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

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

Critical Aspects of Electric Motor Drive Controllers and Mitigation of Torque Ripple - Review

Electric vehicles (EVs) are playing a vital role in sustainable transportation. It is estimated that by 2030, Battery EVs will become mainstream for passenger car transportation. Even though EVs are gaining interest in sustainable transportation, the future of EV power transmission is facing vital concerns and open research challenges. Considering the case of torque ripple mitigation and improved reliability control techniques in motors, many motor drive control algorithms fail to provide efficient control. To efficiently address this issue, control techniques such as Field Orientation Control (FOC), Direct Torque Control (DTC), Model Predictive Control (MPC), Sliding Mode Control (SMC), and Intelligent Control (IC) techniques are used in the motor drive control algorithms. This literature survey exclusively compares the various advanced control techniques for conventionally used EV motors such as Permanent Magnet Synchronous Motor (PMSM), Brushless Direct Current Motor (BLDC), Switched Reluctance Motor (SRM), and Induction Motors (IM). Furthermore, this paper discusses the EV-motors history, types of EVmotors, EV-motor drives powertrain mathematical modelling, and design procedure of EV-motors. The hardware results have also been compared with different control techniques for BLDC and SRM hub motors. Future direction towards the design of EV by critical selection of motors and their control techniques to minimize the torque ripple and other research opportunities to enhance the performance of EVs are also presented.publishedVersio

Field weakening and sensorless control solutions for synchronous machines applied to electric vehicles.

184 p.La polución es uno de los mayores problemas en los países industrializados. Por ello, la electrificación del transporte por carretera está en pleno auge, favoreciendo la investigación y el desarrollo industrial. El desarrollo de sistemas de propulsión eficientes, fiables, compactos y económicos juega un papel fundamental para la introducción del vehículo eléctrico en el mercado.Las máquinas síncronas de imanes permanentes son, a día de hoy la tecnología más empleada en vehículos eléctricos e híbridos por sus características. Sin embargo, al depender del uso de tierras raras, se están investigando alternativas a este tipo de máquina, tales como las máquinas de reluctancia síncrona asistidas por imanes. Para este tipo de máquinas síncronas es necesario desarrollar estrategias de control eficientes y robustas. Las desviaciones de parámetros son comunes en estas máquinas debido a la saturación magnética y a otra serie de factores, tales como tolerancias de fabricación, dependencias en función de la temperatura de operación o envejecimiento. Las técnicas de control convencionales, especialmente las estrategias de debilitamiento de campo dependen, en general, del conocimiento previo de dichos parámetros. Si no son lo suficientemente robustos, pueden producir problemas de control en las regiones de debilitamiento de campo y debilitamiento de campo profundo. En este sentido, esta tesis presenta dos nuevas estrategias de control de debilitamiento de campo híbridas basadas en LUTs y reguladores VCT.Por otro lado, otro requisito indispensable para la industria de la automoción es la detección de faltas y la tolerancia a fallos. En este sentido, se presenta una nueva estrategia de control sensorless basada en una estructura PLL/HFI híbrida que permite al vehículo continuar operando de forma pseudo-óptima ante roturas en el sensor de posición y velocidad de la máquina eléctrica. En esta tesis, ambas propuestas se validan experimentalmente en un sistema de propulsión real para vehículo eléctrico que cuenta con una máquina de reluctancia síncrona asistidas por imanes de 51 kW

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

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

Sensorless position estimation in fault-tolerant permanent magnet AC motor drives with redundancy.

Safety critical applications are heavily dependent on fault-tolerant motor drives being capable of continuing to operate satisfactorily under faults. This research utilizes a fault-tolerant PMAC motor drive with redundancy involving dual drives to provide parallel redundancy where each drive has electrically, magnetically, thermally and physically independent phases to improve its fault-tolerant capabilities. PMAC motor drives can offer high power and torque densities which are essential in high performance applications, for example, more-electric airplanes. In this thesis, two sensorless algorithms are proposed to estimate the rotor position in a fault-tolerant three-phase surface-mounted sinusoidal PMAC motor drive with redundancy under normal and faulted operating conditions. The key aims are to improve the reliability by eliminating the use of a position sensor which is one of major sources of failures, as well as by offering fault-tolerant position estimation. The algorithms utilize measurements of the winding currents and phase voltages, to compute flux linkage increments without integration, hence producing the predicted position values. Estimation errors due measurements are compensated for by a modified phase-locked loop technique which forces the predicted positions to track the flux linkage increments, finally generating the rotor position estimate. The fault-tolerant three-phase sensorless position estimation method utilizes the measured data from the three phase windings in each drive, consequently obtaining a total of two position estimates. However, the fault-tolerant two-phase sensorless position estimation method uses measurements from pairs of phases and produces three position estimates for each drive. Therefore, six position estimates are available in the dual drive system. In normal operation, all of these position estimates can be averaged to achieve a final rotor angle estimate in both schemes. Under faulted operating conditions, on the other hand, a final position estimate should be achieved by averaging position estimates obtained with measurements from healthy phases since unacceptable estimation errors can be created by making use of measured values from phases with failures. In order to validate the effectiveness of the proposed fault-tolerant sensorless position estimation schemes, the algorithms were tested using both simulated data and offline measured data from an experimental fault-tolerant PMAC motor drive system. In the healthy condition, both techniques presented good performance with acceptable accuracies under low and high steady-state speeds, starting from standstill and step load changes. In addition, they had robustness against parameter variations and measurement errors, as well as the ability to recover quickly from large incorrect initial position information. Under faulted operating conditions such as sensor failures, however, the two-phase sensorless method was more reliable than the threephase sensorless method since it could operate even with a faulty phase.Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 201

Electric Machine Control for Energy Efficient Electric Drive Systems

Over the past decade, electric vehicles has increasingly become an area of attention for both academia and industry, much due to challenges such as emissions legislation and the environmental impact of the transportation sector. The absence of the broadband noise from the internal combustion engine brings new acoustic challenges for electric propulsion applications. Magnetic noise from electrical machines is of particular interest in automotive applications. It is not only related to the geometrical design of the machine, but also to the selection of control approach and voltage modulation strategy. This thesis focuses primarily on software-based electric drive system energy efficiency enhancements, supported by extensive experimental testing, incorporating aspects of dynamic performance and acoustic perspectives. The scientific contribution can be summarized in three parts. Firstly, the interdisciplinary research where efficiency enhancements are coupled to acoustic performance. Secondly, the cause and effect of electromagnetic forces as the link between machine design, controls, and perceived acoustic annoyance. Lastly, the findings from the research on optimization-based inverter control and motion sensorless operation. It is proven that alternative modulation techniques can reduce the inverter losses with up to 15 % without degradation of the perceived acoustic annoyance. Moreover, research on finite control set model predictive current control and moving horizon rotor position estimation is presented. It is shown that the proposed solutions are feasible, and that the associated optimization problems at hand can be solved in real-time while exploiting their respective attractive properties. Furthermore, excellent performance is obtained in comparison to state of the art alternatives, at the expense of increased computational complexity

Control solutions for multiphase permanent magnet synchronous machine drives applied to electric vehicles

207 p.En esta tesis se estudia la utilización de un accionamiento eléctrico basado en una máquina simétrica dual trifásica aplicada al sistema de propulsión de un vehículo eléctrico. Dicho accionamiento está basado en una máquina síncrona de imanes permanentes interiores. Además, dispone de un bus CC con una configuración en cascada. Por otra parte, se incorpora un convertidor CC/CC entre el módulo de baterías y el inversor de seis fases para proveer el vehículo con capacidades de carga rápida, y evitando al mismo tiempo la utilización de semiconductores de potencia con altas tensiones nominales. En este escenario, el algoritmo de control debe hacer frente a las no linealidades de la máquina, proporcionando un comando de consigna preciso para todo el rango de par y velocidad del convertidor. Por lo tanto, deben tenerse en cuenta los efectos de acoplamiento cruzado entre los devanados, y la tensión de los condensadores de enlace en cascada debe controlarse y equilibrarse activamente. En vista de ello, los autores proponen un novedoso enfoque de control que proporciona todas estas funcionalidades. La propuesta se ha validado experimentalmente en un prototipo a escala real de accionamiento eléctrico de 70 kW, probado en un laboratorio y en un vehículo eléctrico en condiciones reales de conducción.Tecnali

Control of a fractional-slot, concentrated-wound interior permanent magnet generator for direct-drive wind generation applications

This thesis assesses improvements to two types of control for a novel interior permanent magnet (PM) synchronous generator with fractional-slot, concentrated-wound stator designed for direct-drive wind energy conversion. The two control techniques assessed are a) field oriented control using a back-to-back converter arrangement and b) a current controller with a rectifier-connected boost converter. These were chosen to understand the potential and the limitations of the generator and its control. Modifications to the control techniques are proposed to improve the generator efficiency, the dynamic performance in the flux-weakening range and the torque ripple performance. The adequacy of the distributed-wound PM synchronous machine model for steady-state and dynamic control of this generator was experimentally validated under field oriented control using a back-to-back converter connected to the grid. The effectiveness of the existing current trajectory controls on the efficiency of the new generator was evaluated. A new flux-prioritized maximum torque per ampere technique which is independent of speed-dependent predefined trajectories was introduced, and a similar efficiency improvement was gained as the conventional loss minimization method in the partial load range. Thus, the control model validation and efficiency imrpovement of the new generator are the primary contributions. The dynamic performance of the generator, directly driven by a non-pitchable wind turbine emulator was investigated from cut-in speed to cut-out speed using maximum power point tracking and then constant power control above rated speed. A significant contribution was done in the power control above base wind speed that was achieved by utilizing the extended flux-weakening capability of the machine with its wide constant power-speed range. High torque ripple was observed when operated with a rectifier and boost converter using boost converter inductor current control. A new direct torque control technique using a machine rotor position based torque estimator was proposed to minimize this torque ripple. Eventhough the reduced torque ripple is still higher than that with back-to-back converter, the achieved ripple reduction is significant. The control of generator speed under each method is also demonstrated. Although the new method gives a faster speed dynamics than the conventional method, it shows slower speed response than that of back-to-back converter control. However, the significance of the study using a diode rectifier-connected boost converter control is highlighted with the achieved torque ripple minimization and performance enhancement of the generator. This study is expected to open new investigations in flux-weakening control of the PM generators using rectifier-connected boost converter. In this thesis, back to back converter control is demonstrated in order to optimally control the novel generator under the field oriented control, energy efficient current control and power control together with voltage control operating above rated speed. Torque ripple minimization of the generator is also presented when used with a diode rectifier-connected boost converter control