Rotor Position Estimation Error Research Articles

Full-speed domain position sensorless control strategy for PMSM based on a novel phase-locked loop

This paper proposes a full-speed-domain position-sensor-less control strategy for precise control under forward and reverse rotation conditions to address the weak convex polarity of surface-mounted permanent magnet synchronous motor (SPMSM). The strategy comprises several key stages: pre-positioning of the rotor, constant current variable frequency (I/F) start-up, construct the Luenberger State Observer, and utilization of an improved phase-locked loop (PLL) for position estimation. In the pre-positioning stage, a constant amplitude current is applied to drag the rotor to a predetermined position. Subsequently, the I/F start-up stage accelerates the motor to a predetermined speed before transitioning to the Luenberger observer for closed-loop speed control, which is based on an extended back electromotive force (back-EMF) a two-phase rotating coordinate system. The improved PLL for position and speed estimation features three components: a phase discriminator (PD), a voltage-controlled oscillator (VCO), and loop filter (LF). Experimental results demonstrate the efficacy of the proposed strategy, showing quick start-up response, speed estimation error below 2 RPM, rotor position estimation error under 0.6 degrees post-loop closure, stable tracking during rapid speed changes, and consistent accuracy and stability even under reverse rotation conditions, thereby meeting the control strategy’s objectives.

A compensation method for PMSM sensorless control with parameter identification considering SMO observation error

AbstractSensorless control of permanent magnet synchronous motor (PMSM) can increase the reliability of electric actuators of more electrical aircraft. Numerical online parameter estimation method will enhance the performance for sensorless control methods based on sliding mode observer (SMO). However, numerical online parameter identification methods typically assume zero rotor position estimation error to ensure full rank of the identification equation set. This assumption actually leads to errors in parameter identification, resulting in steady‐state errors in rotor position estimation. This paper focuses on a compensation method for PMSM online parameter identification that takes into account rotor position estimation error. This method is used for sensorless control based on SMO, using model reference adaptive systems for online parameter identification, and no additional parameter adjustment required. Validation is conducted on a PMSM experimental platform with maximum load of 15kW. The experimental results of 1000 r/min steady state operation proved the effectiveness of the method, and the dynamic experiments with 5 and 15kW loads proved that the method has no significant adverse effect on the system dynamics.

Multiple Discrete Adaptive Filter Based Position Error Reduction for Sensorless IPMSM Drives

The inverter nonlinearity and the flux spatial harmonics will lead to noticeable (6κ±1) harmonics in the observed back electromotive force (EMF), causing (6κ) pulsations in the rotor position estimation error and deteriorating the performance of sensorless interior permanent magnet synchronous motor (IPMSM) drives. To improve the sensorless IPMSM control accuracy, a multiple discrete adaptive filter (MDAF) embedded between sliding mode observer (SMO) and normalized quadrature phase-locked loop (PLL) is adopted to solve the above problem in this paper. The MDAF consists of a fundamental extraction block and a harmonic cancellation block. Harmonic cancellation works similarly to fundamental extraction, simply by removing the dominant 5th and 7th harmonics from the distorted back-EMF in a frequency multiplicative manner. The proposed algorithm is designed directly in the discrete domain, avoiding the complex discretization process. The open-loop amplitude-frequency characteristic curves show that the method is able to achieve infinite gain exactly at the expected frequency, thus allowing closed-loop zero steady-state error tracking of the back-EMF and providing higher precision for harmonic estimation. The excellent performance of the suggested method is validated based on a 1.5kW sensorless IPMSM control system.

Improved ROGI-FLL-Based Sensorless Model Predictive Current Control With MRAS Parameter Identification for SPMSM Drives

This paper presents a sensorless finite control set model predictive current control (FCS-MPCC) for surface-mounted permanent magnet synchronous motor drives based on an improved reduced-order generalized integrator-frequency-locked loop (IROGI-FLL). To simplify the structure of the sensorless FCS-MPCC and avoid control performance degradation caused by the rotor position estimation error, an instantaneous power theory-based given current calculation method is designed. Accordingly, the whole algorithm can be realized without using rotor position. IROGI-FLL is adopted for filtering the estimated back electromotive force and estimating motor speed. To enhance its dynamic speed tracking performance, a speed tracking deviation compensation term is designed for FLL. With the feedforward compensation term, speed static tracking deviation in acceleration and deceleration states can be eliminated. Moreover, to avoid the adverse effect of parameter mismatch on control performance, an incremental adjustable model-based model reference adaptive system (MRAS) is introduced to identify the resistance and inductance parameters. The incremental adjustable model can avoid identification error caused by the rank deficiency issue. Finally, the effectiveness of the proposed method is investigated by experiments.

