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

Nonlinear optimal control of interior permanent magnet synchronous motors for electric vehicles

At present time, research in the field of Electric Vehicles (EV) is significantly intensifying around the world due to the ambitious goals of many countries, including the UK, to prohibit the sale of new gasoline and diesel vehicles, as well as hybrid vehicles, in the near future around 2030-35. The primary goal of this Ph.D. research is to improve the propulsion system of electric vehicles' powertrains through improvements in the control of Interior Permanent Magnet Synchronous Motors (IPMSM), which are commonly used in EV applications. The proposed approaches are supported by simulations in Matlab, Matlab-Simulink and laboratory-based experiments. The research initially proposes an analytical solution in implicit view for a combined Maximum Torque per Ampere (MTPA) and Maximum Efficiency (ME) control, allowing to determine the optimal d-axis current, based on the concept of minimisation of the fictitious electric power loss. With the exception of two parameters, the equation is identical to that of the ME control. Therefore, upgrading the ME control to the combined MTPA/ME control is relatively easy and doesn't require any change in hardware beyond a few minors of controller code in the software. The presented research demonstrates an easy-to-apply combined MTPA/ME control leading to the ‘Transients Optimal and Energy-Efficient IPMSM Drive’ providing smooth transitions to the MTPA control during transients and to the ME control during steady states. A concept of ‘Nonlinear Optimal Control of IPMSM Drives’ is also introduced in this Ph.D. research. The velocity control loop develops nonlinearities when energy consumption optimisation methods like MTPA, ME, or combined MTPA/ME are added. In addition, the control system's parameters can be inaccurate and fluctuate depending on the operating point or possible uncertainties in real-time operation. In the proposed method, the control structure is the same as in the Field Oriented II Control (FOC), with the close velocity and two current loops, but the Proportional-Integral (PI) controllers are replaced by Nonlinear Optimal (NO) Controllers. The linear part of the controller is designed as a Linear Quadratic Regulator (LQR) with integral action for each loop separately. This is, in fact, a PI controller with optimal gain parameters for a specific operating point. The nonlinear part takes the required fluctuations of the control system’s optimal gain parameters in real-time operation as new control actions to improve a robust control structure. The design procedure for the nonlinear part is similar to that of the LQR, but the criterion of A. Krasovsky's generalised work is used, and the analytical derivations lead to an explicit control solution for the nonlinear optimal part. The nonlinear part emulates the adjustments for updating the linear part’s optimal LQR gains based on operating conditions, instead of employing extensive look-up tables or complicated estimation algorithms. The proposed control is robust in the allowed range of the system’s parameters. In conclusion, upgrading existing industrial IPMSM drives into a robust and optimal energy-efficient version that can be used for electric vehicle applications is the main advantage of the novel control concept described in this Ph.D. research. For this upgrade, only a small portion of the software that is related to the PI controllers needs to be changed; no new hardware is needed. Therefore, it is cost-effective and simple to transform existing industrial IPMSM drives into a better version with the proposed method. This feature also leads to the design of more adequate IPMSM drives to meet the demands of Electric Vehicle (EV) operating cycles

