Permanent Magnet Synchronous Motor Rotor Research Articles

In Search of the Proper Dimensions of the Optimum In-Wheel Permanent Magnet Synchronous Motor Design

In this paper, a new approach to the optimized design of outer rotor Permanent Magnet Synchronous Motors (PMSMs) for in-wheel light electric vehicle (LEV) applications is presented. The optimized design study is based on various dimensions such as back iron depth, permanent magnet depth and air gap length. The novel method is developed to reveal the quality factor of design (QFD), which implies the maximum possible performance results, and determine the best possible design for in-wheel PMSMs for direct-drive LEV applications. Therefore, the thickness of the back iron, permanent magnet and air gap dimensions are altered accordingly to obtain an optimized design. This design study is conducted for an in-wheel PMSM that has rated values of 2.5 kW, 150 V, 900 min−1, and 24-slot/20-pole configuration intended for LEV propulsion. These designs are simulated in order to obtain the maximized combination of efficiency, shaft power, shaft torque and a minimized combination of total weight, iron losses, copper losses, input current and cogging torque. The measure of the optimized parameters is named QFD, which indicates the goodness of the design through the use of radar charts. The values of the essential coefficients of QFD may vary for different applications, e.g., the design of PMSMs used in traction applications has some certain criteria that imply high-performance operation. Additionally, the QFD can guide motor manufacturers as a starting point for a design study.

Multi-objective optimization design of external rotor permanent magnet synchronous motor for robot arm

Multi-objective optimization design of external rotor permanent magnet synchronous motor for robot arm

Improvement Performances of the SMO Observer for PMSM Sensorless Control Based on DTC Strategy Using Simulated Annealing and Reinforcement Learning TD3 Agent

From the elements that contribute to increasing the reliability of the control system of a Permanent Magnet Synchronous Motor (PMSM), could be enumerated the replacement of the speed transducers with software-implemented speed observers. On this basis, this paper focuses on the sensorless regulation of a PMSM using a Direct Torque Control (DTC) type strategy, in which a speed observer is used in combination with a Reinforcement Learning-Twin Delayed Deep Deterministic Policy Gradient (RL-TD3) type agent to increase the accuracy of the PMSM rotor speed estimate. Simulated Annealing (SA) is also used to achieve superior performance of the velocity observer for optimal tuning of the PI-type velocity controller parameters. The latter can, after the training phase, provide correction signals to the speed observer so that the estimated speed is as close as possible to the estimated speed. The control structures, control algorithms, and operating equations of the PMSM, the control strategy of the DTC type, and the speed observer are presented in this paper. Numerical simulations carried out in the Matlab/Simulink programming environment validate the superiority of the PMSM rotor speed estimation performance in the case of the use of an RL-TD3-type agent in combination with a speed observer, compared to the case of the use of the speed observer alone.

Research on Rotor Loss and Rotor Structure Optimization of Rare Earth Permanent Magnet Synchronous Motors in the Weak Field Area

The rotor loss of rare earth permanent magnet synchronous motor (PMSM) affects the efficiency and reliability of the motor and is an important research direction of rare earth permanent magnet synchronous motors. In this paper, the influence of rotational speed on the loss of the rotor core and the permanent magnet is analyzed through the analysis of the motor magnetic field and rotor loss calculation. Specifically, with the increase in rotational speed, the weak magnetic current increases, the amplitude of flux density change in the rotor core decreases, and the loss of the rotor core also decreases. The greater the influence of the harmonic current magnetic field on the outside of the rotor, the greater the loss. The core loss on the rotor is mainly distributed on the outside of the rotor. For further engineering applications, this paper analyzes the loss composition of three kinds of motors with different rotor structures and judges the optimal scheme based on the minimum loss. Finally, the correctness of this research is verified by comparing the experimental and simulation results of two kinds of motors with different rotor structures. The research content of this paper can provide a reference for the loss analysis and optimization and rotor structure selection of rare earth permanent magnet synchronous motor rotor design.

