Design and Control of Electrical Motor Drives

Dear Colleagues, I am very happy to have this Special Issue of the journal Energies on the topic of Design and Control of Electrical Motor Drives published. Electrical motor drives are widely used in the industry, automation, transportation, and home appliances. Indeed, rolling mills, machine tools, high-speed trains, subway systems, elevators, electric vehicles, air conditioners, all depend on electrical motor drives.However, the production of effective and practical motors and drives requires flexibility in the regulation of current, torque, flux, acceleration, position, and speed. Without proper modeling, drive, and control, these motor drive systems cannot function effectively.To address these issues, we need to focus on the design, modeling, drive, and control of different types of motors, such as induction motors, permanent magnet synchronous motors, brushless DC motors, DC motors, synchronous reluctance motors, switched reluctance motors, flux-switching motors, linear motors, and step motors.Therefore, relevant research topics in this field of study include modeling electrical motor drives, both in transient and in steady-state, and designing control methods based on novel control strategies (e.g., PI controllers, fuzzy logic controllers, neural network controllers, predictive controllers, adaptive controllers, nonlinear controllers, etc.), with particular attention to transient responses, load disturbances, fault tolerance, and multi-motor drive techniques. This Special Issue include original contributions regarding recent developments and ideas in motor design, motor drive, and motor control. The topics include motor design, field-oriented control, torque control, reliability improvement, advanced controllers for motor drive systems, DSP-based sensorless motor drive systems, high-performance motor drive systems, high-efficiency motor drive systems, and practical applications of motor drive systems. I want to sincerely thank authors, reviewers, and staff members for their time and efforts. Prof. Dr. Tian-Hua Liu Guest Edito

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

Torque Control

This book is the result of inspirations and contributions from many researchers, a collection of 9 works, which are, in majority, focalised around the Direct Torque Control and may be comprised of three sections: different techniques for the control of asynchronous motors and double feed or double star induction machines, oriented approach of recent developments relating to the control of the Permanent Magnet Synchronous Motors, and special controller design and torque control of switched reluctance machine

Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine

Optimal performance of the electric machine/drive system is mandatory to improve the energy consumption and reliability. To achieve this goal, mathematical models of the electric machine/drive system are necessary. Hence, this motivated the editors to instigate the Special Issue “Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine”, aiming to collect novel publications that push the state-of-the art towards optimal performance for the electric machine/drive system. Seventeen papers have been published in this Special Issue. The published papers focus on several aspects of the electric machine/drive system with respect to the mathematical modelling. Novel optimization methods, control approaches, and comparative analysis for electric drive system based on various electric machines were discussed in the published papers

Modelling and Detecting Faults of Permanent Magnet Synchronous Motors in Dynamic Operations

Paper VI is excluded from the dissertation until the article will be published.Permanent magnet synchronous motors (PMSMs) have played a key role in commercial and industrial applications, i.e. electric vehicles and wind turbines. They are popular due to their high efficiency, control simplification and large torque-to-size ratio although they are expensive. A fault will eventually occur in an operating PMSM, either by improper maintenance or wear from thermal and mechanical stresses. The most frequent PMSM faults are bearing faults, short-circuit and eccentricity. PMSM may also suffer from demagnetisation, which is unique in permanent magnet machines. Condition monitoring or fault diagnosis schemes are necessary for detecting and identifying these faults early in their incipient state, e.g. partial demagnetisation and inter-turn short circuit. Successful fault classification will ensure safe operations, speed up the maintenance process and decrease unexpected downtime and cost. The research in recent years is drawn towards fault analysis under dynamic operating conditions, i.e. variable load and speed. Most of these techniques have focused on the use of voltage, current and torque, while magnetic flux density in the air-gap or the proximity of the motor has not yet been fully capitalised. This dissertation focuses on two main research topics in modelling and diagnosis of faulty PMSM in dynamic operations. The first problem is to decrease the computational burden of modelling and analysis techniques. The first contributions are new and faster methods for computing the permeance network model and quadratic time-frequency distributions. Reducing their computational burden makes them more attractive in analysis or fault diagnosis. The second contribution is to expand the model description of a simpler model. This can be achieved through a field reconstruction model with a magnet library and a description of both magnet defects and inter-turn short circuits. The second research topic is to simplify the installation and complexity of fault diagnosis schemes in PMSM. The aim is to reduce required sensors of fault diagnosis schemes, regardless of operation profiles. Conventional methods often rely on either steady-state or predefined operation profiles, e.g. start-up. A fault diagnosis scheme robust to any speed changes is desirable since a fault can be detected regardless of operations. The final contribution is the implementation of reinforcement learning in an active learning scheme to address the imbalance dataset problem. Samples from a faulty PMSM are often initially unavailable and expensive to acquire. Reinforcement learning with a weighted reward function might balance the dataset to enhance the trained fault classifier’s performance.publishedVersio