Online loss minimization based direct torque and flux control of IPMSM drive

With the advent of high energy rare earth magnetic material such as, third generation neodymium-iron-boron (NdFeB), permanent magnet synchronous motor (PMSM) is becoming more and more popular in high power industrial applications (e.g., high-speed railway) due to its advantageous features such as high energy density, stable parameters, high power factor, low noise and high efficiency as compared to the conventional ac motors. Over the years, vector control and direct torque and flux control (DTFC) techniques have been used for high performance motor drives. But, the DTFC is faster than that of conventional vector control as the DTFC scheme doesn't need any coordinate transformation, pulse width modulation (PWM) and current regulators. The DTFC utilizes hysteresis band comparators for both flux and torque controls. Most of the past researches on DTFC based motor drives mainly concentrated on the development of the inverter control algorithm with less torque ripple as it is the major drawback of DTFC. The torque reference value is obtained online based on motor speed error between actual and reference values through a speed controller. Traditionally, researchers chose a constant value of air-gap flux reference based on trial and error method which may not be acceptable for high performance drives as the air-gap flux changes with operating conditions and system disturbance. Efficient high performance drives require fast and accurate speed response to cope with disturbances and algorithm to minimize motor losses. However, if the reference air-gap flux is maintained constant it is not possible to control the motor losses. Therefore, this thesis presents a novel loss minimization based DTFC scheme for interior type PMSM drive so that the drive system can maintain both high efficiency and high dynamic performance. An online model based loss minimization algorithm (LMA) is developed to estimate the air-gap flux so that the motor operates at minimum loss condition while taking the general advantages of DTFC over conventional vector control. The performance the proposed LMA based DTFC for PMSM drive is tested in both simulation and real-time implementation at different operating conditions. The results verify the effectiveness of the proposed flux observer based DTFC scheme for PMSM drive

Advances in the Field of Electrical Machines and Drives

Electrical machines and drives dominate our everyday lives. This is due to their numerous applications in industry, power production, home appliances, and transportation systems such as electric and hybrid electric vehicles, ships, and aircrafts. Their development follows rapid advances in science, engineering, and technology. Researchers around the world are extensively investigating electrical machines and drives because of their reliability, efficiency, performance, and fault-tolerant structure. In particular, there is a focus on the importance of utilizing these new trends in technology for energy saving and reducing greenhouse gas emissions. This Special Issue will provide the platform for researchers to present their recent work on advances in the field of electrical machines and drives, including special machines and their applications; new materials, including the insulation of electrical machines; new trends in diagnostics and condition monitoring; power electronics, control schemes, and algorithms for electrical drives; new topologies; and innovative applications

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

A Novel DTFC Based Efficiency and Dynamic Performance Improvement of IPMSM Drive

With the advancements in magnetic materials and semiconductor technology, permanent magnet synchronous motor (PMSM) is becoming more and more popular in high power industrial applications due to its high energy density, high power factor, low noise and high efficiency as compared to conventional AC motors. Field oriented vector control (VC) and direct torque and flux control (DTFC) are used for high performance drives. Among these two techniques DTFC is faster and simpler than that of conventional VC scheme as DTFC scheme doesn’t need any coordinate transformation, pulse width modulation and current regulators. The DTFC based motor drives utilizes hysteresis band comparators for both torque and flux controls. Both torque and flux are controlled simultaneously by the selection of appropriate voltage vectors from the inverter. However, DTFC suffers from high torque ripples due to discrete nature of control system and limited voltage vectors from the inverter. Torque ripples can be minimized by increasing the sector numbers of the DTFC scheme which increases the switching frequency of the inverter. Traditionally, researchers chose a constant value of reference air-gap flux to make the control task easy but it is not acceptable for high performance drives as the air-gap flux changes with the operating conditions and system disturbances. Furthermore, if the reference air-gap flux is maintained constant, it is not possible to control the motor over the wide speed range operation. Moreover, conventional six-sector based DTFC scheme suffers from high torque ripples, which is the major drawbacks to achieve high dynamic performance. Therefore, this thesis presents a novel eighteen-sector based DTFC scheme to achieve high dynamic performance with minimum torque ripples. In addition, the loss minimization algorithm (LMA) is incorporated with proposed DTFC scheme in order to improve the efficiency while maintaining high dynamic performance. This thesis further presents modified eighteen-sector based DTFC scheme to overcome the unbalanced voltage effects in any sector of conventional six-sector based system to improve the dynamic performance of the proposed system. This thesis also presents a novel sector determination algorithm to determine the sector number of the stator flux linkage vector which reduces the computational burden to the microprocessor. A five level torque hysteresis comparator based DTFC scheme is also proposed to reduce the torque ripple. Further, a backstepping based nonlinear controller is developed for IPMSM drive that achieves the lowest possible torque ripples in steady state. In this controller development, the control variable is motor electromagnetic developed torque and stator air-gap flux linkages similar to classical DTFC but the errors are forced to zero using backstepping process to get better dynamic performance. The effectiveness of the proposed systems is verified through the development of a simulation model using Matlab/Simulink. Performance of the proposed nonlinear controller is investigated extensively at different operating conditions such as sudden speed and load changes. Then the complete IPMSM drives, incorporating the proposed LMA and eighteen-sector based DTFC scheme and nonlinear controller with torque and flux as virtual control variables are successfully implemented in real-time using digital signal processor (DSP) board-DS1104 board for laboratory 5-hp motor. The effectiveness of the proposed control techniques are verified in both simulation and experiment at different operating conditions. It is found that, the nonlinear controller based IPMSM drive provides the best performance in terms of torque ripple among all the DTFC scheme developed in the thesis. The results show the robustness of the drive and it’s potentiality to apply for real-time industrial drive applications

