Rotor Position Of Motor Research Articles

Position Servo Control of Electromotive Valve Driven by Centralized Winding LATM Using a Kalman Filter Based Load Observer

The exhaust gas recirculation (EGR) valve plays an important role in improving engine fuel economy and reducing emissions. In order to improve the positioning accuracy and robustness of the EGR valve under uncertain dynamics and external disturbances, this paper proposes a positioning servo system design for an electromotive (EM) EGR valve based on the Kalman filter. Taking a novel valve driven by a central winding limited angle torque motor (LATM) as the object, we have fully considered the influence of the motor rotor position and load current, as well as the magnetic field saturation and cogging effect, improved the existing LTAM model, and derived accurate torque expression. The parameter uncertainty of the above internal model and the external stochastic disturbance were unified as “total disturbance”, and a Kalman filter-based observer was designed for disturbance estimations and real-time feed-forward compensation. Furthermore, using non-contact magnetic angle measurements to obtain accurate valve position information, a position control model with real-time response and high accuracy was established. Numerous simulated and experimental data show that in the presence of ± 25% plant model parameter fluctuations and random shock-type disturbances, the servo system scheme proposed in this paper achieves a maximum position deviation of 0.3 mm, a repeatability of positioning accuracy after disturbances of 0.01 mm, and a disturbance recovery time of not more than 250 ms. In addition, the above performance is insensitive to the duration of the disturbance, which demonstrates the strong robustness, high accuracy, and excellent dynamic response capability of the proposed design.

Position Sensorless Vector Control System for Lawnmower Permanent Magnet Synchronous Motor Based on Extended Kalman Filter

In this paper, we describe a position sensorless vector control system for a permanent magnet synchronous motor (PMSM) for a lawnmower in order to solve the problems of inferior dynamic performance and insufficient load resistance in the control process of lawnmower motors. A speed–current double-closed-loop vector control strategy was adopted to control the motor speed; an extended Kalman filter (EKF) was constructed to track the motor rotor position. STM32F407 was selected as the main control chip to establish the hardware experimental platform, and the performance of the control system was evaluated. The experimental results demonstrate that the control system accurately regulates motor speed, has good dynamic response characteristics, and can maintain stability under various loads; therefore, it meets the performance requirements of lawnmower motors in practical operation.

Novel Design of Multi-DOF Motor Position Estimation Based on Wireless Power Transmission Modeling

In this paper, a multi-coil wireless power transmission model is presented. The model is applied to the multi-degree-of-freedom (multi-DOF) motor rotor position detection system. The wireless power transmission (WPT) system is evenly distributed on the upper part of the rotor, and the receiving coil is placed on the rotor shaft. When the motor rotor rotates along the three motion states of pitch, spin and tilt, the receiving coil and multi-transmit coil will produce angle deviation. The precise mutual inductance estimation method can be used to obtain the rotor position quickly and avoid the complicated finite element calculation. The system can not only realize the pose estimation of the multi-DOF motor, but also provide flexible energy supplement for the manipulator. The WPT position measurement method is used for PID control of multi-DOF motor, and it is compared with the micro-electro-mechanical-system (MEMS) attitude measurement method. The mechanical sliding measurement method of the encoder is taken as a reference. The results show that the position detection method of WPT has high accuracy, and the estimation error is less than 2%.

Sensorless HSPMSM Control of an Improved SMC and EKF Based on Immune PSO

Here, for controlling a high-speed flywheel permanent magnet synchronous motor (HSPMSM), a position sensorless control method for estimation of motor rotor position and speed is proposed to address the problems faced by mechanical position sensors of high cost, large size, and poor interference immunity. The extended Kalman filter (EKF) has difficulty obtaining the optimal covariance matrix when performing state estimation. Therefore, the particle swarm algorithm (PSO) with an immune mechanism is used to optimize the covariance matrix of the EKF. However, the EKF algorithm makes the system less robust due to its delay effect. Based on the traditional sliding mode control rate, the exponential convergence law is improved, and the continuous function sat(s) is used instead of the symbolic function sgn(s). This improves the convergence law and proves the asymptotic stability of the designed sliding mode variable structure controller based on Lyapunov’s stability theorem. Then, the novel control law is applied to the sliding mode surface (SMS). An ordinary sliding mode controller (OSMC) using a linear sliding mode controller (LSMC), a global sliding mode controller (GSMC) using a global sliding mode surface (GSMS), and an integral sliding mode controller (ISMC) using an integral sliding mode surface (ISMS) are designed for improving control. Joint simulation in MATLAB and Simulink verifies that the optimized EKF based on the immune PSO can improve precision and accuracy for controlling the electronic rotor position and speed. Comparing the new sliding mode controller with a traditional PI controller reveals that the proposed system has stronger resistance to load disturbance and better robustness.