Sensorless Passive Control Algorithms for Medium to High Power Synchronous Motor Drives

This study is focused on the definition of sensorless algorithms for Surface-Mounted Permanent Magnet Synchronous Motors (SM-PMSM) and Electrically Excited Synchronous Motors (EESM). Even if these types of motors are rather different from a constructive point of view, they have some common issues regarding sensorless drives. Indeed, SM-PMSMs, which are usually used for low-medium power applications, have a low rotor anisotropy, therefore it is complicated to use sensorless active methods (which are based on high-frequency voltage injection), due to the low signal to noise ratio. On the other hand, active methods on high-power EESM have the drawback of high torque ripple. For these reasons, both for SM-PMSM and EESM, it is interesting to define and use sensorless passive algorithms (i.e., based on observers and estimators). The drawback of such algorithms is that their performance deteriorates significantly in the low-speed region. The aim of this thesis is to define a robust sensorless passive algorithm that could work in a wide speed region and that could start the motor from standstill even with a high load torque. The initial objective of the work is to find, among the various algorithms proposed in the technical literature, the most promising one. For this purpose, four different algorithms are selected. They are chosen considering the most recent articles presented in the technical literature on high reputable journals. Since many improvements are proposed in the literature for the different algorithms, the most recent ones are candidates for being the ones with higher performance. Even if the experimental tests of the four different algorithms are shown in the literature, it is difficult to evaluate a priori which offers the best performance. As a matter of facts, for each algorithm different tests are carried out (e.g., different speed and torque profiles). In addition to that, motor sizing and features are different. Moreover, the test bench characteristics can significantly affect sensorless performance. As an example, inverter features and non-linearities (e.g., switching frequency, dead times, parasitic capacitance) and current measures (e.g., noise, linearity, bias) play a key role in the estimation of rotor position. The added value of this thesis is to perform a fair comparison of the four algorithms, performing the same tests with the same test bench. Additional tests are performed on the most performing algorithm. Even if this sensorless technique is already proposed in the technical literature, a methodology for observer gain tuning is not shown, which is proposed, instead, in this thesis. Moreover, the algorithm is enhanced by adding a novel management of direct axis current, which ensures the stability during fast transient from medium-high speed to low speed. The algorithm is tested with different test benches in order to verify the control effectiveness in various operating conditions. As a matter of facts, it is tested at first in the University of Genoa PETRA Lab on two different test benches. The first test bench is composed of two coupled motors, in which the braking motor could realize different torque profiles (linear torque, quadratic torque and constant torque), whereas in the second test bench the motor is coupled with an air compressor, which is a demanding load since high and irregular torque is applied at standstill. After the test at the University of Genoa, the algorithm is implemented in Phase Motion Control and Physis drive and tested on a six-meter diameter fan. Regarding the EESMs, for these type of motor is necessary to estimate the stator flux amplitude and angle. Indeed, the stator angle is usually used to perform the Park transformations in the FOC scheme and the stator flux amplitude is used to control the excitation current. In this study, the RFO is adapted for estimating the stator flux of an EESM. Regarding the control for EESM, it is tested on a simulative model for high-power motors provided by NIDEC ASI and tested on a small-scale test bench at the University of Genoa