Modelling and Control of Switched Reluctance Machines

Today, switched reluctance machines (SRMs) play an increasingly important role in various sectors due to advantages such as robustness, simplicity of construction, low cost, insensitivity to high temperatures, and high fault tolerance. They are frequently used in fields such as aeronautics, electric and hybrid vehicles, and wind power generation. This book is a comprehensive resource on the design, modeling, and control of SRMs with methods that demonstrate their good performance as motors and generators

Modelling and Control of Switched Reluctance Machines

Today, switched reluctance machines (SRMs) play an increasingly important role in various sectors due to advantages such as robustness, simplicity of construction, low cost, insensitivity to high temperatures, and high fault tolerance. They are frequently used in fields such as aeronautics, electric and hybrid vehicles, and wind power generation. This book is a comprehensive resource on the design, modeling, and control of SRMs with methods that demonstrate their good performance as motors and generators

Global identification of electrical and mechanical parameters in PMSM drive based on dynamic self-learning PSO

A global parameter estimation method for a PMSM drive system is proposed, where the electrical parameters, mechanical parameters and voltage-source-inverter (VSI) nonlinearity are regarded as a whole and parameter estimation is formulated as a single parameter optimization model. A dynamic learning estimator is proposed for tracking the electrical parameters, mechanical parameters and VSI of PMSM drive by using dynamic self learning particle swarm optimization (DSLPSO). In DSLPSO, a novel movement modification equation with dynamic exemplar learning strategy is designed to ensure its diversity and achieve a reasonable tradeoff between the exploitation and exploration during the search process. Moreover, a nonlinear multi-scale based interactive learning operator is introduced for accelerating the convergence speed of the Pbest particles; meanwhile a dynamic opposition-based learning (OBL) strategy is designed to facilitate the gBest particle to explore a potentially better region. The proposed algorithm is applied to parameter estimation for a PMSM drive system. The results show that the proposed method has better performance in tracking the variation of electrical parameters, and estimating the immeasurable mechanical parameters and the VSI disturbance voltage simultaneously

Disturbance/uncertainty estimation and attenuation techniques in PMSM drives–a survey

This paper gives a comprehensive overview on disturbance/uncertainty estimation and attenuation (DUEA) techniques in permanent magnet synchronous motor (PMSM) drives. Various disturbances and uncertainties in PMSM and also other alternating current (AC) motor drives are first reviewed which shows they have different behaviors and appear in different control loops of the system. The existing DUEA and other relevant control methods in handling disturbances and uncertainties widely used in PMSM drives, and their latest developments are then discussed and summarized. It also provides in-depth analysis of the relationship between these advanced control methods in the context of PMSM systems. When dealing with uncertainties,it is shown that DUEA has a different but complementary mechanism to widely used robust control and adaptive control. The similarities and differences in disturbance attenuation of DUEA and other promising methods such as internal model control and output regulation theory have been analyzed in detail. The wide applications of these methods in different AC motor drives (in particular in PMSM drives) are categorized and summarized. Finally the paper ends with the discussion on future directions in this area