DocumentCode :
2655076
Title :
Short term power demand forecasting in light- and heavy-duty electric vehicles through linear prediction method
Author :
Sangdehi, Mahdi Mousavi ; Iyer, K. Lakshmi Varaha ; Mukherjee, Kaushik ; Kar, Narayan C.
Author_Institution :
Centre for Hybrid Automotive Res. & Green Energy, Univ. of Windsor, Windsor, ON, Canada
fYear :
2012
fDate :
18-20 June 2012
Firstpage :
1
Lastpage :
6
Abstract :
In this paper a novel method based on linear prediction technique is proposed for short term power demand forecasting in light and heavy-duty electric vehicles for improvement in the overall efficiency of the vehicle. The paper also utilizes filtering of unnecessary information which would have been a major bottleneck in improving the method´s accuracy. The predicted demand function is fed to a wavelet function, which apportions the share between the battery and the ultracapacitor of the considered energy management system. The proposed method is validated with empirical power demand data obtained from on road tests of both light and heavy-duty electric vehicles through numerical investigations.
Keywords :
battery powered vehicles; demand forecasting; energy management systems; filtering theory; load forecasting; prediction theory; supercapacitors; battery; demand function prediction; energy management system; heavy-duty electric vehicle; information filtering; light-duty electric vehicle; linear prediction method; short term power demand forecasting; ultracapacitor; wavelet function; Correlation; Energy management; Filtering; Power demand; Power measurement; Predictive models; Vehicles; Energy management system; heavy duty electric vehicles; light duty electric vehicles; linear prediction; predictive control scheme; wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transportation Electrification Conference and Expo (ITEC), 2012 IEEE
Conference_Location :
Dearborn, MI
Print_ISBN :
978-1-4673-1407-7
Electronic_ISBN :
978-1-4673-1406-0
Type :
conf
DOI :
10.1109/ITEC.2012.6243480
Filename :
6243480
Link To Document :
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