Permanent Magnet Synchronous Motor Motor Research Articles

Speed regulation of PMSM drive in electric vehicle applications with sliding mode controller based on harris Hawks optimization

This paper focuses on the speed regulation of permanent magnet synchronous motors (PMSM) in electric vehicle application using sliding mode control (SMC). Harris hawks optimizations (HHO) based sliding mode controller is adopted to increase the dynamic response of the PMSM motor, thereby enhancing vehicle performance. For the independent control of torque and flux, field oriented-control (FOC) is used to drive the PMSM. In this work, the speed reference provided for the controller is based on an electric car driving cycle that replicates real-world driving conditions. The optimal selection of sliding mode controller parameter enhances the dynamic characteristics of the speed regulation in electric vehicles, which is validated using the hardware in the loop (HIL-402) device. The HHO based sliding mode controller has superior performance in terms of robustness against load disturbances, fast convergence, and tracking accuracy.

PMSM motor drive and their control schemes

This paper investigated different control Techniques of Permanent magnet synchronous motor (PMSM) drive with open loop, voltage/frequency (V/F) control, closed-loop Space Vector Pulse Width Modulation (SVPWM) control, and sensor-less Modified Space Vector Pulse Width Modulation (MSVPWMM) control with MATLAB/Simulink. The different applications of commercial used required different control schemes due to cost-effectiveness. In a small commercial application where not much precision is required, open-loop or V/F control is used, due to their easy calculation and implementation and becomes a low-cost product outcome. Where their high precision has required closed-loop control is being adopted. In this paper, closed-loop SVPWMM and sensor-less MSVPWM techniques are proposed. The algorithm has a very fast response and output has fewer glitches, highly efficient. Constant speed response available at desired load. The control techniques have been modeled and simulated in MATLAB simulation software. The proposed scheme provides efficient performance in steady-state and dynamic load conditions.

Design, Analysis and Experimental Verification of a Coreless Permanent Magnet Synchronous Motor

The paper presents a new cost-effective magnetic circuit structure of a coreless permanent magnet synchronous motor (PMSM) with 16 poles and 12 coils for a mass production fan drive unit. 2D and 3D numerical models of the coreless PMSM were developed. Optimisation calculations were carried out using the field model of the machine. Multistage calculations were performed using the professional FEM package, ANSYS Maxwell and the author’s proprietary finite element method (FEM) code. On the basis of the conducted tests and analysis of the obtained results, the “optimal” magnetic circuit structure of the PMSM motor was selected. The prototype motor was subjected to measurement to verify the developed models and the proposed design approach that takes advantage of finite element analysis (FEA).

Dynamic PMSM Motor Model with Turn Short Fault for Wind Power Generation

A PMSM (Permanent Magnet Synchronous Motor) stator inter turn short fault generates the back emf and impedance unbalance element. Those unbalance element cause the torque ripple and the escalating partial heat defect. This paper proposes a dynamic motor model under the internal turn short fault. The proposed model is derived in the positive and negative sequence synchronous reference frame to be easily utilized for the fault detection rule. To validate the proposed scheme, the finite elements method (FEM) simulation with electric circuit is conducted on the PMSM.

Analysis of PMSM Short-Circuit Detection Systems Using Transfer Learning of Deep Convolutional Networks

Abstract Modern permanent magnet synchronous motor (PMSM) diagnostic systems are now combined with advanced artificial intelligence techniques, such as deep neural networks. However, the design of such systems is mainly focussed on a selected type of damage or motor type with a limited range of rated parameters. The application of the idea of transfer learning (TL) allows the fully automatic extraction of universal fault symptoms, which can be used for various diagnostic tasks. In the research, the possibility of using the TL idea in the implementation of PMSM stator windings fault-detection systems was considered. The method is based on the characteristic symptoms of stator defects determined for another type of motor or mathematical model in the target diagnostic application of PMSM. This paper presents a comparison of PMSM motor inter-turn short circuit fault detection systems using TL of a deep convolutional network. Due to the use of direct phase current signal analysis by the convolutional neural network (CNN), it was possible to ensure high accuracy of fault detection with simultaneously short reaction time to occurring fault. The technique used was based on the use of a weight coefficient matrix of a pre-trained structure, the adaptation of which was carried out for different sources of diagnostic information.

