Magnetic Modelling of Synchronous Reluctance and Internal Permanent Magnet Motors Using Radial Basis Function Networks

The general trend toward more intelligent energy-aware ac drives is driving the development of new motor topologies and advanced model-based control techniques. Among the candidates, pure reluctance and anisotropic permanent magnet motors are gaining popularity, despite their complex structure. The availability of accurate mathematical models that describe these motors is essential to the design of any model-based advanced control. This paper focuses on the relations between currents and flux linkages, which are obtained through innovative radial basis function neural networks. These special drive-oriented neural networks take as inputs the motor voltages and currents, returning as output the motor flux linkages, inclusive of any nonlinearity and cross-coupling effect. The theoretical foundations of the radial basis function networks, the design hints, and a commented series of experimental results on a real laboratory prototype are included in this paper. The simple structure of the neural network fits for implementation on standard drives. The online training and tracking will be the next steps in field programmable gate array based control systems

Neural-Network Vector Controller for Permanent-Magnet Synchronous Motor Drives: Simulated and Hardware-Validated Results

This paper focuses on current control in a permanentmagnet synchronous motor (PMSM). The paper has two main objectives: The first objective is to develop a neural-network (NN) vector controller to overcome the decoupling inaccuracy problem associated with conventional PI-based vector-control methods. The NN is developed using the full dynamic equation of a PMSM, and trained to implement optimal control based on approximate dynamic programming. The second objective is to evaluate the robust and adaptive performance of the NN controller against that of the conventional standard vector controller under motor parameter variation and dynamic control conditions by (a) simulating the behavior of a PMSM typically used in realistic electric vehicle applications and (b) building an experimental system for hardware validation as well as combined hardware and simulation evaluation. The results demonstrate that the NN controller outperforms conventional vector controllers in both simulation and hardware implementation

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

Maximum Torque per Ampere Control of Permanent Magnet Assisted Synchronous Reluctance Motor: An Experimental Study

In recent times, permanent magnet assisted synchronous reluctance motors (PMaSRM) have been considered as suitable traction motors for electric vehicle applications. In this type of machine, where the share of reluctance torque is more significant than the excitation torque, it is more appropriate to use a control strategy that can fully utilize the reluctance torque. This paper deals with a new structure of permanent magnet-assisted synchronous reluctance motors that was designed and manufactured in a previous study. This paper suggests applying, in a first study, a constant parameter maximum torque per ampere (MTPA) strategy to make a contribution towards the control of such structure that is becoming increasingly attractive in the field of electric transportation. This method is usually used to control interior permanent magnet synchronous motors to minimize the copper losses of the system. Before implementing and simulating this method, the mathematical models of the suggested motor and the inverter are given. An experimental study is conducted on a small-scale 1 kW prototype PMaSRM using a MicrolabBox Dspace to test and examine the proposed control. Simulation and experimental results are presented in this article in order to verify the validity of the developed control strategy

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

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

Modulated Model Predictive Control of Permanent Magnet Synchronous Motors with Improved Steady-State Performance

Finite Control Set Model Predictive Control (FCS-MPC) is an optimal control strategy that predicts the future trends of the control goals by assessing the discrete-time model of the system. FCS-MPC has many advantages, such as it has a fast dynamic response, and nonlinearities can be controlled by the customized cost function. Besides the featured benefits of the FCS-MPC strategy, the ripple in the output variable (in most cases, control variable) may be problematic due to the uncontrolled switching frequency. For that reason, the MPC-based closed-loop strategy offers a better regulation performance at high-sampling frequency. However, the selection of a low sampling rate causes an unpleasant distortion or poor power quality. A modulated model predictive control method is proposed in this work to suppress the unwanted distortion in the control variable. In the proposed method, a space vector modulator is integrated into the FCS-MPC-based control method to attain a fixed-switching frequency. By doing so, the distortions and unwanted harmonics are significantly decreased. In this paper, a modulated model predictive control (M2PC) method is proposed for controlling the permanent magnet synchronous motor. The proposed method calculates the dwell-time of the modulator stage by assessing the multi-objective cost function. The noticeable lower distortions in the stator currents are obtained by the proposed routine. All theoretical concepts are verified by extensive simulations. Based on the simulation results, the proposed method provides a better control performance for permanent magnet synchronous motors (PMSM). Furthermore, the proposed modulated MPC strategy offers superior steady-state performance compared to the conventional MPC method in all regards

Constrained field-oriented control of permanent magnet synchronous machine with field-weakening utilizing a reference governor

This paper presents a complete solution for constrained control of a permanent magnet synchronous machine. It utilizes field-oriented control with proportional-integral current controllers tuned to obtain a fast transient response and zero steady-state error. To ensure constraint satisfaction in the steady state, a novel field-weakening algorithm which is robust to flux linkage uncertainty is introduced. Field weakening problem is formulated as an optimization problem which is solved online using projected fast gradient method. To ensure constraint satisfaction during current transients, an additional device called current reference governor is added to the existing control loops. The constraint satisfaction is achieved by altering the reference signal. The reference governor is formulated as a simple optimization problem whose objective is to minimize the difference between the true reference and a modified one. The proposed method is implemented on Texas instruments F28343 200 MHz microcontroller and experimentally verified on a surface mounted permanent magnet synchronous machine