Inter-turn winding faults in five-phase ferrite-permanent magnet-assisted synchronous reluctance motors (fPMa-SynRMs) can lead to catastrophic consequences if not detected in a timely manner, since they can quickly progress into more severe short-circuit faults, such as coil-to-coil, phase-to-ground or phase-to-phase faults. This paper analyzes the feasibility of detecting such harmful faults in their early stage, with only one short-circuited turn, since there is a lack of works related to this topic in multi-phase fPMa-SynRMs. Two methods are tested for this purpose, the analysis of the spectral content of the zero-sequence voltage component (ZSVC) and the analysis of the stator current spectra, also known as motor current signature analysis (MCSA), which is a well-known fault diagnosis method. This paper compares the performance and sensitivity of both methods under different operating conditions. It is proven that inter-turn faults can be detected in the early stage, with the ZSVC providing more sensitivity than the MCSA method. It is also proven that the working conditions have little effect on the sensitivity of both methods. To conclude, this paper proposes two inter-turn fault indicators and the threshold values to detect such faults in the early stage, which are calculated from the spectral information of the ZSVC and the line currents.Energies 2019, 12, 2733 2 of 15 ripple in the output, although torque pulsations can be minimized by means of a suitable design, including rotor skewing, asymmetric flux barriers or selected rotor steps [5].Faults in electrical machines could produce loss of system reliability, unscheduled shutdowns [9], important economic losses or even harmful effects to humans. Therefore, there is a growing demand for improved fault diagnosis approaches in electrical machines, in particular for high-performance applications [10]. This strategy ensures the safe and reliable operation of the plant, while greatly reducing unexpected and unscheduled fault occurrences, thus improving system availability and minimizing economic losses and the likelihood of accidents [11].Rotating electric machines are designed with mechanical and electrical symmetry to maximize performance and efficiency and to minimize vibrations. When operating under faulty conditions this symmetry is lost, thus changing the magnitude or the shape of different machine signals, such as the electromotive force, line currents, vibrations profile or the temperature, among others [12]. Most of these faults generate specific patterns of such signals, so these changes can be used for fault diagnosis purposes.Different fault diagnosis techniques have been analyzed in the technical literature, based on on-line or off-line approaches. Whereas off-line methods require the disconnection of the machine and sometimes the removal of some components, on-line diagnosis methods require the addition of specific sensors to acquire data from the machine during normal operation, although in some cases no extra sensors are required. Due to the ex...

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During the last years, the requirements for a fast and reliable design of electrical machines by applying optimization methods using finite element analysis (FEA), has become a subject of study. Due to their capabilities, permanent magnet synchronous machines (PMSMs) have become the preference choice for many applications, including electric vehicles (EVs) propulsion, water-pumping, robotics, or renewable power generation among others. This paper presents a novel methodology for designing and optimizing PMSMs using the torque-speed-efficiency map. The design-optimization algorithm requires as input, the torque-speed-efficiency map of the target motor, to define the required performance for the given application. The objective is to find the motor geometry which better approximates the target torque-speed-efficiency map. The PMSM is evaluated by using magneto-static FEA combined with direct-quadrature (d-q) electrical modeling, thus greatly reducing the computational burden when compared to conventional time-dependent FEA methods. The magneto-static FEA method calculates iron losses taking into account the magnetic flux density harmonic content by applying a time-space conversion approach. The design-optimization process takes into account the control strategy as well as losses separation, which is validated by using the public experimental data of the Toyota Prius and Camry PMSMs. Index Terms-Permanent magnet machines, Design optimization, Design tools, Magnetic losses, Finite element analysis NOMENCLATURE Bxy Magnetic flux density in a defined region [T] dwire Wire diameter [m] Dir Inner rotor diameter [m] Dis Inner stator diameter [m] Dor Outer rotor diameter [m] Dos Outer stator diameter [m] fobj Objective function [-] g Air gap length [m] hbrg Rotor bridge height [m] hPM Permanent magnet height [m] hrib Rotor rib height [m] hso Slot opening height [m] hsy Stator yoke height [m] ht Tooth height [m] Imax Maximum current [ARMS] L Stack lamination length [m]

This paper analyzes partial demagnetization faults in a five-phase permanent magnet assisted synchronous reluctance motor (fPMa-SynRM) incorporating ferrite permanent magnets (PMs). These faults are relevant because of the application of field weakening, or due to high operating temperatures or short circuit currents, the PMs can become irreversibly demagnetized, thus affecting the performance and safe operation of the machine. This paper proposes fault indicators to detect such fault modes with low demagnetization levels between 5.0% to 16.7% relative demagnetization. Four partial demagnetization fault detection methods are tested, which are based on the analysis of the harmonic content of the electromotive force (EMF) under no load conditions, the harmonic content of the line currents, the harmonic content of the zero-sequence voltage component (ZSVC) and the analysis of the power factor (PF). This work also compares the sensitivity and performance of the proposed detection methods. According to the fault indicators proposed in this paper, the results show that the analysis of the EMF, ZSVC and PF are the most sensitive detection methods. Experimental results are presented to validate finite element analysis (FEA) simulations.

The need to reduce water pumps size to achieve compact designs adapted to multiple working points opens new fields of study. PMSMs are the preferred choice due to outstanding torque-speed range capabilities. This paper presents a methodology to design and optimize PMSMs by defining the desired torque-speed-efficiency map, adapting its performance to the hydraulic characteristics of the water pump. Once the hydraulic efficiency is known, an initial PMSM reference torquespeed-efficiency map is defined according to the objective motor performance, including the distribution of power losses and the power rating of the selected application. The designer has full freedom to define the efficiency levels and distribution along the torque-speed map. The design optimization algorithm achieves the PMSM characteristics which adjust as much as possible to the defined performance. This methodology uses ultra-fast finite element analysis by applying magneto-static computations and a time-space conversion to compute the iron losses, reducing the computational requirements. The torque-speed-efficiency map is calculated by applying a direct-quadrature electrical model. The objective function uses a novel image comparison technique that allows comparing the similarity between the objective and optimized maps. The methodology is validated experimentally by designing and testing a PMSM adapted to a real WP application.