Enhancement of Sensorless Control for Non-Sinusoidal Multiphase Drives-Part I: Operation in Medium and High-Speed Range

This two-part study proposes a new sensorless control strategy for non-sinusoidal multiphase permanent magnet synchronous machines (PMSMs), especially integrated motor drives (IMDs). Based on the Sliding Mode Observer (SMO), the proposed sensorless control strategy uses the signals (currents and voltages) of all fictitious machines of the multiphase PMSMs. It can estimate the high-accuracy rotor positions that are required in vector control. This proposed strategy is compared to the conventional sensorless control strategy that applies only current and voltage signals of the main fictitious machine, including the fundamental component of back electromotive force (back EMF) of non-sinusoidal multiphase PMSMs. Therefore, in order to choose an appropriate sensorless control strategy for the non-sinusoidal multiphase PMSMs, these two sensorless control strategies will be highlighted in terms of precision with respect to rotor position and speed estimation. Simulations and the experimental results obtained with a non-sinusoidal seven-phase PMSM will be shown to verify and compare the two sensorless control strategies. In this part of the study (part I), only sensorless control in the medium and high-speed range is considered. Sensorless control at the zero and low-speed range will be treated in the second part of this study (part II).

An Extreme Learning Machine Based Adaptive VISMA for Stability Enhancement of Renewable Rich Power Systems

Maintaining power system stability in renewable-rich power systems can be a challenging task. Generally, the renewable-rich power systems suffer from low and no inertia due to the integration of power electronics devices in renewable-based power plants. Power system oscillatory stability can also be affected due to the low and no inertia. To overcome this problem, additional devices that can emulate inertia without adding synchronous machines can be used. These devices are referred to as virtual synchronous machines (VISMA). In this paper, the enhancement of oscillatory stability of a realistic representative power system using VISMA is proposed. A battery energy storage system (BESS) is used as the VISMA by adding an additional controller to emulate the inertia. The VISMA is designed by using Fruit Fly Optimization. Moreover, to handle the uncertainty of renewable-based power plants, the VISMA parameters are designed to be adaptive using the extreme learning machine method. Java Indonesian Power Grid has been used as the test system to investigate the efficacy of the proposed method against the conventional POD method and VISMA tuning using other methods. The simulation results show that the proposed method can enhance the oscillatory stability of the power system under various operating conditions.

GA Optimization for Regression Modeling of Electromagnetic Performances Predicted by a Subdomain Model for SMPMSM in an Electric Vehicle

This paper investigates a nonlinear modeling optimization of 12s/8p surface-mounted permanent magnet synchronous machines (SMPMSM) with a radial magnetization pattern. The modeling is based on subdomain model (SDM) computation, where the analytical models are developed to predict the electromagnetic (EM) performances, such as, average EM torque and EM torque ripple in PM machines. A genetic algorithm is applied to the proposed model in order to search for the optimal solutions. The objective function of the optimizations is obtaining a higher average EM torque and achieving the minimum EM torque ripple. The data, viz, and the average EM torque and its ripples predicted by SDM are employed in regression analysis in order to find the model of best fit. After that, the most suitable fit of the computing equation is selected. The preliminary and optimal designs of 12s/8p PM motors are also compared in terms of parameters and motor performance. As a result, the regression model and GA framework has reduced the use of magnet materials and the EM torque ripple of the SMPMSM, making it ideal for use in an electric car. Lastly, the proposed model can determine the appropriate configuration design parameters for SMPMSM in order to achieve the best motor performance.

Design and Simulation of a Servo-Drive Motor Using ANSYS Electromagnetics

The paper is devoted to determining the output parameters of a servomotor, which belongs to synchronous machines with permanent magnets, in order to further determine the characteristics of transient modes in the software package ANSYS Electromagnetics. RMxprt, part of ANSYS Electromagnetics, allows to determine the parameters of windings, losses, motor performance, but requires filling out a form with a complete set of geometric dimensions and winding data. Of course, such data are not available in the motor data sheet, so the first task solved in the paper is to determine all the necessary and sufficient parameters to perform the calculation in RMxprt. The results of the calculations were compared with the measurements on the experimental servomotor EMG-10APA22. This paper shows how to export a servomotor object from RMxprt to the Simplorer workspace, which is also part of the ANSYS Electromagnetics. According to the simulation results in ANSYS Simplorer, the characteristics of the transient modes of the servomotor powered by a stable three-phase source are obtained. Prospects for further research related to the improvement of the simulation model in ANSYS Simplorer are presented.

SIMULATION OF STARTING MODES OF SYNCHRONOUS ELECTRIC DRIVE OF A PUMP STATION

The article studies the starting modes of a synchronous electric drive of a pumping station, in direct and soft start of high-voltage synchronous motors of an irrigation pumping station of the first stage. The analysis of negative starting factors of synchronous machines is made on the basis of computer modeling of the research object. The simulation results are clearly shown for the main parameters of a synchronous electric drive, such as its rotation speed, stator currents, electromagnetic torque on the shaft, etc.