DocumentCode :
3477745
Title :
Real-time electric vehicle mass identification
Author :
Wilhelm, Erik ; Rodgers, Lennon ; Bornatico, Raffaele
Author_Institution :
Singapore Univ. of Technol. & Design, Singapore, Singapore
fYear :
2013
fDate :
17-20 Nov. 2013
Firstpage :
1
Lastpage :
6
Abstract :
A technique capable of identifying electric vehicle (EV) mass in real-time has been a topic of research for several years due to the advantages it presents, such as the ability to dramatically improve range estimates, perform more effective torque vectoring for ABS/ESC, track delivery vehicle weight, etc. Some crucial issues in mass identification impede an easy implementation of such an algorithm, however, and this work introduces a simple method to calculate EV mass on-the-fly using standard data available on most CAN buses and therefore without the need of additional sensors. The results presented here are achieved using an eight step technique suitable for accurate mass estimations during wide-open-throttle acceleration events. The algorithm´s instantaneous error is less than 10%, and converges to better than 3% absolute accuracy performance with subsequent measurements. A preliminary analysis of trips lacking hard acceleration presented in this paper show an inability to differentiate between loaded and unloaded conditions.
Keywords :
electric vehicles; eight step technique; mass estimations; real time electric vehicle mass identification; wide open throttle acceleration events; Acceleration; Batteries; Equations; Mathematical model; Real-time systems; Torque; Vehicles; electric vehicles; mass identification; modeling & simulation; real-time;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Vehicle Symposium and Exhibition (EVS27), 2013 World
Conference_Location :
Barcelona
Type :
conf
DOI :
10.1109/EVS.2013.6914840
Filename :
6914840
Link To Document :
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