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

Investigating electrical drive performance employing model predictive control and active disturbance rejection control algorithms

Many issues can degrade the electrical drive performance such as cross-coupling, time delay, external disturbances, and parameter variation. The Synchronous Reference Frame (SRF) PI Current Controller (CC) is the most popular control scheme for the motor drive current control due to its simplicity. However, the PI controller does not have an optimal dynamic response due to the reasonably low transient response of the integral parts. Furthermore, the tuning of the PI controller depends heavily on the machine’s parameters. Recently, alternative control schemes such as Model Predictive Control (MPC) and Active Disturbance Rejection Control (ADRC) are studied due to their dynamic performance and disturbance rejection capability, respectively. This paper presents a comparative study between the conventional PI, ADRC, and MPC control schemes applied for Permanent Magnet Synchronous Motor (PMSM) taking into consideration the operational issues of electrical drives

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

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

On the reliability of electrical drives for safety-critical applications

The aim of this work is to present some issues related to fault tolerant electric drives,which are able to overcome different types of faults occurring in the sensors, in thepower converter and in the electrical machine, without compromising the overallfunctionality of the system. These features are of utmost importance in safety-criticalapplications. In this paper, the reliability of both commercial and innovative driveconfigurations, which use redundant hardware and suitable control algorithms, will beinvestigated for the most common types of fault: besides standard three phase motordrives, also multiphase topologies, open-end winding solutions, multi-machineconfigurations will be analyzed, applied to various electric motor technologies. Thecomplexity of hardware and control strategies will also be compared in this paper, sincethis has a tremendous impact on the investment costs

Discussion on "AC Drive Observability Analysis"

In the paper by Vaclavek et al. (IEEE Trans. Ind. Electron., vol. 60, no. 8, pp. 3047-3059, Aug. 2013), the local observability of both induction machine and permanent-magnet synchronous machine (PMSM) under motion-sensorless operation is studied. In this letter, the "slowly varying" speed assumption is discussed, and the PMSM observability condition at standstill is revisited

Improved current-regulated delta modulator for reducing switching frequency and low-frequency current error in permanent magnet brushless AC drives

The conventional current-regulated delta modulator (CRDM) results in a high current ripple and a high switching frequency at low rotational speeds, and in low-frequency current harmonics, including a fundamental current error, at high rotational speeds. An improved current controller based on CRDM is proposed which introduces a zero-vector zone and a current error correction technique. It reduces the current ripple and switching frequency at low speeds, without the need to detect the back-emf, as well as the low-frequency error at high speeds. The performance of the modulator is verified by both simulation and measurements on a permanent magnet brushless ac drive

High-frequency issues using rotating voltage injections intended for position self-sensing

The rotor position is required in many control schemes in electrical drives. Replacing position sensors by machine self-sensing estimators increases reliability and reduces cost. Solutions based on tracking magnetic anisotropies through the monitoring of the incremental inductance variations are efficient at low-speed and standstill operations. This inductance can be estimated by measuring the response to the injection of high-frequency signals. In general however, the selection of the optimal frequency is not addressed thoroughly. In this paper, we propose discrete-time operations based on a rotating voltage injection at frequencies up to one third of the sampling frequency used by the digital controller. The impact on the rotation-drive, the computational requirement, the robustness and the effect of the resistance on the position estimation are analyzed regarding the signal frequency

Influence of skew and cross-coupling on flux-weakening performance of permanent-magnet brushless AC machines

A method is proposed for predicting the flux-weakening performance of permanent-magnet (PM) brushless ac machines accounting for skew and d-q axis cross-coupling. The method is based on a d-q-axis flux-linkage model, a hybrid 2-D finite-element (FE)-analytical method being used to predict the d- and q-axis inductances. However, it only requires 2-D FE analysis of the magnetic field distribution over a cross section of the machine. The developed method is used to predict the torque-speed characteristic of an interior PM brushless ac machine with one stator slot-pitch skew. This is compared with predictions from a direct FE analysis of the machine and validated by measurements