Machine Learning based Early Fault Diagnosis of Induction Motor for Electric Vehicle Application

Electrified vehicular industry is growing at a rapid pace with a global increase in production of electric vehicles (EVs) along with several new automotive cars companies coming to compete with the big car industries. The technology of EV has evolved rapidly in the last decade. But still the looming fear of low driving range, inability to charge rapidly like filling up gasoline for a conventional gas car, and lack of enough EV charging stations are just a few of the concerns. With the onset of self-driving cars, and its popularity in integrating them into electric vehicles leads to increase in safety both for the passengers inside the vehicle as well as the people outside. Since electric vehicles have not been widely used over an extended period of time to evaluate the failure rate of the powertrain of the EV, a general but definite understanding of motor failures can be developed from the usage of motors in industrial application. Since traction motors are more power dense as compared to industrial motors, the possibilities of a small failure aggravating to catastrophic issue is high. Understanding the challenges faced in EV due to stator fault in motor, with major focus on induction motor stator winding fault, this dissertation presents the following: 1. Different Motor Failures, Causes and Diagnostic Methods Used, With More Importance to Artificial Intelligence Based Motor Fault Diagnosis. 2. Understanding of Incipient Stator Winding Fault of IM and Feature Selection for Fault Diagnosis 3. Model Based Temperature Feature Prediction under Incipient Fault Condition 4. Design of Harmonics Analysis Block for Flux Feature Prediction 5. Flux Feature based On-line Harmonic Compensation for Fault-tolerant Control 6. Intelligent Flux Feature Predictive Control for Fault-Tolerant Control 7. Introduction to Machine Learning and its Application for Flux Reference Prediction 8. Dual Memorization and Generalization Machine Learning based Stator Fault Diagnosi

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

Power quality improvement utilizing photovoltaic generation connected to a weak grid

Microgrid research and development in the past decades have been one of the most popular topics. Similarly, the photovoltaic generation has been surging among renewable generation in the past few years, thanks to the availability, affordability, technology maturity of the PV panels and the PV inverter in the general market. Unfortunately, quite often, the PV installations are connected to weak grids and may have been considered as the culprit of poor power quality affecting other loads in particular sensitive loads connected to the same point of common coupling (PCC). This paper is intended to demystify the renewable generation, and turns the negative perception into positive revelation of the superiority of PV generation to the power quality improvement in a microgrid system. The main objective of this work is to develop a control method for the PV inverter so that the power quality at the PCC will be improved under various disturbances. The method is to control the reactive current based on utilizing the grid current to counteract the negative impact of the disturbances. The proposed control method is verified in PSIM platform. Promising results have been obtaine

Sensors Fault Diagnosis Trends and Applications

Fault diagnosis has always been a concern for industry. In general, diagnosis in complex systems requires the acquisition of information from sensors and the processing and extracting of required features for the classification or identification of faults. Therefore, fault diagnosis of sensors is clearly important as faulty information from a sensor may lead to misleading conclusions about the whole system. As engineering systems grow in size and complexity, it becomes more and more important to diagnose faulty behavior before it can lead to total failure. In the light of above issues, this book is dedicated to trends and applications in modern-sensor fault diagnosis

Advanced Mathematics and Computational Applications in Control Systems Engineering

Control system engineering is a multidisciplinary discipline that applies automatic control theory to design systems with desired behaviors in control environments. Automatic control theory has played a vital role in the advancement of engineering and science. It has become an essential and integral part of modern industrial and manufacturing processes. Today, the requirements for control precision have increased, and real systems have become more complex. In control engineering and all other engineering disciplines, the impact of advanced mathematical and computational methods is rapidly increasing. Advanced mathematical methods are needed because real-world control systems need to comply with several conditions related to product quality and safety constraints that have to be taken into account in the problem formulation. Conversely, the increment in mathematical complexity has an impact on the computational aspects related to numerical simulation and practical implementation of the algorithms, where a balance must also be maintained between implementation costs and the performance of the control system. This book is a comprehensive set of articles reflecting recent advances in developing and applying advanced mathematics and computational applications in control system engineering