Analysis and Compensation of Position Estimation Error for Sensorless Reduced DC-Link Capacitance IPMSM Drives

To extend the lifetime, improve the power density and reduce the system cost, the film capacitor is applied to replace the large-volume electrolytic capacitor in motor drives. As the dc-link voltage fluctuates periodically, the rotor position estimation error and operation stability are necessary to be concerned in the position sensorless control methods. A cross-decoupling complex filtering-based position estimation method is investigated for the reduced capacitance interior permanent magnet synchronous motor drive system. Harmonic components of the extended back electromotive force (EEMF) caused by the dc-link voltage fluctuation are analyzed to evaluate the additional rotor position error. A cross-decoupling complex filter realized by the multiple first-order complex filters with different center frequencies is designed to improve the position estimation precision. Harmonics of the EEMF are suppressed and the position error can be eliminated. The estimation precision and operation ability are improved. Experimental results are performed to verify the effectiveness of the proposed method.

Sensorless Control Analysis of Electric Motor Drives Based on High-Frequency Signal Injection and Its Simulation Verification

The subject of this research is the sensorless control method verification of an asynchronous motor by a simulation in the area of low speed (up to 5 Hz) via the high-frequency analog signal injection method. The implementation of the continuous signal injection method is simpler when compared with the discrete signal injection; however, the discrete signal injection method has more advantages in signal processing. The injected analog signal will be superimposed on the main stator voltage. The response to this signal will be manifested mainly based on the asymmetries of the asynchronous motor, which are given by the design of the motor. The influence of the stator inductance LS will be suppressed by a suitable elimination method since this asymmetry is undesirable for the rotor position detection. The asymmetry caused by the rotor slotting will be used to detect the rotor position. The less the rotor slots are inclined, the stronger the asymmetry. Therefore, to verify the given estimation method as realistically as possible, a mathematical model of an asynchronous motor, including asymmetries due to magnetic core saturation and asymmetries due to rotor slotting, has been designed in order to get as close as possible to the real condition. Thus, the chapter “Asymmetry Creation due to Rotor Slotting” describes the given phenomenon in more detail. Subsequently, the INFORM method the rotor position detection is implemented and defined in the chapter: “Rotor Position Estimation Based on HF Signal Injection.” Given the fact that the asymmetries caused by magnetic core saturation are undesirable, he estimation error reaches up to 10%; therefore, saturations are suppressed by a convenient method. After filtering out these asymmetries, the control accuracy is achieved with the maximum rotor position estimation error of 0.05 rad, representing 1%. The inaccuracy is directly proportional to the rotor rotation speed, and it is also caused by the computing power, the processing frequency, and the complexity of the computing algorithm. The present research paper serves essentially to verify the sensorless method based on a high-frequency signal injection and as a basis for effectiveness and efficiency compared with other control methods.

Real-Time Reduction of Rotor Position Estimation Error Based on the Stator Flux Estimation-Combined Method for Sensorless Control of PMSMs Drives

This paper presents the implantation and the performance improvement of real-time reduction of rotor position estimation error based on the stator flux estimation-combined method for sensorless control of PMSMs drives. Wherein, the proposed method is designed based on a simple algorithm for accurate estimation and robust control of quasi-exact stator flux and position/speed of PMSMs. A large-speed range of applications in sensorless control strategies is achieved by using the mathematical model of PMSM motor. The latter presents the main idea of the estimators’ structures design. They are generally composed of voltage and current models (VM and CM). However, the dynamic performances of these methods are influenced in the low and high-speed ranges, and they are sensitive to parameters variations. The estimators’ structures are dominated by the current model at the low-speed range, and by the voltage model at the high-speed range. The technique proposed in this study is the combination of the two preceding models; this provides performances’ improvement in the PMSM dynamics for a large speed variation with compensating estimation errors for the two separate methods (VM and CM). The main objective of this combined method is the drawback reduction for the separate use of VM and CM estimators. The algorithm principle is based on exploiting and combining the two estimators while measuring the stator voltages and the currents, in addition to estimating the rotor position and the speed. Furthermore, the performances of the proposed method have been tested and validated through real-time experiments by using dSPACE ds 1104 DSP board.

