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.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings - 2014 IEEE International Workshop on Intelligent Energy Systems, IWIES 2014 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 82-87 |
| Number of pages | 6 |
| ISBN (Print) | 9781479958573 |
| DOIs | |
| State | Published - Nov 13 2014 |
| Externally published | Yes |
| Event | 2014 IEEE International Workshop on Intelligent Energy Systems, IWIES 2014 - San Diego, United States Duration: Nov 8 2014 → … |
Other
| Other | 2014 IEEE International Workshop on Intelligent Energy Systems, IWIES 2014 |
|---|---|
| Country | United States |
| City | San Diego |
| Period | 11/8/14 → … |
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Keywords
- battery
- hybrid energy storage system
- power demand prediction
- supercapacitor
ASJC Scopus subject areas
- Artificial Intelligence
- Energy Engineering and Power Technology
- Fuel Technology
Cite this
Dynamic power demand prediction for battery-supercapacitor hybrid energy storage system of electric vehicle with terrain information. / Zhang, Qiao; Deng, Weiwen; Wu, Jian; Ju, Feng; Li, Jingshan.
Proceedings - 2014 IEEE International Workshop on Intelligent Energy Systems, IWIES 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 82-87 6957051.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Dynamic power demand prediction for battery-supercapacitor hybrid energy storage system of electric vehicle with terrain information
AU - Zhang, Qiao
AU - Deng, Weiwen
AU - Wu, Jian
AU - Ju, Feng
AU - Li, Jingshan
PY - 2014/11/13
Y1 - 2014/11/13
N2 - 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.
AB - 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.
KW - battery
KW - hybrid energy storage system
KW - power demand prediction
KW - supercapacitor
UR - http://www.scopus.com/inward/record.url?scp=84916636053&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84916636053&partnerID=8YFLogxK
U2 - 10.1109/IWIES.2014.6957051
DO - 10.1109/IWIES.2014.6957051
M3 - Conference contribution
AN - SCOPUS:84916636053
SN - 9781479958573
SP - 82
EP - 87
BT - Proceedings - 2014 IEEE International Workshop on Intelligent Energy Systems, IWIES 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -