Control Of Permanent Magnet Synchronous Motor Research Articles

Model-Free Predictive Current Control of Five-Phase PMSM Drives

Model predictive control is highly dependent on accurate models and the parameters of electric motor drives. Multiphase permanent magnet synchronous motors (PMSMs) contain nonlinear parameters and mutual cross-coupling dynamics, resulting in challenges in modeling and parameter acquisition. To lessen the parameter dependence of current predictions, a model-free predictive current control (MFPCC) strategy based on an ultra-local model and motor outputs is proposed for five-phase PMSM drives. The ultra-local model is constructed according to the differential equation of current. The inherent relation between the parameters in the predictive current model and the ultra-local model is analyzed in detail. The unknowns of the ultra-local model are estimated using the motor current and voltage at different time instants without requiring motor parameters or observers. Moreover, space vector modulation technology is employed to minimize the voltage tracking error. Finally, simulations and experiments are conducted to verify the effectiveness of the MFPCC with space vector modulation. The results confirm that the proposed method can effectively eliminate the impact of motor parameters and improve steady-state performance. Moreover, this control strategy demonstrates good robustness against load variations.

Sensorless control of dual three-phase permanent magnet synchronous motor based on speed feedback and frequency-variable tracking.

The dual three-phase Permanent Magnet Synchronous Motor (PMSM) control system is characterized by its high reliability, slight torque fluctuation and low harmonic content. It is very suitable for systems requiring high power output and high reliability, for instance, electric vehicles, aerospace and military equipment. In this paper, a full speed domain sensorless control technology for dual three-phase PMSM is proposed which solves the limitations of other sensorless controls, improves system accuracy and stability, and has high practicality in fields such as new energy vehicles. The mathematical model of this motor in a static coordinate system is established, and the sine and cosine signals along with the velocity and angle information are obtained by using the flux linkage observer. Moreover, the estimated angle error parameter is introduced into the flux linkage observer; as a result, the estimation accuracy is improved by the estimated speed feedback, and the current frequency is tracked by the stator current Frequency-Variable Tracker (FVT) to reduce the current error. Meanwhile, to make the observer's estimation more accurate and to improve its ability to resist disturbance, a rotor disturbance is added to act as a disturbance variable. Through the mechanical motion equation of the motor, a fourth-order Extended State Observer (ESO) is built to calculate the rotor position and speed. Finally, the technology accuracy is verified using simulation and experimental results. The findings prove that the sensorless detection technology, with speed feedback introduce in this paper, has good reliability and high precision for dual three-phase PMSM under dynamic and static conditions.

Novel Composite Speed Control of Permanent Magnet Synchronous Motor Using Integral Sliding Mode Approach

Permanent magnet synchronous motors (PMSMs) are widely applied in industry, and proportional integral (PI) controllers are often used to control PMSMs. Aiming at the characteristics of the poor anti-disturbance ability and speed ripple of traditional PI controllers, a novel composite speed controller for PMSMs is proposed in this paper that uses a novel sliding mode control (SMC). To improve the chattering problem of traditional SMC, a high-order approaching law super-twisting algorithm (STA) is applied. Considering the internal and external disturbance of motor driver systems, such as motor parameter drifts and load torque changes, a disturbance estimator based on an extended state observer (ESO) is proposed, and it is used for the feed-forward compensation of the current. The composite super-twisting integral sliding mode controller (ST-ISMC) with a nonlinear ESO is tested by simulations and experiments, and the comparative results verify that the proposed controller has the higher control accuracy, smaller speed ripple and stronger robustness.