Real-Time Fault Diagnosis of Permanent Magnet Synchronous Motor and Drive System

Permanent Magnet Synchronous Motors (PMSMs) have gained massive popularity in industrial applications such as electric vehicles, robotic systems, and offshore industries due to their merits of efficiency, power density, and controllability. PMSMs working in such applications are constantly exposed to electrical, thermal, and mechanical stresses, resulting in different faults such as electrical, mechanical, and magnetic faults. These faults may lead to efficiency reduction, excessive heat, and even catastrophic system breakdown if not diagnosed in time. Therefore, developing methods for real-time condition monitoring and detection of faults at early stages can substantially lower maintenance costs, downtime of the system, and productivity loss. In this dissertation, condition monitoring and detection of the three most common faults in PMSMs and drive systems, namely inter-turn short circuit, demagnetization, and sensor faults are studied. First, modeling and detection of inter-turn short circuit fault is investigated by proposing one FEM-based model, and one analytical model. In these two models, efforts are made to extract either fault indicators or adjustments for being used in combination with more complex detection methods. Subsequently, a systematic fault diagnosis of PMSM and drive system containing multiple faults based on structural analysis is presented. After implementing structural analysis and obtaining the redundant part of the PMSM and drive system, several sequential residuals are designed and implemented based on the fault terms that appear in each of the redundant sets to detect and isolate the studied faults which are applied at different time intervals. Finally, real-time detection of faults in PMSMs and drive systems by using a powerful statistical signal-processing detector such as generalized likelihood ratio test is investigated. By using generalized likelihood ratio test, a threshold was obtained based on choosing the probability of a false alarm and the probability of detection for each detector based on which decision was made to indicate the presence of the studied faults. To improve the detection and recovery delay time, a recursive cumulative GLRT with an adaptive threshold algorithm is implemented. As a result, a more processed fault indicator is achieved by this recursive algorithm that is compared to an arbitrary threshold, and a decision is made in real-time performance. The experimental results show that the statistical detector is able to efficiently detect all the unexpected faults in the presence of unknown noise and without experiencing any false alarm, proving the effectiveness of this diagnostic approach.publishedVersio

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

High performance disturbance observer based control system design for permanent magnet synchronous AC machine applications

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonAn electrical machine is one of the main workforces in different industries and serves them in various applications. Machine drive control design involves many technical issues for efficient and robust exploitation. Over several decades, Permanent Magnet Synchronous Motor (PMSM) is getting preferred for industrial applications over its counterpart Squirrel Cage Induction Motor (SCIM) drive, because of their higher efficiency, power density, and higher torque to inertia ratio. In the prospective that PMSM drives are considered the drives of the future, there are still technical challenges and issues related to PMSM control. Many studies have been devoted to PMSM control in the past, but there are still some open research areas that bring worldwide researchers’ interests back to PMSM drive control. One of the approaches that may facilitate better performance, higher efficiency, and robust and reliable work of the control system is the disturbance observer-based control (DOBC) with linear and nonlinear output feedback control for PM synchronous machine applications. DOBC is adopted due to its ability to reject external and internal disturbances with improving tracking performance in the variable speed wind energy conversion system (WECS) to maximize power extraction. The high order disturbance observer (HODO) is utilized to estimate the aerodynamic torque-based wind speed without the use of a traditional anemometer, which reduces the overall cost and improves the reliability of the whole system. Also, this method has been designed to improve the angular shaft speed tracking of the PMSM system under load torque disturbance and speed variations. The model-based linear and nonlinear feedback control are used in the proposed control systems. The sliding mode control (SMC) with switching output feedback control law and integral SMC with linear feedback and state-dependent Riccati equation (SDRE) based approaches have been designed for the systems. The SDRE control accounts for the nonlinear multivariable structure of the WECS and is approximated with Taylor series expansion terms. The chattering inherited from SMC is eliminated by the continuous approximation technique. The sliding mode is guaranteed by eliminating the reaching mode in the proposed integral SMC. The model-free cascaded linear feedback control system based on the proportional-integral (PI) controllers use a back-calculation algorithm anti-windup scheme. The proposed speed controllers are synthesized with HODO to compensate for the external disturbance, model uncertainty, noise, and modelling errors. Moreover, servomechanism-based SDRE control, a near-optimal control system is designed to suppress the model uncertainty and noise without the use of disturbance observers. The proposed control systems for PMSM speed regulation have demonstrated a significant improvement in the angular shaft speed-tracking performance at the transients. Their performances have been tested under speed, load torque variations, and model uncertainty. For example, HODO-based SMC with switching output feedback control law (SOFCL) has demonstrated improvement by more than 78% than the PI-PI control system of the PMSM. The performance of the HODOs-based Integral SMC with SDRE nonlinear feedback is improved by 80.5% under external disturbance, model uncertainty, and noise than Integral SMC with linear feedback in the WECS. The HODO-based SDRE control with servomechanism has shown an 80.2% improvement of mean absolute percentage error under disturbances than Integral SMC with linear feedback in the WECS. The PMSM speed tracking performance of the proposed HODO-based discrete-time PI-PI control system with back-calculation algorithm anti-windup scheme is improved by 87.29% and 90.2% in the speed commands and load torque disturbance variations scenarios respectively. The simulations for testing the proposed control system of the PMSM system and WECS have been implemented in Matlab/Simulink environment. The PMSM speed control experimental results have been obtained with Lucas-Nuelle DSP-based rapid control prototyping kit.Center for International Program “Bolashak” of the Ministry of Education and Science Republic of Kazakhsta