@inproceedings{a2746c808b2d41e2ba12232ab2001518,
title = "Dynamic power demand prediction for battery-supercapacitor hybrid energy storage system of electric vehicle with terrain information",
abstract = "Accurate and reliable prediction on power demand is critically important for effective power or energy management for hybrid energy storage systems with battery- super-capacitor for electric vehicles. Terrain information is one of the most common factors on power demand prediction from both driving and regenerative braking. This paper first establishes system dynamic models with battery, super-capacitor and electric motor. Based on these models, the dynamic response and characteristics of battery and super-capacitor are analyzed. Then the system time constant is formulated and studied in order to predict the dynamic power demand for battery-super-capacitor hybrid energy storage system of electric vehicle. Simulation has been conducted to verify that the proposed method in predicting dynamic power demand of electric vehicle is valid.",
keywords = "battery, hybrid energy storage system, power demand prediction, supercapacitor",
author = "Qiao Zhang and Weiwen Deng and Jian Wu and Feng Ju and Jingshan Li",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Workshop on Intelligent Energy Systems, IWIES 2014 ; Conference date: 08-11-2014",
year = "2014",
month = nov,
day = "13",
doi = "10.1109/IWIES.2014.6957051",
language = "English (US)",
series = "Proceedings - 2014 IEEE International Workshop on Intelligent Energy Systems, IWIES 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "82--87",
booktitle = "Proceedings - 2014 IEEE International Workshop on Intelligent Energy Systems, IWIES 2014",
}