Multiscenarios Parameter Optimization Method for Active Disturbance Rejection Control of PMSM Based on Deep Reinforcement Learning

In this article, a multi-scenarios parameter optimization method for active disturbance rejection controller (ADRC) of permanent magnet synchronous motor (PMSM) based on deep reinforcement learning (DRL) is proposed as MSPO-DRL. The parameter setting of nonlinear ADRC has always been one of the difficulties affecting the optimal performance of ADRC, and there will be different optimal parameters under different control requirements. In this article, artificial intelligence algorithm is introduced into the parameter optimization process of ADRC, and the DRL parameter optimization model which can automatically optimize and adjust the ADRC parameters in different application scenarios is constructed so that the ADRC can achieve the best control effect conveniently, and the limitation of current methods has been solved. ADRC is applied to the speed loop of flux weakening control of PMSM for more electric aircraft, and the mathematical model of ADRC in this environment is built above all. The Markov decision process is integrated into ADRC. The interface module and reward function between ADRC and MSPO-DRL are designed. The concept of ADRC control scenario is defined and integrated into the concept of Markov decision process to improve the generalization of DRL. Then the MSPO-DRL model is established, and the deep deterministic gradient strategy is used as the gradient descent strategy to converge the parameters optimization. After the model learning is completed, different environmental conditions are randomly selected for simulation and experiments to verify the optimization effect and generalization performance of the algorithm. Optimizations which are carried out by the heuristic algorithms are used for comparisons, and the superiority and feasibility of the proposed algorithm is verified.

Predictive Torque Control of the Vehicle’s Permanent-Magnet Synchronous-Motor Model Based on Multi-Objective Sorting

The permanent-magnet synchronous motor (PMSM), with the advantages of low energy consumption and stable operation, is considered a green power source to replace gasoline engines. Motor control is the core problem of the electric-drive system, so it is important to study the high-performance motor control algorithm. The traditional PMSM control strategy has problems such as torque pulsation, large overshoot, and parameters which are not easy to adjust. This work proposes a new model-predictive torque control (MPTC) based on multi-objective ranking for these issues. The Romberg observer was utilized to accurately estimate motor flux and torque across a wide range of speeds and ensure optimal performance of the MPTC. The optional voltage vectors were classified using graph theory. The model’s cost function was optimized and the control delay caused by hardware processing was compensated by a modified Euler method. A multi-objective ranking method was used to avoid the offline selection of MPTC weight coefficients. Additionally, one ranking method was used to reduce the complexity of the algorithm for multiple objectives. Based on the simulation results, the newly proposed MPTC method, when compared with traditional approaches, reduced the total harmonic distortion from 2.78% to 2.26%. Torque ripple decreased by approximately 58.4%, and the switching frequency was reduced by 3.05%, lowering the inverter’s switching losses. Therefore, the newly proposed MPTC had faster torque response, reduced computation time, and less torque pulsation, which further improved the dynamic performance of the permanent-magnet synchronous motor.

Extended State Observer-Based Predictive Current Control for Dual Three-Phase PMSM with High Dynamic Performance

Model predictive controllers are widely discussed in the field of dual three-phase permanent magnet synchronous motor control. However, conventional predictive current controllers usually suffer from parameter inaccuracies or model uncertainties, resulting in prediction errors and deterioration of control performance. Therefore, in this paper, an extended state observer-based (ESO) model predictive current controller is proposed to effectively improve the dynamic performance of the motor and its robustness to parameters or disturbances. Parameter inaccuracies or model uncertainties are considered to be lumped disturbances and expressed in the modified mathematical model of the motor. Then, with the designed observer estimating the external disturbances in real time, the prediction error is compensated and corrected periodically. Additionally, the parameter design method of the observer is presented to simplify the controller design. Finally, comparative experiments are implemented to sufficiently demonstrate the effectiveness of the proposed method for dynamic performance improvement as well as for parameter robustness. The results show that the proposed method takes only 17μs of computation time with a closed-loop bandwidth of 1839rad/s. In addition, the maximum d-axis following error of the proposed method is only 0.10A in the load dynamics experiments, which is a significant improvement compared to the 0.79A of the traditional proportional-integral controller.

