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Electric vehicles (EVs) require uninterrupted and safe conditions during operations. Therefore, the diagnostic of power devices and electric motor faults are needed to improve the availability of the system. Hence, fault-tolerant control (FTC), which combines switch fault detection, hardware redundancy and post-fault control, is used. This paper aims to propose an accurate open-phase fault detection and FTC of a direct torque control permanent magnet synchronous motor electrical vehicles by using discrete Fourier-transform phase method.

The main idea is to propose detection and identification of open-phase fault (faulty leg) among three phases voltage source invertor (VSI)-fed permanent magnet synchronous motor drives. Once the faulty leg is detected and isolated, a redundant phase leg insertion, shared by a three-phase VSI, is done by using independent bidirectional TRIAC switches to conduct FTC system. This accurate fault detection significantly improves system availability and reliability. The proposed method of open-phase fault detection and identification is based only on stator phase current measurement.

A novel method is proposed with experimental validation for fault detection, isolation and FTC for a three-phase VSI-fed permanent magnet synchronous motor.

The novel discrete Fourier-transform phase method is proposed to detect an open phase based on the measurement in real time of the instantaneous phase of stator current components in the stationary frame. The experimental implementation is carried out on powerful dSpace DS1104 controller board based on the digital signal processor TMS320F240. The validity of the proposed method has been experimentally verified.

This work proposes a method to improve the estimation performance at standstill and low speed operations of an adaptive fuzzy logic speed‐sensorless field‐oriented control of an induction motor.

First, the speed estimation algorithm presented in Tursini et al., which it has been designed to consider constant speed operation, is modified in an attempt to reduce the estimation error. Second, the speed regulation by fuzzy logic controller (FLC) with fuzzy adapted gains (FAG) is proposed for speed regulation. The main features of the proposed algorithm are investigated and compared with those of the algorithm of (Tursini) considering different dynamic operating conditions.

Simulation results clearly show the performance of the proposed algorithm.

The proposed scheme is recommended for applications requiring robust speed control and field‐orientation even in the presence of some key parameter deviations.

This paper aims to analyze and investigate the performance of an improved fault detection and identification (FDI) method based on multiple criteria, applied to six-switch three-phase inverter (SSTPI)-fed induction motor (IM) drives under both single and multiple open insulated-gate bipolar transistors(IGBT) faults.

This paper proposes an advanced diagnostic method for both single and multiple open IGBT faults dedicated to SSTPI-fed IM drives considering five distinct faulty operating conditions as follows: a single IGBT open-circuit fault, a single-phase open-circuit fault, a non-crossed double fault in two different legs, a crossed double fault in two different legs and a three-IGBT open-circuit fault. This is achieved because of the introduction of a new diagnosis variable provided using the information of the slope of the current vector in (α-β) frame. The proposed FDI method is based on the synthesis and the analysis, under both healthy and faulty operations, of the behaviors of the introduced diagnosis variable, the three motor phase currents and their normalized average values. Doing so, the developed FDI method allows a best compromise of fast detection and precision localization of IGBT open-circuit fault of the inverter.

Simulation works, carried out considering the implementation of the direct rotor flux oriented control in an IM fed by the conventional SSTPI, have proved the high performance of the advanced FDI method in terms of fast fault detection associated with a high robustness against false alarms, against speed and load torque fast variations and against the oscillations of the DC-bus voltage in the case of both healthy and faulty operations.

This work should be extended considering the validation of the obtained simulation results through experiments.

Different from other FDI methods, which suffer from a low diagnostic effectiveness for low load levels and false alarms during transient operation, this method offers the potentialities to overcome these drawbacks because of the introduction of the new diagnosis variable. This latter, combined with the information provided from the three motor phase currents and their normalized average values allow a more efficient detection and identification of IGBT open-circuit fault.