Variable-step close-loop angle compensation method of PMSM rotor position estimation based on super-twisting sliding-mode observer using tangent reaching law

Super-Twisting Sliding-Mode Observer (STSMO) is a kind of second-order sliding-mode observer which has been widely used in position sensorless control of permanent magnet synchronous motor (PMSM), for it can significantly reduce the chattering phenomenon of system near sliding-mode manifold. In theory, a low-pass filter (LPF) is not necessary to STSMO because of its low-chattering character near sliding-mode manifold, and as a result, phase delay should not exist in the observing result of STSMO, which means that there is no need to compensate the rotor position estimated by STSMO with phase-locked loop (PLL). However, in practical situations, a number of non-ideal factors such as sampling delay and data-updating delay can affect the accuracy of STSMO estimation, especially in dynamic process. Error contained in electric angle estimated by STSMO can be very high without compensation, which will make the stability as well as performance of system worse. In this article, the idea that STSMO needs a close-loop angle compensation method while estimating rotor position is proposed. First, on the basis of the mathematical model of angle compensation method established in this paper, traditional angle compensation method based on PI regulator is analyzed, which reveals that PI method is approximately equivalent to using a sliding-mode controller with exponential reaching law to control the angle estimation error. To improve the dynamic compensation performance together with ability against disturbances, a variable-step close-loop angle compensation method using tangent reaching law is proposed from the perspective of sliding-mode control and reaching law. Then, to measure the dynamic performance and ability against disturbances of a compensation method, the definition of normalized compensation sensitivity is proposed. Calculation results of normalized compensation sensitivities of both algorithms show that tangent reaching law method has better ability against disturbances as well as dynamic performance. Finally, this conclusion is verified through simulations. The simulation results suggest that compared with traditional method based on PI regulator, this new algorithm does achieve better dynamic compensation performance and ability against disturbances while keeping a good steady-state compensation accuracy. Meanwhile, it also simplifies the design of compensation algorithm.

Analysis and optimization of interior permanent magnet synchronous motor for electric vehicle applications using ANSYS Motor-CAD

The Permanent Magnet Synchronous Motor (PMSM) has the capability to high torque to current ratio, high power to weight ratio, high efficiency and stability. Due to the above positive points, PMSM is extensively employed in recent variable speed AC drives, particularly in electric vehicle applications. The electric vehicle is convenient for the city traffic without toxic gas emissions with low noise. PMSM became at the top of AC motor types due to the positive features written in the previous lines. However, it has two major drawbacks i.e. high cost and small speed range but it can be controlled and exceed to the small speed range with some control methods. A radial flux inner rotor PMSM architecture for electric vehicle application is presented in the project. The Interior Permanent Magnet Synchronous Motor (IPMSM) of the electric vehicle Leaf model, which was first produced by Nissan company in 2012, will be analyzed with ANSYS Motor-CAD and then the analysis results will be compared with the theoretical results and finally will be optimized in the project. The paper will provide insights about various change of parameters and their effects to the other parameters.

Double control strategy of PMSM rotor speed-based traction drive using resolver

This study addresses the challenge of speed control in permanent magnet synchronous motors (PMSMs), particularly in complex industrial applications. The research investigates the control of rotor speed in an electric-traction drive scenario. The setup involves an 8kW high-voltage battery powering a 35 kW PMSM through a controlled 3-phase (3-φ ) converter. Sensor feedback provides torque, currents, and voltage data, while a resolver captures speed and position information. The control strategy employs a two-loop algorithm. The outer loop uses a Proportional–integral to achieve zero steady-state error in this design (PI) controller for speed control, while two PI controllers are utilized to govern stator current in the Q and D directions. The input battery is very important in this design to achieve zero steady-state error. During a 0.2 s simulation, the rotor speed demand is incrementally raised from 0 to 1200 RPM. The proposed approach is implemented and verified using the Matlab2020a Simulink environment. The simulation results prove the efficacy of the proposed algorithm efficiently.

Torque Ripple Suppression Research of V-Shaped External Rotor Permanent Magnet Motor

Aiming at the problems of large torque ripple and poor output torque performance of external rotor permanent magnet synchronous motors, this paper took a three-phase 24-slot 19-pole external rotor motor as the research object, uses the magnetic circuit method and Lorentz theorem to analyze and calculate the motor torque, and improved the output torque by optimizing the position parameters of the V-shaped permanent magnet. The output torque was further optimized by a circular groove on the side of the stator teeth. The finite element simulation results show that the output performance of the motor can be improved by selecting the proper permanent magnet position. Stator tooth chooses slot position for Z = 1.2 mm, R = 3.5 mm torque ripple when dropped by 81.9%, up 7.6% on the output torque, motor performance is improved.

