In this paper, an effective procedure for broken rotor bar (BRB) fault detection in a three-phase squirrel-cage induction machine (SCIM) is proposed. This approach relies on a motor current signature analysis (MCSA) by observing the specific fault-related current component generated by applying the DC injection braking method. Unlike the traditional MCSA, which is commonly focused on the detection of BRB sidebands around the fundamental current component, the proposed methodology introduces a new BRB feature in the current spectrum which makes it much easier for identification. The distinctive time-frequency evolution pattern of this feature provides the reliable identification of BRBs, even under no-load operating conditions, thus overcoming the major drawback of traditional MCSA-based methods. Fault severity classification is easily performed through the magnitude inspection of the BRB fault-related current component. In addition, the proposed approach does not require high-complexity signal processing algorithms to achieve reliable results. The proposed concept is presented theoretically, assisted by a magnetically coupled multiple circuit model of the SCIM, both with healthy and faulty rotor bars. Finally, the experimental tests validate the proposed methodology and demonstrate its effectiveness and usefulness.

In this paper, we proposed a novel steady-state multiple parameters estimation method of the two-coil inductive power transfer (IPT) system based on the measurement of the primary-side voltage and current fundamentals. The method is used to estimate key parameters, such as mutual inductance and equivalent load resistance, as well as receiver self-inductance and compensation capacitance values, and the total parasitic resistance of the secondary side. The method also allows the identification of the secondary-side resonant frequency. The parameters estimation procedure involves three operating modes of the IPT system: 1) open-circuit of the secondary side, 2) short-circuit of the secondary side, and 3) load connection. Each of these modes allows the identification of different parameters. To make the system operate in predefined modes, two switches are added to the receiver circuit. These switches are controlled from the secondary side, while the parameters estimation process, including load voltage and/or current control, is fully conducted on the primary side. The experimental tests on the prototype have validated the proposed method and demonstrated its effectiveness. The method can be applied to a new generation of high-performance wireless battery charging systems, where the single transmitter unit can be used to charge the battery pack in different devices.

The most widely adopted category of the mid-range wireless power transmission (WPT) systems is based on the magnetic resonance coupling (MRC), which is appropriate for a very wide range of applications. The primary concerns of the WPT/MRC system design are the power transfer capabilities. Using the scattering parameters based on power waves, the power transfer of an asymmetric WPT/MRC system with the series-series compensation structure is studied in this paper. This approach is very convenient since the scattering parameters can provide all the relevant characteristics of the WPT/MRC system related to power propagation. To maintain the power transfer capability of the WPT/MRC system at a high level, the scattering parameter $S_{21}$ is used to determine the operating frequency of the power source. Nevertheless, this condition does not coincide with the maximum possible power transfer efficiency of the system. In this regard, the WPT/MRC system is thereafter configured with a matching circuit, whereas the scattering parameter $S_{21}^{\prime }$ S21’is used to calculate and then adjust the matching frequency of the system. This results in the maximum available power transfer efficiency and thereby increases the overall performance of the system. Theoretical investigations are followed by numerical simulation and experimental validation.

In this paper, a suitable method for the on-line detection of the airgap mixed eccentricity fault in a three-phase cage induction motor has been proposed. The method is based on a Motor Current Signature Analysis (MCSA) approach, a technique that is often used for an induction motor condition monitoring and fault diagnosis. It is based on the spectral analysis of the stator line current signal and the frequency identification of specific components, which are created as a result of motor faults. The most commonly used method for the current signal spectral analysis is based on the Fast Fourier transform (FFT). However, due to the complexity and memory demands, the FFT algorithm is not always suitable for real-time systems. Instead of the whole spectrum analysis, this paper suggests only the spectral analysis on the expected airgap fault frequencies employing the Goertzel?s algorithm to predict the magnitude of these frequency components. The method is simple and can be implemented in real-time airgap mixed eccentricity monitoring systems without much computational effort. A low-cost data acquisition system, supported by the LabView software, has been used for the hardware and software implementation of the proposed method. The method has been validated by the laboratory experiments on both the line-connected and the inverter-fed three-phase fourpole cage induction motor operated at the rated frequency and under constant load at a few different values. In addition, the results of the proposed method have been verified through the motor?s vibration signal analysis.

In this paper a novel hybrid mathematical model for the local iron loss power density calculation method of Interior Permanent Magnets Synchronous Machines (IPMSM) using Finite Element Analysis (FEA) is presented. The proposed model calculates hysteresis losses based on experimentally obtained static hysteresis loops of the ferromagnetic material. This mathematical model provides an alternative for the scarcity of experimental data by estimating hysteresis loops using the Preisach distribution model. The model incorporates waveforms of non-sinusoidal magnetic flux density for each and every finite element individually to precisely calculate eddy current losses. Therefore, its application is suitable for the estimation of local iron loss distribution and its detrimental thermal effects in the wide-speed range operation. The proposed model was verified on an IPMSM machine used for a case study, and it was compared with the conventional method based on Bertotti iron loss model.

In inductive power transfer (IPT) systems, the relative position between the primary and secondary side assemblies affects the self-inductance of the coils and their mutual inductance. Additionally, the aging effect of capacitors influences the value of compensation capacitors. It is, therefore, necessary to determine a minimum set of key IPT system parameters when implementing a constant-current (CC) / constant-voltage (CV) battery charging algorithm without real-time communication. This paper presents a method for implementing the CC/CV battery charging algorithm in an LCC-S IPT system without requiring real-time communication or all system parameters. Using only measurements from the primary side, the method is based on the phasor estimation of the primary-side electromotive force (EMF). Estimated parameters include the mutual inductance, the primary-side coil self-inductance and its parasitic resistance, and the secondary-side circuit resonant frequency. The first three parameters are estimated before the battery charging process starts, whereas the secondary-side circuit resonant frequency is identified during the charging process without influencing it. To verify the validity of the proposed method, an IPT prototype with 48 V charging voltage and 4 A charging current is implemented. Experimental results indicate that the estimated parameter set provides fast and accurate output voltage and current control.