Parameters Of Permanent Magnet Synchronous Motor Research Articles

Direct torque control for PMSM based on the RBFNN surrogate model of electromagnetic torque and stator flux linkage

Direct Torque Control (DTC) is widely used in motion control of motors. Classical DTC utilizes the Park transformation(dq-model) or observer to estimate the stator fluxlinkage and electromagnetic torque. However, the dq-model and observer lack descriptions of the cogging torque and magnetic saturation in permanent magnet synchronous motors (PMSM). This paper proposes a novel method based on the surrogate model to estimate stator fluxlinkage and torque for PMSM DTC. First, a finite element model (FEM) was established based on the parameters of PMSM. Using the FEM and Latin hypercube sampling (LHS), a surrogate model for estimating the stator fluxlinkage and torque of PMSM was constructed. The stator fluxlinkage and torque surrogate model, active flux observer, and dq current model under different control methods are constructed, respectively. The servo control parameters were tuned using the extended symmetric optimum algorithm, and simulation and experiments were conducted. Finally, electromechanical coupling models with a ball screw feed system were built based on various control and feedback methods. Simulation and experiment results indicate that the surrogate model reduces torque ripple, stator fluxlinkage offset, and feed system tracking error.

Adaptive Quick Sliding Mode Reaching Law and Disturbance Observer for Robust PMSM Control Systems

The permanent magnet synchronous motor (PMSM) has been of interest to eco-friendly industries on account of its advantages such as high performance, efficiency, and precision control. However, perturbations due to PMSM parameter uncertainty, load torque, and external disturbance interfere with the construction of PMSM precision control systems. Therefore, a robust control system is needed to avoid unnecessary system movement caused by perturbations. In this paper, sliding mode control (SMC) is adopted to implement a robust control system for the PMSM. In order to reduce the reaching time from the initial system state to the sliding surface and the chattering phenomenon that can cause the system to malfunction, the adaptive quick sliding mode reaching law based on an exponential function and power equation is proposed. Although the SMC is robust to disturbance and parameter uncertainty, unexpected disturbances can destabilize the system. To estimate the unmatched disturbance in a short time, the second-order fast terminal sliding mode observer (SFTSMO) is proposed. The results show that the motor control system based on the proposed method has a fast convergence speed to an objective value, position tracking performance, and robustness.

Simulation of Speed Control on a PMSM Using a PI Controller

In order to manage the speed of a permanent magnet synchronous motor drive system, a practical approach for a PI controller has been developed and put into practice in this study. The adopted approach, which also preserves the proportional integral controller's straightforward structure and features, significantly enhanced the performance of the prior proportional integral controller. The final PI controller delivers quick and precise response, strong noise rejection, and minimal sensitivity to permanent magnet synchronous motor parameter fluctuations. The findings demonstrate that the suggested controller may provide best performance in terms of accuracy, parametric variation, and load torque disturbance when entering a proportional value of 0,013 and an integral value of 16,61. The proposed method has been exhaustively tested under various circumstances. The proposed solution not only possesses attributes like simplicity and ease of implementation for real-time, but also stability and effectiveness.

Parameter Identification of Permanent Magnet Synchronous Motor with Dynamic Forgetting Factor Based on H∞ Filtering Algorithm

To address system parameter changes during permanent magnet synchronous motor (PMSM) operation, an H∞ filtering algorithm with a dynamic forgetting factor is proposed for online identification of motor resistance and inductance. First, a standard linear discrete PMSM parameter identification model is established; then, the discrete H∞ filtering algorithm is derived using game theory reducing state and measurement noise influence. A cost function is defined, solving extremes values of different terms. A dynamic forgetting factor is introduced to the weighted combination of initial and current measurement noise covariance matrices, eliminating identification issues from different initial values. On this basis, a dynamic forgetting factor is added to weigh the combination of the initial measurement noise covariance matrix and the current measurement noise covariance matrix, which eliminates the influence of the discrimination error caused by the different initial values. Finally, the identification model is built in MATLAB/Simulink for simulation analysis to verify the feasibility of the proposed algorithm. The simulation results show the proposed H∞ filtering algorithm rapidly and accurately identifies resistance and inductance values with significantly improved robustness. The forgetting factor enables quick stable recognition even with poor initial values, enhancing PMSM control performance.

