DocumentCode :
666431
Title :
DC-link stability control for dual-source electric vehicles using an extended kalman filter
Author :
Machado, Felipe ; Trovao, Joao P. ; Henggeler Antunes, Carlos
Author_Institution :
DEEC, Univ. of Coimbra, Coimbra, Portugal
fYear :
2013
fDate :
10-13 Nov. 2013
Firstpage :
4600
Lastpage :
4605
Abstract :
In this paper, an innovative control method for a hybrid source electric vehicle (EV) is presented. Since the usual and practical way to measure currents consists in using sensors based on Hall effect, we present a technique to significantly reduce the noise generated by these sensors. Firstly, the model to build such controller and the variables involved is discussed. Then, to have a stable system and a controller easy to setup, a method to solve the control problem using a linear-quadratic regulator (LQR) is proposed. An Extended Kalman Filter (EKF) that uses the sensors and the converter model is exploited to obtain almost noise-free currents. The LQR and the EKF are validated separately, using an overall model implemented in Matlab/Simulink. The results obtained reveal a good behaviour by the controllers and an almost noise-free environment after the addition of the EKF. Further, the global performance is also validated using a standard driving cycle.
Keywords :
Hall effect; Kalman filters; electric sensing devices; electric vehicles; linear quadratic control; nonlinear filters; stability; EKF; Hall effect; LQR; Matlab-Simulink; almost noise-free currents; dc-link stability control; dual-source electric vehicles; extended Kalman filter; global performance; hybrid source EV; innovative control method; linear-quadratic regulator; sensors; standard driving cycle; Batteries; Current measurement; Load modeling; Mathematical model; Noise; Sensors; Voltage control; Batteries; DC-DC power converters; Electric Vehicle; Linear-Quadratic Regulator; Supercapacitors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
ISSN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2013.6699877
Filename :
6699877
Link To Document :
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