Speed Estimation Strategy for Closed-Loop Control of PMSM Based on PSO Optimized KF Series Algorithms

In this paper, solving the problem of the noise covariance matrix parameters tuning of the extended Kalman filter (EKF) and unscented Kalman filter algorithms (UKF) is difficult. A speed estimation strategy for a permanent magnet synchronous motor (PMSM) based on particle swarm optimization (PSO) optimized Kalman filter (KF) series algorithms is proposed. By using MATLAB/Simulink, in this paper, 20 effective simulation experiments on the noise covariance matrix parameter optimization process are conducted to obtain the optimal covariance matrix parameters of the extended Kalman filter and unscented Kalman filter. Moreover, EKF, PSO-EKF, UKF, and PSO-UKF are also compared to verify the effectiveness of the particle swarm optimization algorithm in optimizing the systems using the extended Kalman filter and unscented Kalman filter. For the error of speed estimation, taking 4000 rpm as a reference, the system using PSO-EKF has improved by 2.125% compared to that using EKF, and the system applying PSO-UKF has improved by 0.55% compared to the system applying UKF. For the error of electrical angle estimation, taking the system errors of original algorithms as references, the system adopting PSO-EKF has decreased by 60% compared to that adopting EKF, and the system using PSO-UKF has decreased by 47% compared to the system using UKF.

Double-hierarchical fuzzy exponential convergence law fractional-order sliding mode control for PMSM drive control in EV

In the vector control of permanent magnet synchronous motor (PMSM), the speed overshoot and torque pulsation phenomena need to be solved. There are two prerequisites for the drive control of PMSM in electric vehicle (EV). The first is that the vehicle control has to be ensured as a whole. The second is, to ensure the economy of the vehicle control while ensuring the stable control of the motor. Therefore, this paper first proposes the fuzzy exponential convergence law fractional-order sliding mode control (F-CFSMC), it is constructed with the purpose of online correction of the exponential convergence law of the fractional-order sliding mode surface. It is expressing the arrival time and convergence speed of the fractional-order sliding mode surface explicitly with parameters. The stability of the F-CFSMC is proved to be derived using the Lyapunov equation. The F-CFSMC is applicable to PMSMs with different parameters. Next, the fuzzy controller that considers the battery parameter factor in EV is introduced to combine the lithium battery and PMSM to enhance energy utilization. At this point, the double-hierarchical fuzzy exponential convergence law fractional-order sliding mode control (DF-CFSMC) build is complete. Moreover, comparative simulations and experiments using the DF-CFSMC and the conventional PMSM control are conducted, and the results are performed in PMSM hierarchical. Simulations are also performed in the EV hierarchical application to show the universality, repeatability and advantages of DF-CFSMC.

Speed Control of PMSM Based on Fuzzy Active Disturbance Rejection Control under Small Disturbances

Permanent Magnet Synchronous Motors (PMSMs), with their simple design, small size, and high-power factor, are ideally suited for realizing high-power AC drives and are widely used in various industries. In this study, Fuzzy Active Disturbance Rejection Control (Fuzzy-ADRC) is used to control the speed of the PMSM. When a slight external disturbance occurs, this control strategy maintains the suppression characteristics of the self-excited control for the disturbance and enhances its ability to compensate for the disturbance. First, a mathematical model was developed to study the surface mount PMSM. Then, a motor control simulation model was created using PI control, vector control, and other control methods. The verification results indicate that the improved Fuzzy-ADRC system performs well under both internal and external minor disturbances. It exhibits a faster dynamic response and reduced regulation time (0.026 s to 0.017 s) compared to the traditional ADRC system. Furthermore, it shows less overshoot (reduced from 70% to 2.9%) compared to the Sliding Mode Observer (SMO). Taken together, the improved Fuzzy-ADRC system is characterized by small steady-state error, high load capacity, and control accuracy. With the assistance of this control strategy, the system can track speed with high accuracy and possesses stronger anti-interference capability to mitigate load disturbances.