An application of kho-Kho optimization algorithm to estimation parameter of permanent magnet synchronous machine

Permanent magnet synchronous motors (PMSM) are among the popular motors used in industrial applications. Designing an appropriate control scheme to obtain the desired output for these motors depends on the motor parameters. In this aspect, this paper presents the application of a well-known meta-heuristics optimization scheme, i.e., the Kho-Kho optimization (KKO) algorithm to estimate the parameters of PMSM. The KKO algorithm introduced in [1] is a population-based meta-heuristic optimization scheme that replicated the chasing strategy of a defending team in a Kho-Kho game. To show the supremacy of the suggested scheme in determining the unknown parameters of the PMSM, a PMSM with known coefficients is considered and the parameter of the model is estimated using the KKO algorithm.

Investigation on application and running characteristics of permanent magnet synchronous motor used in lifting system of deep well drilling rig

Most geological drilling rigs using asynchronous motor with gear box as the drive device of drawworks have problems of instability at low speed, complex mechanism, and lots maintenance work. This paper proposes an application of permanent magnet synchronous motor (PMSM) used in drawworks. Firstly, running characteristics of PMSM in steady state are analyzed and calculated theoretically, and mathematical models of motor’s power, torque, and power loss are given. Secondly, vector control principle of PMSM is analyzed and introduced, and maximum torque/current control method is finally decided as the basis for the design of control system. Thirdly, running parameters of PMSM in three stages (lowering drill string, constant speed/pressure drilling, and lifting drill string) of each test point were measured, and the curves of key parameters of PMSM are given. Finally, it is concluded that drawworks with PMSMs can not only improve control performance, reduce power consumption, and save energy, but also omit the gearbox, which makes structure of lifting system more compact and reduce lots maintenance work. The research work of this paper lays a foundation for the popularization and application of PMSM in the industry of deep well drilling rig.

Intelligent Parameter Identification and Sensorless Control of Permanent Magnet Synchronous Motor

In this paper, a spider monkey optimisation (SMO) algorithm is utilised to identify the parameters of the permanent magnet synchronous motor (PMSM), considering the parameters vary during the motor operation, which affects the sensorless control (SC) performance of the motor. An improved sliding mode observer (SOBS) is proposed for estimating the position and speed of the rotor. First, the SMO algorithm is used to identify the parameters of PMSM. Then, based on the identification results, an improved SOBS is proposed by a piecewise Sigmoid function. Furthermore, the stator position and speed are estimated by extended state observer (ESO) and phase-locked loop (PLL). Finally, a comparison simulation scenario is provided to demonstrate the efficacy of the suggested approach.

Comparison of Differential Evolution and Nelder–Mead Algorithms for Identification of Line-Start Permanent Magnet Synchronous Motor Parameters

Line-start permanent magnet synchronous motors (LSPMSMs) are of great interest to researchers because of their high energy efficiency, due to the growing interest of manufacturers in energy-efficient units. However, LSPMSMs face some difficulties in starting and synchronization processes. The LSPMSM lumped parameter model is applicable to estimating the successfulness of starting and further synchronization. The parameters of such a model can be determined using computer-aided identification algorithms applied to real motor transient processes’ curves. This problem demands significant computational time. A comparison between two algorithms, differential evolution and Nelder–Mead, is presented in this article. The algorithms were used for 0.55 kW, 1500 rpm LSPMSM parameter identification. Moreover, to increase computational speed, it is proposed to stop and restart the algorithms’ procedures, changing their parameters after a certain number of iterations. A significant advantage of the Nelder–Mead algorithm is shown for the solving of the considered problem.

Model-Free Predictive Current and Disturbance Rejection Control of Dual Three-Phase PMSM Drives Using Optimal Virtual Vector Modulation

Model-based predictive current control (MBPCC) relies heavily on adequate system modeling and accurate parameters. The detailed models of dual three-phase permanent magnet synchronous motors (PMSMs) contain mutual cross-coupling dynamics which make it difficult to extract accurate parameters. Also, some of the physical parameters of PMSMs are generally nonlinear functions of current and rotor position. In this article, a model-free predictive current control (MFPCC) based on an ultralocal model and an extended state observer is proposed for an asymmetrical dual three-phase (ADTP) PMSM. The MFPCC method is shown to provide superior current regulation when compared to the standard MBPCC approach under uncertain parameter conditions. Furthermore, the harmonic currents and the current ripple in the ADTP PMSM drive have been regulated to near-zero values by using optimized voltage vectors comprised of virtual vectors and null vectors. A generalized center-aligned pulsewidth modulation (PWM) scheme is presented to facilitate the synthesis of the optimal virtual voltage vectors for implementation on a low-cost digital signal processing platform. The performance improvements of the MFPCC with optimal virtual vector modulation are verified and compared with the conventional MBPCC method in both simulations and experiments on a surface-mount type dual three-phase PMSM.

