Model Of Permanent Magnet Synchronous Motor Research Articles

Velocity Control for Sideband Harmonics Compensation in Permanent Magnet Synchronous Motors With Low Switching Frequency Inverter

The existing methods for improving the control performance of permanent magnet synchronous motors (PMSMs) do not consider the effect of sideband harmonics during the intrinsic switching process in inverters. Undesirable sideband harmonics increase when the switching frequency of inverters is not sufficiently high compared to the fundamental frequency. These large sideband harmonics lead to torsional oscillations, which may severely damage motion control systems. In this article, we propose velocity control to reduce sideband harmonics in PMSMs with a low switching frequency inverter. The proposed method consists of a velocity controller and a sideband harmonics compensator. The desired dynamics for velocity tracking are developed via a PMSM model. The velocity controller is developed to improve velocity control performance using the desired dynamics. The sideband harmonics compensator is designed by utilizing sideband harmonics dynamics, which are proposed to suppress the main components of the sideband harmonics. First, a sideband harmonics observer is developed to estimate the sideband harmonics using sideband harmonics dynamics. Then, the sideband harmonics are rejected by the sideband harmonics compensator. The stability of the closed loop is proven by employing the input-to-state stable property. The performance of the proposed method is validated via experiments.

Design and implementation of a single-side flat synchronous linear motor model

In recent decades, the demand for a linear motor has increased in various applications, due to its ability to develop a linear motion directly. One of the significant problems facing the operation of the linear motor is the presence of force ripple caused by the irregular magnetic field of the permanent magnets. Accordingly, a developed single-side permanent magnet synchronous flat linear motor (PMSLM) model has been designed based on minimizing its force ripple produced. A Maxwell ANSYS simulation is performed to study and enhance the dynamic characteristics and performance of the model and then verifying it with experimental measurements. Multi-objective optimization had been achieved through reducing the size of permanent magnets and reaction rail at specific rates with maintaining the required thrust and reducing the cogging force. The results of the improved model design showed that the maximum value of the force ripple is reduced by about 81.13% compared with the primary model at a smaller ripple coefficient of 0.22%. The comparison between the experimental measurements and numerical analysis showed a good agreement and accuracy of the analytical results.

FPGA-Based Predictive Speed Control for PMSM System Using Integral Sliding-Mode Disturbance Observer

This article proposes a fast-terminal cost index (FTCI) based continuous control set model-based predictive speed control (CCS-MPSC) to improve the tracking performance of CCS-MPSC. First, an extended surface-mounted permanent magnet synchronous motor model that incorporates parameter mismatches and external interference into a disturbance term is utilized to facilitate the determination of parameters and reduce computational complexity. Second, by introducing a differential feedforward term, an exponential convergence cost index (ECCI) based CCS-MPSC has a smaller lag error than conventional CCS-MPSC when tracking a given speed. Third, an FTCI, which simultaneously includes a terminal attractor, a differential feedforward term, and a lumped disturbance term, is developed to improve the tracking performance of ECCI further. Finally, a fast-terminal integral sliding-mode observer is designed to estimate the lumped disturbance and the differential feedforward term fast and accurately. Experiments of proportional-integral control, conventional CCS-MPSC, ECCI, and FTCI have been carried out on an FPGA-based hardware system, and the experimental results validate the excellent tracking performance of the FTCI strategy.

Analysis of multistability, hidden chaos and transient chaos in brushless DC motor

Abstract The dynamics of brushless DC motor (BLDCM), a type of permanent magnet synchronous motor (PMSM) is investigated. The dynamical model of the BLDCM is compared to a mostly used model of PMSM. The BLDCM transition to chaos is briefly investigated both on the local level through local bifurcations and global level through manifold and invariant sets. All the transition parameter values are given. Apart from transition, multistability of the BLDCM is observed and assessed with stability basin. For some parameter values all dynamic modes (stable fixed point, limit cycle, chaotic attractor) coexist. For other parameter values multistability concerns different stable equilibria. Also, hidden chaos which is of non-Shilnikov type is examined and reported in BLDCM with the method of homotopy. Hidden chaos is defined from the basin of attraction. Transient features of the hidden chaotic set are studied. Finally, transient time of hidden chaos improves with two methods: critical velocity (acceleration) surfaces and Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm.