Sliding mode control with an adaptive switching power reaching law

This paper proposes a adaptive reaching law-based sliding mode control (SMC) method for maintaining favorable velocity control performance of permanent magnet synchronous motors (PMSMs) under internal and external perturbations. An adaptive switching power reaching law (ASPRL) is designed, which contains adaptive terms and state variables of the sliding mode surface function. This augmented reaching law decreases the chatter of the control system and increases the rate at which the state variables of the system reach the sliding mode surface. Additionally, a Luenberger observer load torque (LOLT) is designed to observe the external load and provide feedback to the velocity controller, reducing the impact of load disturbances and improving the jamming performance of the controller. Simulation experiments confirm that ASPRL reduces buffeting, decreases overshoot, and shortens response time, demonstrating its advantages in PMSM control.

A novel sliding mode control with MRAS inertia identification for permanent magnet synchronous motors

To enhance the anti-inertia disturbance ability of permanent magnet synchronous motor (PMSM) speed system, an adaptive sliding mode control with inertia identification is proposed. A novel sliding mode control (NSMC) based on a new reaching law coupled with model reference adaptive system (MRAS) inertia identification is realized the adaptive control, named MRAS+NSMC. In the NSMC construct process, an integral sliding mode surface and a variable speed reaching law are introduced to avoid speed differentiation and improve dynamics, respectively. And the new reaching law imported a successive sigmoid( s) to replace the traditional sign( s) to suppress chattering phenomena. For the problem that the performance deteriorated by rotational inertia variation caused by load changes, the inertia is estimated in real time according to the MRAS theory, and the identification value is updated to the NSMC controller to realize adaptive MRAS+NSMC speed control. Experimental results show that the proposed adaptive MRAS+NSMC control has a faster speed response, and the speed response time is reduced from 85 to 49 ms compared with conventional SMC control. In addition, it has strong robustness to inertia disturbances and high speed tracking accuracy. Compared with conventional SMC, the speed tracking accuracy of proposed MRAS+NSMC is increased from 12% to 4%. This makes the proposed MRAS+NSMC control has great potential practical significance for speed control of PMSM.

Research on current dual closed-loop scheme for PMSM control system utilizing cascaded PI-RC controller

In the permanent magnet synchronous motor (PMSM) control system used proportional integral (PI) controller, a large resonance in high-frequency band will be generated through the PI controller. Additionally, high amount alternating current harmonics will be introduced to the PMSM caused by the inverter nonlinearity and other factors, which cannot be eliminated by PI controller. To eliminate the current harmonics in the control system, a novel current dual closed-loop scheme used the PI controller on the current inner loop and the repetitive controller on the current outer loop (cascaded PI-RC controller) is proposed in this paper. First of all, the reference current signal is added to the inner current loop, thus, the satisfied dynamic performance to the control system can be guaranteed. And then, the frequency characteristic and the resonance of the control plant are analysed. Furthermore, in order to suppress the periodic current harmonics for this PMSM, the internal model element and the compensator are studied for the current outer loop controller. Consequently, the stability of the proposed cascaded PI-RC controller is actual by Lyapunov theory. Finally, the effectiveness of the proposed current dual closed-loop scheme is verified by simulation results.

Design and performance analysis of cascaded pseudo derivative feedback plus pseudo derivative feedforward controller for PMSM drive

PurposeThis paper aims to present a cascaded pseudo derivative feedback (PDF) plus pseudo derivative feedback plus pseudo derivative feedforward (PDFF) controller for a permanent magnet synchronous motor (PMSM) to improve the transient response of the system.Design/methodology/approachProportional integral (PI) plus PI controller and the proposed PDF plus PDFF controller are designed, stability analysis is performed using the extended root locus method, and the effect of the damping coefficient is also extensively studied to validate the robustness of the proposed controller.FindingsWhen compared to a cascaded PI plus PI controller, the proposed control approach has a much shorter settling time for the entire system and a 50% reduction in overshoot in stator current under extensive variations in speed with load disturbance.Originality/valueThe proposed controller is programmed into an FPGA Altera Cyclone II and applied to a 1.5 kW laboratory prototype PMSM drive. The effectiveness of the proposed methods has been demonstrated experimentally throughout a wide variable speed range, from 0 to 157 rad/s at different load conditions.