Sensorless control of permanent magnet synchronous motor based on adaptive back-EMF observer

Aiming at the problem that the change of motor parameters in actual operation will significantly reduce the control accuracy of the motor, this paper proposes a sensorless control method of permanent magnet synchronous motor based on an adaptive back-EMF observer. Firstly, in the sensorless vector control algorithm, the mathematical model of the permanent magnet synchronous motor based on the coordinate axis transformation is established, online identification of permanent magnet synchronous motor flux linkage, and the adaptive back EMF observer is constructed. The parameters update the motor model to achieve accurate control of the rotor position and speed of the permanent magnet synchronous motor. Then the back-EMF observer and the adaptive back-EMF observer are verified in the simulation environment. Then the simulation model of the back-EMF observer and the adaptive back-EMF observer is carried out, and the comparison analysis is made. Finally, a permanent magnet synchronous motor control platform is built in the laboratory, and the method proposed in this paper is verified. The results show that, under the condition that the permanent magnet synchronous motor parameters change, the online identification of the parameters and the accurate speed of the permanent magnet synchronous motor can be realized control.

Adaptive quasi-proportional resonant control with parameter estimation for PMSM sensorless control

Conventional sliding mode control (SMO) utilizes a sign function and a low-pass filter (LPF) to achieve sensorless control of a permanent magnet synchronous motor (PMSM). However, the introduction of the sign function generates a large number of high harmonics, resulting in a significant system output chattering, whereas the addition of the LPF generates control delays and phase shifts. These degrade the PMSM speed and the position estimation accuracy and reduce the system control performance. To improve the performance of the PMSM, adaptive quasi-proportional resonant sensorless control with parameter estimation (AQPR_PE) is proposed. In this control model, an adaptive quasi-proportional resonance controller is used reduce the system output error and to weaken the chattering phenomenon. Meanwhile, the system PMSM parameters are estimated online and fed back to the control model to improve the system parameter robustness and the control accuracy. The Bode diagram, Popov theory, and root trajectory are used to analyze the stability of AQPR, parameter estimation, and AQPR_PE, respectively. Finally, the effectiveness of the proposed method is demonstrated by experimental validation.

Dual Mode Symmetrical Proportional Resonant Controlled Quadratic Boost Converter for PMSM-Drive

Power electronics-based converters have been widely used in several applications, specifically electric propulsion systems. Ongoing advancements in converters have led to high-gain Quadratic Boost Converters (QBC) which control Permanent Magnet Synchronous Motor (PMSM) drive. In this work, a novel scheme is employed, particularly a three-phase inverter between QBC and PMSM operated by a dual-mode controller strategy. Precisely, the novelty of this work is to use the quadratic boost converter to control the PMSM drive by applying different control strategies. This work also demonstrates the simulation of two different current control strategies applied to a Semi-Converter (SC) fed QBC based on PMSM-based EV. It also presents the strategy, inquiry, and model of SC-based QBC three-phase inverter (TPI) fed PMSM with symmetrical operated PI (Proportional Integral), FOPID (Fractional Order Proportional Integral Derivative), and PR (Proportional Resonant) controllers. The simulated results offer a significant improvement in PMSM parameters compared with the PI-PI framework, notably voltage, speed, and torque against source disturbances. Further, the PR-PR control approach provides better time-domain parameters than the PI-PI control strategy (including the least rise time (Tr) of 1.15 s, peak time (Tp) of 2.38 s, settling time (Ts) of 4.12 s, and steady-state error (Ess) of 4.89 s). Furthermore, the experimental module is designed to test the effectiveness of the proposed control strategies and was found to be more advantageous in dual mode symmetric PR-PR controlled SC-based QBC-TPI fed PMSM.