Analysis of different control schemes of PMSM motor and also a comparison of FOPI and PI controller for sensorless MSVPWMM scheme

This paper investigated different control Techniques of Permanent magnet synchronous motor (PMSM) drive with open loop, voltage/frequency (V/F) control, closed-loop Space Vector Pulse Width Modulation (SVPWM) control, and sensor-less Modified Space Vector Pulse Width Modulation (MSVPWMM) control with MATLAB/Simulink. The different applications of commercial use require different control schemes due to cost-effectiveness. In a small commercial application where not much precision is required, open-loop or V/F control is used, due to their easy calculation and implementation and becomes a low-cost product outcome. Where their high precision has required closed-loop control is being adopted. In this paper, closed-loop SVPWMM and sensor-less MSVPWM techniques are proposed. The algorithm has a much faster response in the switching of the inverter that is used provides better output has fewer harmonic contents. Fractional order controllers can provide more flexibility in tuning and can better adapt to complex and nonlinear systems. This often leads to improved control performance, especially in systems with unknown or time-varying dynamics. It helps to reduce steady-state error compared to integer order PI controllers. By adjusting the fractional order exponent, the system's characteristics matched better with the controller's response. Also, the FO-PI controllers allow for smoother transitions between different control modes or set points and help to reduce overshoot and rise time in dynamical systems, as they allow for more precise control of the transient response and Constant speed response available at desired load. The control techniques have been modeled and simulated in MATLAB simulation software. The proposed scheme provides efficient performance in steady-state and dynamic load conditions.

Optimization of Field-Oriented Control for PMSM Motor

This research focuses on designing and simulating a sensorless control technique for optimising field-oriented control to achieve an optimization control applicable to water pressure regulation management. In the irrigation system, water pressure changes are determined by the number of activated emitters operating at different times. Unstable water pressure may reduce irrigation efficiency, leaving brown areas of the landscape not receiving adequate watering. Thus, the Field-oriented control technique is introduced in the paper to regulate the water pressure in the water pump controller using a permanent magnet synchronous motor (PMSM). The PSO-SFC field-oriented control technique for the PMSM was studied to improve motor efficiency and precision motor control over the torque and speed. The cascade-free state feedback controller (SFC) can achieve better dynamics and disturbance compensation in the controller. The SFC's tuning process has been achieved by using a linear-quadratic optimization method and PSO (particle swarm optimization) in the cascaded process. The process improves the coefficient of gain K produced by linear-quadratic optimization and PSO to obtain promising Q and R matrices in the adaptive system with improved output response in the simulation.

Optimization of cogging torque in interior permanent magnet synchronous motor using optimum magnet v-angle

Introduction. At present, the most important requirement in the field of electrical engineering is the better utilization of electrical power, due to its increasing demand and not-so-increasing availability. A permanent magnet synchronous motor (PMSM) is increasingly gaining popularity in various household and industrial applications because of its superior performance compared to conventional electrical motors. Purpose. PMSM is designed based on the selection of various design variables and optimized to fulfill the same. Being superiorly advantageous over other motors, PMSM has the major disadvantage of higher cogging torque. Higher cogging torque generates torque ripple in the PMSM motor leading to various problems like vibration, rotor stress, and noisy operation during starting and steady state. The designer should aim to reduce the cogging torque at the design stage itself for overall better performance. Methods. An interior rotor v-shaped web-type PMSM is designed and its performance analysis is carried out using finite element analysis (FEA). Magnet v-angle is optimized with the objective of cogging torque reduction. Performance comparison is carried out between the optimized motor and the initially designed motor with FEA. Novelty. Magnet v-angle analysis is performed on the same keeping all other parameters constant, to obtain minimum cogging torque. The proposed method is practically viable as it does not incur extra costs and manufacturing complexity. Practical value. It is observed that the magnet v-angle is an effective technique in the reduction of cogging torque. Cogging torque is reduced from 0.554 N×m to 0.452 N×m with the application of the magnet v-angle optimization technique.

