An Effective Model-Free Predictive Current Control for Synchronous Reluctance Motor Drives

The performances of a model predictive control algorithm largely depend on the knowledge of the system model. A model-free predictive control approach skips all the effects of parameters variations or mismatches, as well as of model nonlinearity and uncertainties. A finite-set model-free current predictive control is proposed in this paper. The current variations predictions induced by the eight base inverter voltage vectors are estimated by means of the previous measurements stored into lookup tables. To keep the current variations information up to date, the three current measurements due to the three most recent feeding voltages are combined together to reconstruct all the others. The reconstruction is performed by taking advantage of the relationships between the three different base voltage vectors involved in the process. In particular, 210 possible combinations of three-state voltage vectors can be found, but they can be gathered together in six different groups. A light and computationally fast algorithm for the group identification is proposed in this paper. Finally, the current reconstruction for the prediction of future steps is thoroughly analyzed. A compensation of the motor rotation effect on the input voltages is proposed, too. The control scheme is evaluated by means of both simulation and experimental evidences on two different synchronous reluctance motors

NOVEL METHODS FOR PERMANENT MAGNET DEMAGNETIZATION DETECTION IN PERMANENT MAGNET SYNCHRONOUS MACHINES

Monitoring and detecting PM flux linkage is important to maintain a stable permanent magnet synchronous motor (PMSM) operation. The key problems that need to be solved at this stage are to: 1) establish a demagnetization magnetic flux model that takes into account the influence of various nonlinear and complex factors to reveal the demagnetization mechanism; 2) explore the relationship between different factors and demagnetizing magnetic field, to detect the demagnetization in the early stage; and 3) propose post-demagnetization measures. This thesis investigates permanent magnet (PM) demagnetization detection for PMSM machines to achieve high-performance and reliable machine drive for practical industrial and consumer applications. In this thesis, theoretical analysis, numerical calculation as well as experimental investigations are carried out to systematically study the demagnetization detection mechanism and post-demagnetization measures for permanent magnet synchronous motors. At first a flux based acoustic noise model is proposed to analyze online PM demagnetization detection by using a back propagation neural network (BPNN) with acoustic noise data. In this method, the PM demagnetization is detected by means of comparing the measured acoustic signal of PMSM with an acoustic signal library of seven acoustical indicators. Then torque ripple is chosen for online PM demagnetization diagnosis by using continuous wavelet transforms (CWT) and Grey System Theory (GST). This model is able to reveal the relationship between torque variation and PM electromagnetic interferences. After demagnetization being detected, a current regulation strategy is proposed to minimize the torque ripples induced by PM demagnetization. Next, in order to compare the demagnetization detection accuracy, different data mining techniques, Vold-Kalman filtering order tracking (VKF-OT) and dynamic Bayesian network (DBN) based detection approach is applied to real-time PM flux monitoring through torque ripple again. VKF-OT is introduced to track the order of torque ripple of PMSM running in transient state. Lastly, the combination of acoustic noise and torque is investigated for demagnetization detection by using multi-sensor information fusion to improve the system redundancy and accuracy. Bayesian network based multi-sensor information fusion is then proposed to detect the demagnetization ratio from the extracted features. During the analysis of demagnetization detection methods, the proposed PM detection approaches both form torque ripple and acoustic noise are extensively evaluated on a laboratory PM machine drive system under different speeds, load conditions, and temperatures

Implementation and Analysis of Direct Torque Control for Permanent Magnet Synchronous Motor Using Gallium Nitride based Inverter

Permanent magnet synchronous machines (PMSMs) attract considerable attention in various industrial applications, such as electric and hybrid electric vehicles, due to their high efficiency and high-power density. In this thesis, the mathematical model of PMSM and two popular control strategies, field-oriented control (FOC) and direct torque control (DTC), are analyzed and compared. The results demonstrated that the DTC has better dynamic response in comparison to FOC. Moreover, DTC can eliminate the use of position sensor, which will save the cost of the PMSM drive system. Therefore, this thesis focuses on the design and implementation of high-performance DTC for PMSMs with a Gallium Nitride (GaN) based high switching frequency motor drive. First, the characteristics and operation principles of a PMSM are introduced. Then, the mathematical models of a PMSM under different coordinate systems are investigated. Consequently, a PMSM model is developed based on the dq rotating reference frame and implemented in the MATLAB/Simulink for validation. Two advanced PMSM control strategies, FOC and DTC, are investigated and compared in terms of control performance through comprehensive simulation studies and the results demonstrate that DTC has better dynamic performance. Conventional DTC contributes to higher torque ripple in the PMSM due to the limited switching frequency in a conventional semiconductor-based motor drive, which inevitably deteriorates the drive performance. Therefore, this thesis aims to reduce the torque ripple in the DTC based PMSM drive by using the new generation wide bandgap switching devices. More specifically, DTC is improved by using the optimized space vector pulse width modulation strategy and a higher switching frequency contributed by the GaN based motor drive. Finally, the proposed DTC-SVM based PMSM control strategy is implemented on the digital signal processor (DSP) and evaluated on the laboratory GaN based PMSM drive. Both the simulation and experimental results show that the proposed improvement in the DTC can further improve the PMSM drive performance

