A linear switched reluctance motor (LSRM) is an attractive candidate for high-precision position control applications in industry. Compared to its single-sided counterpart, a double-sided LSRM (DLSRM) has a more propulsion force to mass ratio and normal force can be counteracted from serially connected excitation windings and a symmetric machine structure. In this study, a nonlinear inductance modelling method is proposed by introducing a K factor that reflects both current and position effect on inductance. Considering uncertainties and disturbances from the DLSRM-based motion system, this study implements online parameter estimation with adaptive control strategy to detect system parameter variations and regulate control parameters in real time. Experimental results demonstrate that the proposed control method is capable of position tracking with the desired performance and adaptive to operational changes either under command signal variations or external disturbances. These results prove the effectiveness of the proposed control method for high-precision position control of the DLSRM.

In this study, an optimal design of a new line-start permanent magnet synchronous shaded-pole motor (LSPMSSPM) is proposed. A genetic algorithm optimisation method based on transient two-dimensional finite-element method (FEM) is applied to reach a global optimum design. Advantages and challenges of the proposed LSPMSSPM are investigated, and its performance characteristics are calculated. Efficiency, power factor, starting behaviour and cost as important key factors are analysed. Finally, FEM results are verified with experimental tests.

This study presents an improved control algorithm for a stand-alone double-output induction machine-based variable speed constant frequency generator. The algorithm ensures sinusoidal load voltage and machine stator current for all types of loads such as balanced, unbalanced, linear and non-linear in any arbitrary combination. This is achieved by incorporating harmonic and unbalanced load compensation function to the stator side converter. Unlike other control strategies reported in the literature for this purpose, the proposed algorithm does not require extraction or compensation of individual harmonic/unbalance components of the load voltage/stator current. Harmonic compensation performance of the algorithm is thoroughly analysed theoretically and design guidelines provided. The experimental results obtained from a laboratory prototype demonstrate excellent load voltage regulation property during severe transient operating conditions. Total harmonic distortion and unbalance of the load voltage and stator current even with large unbalanced non-linear loads are also found to be much smaller compared with similar systems reported earlier in the literature.

Mechanical deformations of transformer windings are identified through variations observed in their frequency response (FR). This study proposes a new way of determining a transfer function (TF) from measured FR data using factorisation principles as against established ways of finding it through rational fitting algorithms or least-square estimation. It is observed that some characteristics of FR of a transformer winding are similar to FR of first- and second-order systems, and this has been the basic motivation for the reported work. In the proposed method, TF is expressed as a combination of first- and second-order polynomials. The algorithm is applicable over a wide-frequency range and for high-order systems. Initial guesstimates for locations of poles/zeros, orders of TFs, and enforcement of poles to the left half of the s-plane are not required. The algorithm is validated through three case studies and its accuracy is checked through commonly used statistical indicators. The application of the algorithm is also demonstrated on a 500 kVA distribution transformer. The method is simple and accurate in estimating TFs for their further use in the deformation diagnostics of transformer windings.

The aim of this study is to find out the performance characteristics of single-phase axial flux induction motors. In this study, three-dimensional time-stepping finite-element method is employed to analyse electromagnetic fields. Both eddy current and saturation effects are considered in the simulation. Since this transient solution is a computationally expensive method, a mathematical model based on d−q-axis theory is presented in this study. Then, the motor's electrical parameters, whose values are requested in the d−q model, are calculated using the analytical method and the DC-charge test of the built motor. The comparison between experimental and simulation results verifies the success of simulation.

Most of the induction motor (IM) fault detection schemes are based on one sensor with one detection logic which are generally incapable of bringing out any consistent feature related to rotor misalignment. Moreover, these logics do not consider simultaneously the asymmetric load condition with variable speed operation. In this study, a data fusion-based misalignment related fault identification algorithm is presented, which isolates fault features from similar features generated because of other operating conditions. In the proposed scheme, the feature vector is constructed by using signatures created from frequency-domain characteristics obtained from stator vibration and line current measurements. Thereafter, the feature fusion technology, by means of the weighted linear combination concept, is adopted to take advantage of the best features from both sensors and to discern the pattern of misalignment with other signatures. The technique is validated experimentally on a 5.5 hp IM and the results are presented.

This study deals with the modelling and the control of the hybrid excitation synchronous machine connected to a diode bridge rectifier. The set operates as a DC generator that supplies an isolated grid in embedded applications such as aircraft electrical power generation. The elaborated model includes the magnetic circuit saturation effect. The aim of the control is to maintain the DC bus voltage constant when the load and/or the speed of the rotor vary. Simulation results and experiments validate the approach. The electrical parameters of the laboratory prototype machine are identified prior to the control test.

This study presents multi-rate parameter and state estimation methods for the induction motor. Based on multi-rate control theory and the extended Kalman filter (EKF) theory, a multi-rate EKF algorithm including input and output algorithms is proposed for load torque estimation in the induction motor. The methods are implemented in real-time on PC-cluster node which acts as the controller for an induction motor experimental set-up. Rotor time constant is a sensitive variable in indirect field-oriented control method. A multi-rate model reference adaptive system (MRAS) is proposed to estimate the rotor time constant in order to guarantee the high-performance control of induction motor. Experimental result verified the effectiveness of the algorithms. Simulations compare the multi-rate EKF algorithm with the traditional single-rate EKF algorithm performance to show improved performance of load torque estimator. The comparison between the traditional MRAS and the multi-rate MRAS shows the superiority of the proposed method, with a satisfactory accuracy.