Current commutation and control of brushless direct current drives using back electromotive force samples

Brushless DC machines (BLDC) are widely used in home, automotive, aerospace and military applications. The reason of this interest in different industries in this type of machine is due to their significant advantages. Brushless DC machines have a high power density, simple construction and higher efficiency compared to conventional AC and DC machines and lower cost comparing to permanent magnet AC synchronous machines. The phase currents of a BLDC machine have to commutate properly which is realised by using power semiconductors. For a proper commutation the rotor position is often obtained by an auxiliary instrument, mostly an arrangement of three Hall-effect sensors with 120 spatial displacement. In modern and cost-effective BLDC drives the focus is on replacing the noise sensitive and less reliable mechanical sensors by numerical algorithms, often referred to as sensorless or self-sensing methods. The advantage of these methods is the use of current or voltage measurements which are usually available as these are required for the control of the drive or the protection of the semiconductor switches. Avoiding the mechanical position sensor yields remarkable savings in production, installation and maintenance costs. It also implies a higher power to volume ratio and improves the reliability of the drive system. Different self-sensing techniques have been developed for BLDC machines. Two algorithms are proposed in this thesis for self-sensing commutation of BLDC machines using the back-EMF samples of the BLDC machine. Simulations and experimental tests as well as mathematical analysis verify the improved performance of the proposed techniques compared to the conventional back-EMF based self-sensing commutation techniques. For a robust BLDC drive control algorithm with a wide variety of applications, load torque is as a disturbance within the control-loop. Coupling the load to the motor shaft may cause variations of the inertia and viscous friction coefficient besides the load variation. Even for a drive with known load torque characteristics there are always some unmodelled components that can affect the performance of the drive system. In self-sensing controlled drives, these disturbances are more critical due to the limitations of the self-sensing algorithms compared to drives equipped with position sensors. To compensate or reject torque disturbances, control algorithms need the information of those disturbances. Direct measurement of the load torque on the machine shaft would require another expensive and sensitive mechanical sensor to the drive system as well as introducing all of the sensor related problems to the drive. An estimation algorithm can be a good alternative. The estimated load torque information is introduced to the self-sensing BLDC drive control loop to increase the disturbance rejection properties of the speed controller. This technique is verified by running different experimental tests within different operation conditions. The electromagnetic torque in an electrical machine is determined by the stator current. When considering the dynamical behaviour, the response time of this torque on a stator voltage variation depends on the electric time constant, while the time response of the mechanical system depends on the mechanical time constant. In most cases, the time delays in the electric subsystem are negligible compared to the response time of the mechanical subsystem. For such a system a cascaded PI speed and current control loop is sufficient to have a high performance control. However, for a low inertia machine when the electrical and mechanical time constants are close to each other the cascaded control strategies fail to provide a high performance in the dynamic behavior. When two cascade controllers are used changes in the speed set-point should be applied slowly in order to avoid stability problems. To solve this, a model based predictive control algorithm is proposed in this thesis which is able to control the speed of a low inertia brushless DC machine with a high bandwidth and good disturbance rejection properties. The performance of the proposed algorithm is evaluated by simulation and verified by experimental results as well. Additionally, the improvement on the disturbance rejection properties of the proposed algorithm during the load torque variations is studied. In chapters 1 and 2 the basic operation principles of the BLDC machine drives will be introduced. A short introduction is also given about the state of the art in control of BLDC drives and self-sensing control techniques. In chapter 3, a model for BLDC machines is derived, which allows to test control algorithms and estimators using simulations. A further use of the model is in Model Based Predictive Control (MBPC) of BLDC machines where a discretised model of the BLDC machine is implemented on a computation platform such as Field Programmable Gate Arrays (FPGA) in order to predict the future states of the machine. Chapter 4 covers the theory behind the proposed self-sensing commutation methods where new methodologies to estimate the rotor speed and position from back-EMF measurements are explained. The results of the simulation and experimental tests verifies the performance of the proposed position and speed estimators. It will also be proved that using the proposed techniques improve the detection accuracy of the commutation instants. In chapter 5, the focus is on the estimation of load torque, in order to use it to improve the dynamic performance of the self-sensing BLDC machine drives. The load torque information is used within the control loop to improve the disturbance rejection properties of the speed control for the disturbances resulting from the applied load torque of the machine. Some of the machine parameters are used within speed and load torque estimators such as back-EMF constant Ke and rotor inertia J. The accuracy with which machine parameters are known is limited. Some of the machine parameters can change during operation. Therefore, the influence of parameter errors on the position, speed and load torque is examined in chapter 5. In Chapter 6 the fundamentals of Model based Predictive Control for a BLDC drive is explained, which are then applied to a BLDC drive to control the rotor speed. As the MPC algorithm is computationally demanding, some enhancements on the FPGA program is also introduced in order to reduce the required resources within the FPGA implementation. To keep the current bounded and a high speed response a specific cost function is designed to meet the requirements. later on, the proposed MPC method is combined with the proposed self-sensing algorithm and the advantages of the combined algorithms is also investigated. The effects of the MPC parameters on the speed and current control performance is also examined by simulations and experiments. Finally, in chapter 7 the main results of the research is summarized . In addition, the original contributions that is give by this work in the area of self-sensing control is highlighted. It is also shown how the presented work could be continued and expanded