Echo State Network for Extended State Observer and Sliding Mode Control of Vehicle Drive Motor with Unknown Hysteresis Nonlinearity

An echo state network (ESN) for extended state observer (ESO) and sliding mode control (SMC) of permanent magnet synchronous motor (PMSM) in an electric vehicle system is investigated in this paper. For the PMSM model, most researches neglect the hysteresis loss and other nonlinear factors, which reduces the accuracy of the PMSM model. We present a modified PMSM model considering the hysteresis loss and then transform the new PMSM model to a canonical form to simplify the controller design. In order to deal with the hysteresis loss, an ESN is utilized to estimate the nonlinearity. Considering that some states cannot be directly obtained, an ESO with ESN is proposed to estimate unknown system states of the electric vehicle PMSM system. Afterwards, an SMC is adopted to control the closed-loop system based on the ESO with ESN, and a double hyperbolic function instead of the sign function is used to suppress the chattering of the SMC. The stabilities of the observer and the controller are all guaranteed by Lyapunov functions. Finally, simulations are presented to verify the validity of the echo state network for extended state observer and the neural network sliding mode control.

Research on parameter adaptive control for MEES

The Mechanical elastic energy storage (MEES) is a new type of physical energy storage. The energy storage medium is large-scale planar vortex spring (LSPVS), and the energy storage form is mechanical elastic potential energy. Multiple groups of LSPVS are fixed in a single energy storage box, and multiple energy storage boxes are connected in series to form a linked energy storage box group as the energy storage unit of MEES. In the process of energy storage, the torque and inertia of LSPVS change simultaneously. The permanent magnet synchronous motor (PMSM), as the driving device, is required to realize the fast response of torque change and effectively suppress the disturbance of inertia. In this paper, firstly, the mathematical model of linked energy storage box group is established. Secondly, combining with the direct torque control (DTC) model of PMSM and the backstepping control algorithm, the adaptive parameters of torque and inertia control strategy is designed. Finally, the experimental verification shows that the control strategy proposed in this paper has faster torque response and the disturbance of inertia is suppressed simultaneously, so as the energy storage process of MEES can be carried out smoothly and efficiently.

Model predictive control method with common-mode voltage suppression for dual three-phase permanent magnet synchronous motor

Recently, the interest in model predictive control (MPC) and dual three-phase drives has been growing rapidly. Due to the high redundancy of voltage vector in the system composed of dual three-phase permanent magnetic synchronous motor (PMSM) and six-phase inverter, the computational complexity and current harmonics of MPC are high. In addition, the zero vector has been used by traditional MPC, which will cause higher common-mode voltage. In this paper, a novel MPC method with twice predictions and synthetic vectors is proposed which can not only suppress common-mode voltage, but also reduce computational complexity and current harmonics. The mathematical model of a dual three-phase PMSM are verified by the experimental results under the common-mode voltage suppression.

Research on modeling and fault diagnosis of inter-turn short fault of permanent magnet synchronous motor

The stator winding inter-turn short fault of permanent magnet synchronous motor (PMSM) is a common motor fault with high probability. If this fault is not detected and handled in time, small initial fault will rapidly develop into other faults such as grounding short, inter-phase short, winding short et al., and even the motor damage. In order to diagnose the inter-turn short fault of PMSM, this paper firstly builds the model of the inter-turn short fault of PMSM, and then proposes a fast and simple fault diagnosis method for extracting the features of the inter-turn short fault under noise. For the first time, by introducing the full-short-circuit resistance Rf that relates with the fault severity factor δ and by estimating the inductance of inter-turn short fault motor on-line according to the three principles of the inductance calculation, which is used in the inter-turn short fault of transformer winding, the inter-turn short analysis model of PMSM is deduced. The model can be used to simulate the performance not only the health of PMSM but also the fault of inter-turn short fault of PMSM in one phase winding. This paper analyses the transient and steady state performance of 3-phase unbalanced current, speed and electromagnetic torque ripple and the relationship between full-short-circuit resistance and short current under fault condition. Finally, a fast and simple on-line fault diagnosis method of PMSM with inter-turn short fault is proposed based on phase sensitive detection (PSD) algorithm. The method uses the fundamental and third harmonic features of inter-turn short fault current. The simulation results show that the model can be well suited for the simulation of PMSM with inter-turn short fault, and the method can effectively extract the features and diagnose the fault.