Sensorless model predictive control based on I‐f integrated sliding mode observer for surface permanent magnet synchronous motor

SummaryDue to the limited fast dynamic response of the dual proportional‐integral (PI) control strategy in sensorless speed control, a novel composite control strategy is proposed for sensorless control of the full speed range of the surface‐mounted permanent magnet synchronous motor. This strategy combines dual closed‐loop model predictive control (MPC) with a sliding mode observer (SMO) and a constant current‐frequency ratio (I‐f). The I‐f control scheme is employed in the low‐speed range, while the SMO is utilized for motor speed and rotor position estimation in the medium and high‐speed ranges, enabling the dual‐loop MPC. Furthermore, a new smooth switching method is proposed for transitioning between the two control methods. In addition, the MPC outer loop parameters were thoroughly analyzed and optimized for better dynamic performance of sensorless control. The steady‐state performance of this control strategy is compared to PI control and improved the dynamic responsiveness of the system. Experiments have verified the feasibility of this strategy. Under the control of the MPC outer loop, the steady‐state speed fluctuation of the motor is within 10 r/min. Compared to PI control, the motor settling time was reduced by 17% and 60% during the start‐up phase and after a sudden speed change, respectively.

Multiparameter Estimation-Based Sensorless Adaptive Direct Voltage MTPA Control for IPMSM Using Fuzzy Logic MRAS

This paper introduces a parameter-estimation-based sensorless adaptive direct voltage maximum torque per ampere (MTPA) control strategy for interior permanent magnet synchronous machines (IPMSMs). In direct voltage control, the motor’s electrical parameters, speed, and rotor position are of great significance. Thus, any mismatch in these parameters or failure to acquire accurate speed or position information leads to a significant deviation in the MTPA trajectory, causing high current consumption and hence affecting the performance of the entire control system. In view of this problem, a fuzzy logic control-based cascaded model reference adaptive system (FLC-MRAS) is introduced to mitigate the effect of parameter variation on the tracking of the MTPA trajectory and to provide precise information about the rotor speed and position. The cascaded scheme consists of two parallel FLC-MRAS for speed and multiparameter estimation. The first MRAS is utilized to estimate motor speed and rotor position to achieve robust sensorless control. However, the speed estimator is highly dependent on time-varying motor parameters. Therefore, the second MRAS is designed to identify the quadratic inductance and permanent magnet flux and continuously update both the speed estimator and control scheme with the identified values to ensure accurate speed estimation and real-time MTPA trajectory tracking. Unlike conventional MRAS, which uses linear proportional-integral controllers (PI-MRAS), an FLC is adopted to replace the PI controllers, ensuring high estimation accuracy and enhancing the robustness of the control system against sudden changes in working conditions. The effectiveness of the proposed scheme is evaluated under different speed and torque conditions. Furthermore, a comparison against the conventional PI-MRAS is extensively investigated to highlight the superiority of the proposed scheme. The evaluation results and our quantitative assessment show the ability of the designed strategy to achieve high estimation accuracy, less oscillation, and a faster convergence rate under different working conditions. The quantitative assessment reveals that the FLC-MRAS can improve the estimation accuracy of speed, permanent magnet flux, and quadratic inductance by 19%, 55.8% and 44.55%, respectively.

An improved initial rotor position estimation method using high-frequency pulsating voltage injection for PMSM

High frequency pulsating voltage injection method is a good candidate for detecting the initial rotor position of permanent magnet synchronous motor. However, traditional methods require a large number of filters, which leads to the deterioration of system stability and dynamic performance. In order to solve these problems, a new signal demodulation method is proposed in this paper. The proposed new method can directly obtain the amplitude of high-frequency current, thus eliminating the use of filters, improving system stability and dynamic performance and saving the work of adjusting filter parameters. In addition, a new magnetic polarity detection method is proposed, which is robust to current measurement noise. Finally, experiments verify the effectiveness of the method.