Improved Performance for PMSM Sensorless Control Based on the LADRC Controller, ESO-Type Observer, DO-Type Observer, and RL-TD3 Agent

Starting from the fact that in sensorless control systems of the Permanent Magnet Synchronous Motor (PMSM), the load torque can have short and significant variations, this paper presents the sensorless control of a PMSM based on a Linear Adaptive Disturbance Rejection Controller (LADRC) type controller. Essentially, the successful operation of the LADRC controller to achieve PMSM rotor speed control performance depends on a good estimation of the disturbances acting on the system. Traditionally, an Extended State Observer (ESO) is used to make such an estimate. In this paper, it is proposed to use a Disturbance Observer (DO) to estimate the external disturbances, and after their rejection, the LADRC controller ensures an equivalent global behavior of the control system with an ideal double integrator, thus increasing ease in achieving the desired control performance. Control structures and Matlab/Simulink implementation of the PMSM sensorless control system based on the LADRC controller with an ESO-/DO-type observer are presented, as is its use in tandem with a Reinforcement Learning Twin-Delayed Deep Deterministic Policy Gradient (RL-TD3) specially trained agent that provides correction signals for more accurate estimation of external disturbances and hence improved control performance. To optimize the gain value of the DO-type observer, a computational intelligence algorithm such as the Ant Colony Algorithm (ACO) is used. Qualitatively superior performance is achieved by using LADRC with the RL-TD3 agent control structure in terms of parametric robustness, response time, and steady-state error. In addition, by calculating the fractal dimension (DF) of the controlled signal and the PMSM rotor speed, it is found that the higher the DF, the better the performance of the control system. The validation of the superiority of the proposed control structures is carried out by means of numerical simulations in the Matlab/Simulink environment.

Improved Performance for PMSM Sensorless Control Based on Robust-Type Controller, ESO-Type Observer, Multiple Neural Networks, and RL-TD3 Agent.

This paper summarizes a robust controller based on the fact that, in the operation of a permanent magnet synchronous motor (PMSM), a number of disturbance factors naturally occur, among which both changes in internal parameters (e.g., stator resistance Rs and combined inertia of rotor and load J) and changes in load torque TL can be mentioned. In this way, the performance of the control system can be maintained over a relatively wide range of variation in the types of parameters mentioned above. It also presents the synthesis of robust control, the implementation in MATLAB/Simulink, and an improved version using a reinforcement learning twin-delayed deep deterministic policy gradient (RL-TD3) agent, working in tandem with the robust controller to achieve superior performance of the PMSM sensored control system. The comparison of the proposed control systems, in the case of sensored control versus the classical field oriented control (FOC) structure, based on classical PI-type controllers, is made both in terms of the usual response time and error speed ripple, but also in terms of the fractal dimension (DF) of the rotor speed signal, by verifying the hypothesis that the use of a more efficient control system results in a higher DF of the controlled variable. Starting from a basic structure of an ESO-type observer which, by its structure, allows the estimation of both the PMSM rotor speed and a term incorporating the disturbances on the system (from which, in this case, an estimate of the PMSM load torque can be extracted), four variants of observers are proposed, obtained by combining the use of a multiple neural network (NN) load torque observer and an RL-TD3 agent. The numerical simulations performed in MATLAB/Simulink validate the superior performance obtained by using properly trained RL-TD3 agents, both in the case of sensored and sensorless control.

Analytical Modeling, Analysis and Diagnosis of External Rotor PMSM with Stator Winding Unbalance Fault

Multiple factors and consequences may lead to a stator winding fault in an external rotor permanent magnet synchronous motor that can unleash a complete system shutdown and impair performance and motor reliability. This type of fault causes disturbances in operation if it is not recognized and detected in time, since it might lead to catastrophic consequences. In particular, an external rotor permanent magnet synchronous motor has disadvantages in terms of fault tolerance. Consequently, the distribution of the air-gap flux density will no longer be uniform, producing fault harmonics. However, a crucial step of diagnosis and controlling the system condition is to develop an accurate model of the machine with a lack of turns in the stator winding. This paper presents an analytical model of the stator winding unbalance fault represented by lack of turns. Here, mathematical approaches are used by introducing a stator winding parameter for the analytical modeling of the faulty machine. This model can be employed to determine the various quantities of the machine under different fault levels, including the magnetomotive force, the flux density in the air-gap, the flux generated by the stator winding, the stator inductances, and the electromagnetic torque. On this basis, a corresponding link between the fault level and its signature is established. The feasibility and efficiency of the analytical approach are validated by finite element analysis and experimental implementation.

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.