Deadbeat Predictive Current Control for SPMSM at Low Switching Frequency With Moving Horizon Estimator

The deadbeat predictive current control (DPCC) of permanent-magnet synchronous motors (PMSMs) is well known for its simple structure and fast dynamic. However, it is sensitive to parameter mismatches and system delays, which becomes more serious at the low switching frequency. To handle such problems, this article proposes an accurate deadbeat control method based on an exact model of surface-mounted PMSM in a stationary two-phase frame with a moving horizon estimator (MHE). The motor model is obtained from differential equations, and transformations between stationary frame and rotating frame are reduced to eliminate the influence of the lag of electrical angle. MHE is utilized to estimate the back-electromotive force (EMF) and disturbance caused by parameter variations. The rotor flux is eliminated in the algorithm and the resistance and inductance mismatches are compensated by the estimator. Several simulations and experiments are performed in three methods-the conventional DPCC in rotating $dq $ -axis, DPCC in $\alpha \beta $ -axis with the accurate model, and the proposed method. These comparisons validate that the proposed method has good current tracking performance at low switching frequency and a strong robustness to parameter variations.

Reliable Fuzzy H∞ Control for Permanent Magnet Synchronous Motor Against Stochastic Actuator Faults

This article examines the issue of reliable fuzzy H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control with permanent magnet synchronous motor (PMSM) and stochastic actuator faults. The principle target of modeling the reliable control for PMSM is to improve the performance of PMSM in terms of speed of response, tracking accuracy, and robustness. In contrast to work found in the literature, the proposed dynamic model of a PMSM the load torque variation acts as disturbances, speed control strategy is developed based on the Takagi-Sugeno (T-S) fuzzy model and stochastic actuator faults are considered which is more practical and challenging. In such a manner, first, the nonlinear PMSM model is altered into corresponding linear submodels through the sufficient T-S fuzzy membership rules. Then, based on the obtained dynamic model, reliable H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control is designed for the considered PMSM. By executing an appropriate Lyapunov-Krasovskii (L-K) functional together with linear matrix inequality (LMI) optimization procedure, Wirtinger-based integral inequality approach, and arrangement of the delay-dependent adequate condition is determined which ensures that the closed-loop PMSM is robust asymptotic stable. Based on the acquired condition, the controller gains are derived by solving a set of LMIs. At last, the simulation results are depicted to validate the efficiency of our presented control method.

PMSM control for electric vehicle based on fuzzy PI

A fuzzy PI speed controller based on fuzzy control theory is proposed, which makes the drive control system of electric vehicle insensitive to disturbance and parameter change. The mathematical model of permanent magnet synchronous motor (PMSM) in d-q reference frame is established, fuzzy PI speed controller is designed based on fuzzy control theory, and simulation models of PMSM based on fuzzy PI control theory and sliding mode control theory are built in this paper. Two simulation models are simulated and analysed by Simulink, and simulation result shows that fuzzy PI control has faster dynamic response speed, better dynamic performance and better antiinterference ability than sliding mode control. Therefore, fuzzy PI control is an ideal control method, which has a certain reference value in vector control of PMSM for electric vehicle.

Unified Predictive Current Control of PMSMs with Parameter Uncertainty

Predictive current control (PCC) applied on permanent magnet synchronous motors (PMSMs) has been developed into mainly three methods: the conventional finite-control-set PCC, the double voltage vectors PCC, and deadbeat PCC. However, each approach has its particular calculation way for voltage vectors selection and respective execution duration. This paper, based on the deadbeat idea, presents a unified predictive current control scheme of PMSMs. Under this scheme, the prior three classes are able to be clearly unified into one frame with lower calculation effort. Furthermore, to cope with problem of parameter mismatch in dq-axis current predictive model, a integrated identification method is proposed. Firstly, data selectors are designed to reject abnormal data of sampling signals, and then the interval-varying multi-innovation least squares algorithm is combined with forgetting factor (V-FF-MILS) to approximate the error terms caused by electromagnetic parameters error. The estimated results are online fed to the model of PMSM to enhance its accuracy. Finally, the processor in loop (PIL) simulation results verify that the proposed integrated scheme has advantages in current control of PMSMs with large-scale parameter uncertainty.