Iron Loss Computation in a Synchronous Machine from a Static Field Solution

Owing to the increasing energy demand, a highly efficient synchronous machine can play a crucial role in energy saving by reducing energy consumption. An optimum machine design requires a good estimation of the power losses, particularly the iron loss due to the complexity involved with the accurate loss prediction. The prediction of iron loss in the synchronous machine has drawn massive attraction due to the extensive use in the power stations and other industrial applications. The conventional time-stepping method for iron loss calculation is computationally highly expensive and can be productive as long as the number of computations remains in a respectable range. However, the situation is different when an excessive number of computations are required, such as for machine optimization, which turns this method into unprofitable. The development of fast and computationally efficient static analysis in case of synchronous machine induce a thought of computing the iron loss using this method which can minimize the computation cost and substitute the time consuming traditional loss computation method. Based on this notion, an effective iron loss computation technique was developed from a single static field simulation which is much faster than the conventional time-stepping method and provide a fair accuracy. A two-dimensional Finite Element Method was used, and the model was integrated with the static FEM analysis program in the in-house software FCSMEK. The model was applied to a 12.5 MW salient pole synchronous machine, and the computational accuracy was validated with the conventional time-stepping simulation

Advances in Electrical Machine, Power Electronic, and Drive Condition Monitoring and Fault Detection: State of the Art

© 2015 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] Recently, research concerning electrical machines and drives condition monitoring and fault diagnosis has experienced extraordinarily dynamic activity. The increasing importance of these energy conversion devices and their widespread use in uncountable applications have motivated significant research efforts. This paper presents an analysis of the state of the art in this field. The analyzed contributions were published in most relevant journals and magazines or presented in either specific conferences in the area or more broadly scoped events.Riera-Guasp, M.; Antonino-Daviu, J.; Capolino, G. (2015). Advances in Electrical Machine, Power Electronic, and Drive Condition Monitoring and Fault Detection: State of the Art. IEEE Transactions on Industrial Electronics. 62(3):1746-1759. doi:10.1109/TIE.2014.2375853S1746175962

Sensorless Rotor Position Estimation For Brushless DC Motors

Brushless DC motor speed is controlled by synchronizing the stator coil current with rotor position in order to acquire an accurate alignment of stator rotating field with rotor permanent-magnet field for efficient transfer of energy. In order to accomplish this goal, a motor shaft is instantly tracked by using rotating rotor position sensors such as Hall effect sensors, optical encoders or resolvers etc. Adding sensors to detect rotor position affects the overall reliability and mechanical robustness of the system. Therefore, a whole new trend of replacing position sensors with sensorless rotor position estimation techniques have a promising demand. Among the sensorless approaches, Back-EMF measurement and high frequency signal injection is the most common. Back-EMF is an electromotive force, directly proportional to the speed of rotor revolutions per second, the greater the speed motor acquires the greater the Back-EMF amplitude appears against the motion of rotation. However, the detected Back-EMF is zero at start-up and does not provide motor speed information at this instant. There-fore, Back-EMF based techniques are highly unfavourable for low speed application specially near zero. On the other hand, signal injection techniques are comparatively developed for low or near zero motor speed applications and they also can estimate the on-line motor parameters exploiting the identification theory on phase voltages and currents signals. The signal injection approach requires expensive additional hardware to inject high frequency signal. Since, motors are typically driven with pulse width modulation techniques, high frequency signals are naturally already present which can be used to detect position. This thesis presents rotor position estimation by measuring the voltage and current signals and also proposes an equivalent permanent-magnet synchronous motor model by fitting thedata to a position dependent circuit model

High efficiency sensorless fault tolerant control of permanent magnet assisted synchronous reluctance motor