Identification of Rotor Position of Permanent Magnet Spherical Motor Based on Compressed Sensing

The accurate identification of the rotor position of permanent magnet spherical motor (PMSM) is crucial to its closed-loop control. A novel method for rotor position identification of the PMSM based on compressive sensing is proposed, which can obtain accurate rotor position by a limited number of Hall sensors. Firstly, the paper designs a Hall sensor array based on the distribution characteristics of the rotor magnetic and the frequency domain characteristics of the air gap magnetic field, combined with the Fibonacci sequence. Then, an observation matrix construction method is proposed, used for compressed sensing of the radial magnetic field strength information in air gap. Finally, the position of the spherical rotor is identified according to the reconstructed information based on the sensor output value. The identification method is verified by experiments, which shows that the identification accuracy is about 1 degree.

Position Detection and Speed Recording Method for Power-Off IPMSM in Full-Speed Range Based on Ultrahigh Frequency Signal Injection

For the sensorless interior permanent magnet synchronous motor (IPMSM), this letter proposes a rotor position and speed recording method applied in full-speed range after the main power supply (MPS) is OFF. The proposed method injects ultrahigh-frequency (UHF) sinusoidal voltage into the motor windings after the motor is powered off, and then calculates the motor rotor position and speed in real time by detecting the RMS value of the UHF sinusoidal signals. Based on the UHF signal injection method designed for the low-speed region, this letter improves the injection and detection timing and optimizes the online calculation method of rotor position and speed. The proposed method can work only when there is no power supplied to the motor, and it is used solely for the purpose of recording. This letter implements the first inductance-based full-speed motor power-off rotor position detection and speed calculation. It breaks the cognitive limitation that the inductance-based rotor position detection method is only applicable to the low-speed region.

Designing Ultrahigh Frequency Motor Rotor Position Search Coils for Electric Propulsion in Drones

As the core of electric propulsion in drones, the motor has higher requirements for its reliability and fault tolerance. Accurate acquisition of rotor position information is a prerequisite for a motor-driven drone’s system to operate stably. Traditional search coils can provide fault tolerance for position detection, but they cannot detect rotor position in the full speed range (stationary to rated speed). In order to make the search coils provide rotor position in the full speed range, this study proposes to inject an ultrahigh frequency (UHF) signal (50–100 kHz) into the search coils. By optimizing the self-inductance of the search coil, the mutual inductance between the search coil and the armature winding, the back electromotive force (BEMF) of the search coil, and the mutual inductance between the search coils, the structure of the UHF search coil designed in this paper is helpful to extract the UHF feedback signal. Finally, based on the mapping relationship between the self-inductance of the search coil and the rotor position, the rotor position of the motor can be detected in the full speed range. The novelty of the proposed work lies in the UHF search coil with zero mutual inductance coupling to the armature winding, small BEMF, and low interphase mutual inductance that can detect the rotor position in the full speed domain. Maxwell software is used to optimize the structure of the UHF search coil, and the feasibility of the design results is verified by co-simulation.

Torque control-based induction motor speed control using Anticipating Power Impulse Technique

In this model, the induction motor speed control is based on torque control drive analysis of the output power using Anticipating Power Impulse Technique (APIT). Induction motors are used in various applications; this is a model of a motor used in constant speed applications. Vibrations and singularities are eliminated with the sliding mode control of conventional terminals. In this method, the reference state is determined in a systematic manner so that the maximum torque per ampere and flux limiting operation and the reference torque tracking can be determined. The difficulty of a controller driver is choosing a switch with the proper control scheme to achieve dynamic and steady-state response speed requirements and the proposed method is completely varied from the conventional model. An Anticipating Power Impulse Technique (APIT) is the proposed system for the induction motor drive control; it is also applied to the speed control of the motor. The system presented here analyses motor current and rotor position, which helps to obtain a suitable switching pulse diver circuit, because of low switching loss speed control. In this system, MATLAB software is used to develop control circuit simulations. It is expected that the simulation output will reduce the torque ripple verified by experiments and Anticipating Power Impulse Technique (APIT), giving the system output excellent stability.