Chaotic Heterogeneous Comprehensive Learning Particle Swarm Optimizer Variants for Permanent Magnet Synchronous Motor Models Parameters Estimation

Chaotic response in the permanent magnet synchronous motor (PMSM) is an undesirable performance that may affect motor stability. This unexpected behavior occurs due to the disruption in the system parameters and load disturbance. To control this unwanted performance, it’s essential to introduce a robust method to determine the PMSM model parameters efficiently and expeditiously. Two PMSM models depending on the type of its nonlinear differential equations are investigated. The first one is the integer-order PMSM model, while the other is the fractional-order model. In this work, novel developed optimization variants called chaotic heterogeneous comprehensive learning particle swarm optimizer (CHCLPSO) is proposed. In CHCLPSO, the standard heterogeneous comprehensive learning particle swarm optimizer (HCLPSO) is cooperated into ten different chaos maps to adjust some of its parameters. Six CHCLPSO variables are introduced in addition to the standard HCLPSO version to estimate the parameters of the integer-order and the fractional-order PMSM models that are corresponding to the chaotic behavior. A comparison among the results of the introduced variants and the original algorithm is carried out. Moreover, a comprehensive comparison with other recent algorithms is performed. The primary outcome proves that the chaos maps have a remarkable influence in both of the consistency and the accuracy of the results of the HCLPSO with less execution time over the integer and the fractional-order models, especially CHCLPSO-III and CHCLPSO-V with sinusoidal and piecewise maps, respectively.

Design and fault tolerant analysis of five-phase permanent magnet synchronous motor

&lt;span lang="EN-IN"&gt;This paper presents a design of 15-slot/12-pole, five-phase, surface-mounted permanent magnet synchronous motor (PMSM). The five-phase PMSM can be an attractive solution to few applications that demand fault tolerant capability such as in aerospace engineering and electric propulsion. The motor model is first investigated based on the implementation of analytical method. The analytical method derived from the subdomain model of the permanent magnet machine is initially applied to estimate the magnetic flux density distributions for the radial component &lt;em&gt;B&lt;/em&gt;&lt;sub&gt;r&lt;/sub&gt; and the tangential component &lt;em&gt;B&lt;/em&gt;&lt;sub&gt;t&lt;/sub&gt; in the machine air gap. Other important motor characteristics such as phase back-EMF, line back-EMF, cogging torque and electromagnetic torque are also calculated. The analytically calculated results are then compared with the numerical method in a 2D finite element analysis. Additionally, the capability of this PMSM model against faulty conditions are further investigated. The results show that the analytical model of the 15-slot/12-pole, five-phase PMSM provides very accurate motor performance within acceptable error margin. For instance, the average electromagnetic torques, inclusive of the cogging torque, as computed by the analytical and numerical methods are 5.53Nm and 5.33Nm respectively, yielding an error of 3.6%. During faulty conditions, the PMSM can possibly continue to operate with lower output torque, about 60% to 80% of its rated torque, when one-phase or two phase windings are out of service.&lt;/span&gt;

Eccentricity Faults Diagnosis in Permanent Magnet Synchronous Motors: a Finite Element-Based Approach

This paper addresses the effects of permanent magnet synchronous motor (PMSM) eccentricity faults on the induced normal magnetic field, flux density, and electromotive forces (EMFs). A 2D finite element method (FEM) is needed for PMSM modeling and three kind of eccentricity faults are considered; static, dynamic, and mixed eccentricities. The achieved simulation results allow distinguishing the three types of eccentricity based on the EMF power spectral density (PSD) computation. The highlighted fault characteristics allow carrying out detection and diagnosis. Sideband components amplitude extracted from the EMF PSD are proposed as faults index, allowing the three considered eccentricity faults to be both detected and distinguished.

The Sliding-Mode Control Based on a Novel Reaching Technique for Permanent Magnet Synchronous Motors

In order to improve the robustness, disturbance rejection and dynamic response performance of permanent magnet synchronous motor (PMSM) speed servo system, a novel sliding mode control (NSMC) strategy is adopted to replace the traditional proportion integral (PI) regulator in the design of speed controller. The mathematical model of PMSM is analyzed and a sliding mode controller based on a novel reaching technique is proposed. The integral of speed error is introduced into sliding mode surface to avoid the requirements of acceleration signal and reduced the steady-state error of the system. Meanwhile, a variable speed reaching method is imported to make the approaching speed correlate with the change of system state |s|, so as to improve the dynamic quality. In addition, the sigmoid function is used to replace the sign function in the conventional SMC, which further reduces chattering phenomena. Simulation and experimental results show that the proposed NSMC method based on the new reaching technique can realize precise speed control. Compared with the conventional PI and SMC control, this method not only achieves a fastest and best response speed, but also has a strongest robustness of resisting the external disturbance.

