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Virtual-Sensor-Based Maximum-Likelihood Voting Approach for Fault-Tolerant Control of Electric Vehicle Powertrains

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4 Author(s)
Tabbache, B. ; Univ. of Brest, Brest, France ; Benbouzid, M.E.H. ; Kheloui, A. ; Bourgeot, J.

This paper describes a sensor fault-tolerant control (FTC) for electric-vehicle (EV) powertrains. The proposed strategy deals with speed sensor failure detection and isolation within a reconfigurable induction-motor direct torque control (DTC) scheme. To increase the vehicle powertrain reliability regarding speed sensor failures, a maximum-likelihood voting (MLV) algorithm is adopted. It uses two virtual sensors [extended Kalman filter (EKF) and a Luenberger observer (LO)] and a speed sensor. Experiments on an induction-motor drive and simulations on an EV are carried out using a European urban and extraurban driving cycle to show that the proposed sensor FTC approach is effective and provides a simple configuration with high performance in terms of speed and torque responses.

Published in:

Vehicular Technology, IEEE Transactions on  (Volume:62 ,  Issue: 3 )

Date of Publication:

March 2013

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