Comparative simulation study of electric motors for high performance of 3D printers

3D printing is a process in which material is joined layer by layer under computer control to make a 3D object easy to get almost any shape. This technology finds applications in various fields and it is attracting considerable interest from industry and academia. There are many different brands and models of motors used in 3D printers, and they all vary in quality and effectiveness. In this article we present the principal of the 3D printer, types of motors used in 3D printer and mathematical modelling of this motors like brushless direct current (DC) motor, permanent magnet synchronous motor (PMSM), and stepper motor. The models of analytical equations describing the three systems of motors are evaluated and developed by Matlab/Simunlink. In this paper, we have conducted a comparison of the series of results from simulation between the performance of PMSM, brushless DC and stepper motor. Among several criteria, this simulation study allows to select the criterion of response time to reach the desired speed and the precision of the rotor position to choose the most performant motor for 3D printers.

Review of Comparative Analysis of Speed Control Techniques of BLDC & PMSM Motor

bstract: Electric vehicles are becoming increasingly popular due to their environmental benefits and the need to reduce dependency on fossil fuels. Due to their great efficiency, dependability, and low maintenance requirements, BLDC (Brushless DC) motors and PMSM (Permanent Magnet Synchronous motors) are frequently utilized in EVs. For these motors to operate as efficiently and as effectively as possible, control is essential. This study provides an overview of the control strategies utilized for BLDC and PMSM motors in EVs. This study examines and compares the torque ripple, efficiency, and cost of these motors, along with the different control techniques utilized. This review paper highlights the problems and potential in this area while providing a thorough analysis of the current state of the art in the control of BLDC and PMSM motors in EVs.

Deep Reinforcement Learning Algorithm based PMSM Motor Control for Energy Management of Hybrid Electric Vehicles

Hybrid electric vehicles (HEV) have great potential to reduce emissions and improve fuel economy. The application of artificial intelligence-based control algorithms for controlling the electric motor speed and torque yields excellent fuel economy by reducing the losses drastically. In this paper, a novel strategy to improve the performance of an electric motor-like control system for Permanent Magnet Synchronous Motor (PMSM) with the help of a sensorless vector control method where a trained reinforcement learning agent is used and provides accurate signals which will be added to the control signals. Control Signals referred to here are direct and quadrature voltage signals with reference quadrature current signals. The types of reinforcement learning used are the Deep Deterministic Policy Gradient (DDPG) and Deep Q Network (DQN) agents. Integration and implementation of these control systems are presented, and results are published in this paper. The advantages of the proposed method over the conventional vector control strategy are validated by numerical simulation results.

Predictive Current Control for Six-Phase PMSM Motor With Multi-Step Synthesis Based Virtual Vectors

The concept of virtual vector has been a standard practice for the multiphase machine drives. However, simply adopting the fixed or adjustable duty-ratio virtual vectors fails to mitigate the current tracking error in the fundamental plane satisfactorily. To that end, this paper proposes a new model predictive control (MPC) method for a six-phase permanent magnet synchronous motor (PMSM) using multi-step synthesis based virtual vectors to regulate two planes simultaneously. The virtual vectors are formed through a two-step synthesis process. First, two groups of real vectors are used to synthesize 12 elementary virtual vectors to nullify the harmonic currents in the secondary plane. Subsequently, the 12 elementary virtual vectors are employed to further form other 60 composite virtual vectors to enhance the current tracking in the fundamental plane. For the sake of easy practical implementation, the pulse width modulation (PWM) switching sequence of all virtual vectors are analyzed to ensure that they present standard PWM switching sequence. The proposed multi-step synthesized composite virtual vectors can suppress the harmonic currents in the secondary plane and reduce the current tracking error in the primary plane simultaneously. Experimentations are conducted to verify the effectiveness of the proposed method.