Dynamic modelling of locomotive with direct drive traction system considering electromechanical coupling effect

Permanent magnet synchronous motors (PMSMs) have been employed in the direct drive traction system of locomotives as the traction motor. Due to the unique traction structure of the direct drive system, complicated excitations such as track irregularity and harmonic torque have a direct effect on the dynamic performance of the motor and other key components of the locomotive. However, the dynamic characteristics under this effect and influencing law have not been revealed completely. This paper develops a dynamics model of a locomotive with direct drive traction system which enables considering the electromechanical coupling effect between the vehicle subsystem and the PMSM control subsystem. The nonlinearity of the wheel–rail contact and flexible transmission coupling are taken into account in this model. By using this model, the dynamic responses of the locomotive are analysed under electrical and mechanical excitations. The results indicate that the harmonic components in the electrical subsystem have considerable effects on the key components of the locomotive, such as the wheelsets and the motors. It can also cause resonance in the mechanical transmission system when the locomotive is operating at a specific speed. This resonance can be eliminated by adopting the harmonic suppression algorithm.

Sensorless Control Method for SPMSMs Based on Improved Sliding Mode Reaching Rate

Due to the advantages of simple structure, small size, and high power density, permanent magnet synchronous motors (PMSM) have attracted the research interest of many scholars both domestically and abroad. However, traditional PMSM equipped with sensors, encoders, and other devices tend to have high equipment costs and rely heavily on the accuracy of the sensors for control effectiveness. Therefore, sensorless control has become a hot trend in the PMSM control field. In response to the chattering problem in sliding mode algorithms, this study first optimized the sliding mode reaching rate of a sensorless control system and applied it to construct a sliding mode observer and speed controller. Next, the improved sliding mode reaching rate-based sensorless control system was modeled and simulated in Matlab/Simulink, and its control performance was compared and analyzed with that of the traditional sliding mode reaching rate and replicated sliding mode reaching rate. Finally, comparative experiments were conducted on a test bench, and the results showed that, under the action of the improved sliding mode reaching rate, the chattering range of the output speed of the motor was +2%~+5%, which optimized the output speed of the PMSM and achieved the purpose of weakening the chattering.

Design of permanent magnet synchronous motor control system for electric vehicle air conditioning compressor

The permanent magnet synchronous motor (PMSM) is extensively utilized in electric vehicle air conditioning compressor control systems due to its numerous advantages, including high efficiency, lightweight design, compact size, excellent reliability, and low maintenance costs. In order to achieve PMSM without position sensor full speed range operation, this paper designs an optimized control strategy for full speed range operation. At low and zero speed, the I/F control mode is employed to achieve quick motor startup with minimized repetition rate, avoiding the overcurrent problem that is easy to occur by traditional V/F control, and the control is switched to the Phase-locked Loop (PLL) adaptive sliding mode observer (SMO) for position estimation at medium and high speed, avoiding the problems of high-frequency jitter and low position accuracy of traditional SMO. The feasibility of this strategy is confirmed by the simulation results of Simulink.

Finite Position Set-Phase-Locked Loop With Low Computational Burden for Sensorless Control of PMSM Drives

This letter proposes a novel finite position set-phase locked loop (FPS-PLL) for permanent-magnet synchronous motors (PMSMs) sensorless drives. A novel cost function is designed to combine with the dichotomy of position for ensuring the astringency of iteration. After the dichotomy of position, through adopting the Newton iteration, the accurate rotor position is obtained only by three iterations. The convergence analysis and calculation accuracy expression are given. Moreover, no parameters need to be adjusted and fast dynamic response is achieved. Compared with reported FPS-PLLs, the calculated burden is markedly reduced. Eventually, the effectiveness of proposed scheme is verified by experiments.