Super High-speed Miniaturized Permanent Magnet Synchronous Motor

This dissertation is concerned with the design of permanent magnet synchronous motors (PMSM) to operate at super-high speed with high efficiency. The designed and fabricated PMSM was successfully tested to run upto 210,000 rpm The designed PMSM has 2000 W shaft output power at 200,000 rpm and at the cryogenic temperature of 77 K. The test results showed the motor to have an efficiency reaching above 92%. This achieved efficiency indicated a significant improvement compared to commercial motors with similar ratings. This dissertation first discusses the basic concept of electrical machines. After that, the modeling of PMSM for dynamic simulation is provided. Particular design strategies have to be adopted for super-high speed applications since motor losses assume a key role in the motor drive performance limit. The considerations of the PMSM structure for cryogenic applications are also discussed. It is shown that slotless structure with multi-strand Litz-wire is favorable for super-high speeds and cryogenic applications. The design, simulation, and test of a single-sided axial flux pancake PMSM is presented. The advantages and disadvantages of this kind of structure are discussed, and further improvements are suggested and some have been verified by experiments. The methodologies of designing super high-speed motors are provided in details. Based on these methodologies, a super high-speed radial-flux PMSM was designed and fabricated. The designed PMSM meets our expectation and the tested results agree with the design specifications. 2-D and 3-D modeling of the complicated PMSM structure for the electromagnetic numerical simulations of motor performance and parameters such as phase inductors, core losses, rotor eddy current loss, torque, and induced electromotive force (back-EMF) are also presented in detail in this dissertation. Some mechanical issues such as thermal analysis, bearing pre-load, rotor stress analysis, and rotor dynamics analysis are also discussed. Different control schemes are presented and suitable control schemes for super high- speed PMSM are also discussed in detail

Design optimization and performance analysis methodology for PMSMs to improve efficiency in hydraulic applications