효율적인 온라인 PMSM 매개변수 추정 방법

This paper proposes an efficient estimation method for PMSM (Permanent Magnet Synchronous Motor) parameters. We usually need to precisely estimate PMSM parameter values of the flux linkage, stator inductance, and resistance for accurate control, condition monitoring, fault diagnosis and prognosis, or others. The conventional methods to estimate the flux linkage, stator inductance, and resistance involve the manipulation of matrices of size 3 by 3 or higher dimensions, which leads to heavy computational burdens. This paper provides a simpler estimation method involving 2-by-2 matrix manipulations. Using the estimated PMSM parameter values of the flux linkage, stator inductance, and resistance, we design an adaptive PI-type PMSM controller. Through numerical comparative simulations, this paper verifies the practicality and efficiency of the proposed method.

Comparative analysis of features of online numerical methods used for parameter estimation of PMSM

As permanent magnet synchronous motors (PMSM) have high power density, efficiency, good dynamic performance, and small size they are becoming popular in electric vehicle (EV) applications. Control performance and the efficiency of the system get affected due to electrical, mechanical parameters. Parameters value gets affected by voltage source inverter (VSI) non-linearities, temperature and magnetic saturation effects. If exact parameters for particular torque speed requirement are found, the efficiency of system increases. There are various offline and online methods for finding parameters. Offline methods are easy to implement but requires extra setup and estimate parameters in steady state. Because the effects of transient conditions are taken into account during identification, online methods for obtaining real-time data under running conditions are becoming more popular. An overview about online numerical methods to estimate electrical parameters of PMSM is given. It discusses difference between various methods in terms of computational cost, convergence speed, noise and identification error. Choosing of method will be easy using this work. For inductance estimation, the extended Kalman filter (EKF) algorithm has an identification error of 0.24% under temperature effect and -0.3% under VSI non-linearities effect. The identification error for Rs and ψf using the recursive least square (RLS) method is 0.5% and 0.02%, respectively, when temperature is considered. EKF and RLS algorithms are proposed.

Real-Time SIL Validation of a Novel PMSM Control Based on Deep Deterministic Policy Gradient Scheme for Electrified Vehicles

Vector control plays a critical role in a permanent magnet synchronous motor (PMSM) drive to deliver the desired torque in electrified vehicle applications. Motor speed and stator current control depend on various nonlinear motor parameters that influence the performance of PMSM. Moreover, tuning of speed and current controller parameters using conventional control techniques also depends on these PMSM parameters. To enhance the robustness of vector control and tracking methodology against PMSM parameter uncertainties and load disturbances, a novel deep reinforcement learning (DRL) based advanced speed and current control technique is proposed in this article. The proposed method mitigates the effects of disturbance due to parameter variations as well as the load torque. The novel architecture delivers closed-loop reinforcement learning agents trained with the deep deterministic policy gradient learning algorithm in the plant environment where the cost of exploration is expensive. First, an overview and need for the proposed DRL vector control architecture are provided. Subsequently, the design and training methods for the proposed DRL controller are elicited. Thereafter, the proposed control scheme is validated with real-time software-in-the-loop testing under various conditions and compared against adaptive proportional–integral control of the same PMSM in OPAL-RT simulator.

PMSM Current Harmonics Control Technique Based on Speed Adaptive Robust Control

Permanent magnet synchronous motor (PMSM) is widely used in electric vehicles due to its high power density. New requirements are constantly proposed with the development of PMSM, one of which is torque ripple. Current harmonic injection is a common method to minimize torque ripple. Designing effective controller to realize current harmonic injection is the key technology. In this paper, the transient voltage-current coupling equation considering magnetic saturation is derived by introducing incremental inductance. After appropriately simplifying, it is shown in form of the harmonic state space (HSS) equation. Considering that PMSM parameters varies with current due to magnetic saturation, robust controller is adopted to ensure stability. In order to eliminate the influence of motor speed change on control stability, the HSS is transformed into a spatial form. Then the speed adaptive robust (SAR) controller is designed. At last, the SAR controller is used in simulation and test bench experiment to verify dynamic response and stability. Compared with traditional PI and PR controller, the SAR controller can ensure good dynamic response, steady-state error and robust stability when speed and PMSM parameters vary. Moreover, SAR controller can well resist the harmonic coupling effect and system lag.

