@inproceedings{3c1a62f8bdf549279a16aa8279e2167a,
title = "Intelligent power monitoring systems for battery-powered electric vehicles",
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.",
keywords = "Two-wheeled balancing vehicle, back propagation artificial neural network, state of charge",
author = "Lin, {Yu Heng} and Li, {Dian Rong} and Chuang, {Jhih Kai} and Leu, {Yih Guang}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics ; Conference date: 08-08-2015 Through 10-08-2015",
year = "2015",
month = sep,
day = "28",
doi = "10.1109/ICInfA.2015.7279272",
language = "English",
series = "2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "133--137",
booktitle = "2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics",
}