Pla de Doctorats Industrials de la Generalitat de CatalunyaIn the recent years, water pumping and other hydraulic applications are increasingly demanding motors capable to operate under different working conditions, including variable pressure and volumetric flow demands. Moreover, the technical evolution trend of pumping components is to minimize the size, offering compact and adaptable hydraulic units. Hence, the need to optimize the electric motor part to reduce the volume according this trend, maximizing the efficiency, decreasing material and fabrication costs, reducing noise and improving thermal dissipation have originated the research field of this project. So far different methodologies have been focused on designing electrical machines considering few aspects, such as the rated conditions with some size limitations. In addition, the optimization strategies have been based on single operation conditions, improving multiple aspects but not considering the overall performance of the machine and its influence with the working system. This research changes the design and optimization paradigm, focusing on defining beforehand the desired performance of the electrical machine in relation with the application system. The customization is not limited to an operating point but to the whole performance space, which in this case is the torque-speed area. Thus, the designer has plenty of freedom to study the system, and define the desired motor performance establishing the size, thermal and mechanical limitations from the beginning of the process. Moreover, when designing and optimizing electrical machines, the experimental validation is of major importance. From an industrial scope so far, the testing methodologies are focused on evaluating point by point the electrical machine performance, being a robust and trustable way to measure and validate the electrical machine characteristics. Nevertheless,this method requires a large time to prepare the experimental setup and to evaluate the whole motor performance. For this reason, there is a special interest on improving parameter estimation and performance evaluation techniques for electrical machines to reduce evaluation time, setup complexity and increase the number of physical magnitudes to measure in order to have deeper information. This research also develops methodologies to extend the electrical machine experimental validation providing information to evaluate the motor performance. This doctoral thesis has been developed with a collaboration agreement between UPC and the company MIDTAL TALENTOS S.L. The thesis is included within the Industrial Doctorates program 2018 DI 019 promoted by the Generalitat de Catalunya.En los últimos años, el bombeo de agua, entre otras aplicaciones hidráulicas, exige cada vez más motores capaces de operar en diferentes condiciones de trabajo, incluyendo las demandas variables de presión y caudal volumétrico. Además, la evolución técnica de los componentes de bombeo está cada vez más minimizando el tamaño ofreciendo unidades hidráulicas compactas y adaptables. De ahí la necesidad de optimizar la parte del motor eléctrico para reducir el volumen de acuerdo con esta tendencia, maximizando la eficiencia, disminuyendo los costos de material y fabricación, reduciendo el ruido y mejorando la disipación térmica. Todos estos factores han creado el campo de investigación sobre el cual se desarrolla este proyecto. Hasta ahora las metodologías se han centrado en diseñar las máquinas eléctricas considerando unos pocos aspectos técnicos, como las condiciones nominales con algunas limitaciones de tamaño. Además, las estrategias de optimización se han basado en condiciones de operación única, mejorando múltiples aspectos sin considerar el rendimiento general de la máquina y su influencia en el sistema de trabajo. Esta investigación cambia el paradigma de diseño y optimización centrándose en definir de antemano el rendimiento deseado de la máquina eléctrica en relación con el sistema de aplicación. La personalización no se limita a un punto de funcionamiento sino a todo el espacio de operación, que en este caso se expresa en el espacio par-velocidad. Así, el diseñador tiene libertad para estudiar el sistema, definir el rendimiento deseado del motor estableciendo el tamaño, limitaciones térmicas y mecánicas desde el inicio del proceso. Además, a la hora de diseñar y optimizar máquinas eléctricas, la validación experimental es de gran importancia. En el ámbito industrial hasta ahora, las metodologías de ensayo han sido enfocadas a evaluar punto por punto la máquina eléctrica, siendo una forma robusta y confiable de medir y validar sus características. Sin embargo, este método requiere mucho tiempo para preparar la configuración experimental y evaluar el motor en toda su zona de operación. Por esta razón, existe un interés especial en mejorar la estimación de parámetros y las técnicas de evaluación de la operación de las máquinas eléctricas reduciendo tiempo, complejidad y aumentando el número de magnitudes físicas a medir teniendo más información sobre la máquina. Esta investigación también desarrolla metodologías para extender la validación experimental de la máquina eléctrica proporcionando información para evaluar el rendimiento del motor. Esta tesis doctoral ha sido desarrollada con un convenio de colaboración entre la Universidad Politécnica de Cataluña UPC y la empresa MIDTAL TALENTOS S.L. La tesis se engloba dentro del plan de Doctorados Industriales 2018 DI 019 impulsado por la Generalitat de Catalunya.Postprint (published version