With the emerging power electronic technologies, numerous electrical devices use high-frequency and nonsinusoidal supplies. Such sources generate complex harmonic fields that overburden the accurate prediction of core losses using the conventional finite element method (FEM). Thereby, to predict core losses under those high-frequency and nonsinusoidal supplies accurately, this study first built a test system for core losses measurement of ferromagnetic materials (e.g., soft ferrite, laminated steels, and nanocrystalline alloy) fed by the square and pulsewidth modulated (PWM) supplies. Then, the loss prediction problems of the classical core loss model under high-frequency and nonsinusoidal supplies are revealed. Afterward, an improved FEM-based core loss model is proposed, which includes a piecewise variable parameters based hysteresis loss model, an eddy current loss model considering different cross sections of magnetic circuit and supply waveforms, and improved excess loss coefficients. Experimental validations on different materials, the nanocrystalline alloy in an 11-kVA intermediate frequency transformer, the ultrathin silicon sheets in a 10-kW high-speed permanent magnet motor, and the nanocrystalline alloy in a 3-kW wireless power transfer system, are conducted systematically. The effectiveness and generality of the improved core loss model were verified.

This article proposes a rotor temperature estimation method for in-service induction machine (IM) based on parameter identification, which combines the advantage of recursive least squares (RLS) and model reference adaptive system (MRAS). The RLS with forgetting factor is firstly adopted to identify the parameters of motor inductances. Then, the online identification of rotor resistance can be realized via the MRAS based on the instantaneous reactive power (IRP) and the proportional integral (PI) regulation adaptive law designed by the Popov hyper-stable theory. Thereby, the rotor temperature is computed by the resistance-temperature relationship of metals. To achieve a fast convergence of the parameter identification, rotor slot harmonics are extracted from the stator current and used to determine the rotor speed in real time. Furthermore, to obtain a more accurate initial value of the stator and rotor leakage inductances and resistances, the first 5-15 cycles of the IM starting process are used to mimic the locked-rotor test condition. A merit of the proposed method is that it requires significantly less time to estimate the rotor resistance than the traditional methods. With a novel test bench, experimental validation is performed on a 22-kW IM. In the test, the rotor temperature is measured in three different ways: 1) wireless sensors inserted in the rotating rotor core and rotor end rings, 2) infrared sensor for rotor end ring temperature, and 3) PT100 installed in stator end winding. With this test bench, the real rotor temperature was revealed, and the effectiveness of the presented method is also verified.

For an inductive power transfer (IPT) system used in electric vehicle (EV) charging, the receiving coil is usually equipped with a shielding structure to reduce iron loss and electromagnetic interference in the chassis. However, the addition of a shielding structure may significantly reduce self-inductance and mutual inductance, and the eddy current on the shielding pad can also produce power loss. To maximize the efficiency of the IPT system used for EV charging and sufficient shielding, this study first analyzed the equivalent circuit model of the IPT system. A 3-D model of an IPT system, with a steel plate and aluminum shielding, is established and investigated in the finite-element analysis (FEA) domain, in which the shielding structure is modeled with some parametric sizes to simplify the modification of the parameters on a shielding structure. The simulation result shows how the ohmic loss on coils and the iron loss on steel plate changes after adding the shielding structure. Afterward, a practical method for optimizing aluminum shielding structure's parameters is proposed to maximize the efficiency of the IPT system, taking iron losses in a steel part and aluminum shielding into account. Furthermore, considering that the optimization procedure becomes complex since the different resonant capacitances are required due to the variable inductances, a new efficiency calculation method by FEA is presented to simplify the optimization procedure. Experimental validation is finally performed on a 3-kW wireless charging prototype; thus, the effectiveness of the proposed method is verified.

A synchronous condenser (SC) can provide the reactive power for the Ultra High Voltage Direct Current (UHVDC) converter station to keep voltage stability and prevent commutation failure. The single-phase short circuit at a transmission line is prevalent and it can result in not only the voltage drop but also the increase of the rotor loss and temperature of the SC. In order to study the ability of the SC to withstand a single-phase short-circuit fault, the rotor loss and temperature field of a 300-MVar SC are studied by coupling the electromagnetic and temperature field models of the SC with the models of the electric circuit and power grid. The loss distributions in the rotor core and slot wedges are calculated under a single-phase short-circuit fault at the different positions of the transmission line. The rotor temperature distributions of the SC under over- and under-excitations are calculated and verified by the experiments. The influence of short-circuit duration on the rotor temperature of the SC is calculated under the single-phase short circuit. The study can provide a theoretic basis for the improvement of the operating ability of the SC under the single-phase short-circuit faults.

Due to the coaction of supply harmonics and the harmonics resulting from the motor structures, the mechanism and distribution characteristics of iron losses become more complicated in inverter-fed induction motors. Therefore, accurate prediction and fine analysis of iron loss are very important at the design stage of high-efficiency inverter-fed induction motors. In order to predict the iron losses accurately, this paper proposes a piecewise iron loss model whose parameters vary with the magnitude and frequency of flux density, and two additional flux density terms are introduced to the classical iron loss model considering the nonlinearity of magnetic material and harmonic fields. With this model, the iron losses are calculated for an inverter-fed 5.5 kW induction motor. The results reveal the distribution characteristics of hysteresis and eddy current losses in stator and rotor cores, and the characteristics of additional iron loss caused by harmonic fields. By the comparison of predicted and measured no-load iron loss under different supply voltages and switching frequencies, the proposed model and the analysis results are validated.

Due to the dynamic load and the complex mechanical link, it is difficult to precisely analyze the characteristics of the energy consumption of Beam Pumping Motor Systems (BPMSs), in the development of energy saving approaches in oil production systems. To solve this problem, this paper establishes a practical model that combines the standard differential equation of induction motor, the crank movement equation and the wave equation of sucker rod, the loss equations of the low- and high-voltage supply lines and distribution transformers, for energy consumption analysis of BPMSs. With this practical model, the influence of different factors, including the load fluctuation, balance degree and dynamic liquid levels, on the electrical loss characteristics of BPMSs, can be analyzed. The variation of the electrical loss in a Type 12 BPMS driven by a 37kW induction motor with the different dynamic liquid levels and the balance degrees is studied, and the distribution characteristic of each loss component under five typical load conditions in oil field is also analyzed. It is revealed that the proportion of iron loss is about 40% of the total electrical loss. The correctness of the model is verified by comparing the calculated results with the measured data for a standard oil well. In addition, the energy saving devices based on the theoretical results obtained by the presented model achieve a significant energy saving ratio in the practical application at oil fields.