y. H., Li, D. R., Chuang, J. K., & Leu, Y-G. (2015). Intelligent power monitoring systems for battery-powered electric vehicles. In 2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics (pp. 133-137). [7279272] (2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICInfA.2015.7279272