Transfer Mechanism Analysis of Injected Voltage Harmonic and its Effect on Current Harmonic Regulation in FOC PMSM

Harmonic injection method is widely used in the suppression of current harmonic and torque ripple in field-oriented control (FOC) permanent magnet synchronous motor (PMSM) servo system. However, under some working conditions of FOC PMSM, the harmonic injection method fails to suppress the current harmonics and causes oscillation. To analyze the cause of oscillation, the transfer mechanism of injected voltage harmonic is analyzed in this article, and the relation between injected voltage harmonic and current harmonic is derived. The theoretical analysis results show that the relation between harmonics will change with motor speed and parameters of FOC PMSM. When the relation between harmonics is reversed, the existing harmonic injection method will fail and cause harmonic oscillation. To solve this problem, a simple improvement of the harmonic injection method is proposed in this article based on the proposed close-loop model. The correctness of the mathematical derivation and the effectiveness of the proposed method is evaluated by experiment and simulation.

Robust plug-in repetitive control for speed smoothness of cascaded-PI PMSM drive

Non-ideal factors can cause steady-state speed ripples for Permanent Magnet Synchronous Motor (PMSM). In this paper current measurement error is mainly analyzed since it can cause multiple (not only 1st- or 2nd-order as analyzed in the existing literature) harmonics when considering its influence on electrical angle. In order to suppress the ripples, a robust plug-in repetitive controller with phase compensation is designed in the outer speed loop of PMSM cascade PI control system. Compared with the repetitive controller added in the current loop, there are two technical challenges: more stringent requirement of high-frequency disturbance suppression and more complex phase compensation design. Hence, a third-order Butterworth filter with phase correction is proposed which can ensure the system’s ability to resist low-frequency periodic disturbances and the high-frequency stability of the system. A hybrid phase correction method combining lead, lag and linear correction is designed which can ensure the stability and the fast convergence of the system at low frequencies. The designed repetitive controller is robust to PMSM parameters variation within a normal range. The experimental results prove that the proposed control strategy can effectively suppress motor speed fluctuation with good steady-state and transient performance.

An Online Flux Estimation for Dual Three-Phase SPMSM Drives Using Position-Offset Injection

The rotor flux linkage of permanent-magnet synchronous motor (PMSM) is of great importance for monitoring and high-performance control. However, most of the existing online estimation methods need prior knowledge of other PMSM parameters such as stator resistance and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> axis inductance, which are difficult to realize in the rank-deficient models of electrical machines. This article proposes a simple online estimation method of rotor flux linkage for the dual three-phase surface-mounted PMSM (SPMSM) drives with the assistance of injected position offset. The independent estimation model has been developed for the rotor flux linkage by appropriate setting of positon offset between two sets of three-phase windings of dual three-phase SPMSM drives. The proposed method not only has little influence on the output torque and high signal-to-noise ratio for observation, but also offers the superior performance in estimation accuracy irrespective of the influence of VSI nonlinearity. In addition, the proposed position-offset-based method is suitable for the full-speed region including the field-weakening operation. Finally, comprehensive experimental results are presented to verify validity of the proposed method under different working conditions.

PMSM Parameter Estimation for Sensorless FOC Based on Differential Power Factor

During the last years, different methods for identifying permanent magnet synchronous motor (PMSM) parameters have been developed. Such methods allow a better characterization of PMSMs, thus enabling a better control. This article presents a novel PMSM parameter estimation method based on the differential power factor due to the harmonic distortion, which allows the identification of the motor parameters from data acquisitions representing the entire torque-speed range. This method does not require measuring any geometric parameters, thus avoiding motor disassembly, or prior knowledge of the applied field oriented control (FOC) strategy. It also enables identifying the current, voltage, and dq components of the flux linkage without knowing the rotor position. The proposed method is based on a dq electrical model that considers the harmonic components of the electrical magnitudes. It avoids to apply any optimization technique, thus requiring a low computational burden. The method is first validated experimentally by comparing the identified dq current space vector against the acquired one using a resolver associated with a commercial drive. Finally, it is further validated by using a second PMSM associated with a sensorless drive, comparing the identified dq inductances with ground truth data obtained by a validated method.