Diagnosis of Stator Winding and Permanent Magnet Faults of PMSM Drive Using Shallow Neural Networks

This paper presents the application of shallow neural networks (SNNs): multi-layer perceptron (MLP) and self-organizing Kohonen maps (SOMs) to the early detection and classification of the stator and rotor faults in permanent magnet synchronous motors (PMSMs). The neural networks were trained based on the vector coming from measurements on a real object. The elements of the input vector of SNNs constituted the selected amplitudes of the diagnostic signal spectrum. The stator current and axial flux were used as diagnostic signals. The test object was a 2.5 kW PMSM motor supplied by a frequency converter operating in a closed-loop control structure. The experimental verification of the proposed diagnostic system was carried out for variable load conditions and values of the supply voltage frequency. The obtained results were compared with an approach based on a deep neural network (DNN). The research presented in the article confirm the possibility of detection and assessing the individual damage of stator winding and permanent magnets as well as the simultaneous faults of the PMSM stator and rotor using SNNs with simple signal preprocessing.

ANFIS based Direct Torque Control of PMSM Motor for Speed and Torque Regulation

Nowadays, the Permanent Magnet Synchronous Motors (PMSM) are gaining popularity among electric motors due to their high efficiency, high-speed operation, ruggedness, and small size. PMSM motors comprise a trapezoidal electromotive force which is also called synchronous motors. Direct Torque Control (DTC) has been extensively applied in speed regulation systems due to its better dynamic behavior. The controller manages the amplitude of torque and stator flux directly using the direct axis current. To manage the motor speed, the torque error, flux error, and projected location of flux linkage are employed to adjust the inverter switching sequence via Space Vector Pulse Width Modulation (SVPWM). One of the most common problems encountered in a PMSM motor is Torque ripple, which is recreated by power electronic commutation and a better controller reduces the ripples to increase the drive's performance. Conventional controllers such as PI, PID and SVPWM-DTC were compared with the proposed Adaptive Neuro-Fuzzy Inference System (ANFIS) in terms of performance measures such as speed and torque ripple. In this work, the Two-Gaussian membership function of the ANFIS controller is used in conjunction with a PMSM motor to reduce torque ripple up to 0.53 Nm and maintain the speed with a distortion error of 2.33 %.

The Control of PMSM Motor to Drive Propeller in Ship Propulsion System

Electric propulsion has advantages such as high maneuverability, good safety and reliability, being able to operate optimally with a control system. It is a future green technology which is environmentally friendly. The application of electric propulsion for ship is that the propeller is driven by using electric motor by regulating speed and/or torque. in this research, an permanent magnet synchronous motor (PMSM) is used to drive propeller of ship propulsion. The controller of proportional integral (PI) scheme is proposed to drive electric motor. The method of Ziegler Nichols stability margin tuning rule algorithm is performed to search the controller parameters. The optimal working point of propeller is determined by the cross intersection between the propeller loading curve to the coefficient of thrust curve of open water test propeller. The speed from the result of propeller working point analysis is set as control input reference. Based on the results of simulation, the proposed control of electric propulsion using PMSM motor is able to achieve the reference of speed.

The control of permanent magnet synchronous motor drive based on the space vector pulse width modulation and fractional order PID controller

This study explains a new way to speed control for PMSMs based on the FOC and SVPWM techniques employed in the building of the permanent magnet synchronous motors (PMSMs). When it comes to current control, two inner and one outside feedback loops were used. Feedback control with FOPID controllers is used to optimize the performance of PMSM motor design. FOPID parameters were optimized using genetic algorithms in MATLAB/Simulink simulations. Good dynamic and static qualities are demonstrated through simulation results. There is also a comparison of PMSM PID and FOPID controllers included.