Application Research of Pulse Vibration High-Frequency Voltage Injection Method Without Speed Sensor in New Energy Vehicles

The high-frequency voltage injection method of pulse vibration in the range of zero/low speed to medium-high speed has to be demonstrated for new energy vehicles., because it is very necessary and necessary to control the safety performance of the whole vehicle without speed sensor. The permanent magnet synchronous motor starts slowly to circle when the clean - energy vehicle cranked, and the correctness of the rotor’s startup position identification is significant. In order to achieve high-performance control of permanent magnet synchronous motor without speed sensor, this paper focuses mainly on how to estimate the rotor position of permanent magnet synchronous motor by amplifying the mathematical model of the motor. The high-frequency mathematical model of the permanent magnet synchronous motor’s voltage parameters are attained in the process of maintaining the motor’s preoperational position to address the problem of self-adaptability between the injected voltage and the likely phase current. The initial position identification of the rotor of a permanent magnet synchronous motor can be achieved by optimizing the adaptive method, and the pulse vibration highfrequency voltage anesthetic method also shows better efficiency and safety when the motor achieves a stable start and has sound output torque. The struggling to retain adaptive measurement device vibration high frequency voltage injection approaches is used by the light-duty low-speed new energy vehicle, which may minimize the mechanical speed sensor after becoming damaged, save the cost and improve the compactness of the electric vehicle space design, which is conducive to solving the situation of energy shortage in my country and alleviating environmental pollution. This is in line with the future development concept of society.

Sensorless control of marine permanent magnet synchronous propulsion motor based on adaptive extended Kalman filter

Gross error interference or noise statistical deviation is the main factor that leads to the accuracy deterioration of extended Kalman filter (EKF) in estimating the speed and rotor position of ship propulsion permanent magnet synchronous motor (PMSM). In this paper, an adaptive extended Kalman filter (AEKF) algorithm based on innovation sequence is proposed. In the proposed method, gross error interference is first added to EKF to analyze its influence on the observation accuracy. Then, the weighting coefficient is set in the calculation of innovation covariance. By adjusting the weight of the innovation covariance matrix at the adjacent time, the innovation covariance difference is calculated and then used in the calculation of Kalman gain. The observation performance comparison between AEKF and EKF strategies is conducted with subject to gross error interference and noise statistics deviate. Simulation and experimental results demonstrate that the proposed AEKF has stronger robustness and higher prediction accuracy of speed and rotor position.

Vector Control of Permanent Magnet Synchronous Motor Based on MRAS Method

In recent years, the application range of electric energy in modern industry has gradually expanded. Permanent magnet synchronous motor has the characteristics of high efficiency and energy saving, and has obvious advantages in traction application. In order to achieve good vector control of permanent magnet synchronous motor in the full speed range, Research on model reference adaptive system (MRAS) and pulsating high frequency injection method to construct the permanent magnet synchronous motor vector control system, and combined with the flux weakening control algorithm to control the motor under the condition of limited inverter output, so as to realize the sensorless vector control of the motor in the full speed range. The difference between the estimated value of the algorithm and the actual value is compared on the actual experimental platform to verify the feasibility of the control algorithm. The experimental results show that, Under medium and high-speed working conditions, the motor speed and rotor position tracking accuracy of MRAS algorithm is high, and the tracking error is less than 0.01rad. The pulsating high-frequency injection method can accurately track the permanent magnet synchronous motor under low-speed working conditions, the speed error is less than 1n / R / min, and the rotor position error is less than 0.03rad. The static and dynamic performance of the control system is good, It can better deal with the sudden change of motor load. Using MRAS algorithm and pulsating high frequency injection method to control permanent magnet synchronous motor in full speed range is of great significance to improve the speed control performance of permanent magnet synchronous motor.

Research on Application of High-Frequency Pulse Vibration in Ship Electric Propulsion System

Aiming at the problems existing in the method of using sensors to detect the rotor position of marine main propulsion motor at low speed, a sensorless rotor position identification method based on high-frequency pulse vibration signal is proposed. In this method, the low-pass filter is used to separate the high-frequency signal component, and the current component of d-axis to q-axis is demodulated. The control mode of PI action law is used to phase-locked processing of the demodulated signal, in which purpose is to obtain the rotor position signal. The design method is simulated and verified by MATLAB/Simulink software. The error between the estimated position and the actual position of the rotor in the simulation waveform is small, and the accuracy is high. The simulation results show that this method can achieve good results when applied to the ship electric propulsion system without position sensor, which provides a theoretical reference for the design of marine main propulsion motor control system.

New Rotor Position Redundancy Decoding Method Based on Resolver Decoder.