On the estimation error of position sensorless control of PM synchronous motors

The influence of several key parameters of the electric drive system on the rotor position estimation error of the sensorless control is studied. Here a saliency based sensorless method using a zero-sequence carrier is considered. Based on the theoretical analysis, there exists a relationship between the current ripple on three phase currents and the estimation error of the rotor position. Through analysis of a simulation model with LRC load, the change of modulation ratio, neutral capacitance and switching frequency can seriously influence the estimation error. Afterwards, all the simulation analysis was validated on a practical electric drive system with a PM synchronous motor. Variable switching frequency PWM (VSFPWM) is also applied to further increase the accuracy of the rotor position estimation. It is proved that the current ripple surely affects the estimation significantly. This study also paves the way of a further theoretical research of the relationship between the current ripple and estimation error, and thus lays the foundation of an optimized parameter selection for the EDSs using the position sensorless control strategy.

Improved control strategy of dual star permanent magnet synchronous generator based tidal turbine system using sensorless field oriented control and direct power control techniques

ABSTRACT This paper presents a grid-connected tidal stream system with a focus on the reduction of the number of sensors needed by the control scheme. The electromechanical converter is a dual star permanent magnet synchronous generator (DS-PMSG) driven by a horizontal axis marine current turbine (HA-MCT). The generator is controlled via the field-oriented control (FOC) strategy, the speed and the position of the rotor are estimated using an extended Kalman filter (EKF), and the speed is regulated using a fuzzy logic controller. The grid side converter (GSC) consist of a two level voltage source inverter controlled by a virtual flux-based direct power control strategy (VF-DPC), and the current is filtered using an LCL filter. The system is simulated using Matlab/Simulink environment, the simulation results show the efficacy of the proposed control scheme, fuzzy speed regulator, and the EKF estimator, where relative mean error (MRE) of speed tracking is only 0.004, and MRE of estimated speed is as low as 7.3e-6, but a low rotor position estimation error of 1.76 degrees can be observed, however, the high number of pole pairs of the generator amplifies the effect of position error, causing divergences between the controlled dq currents seen by the control scheme and the real dq current that flows in the machine, and a decrease of system effeciency; however, the stability is not affected.

Sensorless PMSM Drive Inductance Estimation Based on a Data-Driven Approach

In the permanent magnet synchronous motor (PMSM) sensorless drive method, motor inductance is a decisive parameter for rotor position estimation. Due to core magnetic saturation, the motor current easily invokes inductance variation and degrades rotor position estimation accuracy. For a constant load torque, saturated inductance and inductance error in the sensorless drive method are constant. Inductance error results in constant rotor position estimation error and minor degradations, such as less optimal torque current, but no speed estimation error. For a periodic load torque, the inductance parameter error periodically fluctuates and, as a result, the position estimation error and speed error also periodically fluctuate. Periodic speed error makes speed regulation and load torque compensation especially difficult. This paper presents an inductance parameter estimator based on polynomial neural network (PNN) machine learning for PMSM sensorless drive with a period load torque compensator. By applying an inductance estimator, we also proposed a magnetic saturation compensation method to minimize periodic speed fluctuation. Simulation and experiments were conducted to validate the proposed method by confirming improved position and speed estimation accuracy and reduced system vibration against periodic load torque.

