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
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