An Improved Integral Sliding Mode Control for PMSM Drives Based on New Variable Rate Reaching Law With Adaptive Reduced-Order PI Observer

This paper focuses on speed control in a permanent-magnet synchronous motor (PMSM). To promote the speed tracking performance and anti-disturbance property of PMSM speed regulation system against various unknown disturbances, such as parameter mismatch, load torque variation, friction force, and so on, an improved integral sliding mode control (IISMC) method based on a new variable rate reaching law (NVRRL) and an adaptive reduced-order proportional integral observer (AROPIO) is proposed. The NVRRL method can reduce chattering, and convergence time of the system state at the same time compared to the existing sliding mode reaching law. An anti-windup sliding mode surface is proposed to overcome the overshoot problem of the integral sliding mode surface when the reference speed is large and rises in steps or large ramps. To further improve the system tracking accuracy and anti-disturbance ability, an AROPIO is used to estimate lumped disturbances and provides feedforward compensation for the IISMC. The simulation and experimental results show that the proposed IISMC+AROPIO method not only achieves high speed tracking accuracy and fast convergence speed but also achieves strong anti-interference ability.

Vector Control of PMSM Using TD3 Reinforcement Learning Algorithm

Permanent magnet synchronous motor (PMSM) drive systems are commonly utilized in mobile electric drive systems due to their high efficiency, high power density, and low maintenance cost. To reduce the tracking error of the permanent magnet synchronous motor, a reinforcement learning (RL) control algorithm based on double delay deterministic gradient algorithm (TD3) is proposed. The physical modeling of PMSM is carried out in Simulink, and the current controller controlling id-axis and iq-axis in the current loop is replaced by a reinforcement learning controller. The optimal control network parameters were obtained through simulation learning, and DDPG, BP, and LQG algorithms were simulated and compared under the same conditions. In the experiment part, the trained RL network was compiled into C code according to the workflow with the help of rapid prototyping control, and then downloaded to the controller for testing. The measured output signal is consistent with the simulation results, which shows that the algorithm can significantly reduce the tracking error under the variable speed of the motor, making the system have a fast response.

An ampere‐second‐vector pulse width modulation technique and fault‐tolerant control for CSI11 fed five‐phase permanent magnet synchronous motor with multiple harmonic electromotive forces

AbstractWhen dealing with safety‐critical applications that involve multiphase permanent magnet synchronous motors (PMSMs), the current source inverter (CSI) is a superior choice compared with the voltage source inverter. The conventional technique of pulse width modulation (PWM) presents a challenge for CSI, particularly during faults. The fault‐tolerant control of multiphase PMSMs fed by CSIs has not been well investigated, particularly in situations involving double‐phase open‐circuit faults. Furthermore, fault‐tolerant control becomes more complex when the multiphase PMSM includes harmonic back electromotive forces (EMFs). To deal with these issues, an ampere‐second (AS) vector PWM technique is developed for a five‐phase PMSM powered by CSI11. The modulation ratio of the proposed PWM is identical to that of space vector PWM. The proposed method, however, is easier to implement. A fault‐tolerant control method using AS‐vector is proposed for single‐phase, adjacent double‐phase, and non‐adjacent double‐phase open‐circuit faults. Additionally, a method is developed to suppress the torque ripple that results from harmonic back‐EMFs during fault conditions. Compared without the torque ripple suppression method, during the speed rising, the proposed method can reduce torque ripple to 16.7%, 54.5%, and 37.5%, respectively. The experiments have confirmed the effectiveness of the proposed PWM technique and fault‐tolerant control method.