In the last decades, the development trends of high efficiency and compact electric drives on the motor side focused on Permanent Magnet Synchronous Machines (PMSMs) equipped with magnets based on the rare-earth elements. The permanent magnet components, however, dramatically impact the overall bill of materials of motor construction. This aspect has become even more critical due to the price instability of the rare-earth elements. This is why the Permanent Magnet Assisted Synchronous Reluctance Motor (PMaSynRM) concept was brought to the spotlight as it gives comparable torque density and similar efficiencies as PMSM although at a lower price accredited for the use of magnets built with ferrite composites. Despite these advantages, PMaSynRM drive design is much more challenging because of nonlinear inductances resulting from deep cross saturation effects. It is also true for multi-phase PMSM motors that have gained a lot of attention as they proportionally split power by the increased number of phases. Furthermore, they offer fault-tolerant operation while one or more phases are down due to machine, inverter, or sensor fault. The number of phases further increases the overall complexity for modeling and control design. It is clear then that a combination of multi-phase with PMaSynRM concept brings potential benefits but confronts standard modeling methods and drive development techniques. This Thesis consists of detailed modeling, control design, and implementation of a five-phase PMaSynRM drive for normal healthy and open phase fault-tolerant applications. Special emphasis is put on motor modeling that comprises saturation and space harmonics together with axial asymmetry introduced by rotor skewing. Control strategies focused on high efficiency are developed and the position estimation based on the observer technique is derived. The proposed models are validated through Finite Element Analysis (FEA) and experimental campaign. The results show the effectiveness of the elaborated algorithms and methods that are viable for further industrialization in PMaSynRM drives with fault-tolerant capabilities.En últimas décadas, las tendencias de desarrollo de accionamientos eléctricos compactos y de alta eficiencia en el lado del motor se centraron en las maquinas síncronas de imanes permanentes (PMSM) equipadas con imanes basados en elementos de tierras raras. Sin embargo, los componentes de imán permanente impactan dramáticamente en el coste de construcción del motor. Este aspecto se ha vuelto aún más crítico debido a la inestabilidad de precios de los elementos de tierras raras. Esta es la razón por la que el concepto de motor de reluctancia síncrona asistido por imán permanente (PMaSynRM) se ha tomado en consideración, ya que ofrece una densidad de par comparable y eficiencias similares a las de PMSM, aunque a un precio más bajo acreditado para el uso de imanes construidos con compuestos de ferritas. A pesar de drive PMaSynRM resulta muy complejo debido a las inductancias no lineales que resultan de los efectos de saturación cruzada profunda. Esto también es cierto para los motores PMSM polifásicos que han ganado mucha atención en los últimos años, en los que se divide proporcionalmente la potencia por el mayor número de fases. Además, ofrecen operación tolerante a fallas mientras una o más fases están inactivas debido a fallas en la máquina, el inversor o el sensor. Sin embargo, el número de fases aumenta aún más la complejidad general del diseño de modelado y control. Está claro entonces que una combinación de multifase con el concepto PMaSynRM tiene beneficios potenciales, pero dificulta los métodos de modelado estándar y las técnicas de desarrollo del sistema de accionamiento. Esta tesis consiste en el modelado detallado, el diseño de control y la implementación de un drive PMaSynRM de cinco fases para aplicaciones normales en buen estado y tolerantes a fallas de fase abierta. Se pone especial énfasis en el modelado del motor que comprende la saturación y los armónicos espaciales junto con la asimetría axial introducida por la inclinación del rotor. Se desarrollan estrategias de control enfocadas a la alta eficiencia y se deriva la estimación de posición basada en la técnica del observador. Los modelos propuestos se validan mediante Análisis de Elementos Finitos (FEA) y resultados experimentales. Los resultados muestran la efectividad de los algoritmos y métodos elaborados, que resultan viables para la industrialización de unidades PMaSynRM con capacidades tolerantes a fallas.Postprint (published version

Advances in Rotating Electric Machines

It is difficult to imagine a modern society without rotating electric machines. Their use has been increasing not only in the traditional fields of application but also in more contemporary fields, including renewable energy conversion systems, electric aircraft, aerospace, electric vehicles, unmanned propulsion systems, robotics, etc. This has contributed to advances in the materials, design methodologies, modeling tools, and manufacturing processes of current electric machines, which are characterized by high compactness, low weight, high power density, high torque density, and high reliability. On the other hand, the growing use of electric machines and drives in more critical applications has pushed forward the research in the area of condition monitoring and fault tolerance, leading to the development of more reliable diagnostic techniques and more fault-tolerant machines. This book presents and disseminates the most recent advances related to the theory, design, modeling, application, control, and condition monitoring of all types of rotating electric machines