In view of the frequent safety problems of electric vehicles, the research on accurately obtaining the rotor position of the motor through the resolver is an important means to improve the functional safety of the system. The commonly used resolver decoding method involves the resolver decoding chip method and software decoding method, but few studies integrate the two decoding methods. A single method of motor rotor position acquisition cannot meet the requirements of system functional safety. To fill this gap, this paper proposes a method to simultaneously integrate hardware decoding and software decoding in the motor control system. The decoding chip and software decoding obtain the angle data at the same time, and they provide redundancy to improve the functional safety of the electronic control system. Finally, the effectiveness of the proposed simultaneous operation of hardware decoding and software decoding is verified by experiments.

Sensorless Control of Permanent Magnet Synchronous Motor in Full Speed Range

Aiming at resolving the limitation of the speed regulation range of sensorless control technology, a new composite sensorless control strategy is proposed to realize a control method for a permanent magnet synchronous motor (PMSM) in full speed range. In the medium- and high-speed range, the improved new sliding mode observer method is used to estimate the motor speed and rotor position information. In the zero and low speed range, in order to avoid the defects of the sliding mode method, the rotating high-frequency voltage signal injection method is used. When switching between low, medium, and high speed, the fuzzy control algorithm is adopted to achieve smooth transitions. The simulation experiment results show that the hybrid mode combining the sliding mode observer and rotating high-frequency voltage injection methods, can effectively reduce the jitter in the algorithm switching process, and realize the smooth control of a PMSM in full speed range.

Particle swarm optimization based interval type 2 fuzzy logic control for motor rotor position control of artificial heart pump

Artificial heart pump (AHP) is employed to replace the native damaged heart and perform its functions. Bearingless brushless DC (BBLDC) motors are used for the implementation of the AHP. BBLDC motor is a highly nonlinear model with uncertainties and its mathematical model is hard to be found accurately. In this paper, BBLDC motor is simulated. Proportional plus integral (PI) controller is proposed to control the rotor suspension current. Furthermore, a type 2 proportional plus integral plus derivative-like fuzzy logic controller (T2 PID-Like FLC) is proposed to control the motor rotor (x, y) positions. Particle swarm optimization (PSO) technique is employed to find the best controller scaling factors and to optimize the controller inputs membership functions distribution within its universe of discourse. Simulation results showed enhancement in levitating the rotor to the required position, when using T2 PID-like FLC as compared with using type 1 PID-like fuzzy logic controller. The enhancement is measured using integral of absolute error (IAE) as a cost function to achieve 64.18% and 81.81% in the x and y axes respectively. The Performance of the motor is enhanced by 20%, which decreases the rotor oscillation and increases the ability to withstand the system disturbances and nonlinearity

Research On Sensorless Control Of Permanent Magnet Synchronous Motor

Aiming at the problem that there is no position sensor to observe the rotor position and speed of the built-in permanent magnet synchronous motor under the traditional method of high frequency rotating voltage signal injection, the estimation accuracy of rotor position and speed is low because of the use of a variety of filters in the signal demodulation process. The generalized second-order integrator is used to replace the traditional filters to extract the high frequency response current. In order to reduce the filtering delay problem existing in the traditional signal demodulation method, a new signal demodulation method is proposed, and the rotor position estimation is compensated with appropriate phase compensation. At the same time, appropriate phase compensation is carried out for the estimation of rotor position By constructing IPMSM sensorless vector control simulation module in Simulink simulation, compared with the traditional high-frequency injection method, the improved algorithm can estimate the rotor magnetic pole position more accurately and faster in the process of sensorless control of the motor in the low speed range, and has better stability introduction.

Low speed sensorless control method of brushless DC motor based on pulse high frequency voltage injection

A low speed sensorless position control method for brushless DC motor based on pulse pulse high frequency voltage injection is proposed according to the characteristic that the brushless DC motor (BLDCM) which is produced at present makes the counter electromotive force waveform show sinusoidal waveform in view of the problem that it is difficult to accurately obtain the rotor position and speed of the brushless DC motor at zero and low speed. Its principle is to inject high frequency sinusoidal voltage signal on the estimated direct axis of the synchronous rotating coordinate system so that the motor can generate saturated salient effect, obtain the estimation error containing the rotor position information, and by detecting the output current of PI regulator of quadrature axis current loop, and then estimate the initial position of the rotor and judges the magnetic pole, realize the determination of the actual rotor position, finally, realize the non-position static low speed control of BLDCM by adding current and speed rings. According to the simulation test, it shows that this method can detect the position and speed of the motor rotor well at both zero speed and low speed.