Adaptive constrained generalized predictive controller for the PMSM speed servo system to reduce the effect of different load torques

Fractional-order models have been used in recent years to model the number of processes and applications like boilers, supercapacitors, power electronic devices, permanent magnet synchronous motor (PMSM) speed servo systems, and batteries in many papers. In this paper DC motor equivalent fractional-order model is used to model the PMSM speed servo system. This model has two parts: The electrical part and the Mechanical part. Every aspect has a fractional-order differential equation with an independent fractional order parameter. Its real value is unknown, but its span is evident. To specify the model stability region and to simulate it, the fractional model is approximated with a recursive (Oustaloup) filter. In this work, the PMSM motor's speed is controlled by applying the adaptive recursive least squares (RLS-based) constrained generalized predictive controller (GPC) over the system with unknown model order and in the presence of two types of loads: constant load torque, sinusoidal load. In the last section, adaptive constrained generalized predictive controller (AGPC) has been implemented on the real system. Experimental results also show this controller performance.

Development of a PMSM motor field-oriented control algorithm for electrical vehicles

Recently, with issues such as global warming, melting of glaciers and climate change, the need for sustainable methods of living has seen a drastic increase. Combustion cars that run on petrol and diesel are slowly being replaced with electrical vehicles (EVs). Currently, EVs face challenges in terms of range of kilometers offered, availability of charging systems, infrastructure for their development, etc. As the need for electrical vehicles increase, the usages of Permanent Magnet Synchronous Motor (PMSM) too have seen a growing trend. Motor control in an electrical vehicle is extremely crucial as a vehicle on road is subject to different terrains and hence, different loads. Throughout all these different scenarios, it is essential that the motor operates at its optimum efficiency in order to provide optimum vehicle performance for the driver and passengers. Currently, several methods are available for the control of electrical vehicles, nevertheless the field-oriented control (FOC) method for permanent magnet motors is widely used due to its efficient nature. This paper discusses with the design of modified FOC control algorithm for control the PMSM motor eliminates an initial jerk seen during the starting condition of a motor thereby providing a smoother start. As the entire simulation is done using Hardware in the Loop model, the values obtained have real life constraints taken into account, as opposed to a software only simulation. Moreover, the transient time taken to reach a steady state value in speed and to also change direction of rotation have been improved as well. The simulation has been designed entirely on the Altair Embed software.

Analysis and Design of Dual Three-Phase Fractional-Slot Permanent Magnet Motor With Low Space Harmonic

There are many space harmonics in the stator magnetomotive force (MMF) of fractional-slot concentrated winding (FSCW). These harmonics will produce high eddy current losses in the permanent magnet (PM), which will reduce motor efficiency and affect motor performance. Aiming at the above problems, the harmonic components of traditional stator MMF are first analyzed in this article, and then, a novel space-shifted unequal-turn winding structure is proposed for dual three-phase fractional-slot permanent magnet synchronous motors (PMSMs). Meanwhile, the sub- and super-harmonics in the stator MMF can be simultaneously eliminated using the proposed winding structure. To verify the effectiveness of the proposed structure, an 18-slot/8-pole motor and a 30-slot/14-pole dual three-phase fractional-slot PMSM with low space harmonic are designed by using the proposed space-shifted unequal-turn winding structure based on the analysis of nine-slot/eight-pole and 15-slot/14-pole motors. Finally, by comparing the finite element analysis (FEA) results, it is verified that the dual three-phase PMSM motor with the proposed structure has smaller eddy current losses in PM and better motor performance.

Study on design and flux weakening control of direct drive hub motor

The direct drive hub motor is a motor that directly combines the motor and the wheel. It is accompanied by the development of permanent magnet motor and modern control technology. Permanent magnet synchronous motor (PMSM) is especially suitable for use as hub motor use of its advantages of high efficiency, energy saving, high power and easy control. In this paper, Motor Cad software was applied to optimize the design of an outer rotor PMSM motor of a cellular power, and the simulation and analysis of air gap magnetic density and other performance were carried out. The analysis results not only verify the rationality of the motor design, but also provide a basis for the next study on flux weakening control. The design and control results show that the prototype meets the design requirements fully.