Investigation of analytical solution of super harmonic resonance of rotor system in permanent magnet synchronous motors considering mixed eccentricity

The unbalanced magnetic pull results in the nonlinearity of the system for the permanent magnet synchronous motor rotor having mixed eccentricity. The mass unbalance and static eccentricity form multi-frequency excitation, which results in the coupling effect of forward and backward whirling motions on the steady-state of super harmonic resonance. The analysis is difficult due to the phases of complex amplitudes of two motions which is no longer time invariant compared with the main resonance. To solve this problem, an analysis method of complex amplitudes is presented in this paper. The rotor is considered a Jeffcott rotor, and multi-scale method is applied to this system. A mathematical analysis method of the complex amplitude phases is employed for their time variant characteristics. The results show that both phases are linear time variant and their variation rates are both equal in magnitude to the difference between twice the excitation frequency and natural frequency of the generating system. The characteristics lead to the frequency shift of the two motions by the difference value from the natural frequency of the generating system. The numerical analysis reveals that the phases are independent of the initial condition and hence the complex amplitudes. The analysis solves two problems: the analytical solution of the rotor system carrying phases information can be expressed, which is in good agreement with the numerical result, and the solution construction is analyzed easily, which indicates the contribution of every component of the analytical solution. The phase characteristics analysis is the prerequisite for the frequency characteristics which can be easily carried out, and the coupling mechanism of the two motions is explained.

Control of PMSM Based on Switched Systems and Field-Oriented Control Strategy

Starting from the problem of studying the parametric robustness in the case of the control of a permanent magnet-synchronous motor (PMSM), although robust control systems correspond entirely to this problem, due to the complexity of the algorithms of the robust type, in this article the use of switched systems theory is proposed as a study option, given the fact that these types of systems are suitable both for the study of systems with variable structure and for systems with significant parametric variation under conditions of lower complexity of the control algorithms. The study begins by linearizing a PMSM model at a static operating point and continues with a systematic presentation of the basic elements and concepts concerning the stability of switched systems by applying these concepts to the control system of a PMSM based on the field-oriented control (FOC) strategy, which usually changes the value of its parameters during operation (stator resistance Rs, stator inductances Ld and Lq, but also combined inertia of PMSM rotor and load J). The numerical simulations performed in Simulink validate the fact that, for parametric variations of the PMSM structure, the PMSM control switched systems preserve qualitative performance in terms of its control. A series of Matlab programs are presented based on the YALMIP toolbox to obtain Pi matrices, by solving Lyapunov–Metzler type inequalities, and using dwell time to demonstrate stability, as well as the qualitative study of the performance of PMSM control switched systems by presenting in phase plane and state space analysis of the evolution of state vectors: ω PMSM rotor speed, iq current, and id current.

Rotor position angle control of permanent magnet synchronous motor based on sliding mode extended state observer

ABSTRACT To achieve fast, accurate control of the position angle of the rotor of permanent magnet synchronous motor (PMSM), traditional auto disturbance rejection control often has many adjustable parameters and complex tuning problems. Sliding mode control technology is introduced into the extended state observer (ESO) part of the auto disturbance rejection controller, and a new sliding mode approach law is designed based on several typical sliding mode approaches, which simplifies parameter tuning while retaining the original anti-interference performance of auto disturbance. In addition, the nonlinear state error feedback control law in active disturbance rejection control is enhanced to improve the component order PID control law, which can improve the response speed and robustness of the system, and prove the stability of the controller. Finally, the simulation of the PMSM rotor position control system based on the sliding mode ESO is carried out, and the results verify the validity of the method.

A Double-Stator Single-Rotor Magnetic Field Modulated Motor With HTS Bulks

Double stator single rotor permanent magnet synchronous motor (DSSR-PMSM) has the disadvantages of large torque ripple and abundant back-EMF harmonic content. To improve the electromagnetic performance of the motor, a double-stator single-rotor magnetic field modulation motor (DSSR-MFMM) with high-temperature superconductor (HTS) bulks is proposed in this paper. The epoxy resin is replaced by superconducting materials, and the auxiliary slot is opened in the outer stator of the motor. Some parameters of the motor are optimized by genetic algorithm. Compared with DSSR-PMSM, the proposed model has the characteristics of large back-EMF amplitude and high sinusoidal degree. The output torque is increased by 4.36% and the torque ripple is reduced by 5.12%.

A Nonlinear Dynamic Model of Flywheel Energy Storage Systems Based on Alternative Concept of Back Propagation Neural Networks

Abstract The flywheel energy storage system (FESS) is a closely coupled electric-magnetic-mechanical multiphysics system. It has complex nonlinear characteristics, which is difficult to be described in conventional models of the permanent magnet synchronous motor (PMSM) and active magnetic bearings (AMB). A novel nonlinear dynamic model is developed based on the alternative concept. Using back propagation (BP) neural network as a bridge, alternative mapping functions can be built from parametric calculation data of the finite element method (FEM) models. These functions are implemented in a system level simulation of the FESS. As a serial of linear equations, the alternative mapping function can precisely reproduce the electric-magnetic-mechanical characteristics in a satisfied speed and robust. Study of the cogging torque in the PMSM shows a good coincidence with the theory prediction. The current and displacement stiffness coefficients of the AMB are not constants as conventional linear models but change in different winding current and rotor positions. The influence parameters to the critical speed frequency and vibration amplitude are comprehensively studied, including the rotor mass, moment of inertial, eccentric distance, and the mass centroid offset. An operation boundary of the FESS is summarized to describe the feasible power load in different rotor rotation speed and PMSM winding current.

