To meet increasing demand for higher reliability in power electronics converters applicable in electric vehicles, fault detection (FD) is an important part of the control algorithm. In this study, a model-based open transistor fault diagnsosis method is presented for a voltage-source inverter (VSI) supplying a five-phase permanent magnet motor drive. To realise this goal, a model-based observer is designed to estimate model parameters. After that, the estimated parameters are used to design a sliding mode observer in order to estimate the phase current in an ideal model. Subsequently, the proposed FD technique measures the similarity between the estimated current and real current using cross-correlation factor. This factor is used for the first time in this study to define a FD index in VSI. The presented FD scheme is simple and fast; also, it is able to detect multiple open switch or open phase faults in contrast to conventional methods. On the other side, in order to track reference current of the motor, the estimated parameters are used to design a proportional resonant controller. The FD technique is used to operate a multiphase fault-tolerant brushless direct current (BLDC) motor drive. Experimental results on a five-phase BLDC motor with in-wheel outer rotor applicable in electrical vehicles are conducted to validate the theory.Postprint (author’s final draft

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Abstract-Model predictive control algorithms have recently gained more importance in the field of ١٥ wind power generators. One of the important categories of model predictive control methods is improved ١٦ deadbeat control in which the reverse model of generator is used to calculate the appropriate inputs for the ١٧ next iteration of controlling process. In this paper, a new improved deadbeat algorithm is proposed to ١٨ control the stator currents of an outer-rotor five-phase BLDC generator. Extended Kalman filter is used in ١٩ the estimation step of proposed method, and generator equations are used to calculate the appropriate generators, brushless direct current (BLDC) generators have the advantage of higher torque density, ٣٢simpler winding distribution and more fault tolerance [1]. As a result, these machines are a practical option ٣٣for low-maintenance and high power applications such as off-shore wind power farms. Several methods ٣٤are proposed in literature to have a better control on stator phase currents of BLDC generators. ٣٥Among these algorithms, model predictive control (MPC) has become a suitable option recently. MPC ٣٦concept is easy to understand, and various constraints and nonlinearities can be directly included in its ٣٧ structure. Moreover, the resulting controller is easy to implement [2], [3]. These types of controllers can be ٣٨ effectively implemented in generator controlling algorithm because linear models of BLDC generators are ٣٩quite well known and developed through analytical methods. ٤٠In the field of generator power control, MPC algorithms can be generally divided into two main systems such as PM drives [6]. Considering the finite amount of possible switching states in the converter ٤٧ unit, this type of control algorithm is also famous as "finite set model predictive control" (FS-MPC). ٤٨On the other hand, the second group can be considered as an extension of traditional field-oriented ٤٩ control of generator. In this group, the inner PI controllers are removed and replaced by predictive ٥٠controllers. Moreover, reverse model of generator is used to calculate appropriate reference voltages, and a ٥١modulator is usually used to generate the computed reference voltages [7]. ٥٢Model predictive control has also been examined successfully in the case of multiphase generators [8]. ٥٣Comparing to standard three-phase generators, multi-phase structure of a BLDC generator results in of system states a fault detection and isolation algorithm is developed in [14]. As the mathematical model ٦٨of BLDC generator is sufficiently well developed, EKF is ideally suited for the case of five-phase BLDC ٦٩generator applications. ٧٠In this paper, extended Kalman filter based predictive deadbeat control (EKF-PDC) is developed for ٧١ five-phase BLDC generator. Proposed controlling algorithm includes two main steps namely "current ٧٢ estimation step" and "voltage application step". EKF is developed for five-phase BLDC generator, and is ٧٣executed during "current estimation step" to reduce the effect of ...

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The voltage-source inverters (VSI) supplying a motor drive are prone to open transistor faults. To address this issue in faulttolerant drives applicable to electric vehicles, a new open transistor fault diagnosis (FD) method is presented in this paper. According to the proposed method, in order to define the FD index, the phase angle of the converter output current is estimated by a simple trigonometric function. The proposed FD method is adaptable, simple, capable of detecting multiple open switch faults and robust to load operational variations. Keeping the FD in mind as a mandatory part of the fault tolerant control algorithm, the FD block is applied to a five-phase converter supplying a multiphase fault-tolerant PM motor drive with nonsinusoidal unbalanced current waveforms. To investigate the performance of the FD technique, the fault-tolerant sliding mode control (SMC) of a five-phase brushless direct current (BLDC) motor is developed in this paper with the embedded FD block. Once the theory is explained, experimental waveforms are obtained from a five-phase BLDC motor to show the effectiveness of the proposed FD method. The FD algorithm is implemented on a field programmable gate array (FPGA).