Permanent Magnet Synchronous Motor Winding Fault Simulation and Diagnosis

This paper presents the theory, simulation, diagnosis and prognosis evaluation of an anomaly detector for Permanent Magnet Synchronous Motor (PMSM) stator winding insulation faults. Physics-of-failure mechanisms are used to develop the PMSM model and its insulation fault model. Then, the diagnostic features are identified using Hilbert transforms based on artificial data acquired from the simulation results of different degree of the stator winding insulation faults. Next, the diagnosis and prognosis routine pass the diagnostic features to the Extended Kalman Filter (EKF) based on Bayesian estimation theory. Finally, the real-time diagnosis and prognosis of an anomaly detector for PMSM stator winding insulation faults are performed using Simulink. Simulation results are presented to demonstrate the effectiveness of the proposed method.

Fault-Tolerant Control Strategy for 12-Phase Permanent Magnet Synchronous Motor

Multi-phase motors have attracted increasing attention in fields seeking high reliability, such as electric vehicles, ships, and rail transit, as they exhibit advantages, such as high reliability and fault tolerance. In this study, we consider a 12-phase permanent magnet synchronous motor (PMSM). First, a mathematical model of the 12-phase PMSM in the static coordinate system is established and the model is simplified according to the constraint condition of neutral point isolation. Second, according to the principle of invariant magnetomotive force under normal and fault conditions, two optimal control strategies of winding current, i.e. maximum torque output (MTO) and minimum copper consumption (MCC), are proposed. For a single-phase open-circuit fault, two optimization methods are used to reconstruct the residual phase current, such that the motor can maintain normal torque output and exhibit lower torque ripple under the fault state. Finally, system simulation and experimental research are conducted; the results verify the accuracy and feasibility of the fault-tolerant control strategy of the 12-phase PMSM proposed in this paper.

Robust three‐vector‐based low‐complexity model predictive current control with supertwisting‐algorithm‐based second‐order sliding‐mode observer for permanent magnet synchronous motor

This study presents a robust three-vector-based low-complexity model predictive current control with supertwisting-algorithm-based second-order sliding-mode observer for permanent magnet synchronous motor (PMSM). First, to reduce the computational complexity of the three-vector-based model predictive current control, the optimal voltage vector combination is directly determined by the sector of desired voltage vector. Second, a supertwisting-algorithm-based second-order sliding-mode observer is designed to observe the lump disturbance caused by model mismatch and unmodelled dynamics. The estimated lump disturbance is considered as the compensation to the original PMSM model to reduce steady-state current error, which improves the robustness of the three-vector-based model predictive current control. Finally, the effectiveness of the proposed method is verified by experiments on a two-level-inverter-fed PMSM drive platform. Experimental results prove that, compared with three-vector-based model predictive current control, the proposed method can reduce the computational complexity and enhance robustness against motor parameters variation.

Adaptive Fractional Fuzzy Integral Sliding Mode Control for PMSM Model

This paper aims to address the stabilization problem of permanent magnet synchronous motor (PMSM) based wind energy conversion system (WECS) through a novel adaptive fractional fuzzy integral sliding mode control scheme in contrast to the traditional integer order control schemes. The main objective of modeling the fractional order control for nonlinear PMSM is to enhance the convergence rate which is effectively better when compared to integer order control schemes. In addition, this paper intensively investigates the performance of fractional order controllers in both PMSM and surface-mounted PMSM-based WECS through analyzing the global stability of closed-loop system based on Lyapunov stability theory. In this regard, the nonlinear PMSM model is transformed into equivalent linear submodels through an effective Takagi–Sugeno fuzzy membership rules. Then, a novel automated (adaptive) controller is designed along with fractional sliding surface, which involves an integral term to control the considered PMSM. In general, adaptive controllers are much more effective than manual controllers. Further, the sufficient conditions are derived in terms of linear matrix inequalities via constructing the novel fractional fuzzy Lyapunov functional with quadratic terms, which guarantees the global stabilization of PMSM-based WECS. Overall performance and effectiveness of the proposed theoretical results are demonstrated through numerical simulations.