Temperature Field Analysis of Mine Flameproof Outer Rotor Permanent Magnet Synchronous Motor with Different Cooling Schemes

Aiming at the problem of temperature rise of mine flameproof outer rotor permanent magnet synchronous motor, based on the fluid structure coupling method, the temperature distribution of motor under three cooling schemes of air cooling and water cooling are calculated respectively. For the structure I air cooling system, the influence of different number of heat sink on the maximum temperature rise and pressure drop of fluid channel is analyzed, and the parameters of heat sink are optimized. For the structure II air cooling system, the influence of setting fillet at the turn back of the fluid channel on the head loss in the fluid domain of the motor is analyzed, and the influence of different fillet radius on the head loss and the maximum temperature rise in the fluid domain is obtained. For the structure II water cooling system, the influence of different water flow speed on the maximum temperature rise of the motor is analyzed, and the influence of different assembly clearance of modular stator teeth and yoke on the maximum temperature rise of the motor is analyzed. The cooling effect and temperature rise distribution characteristics of the three cooling schemes are compared and analyzed. Finally, a water-cooled prototype is manufactured, and the temperature rise experiment is carried out, and the influence of the thermal deformation of fluid channel, stator yoke and stator teeth on the maximum temperature of the motor is analyzed. The results show that the calculated temperature field after considering the thermal deformation is closer to the experimental value, which verifies the accuracy of the calculation results, It also provides a reference for the selection and design of the cooling structure of the same type of PMSM electric roller.

Nonlinear Identification of PMSM Rotor Magnetic Linkages Based on an Improved Extended Kalman Filter

The permanent magnet synchronous motor (PMSM) has complex nonlinear, strongly coupled characteristics and the variation of motor parameters makes its control more difficult. Therefore, parameter identification is of great significance for the stable operation of its closed-loop control system. In this paper, a method based on an improved extended Kalman filter (EKF) for the identification of the rotor flux ( ψ f ) of a permanent magnet synchronous motor is investigated for this nonlinear and strongly coupled model. Simulation results show that the method has a more fast convergence rate and more accurate identification result than traditional EKF algorithm.

Improvement of PMSM Sensorless Control Based on Synergetic and Sliding Mode Controllers Using a Reinforcement Learning Deep Deterministic Policy Gradient Agent

The field-oriented control (FOC) strategy of a permanent magnet synchronous motor (PMSM) in a simplified form is based on PI-type controllers. In addition to their low complexity (an advantage for real-time implementation), these controllers also provide limited performance due to the nonlinear character of the description equations of the PMSM model under the usual conditions of a relatively wide variation in the load torque and the high dynamics of the PMSM speed reference. Moreover, a number of significant improvements in the performance of PMSM control systems, also based on the FOC control strategy, are obtained if the controller of the speed control loop uses sliding mode control (SMC), and if the controllers for the inner control loops of id and iq currents are of the synergetic type. Furthermore, using such a control structure, very good performance of the PMSM control system is also obtained under conditions of parametric uncertainties and significant variations in the combined rotor-load moment of inertia and the load resistance. To improve the performance of the PMSM control system without using controllers having a more complicated mathematical description, the advantages provided by reinforcement learning (RL) for process control can also be used. This technique does not require the exact knowledge of the mathematical model of the controlled system or the type of uncertainties. The improvement in the performance of the PMSM control system based on the FOC-type strategy, both when using simple PI-type controllers or in the case of complex SMC or synergetic-type controllers, is achieved using the RL based on the Deep Deterministic Policy Gradient (DDPG). This improvement is obtained by using the correction signals provided by a trained reinforcement learning agent, which is added to the control signals ud, uq, and iqref. A speed observer is also implemented for estimating the PMSM rotor speed. The PMSM control structures are presented using the FOC-type strategy, both in the case of simple PI-type controllers and complex SMC or synergetic-type controllers, and numerical simulations performed in the MATLAB/Simulink environment show the improvements in the performance of the PMSM control system, even under conditions of parametric uncertainties, by using the RL-DDPG.