Performance Analysis of a Full Order Sensorless Control Adaptive Observer for Doubly-Fed Induction Generator in Grid Connected Operation

This paper focuses on the performance analysis of a sensorless control for a Doubly Fed Induction Generator (DFIG) in grid-connected operation for turbine-based wind generation systems. With reference to a conventional stator flux based Field Oriented Control (FOC), a full-order adaptive observer is implemented and a criterion to calculate the observer gain matrix is provided. The observer provides the estimated stator flux and an estimation of the rotor position is also obtained through the measurements of stator and rotor phase currents. Due to parameter inaccuracy, the rotor position estimation is affected by an error. As a novelty of the discussed approach, the rotor position estimation error is considered as an additional machine parameter, and an error tracking procedure is envisioned in order to track the DFIG rotor position with better accuracy. In particular, an adaptive law based on the Lyapunov theory is implemented for the tracking of the rotor position estimation error, and a current injection strategy is developed in order to ensure the necessary tracking sensitivity around zero rotor voltages. The roughly evaluated rotor position can be corrected by means of the tracked rotor position estimation error, so that the corrected rotor position is sent to the FOC for the necessary rotating coordinate transformation. An extensive experimental analysis is carried out on an 11 kW, 4 poles, 400 V/50 Hz induction machine testifying the quality of the sensorless control.

Iron-Loss Modeling With Sensorless Predictive Control of PMBLDC Motor Drive for Electric Vehicle Application

Permanent-magnet brushless dc motor (PMBLDCM) is more suitable for electric vehicle (EV) with higher torque and driving performance. A suitable loss modeling of PMBLDCM with proper analysis can improve the control stability at different road surface conditions. However, the iron loss is not minimal enough to be ignored during high-speed operation of PMBLDCM drives. This article proposes a disturbance observer-based sensorless drive control for accurate estimation of the rotor position. This is achieved by taking the iron loss into consideration in order to further reduce the rotor position estimation error. A modified model predictive control is also proposed to deal with the novel modeling to provide torque ripple-free operation at reduced losses. The EV performances are compared for lossless and loss model of PMBLDCM through both simulation and experimental validation.

Initial Rotor Position Estimation by Detecting Vibration of Permanent Magnet Synchronous Machine

The principal methods of initial rotor position estimation of permanent magnet synchronous machine (PMSM), such as high-frequency rotating signal injection methods and high-frequency pulsating signal injection methods, are implemented by calculating the voltage equations of the stator winding. However, these methods have low adaptability to the PMSMs with different saliency properties and high sensitivity to electrical parameter variations. In this article, an initial rotor position estimation method based on the dynamical equations of the PMSM is proposed to solve the abovementioned problems. First, a series of vibration signals of the PMSM is generated by applying a high-frequency voltage to the rotating virtual d-axis of the rotor. Then, the relationship between the vibration signals and the rotating virtual d-axis position is established. Next, the initial d-axis rotor position of the PMSM is estimated by analyzing the vibration response. Finally, the rotor magnetic polarity is identified on account of the saturation saliency effect. The theoretical analysis and simulation, as well as experiments, are carried out to verify the effectiveness and accuracy of the innovation method. The results demonstrate that the proposed method has the advantages of easy implementation, high adaptability, and strong robustness; also, the maximum initial rotor position estimation error of the proposed method is 1.7 electrical degrees, which is lower than other methods.

Minimization of Additional High-Frequency Torque Ripple for Square-Wave Voltage Injection IPMSM Sensorless Drives

The high-frequency (HF) square-wave voltage injection sensorless control method will bring additional HF torque ripple to interior permanent magnet synchronous motor (IPMSM). Focused on this problem, this article analyzes the relationship between the HF response current and the HF torque ripple resulting from HF square-wave voltage injection. It is concluded that when the fluctuation direction of HF response current is vertical to the stator current vector direction at the maximum torque per ampere (MTPA) operating point, the resulting HF torque ripple reaches its minimum. Based on this conclusion, a novel HF square-wave voltage injection sensorless control method is proposed in this article, which can realize the sensorless control and minimize the HF torque ripple at the same time. The injection angle of HF square-wave voltage in the estimated synchronous rotating reference frame is adjusted in real time according to the operating conditions, so that the HF response current always fluctuates along the vertical direction of the stator current vector at the MTPA operating point. Besides, the corresponding demodulation method of the rotor position estimation error is illustrated. Finally, the experiments are performed on a 20-kW IPMSM platform and the results verify the effectiveness of the proposed method.

Estimation Procedure Based on Less Filtering and Robust Tracking for a Self-Sensing Control of IPMSM

For the self-sensing control of interior permanent magnet synchronous motors (IPMSM), the rotor position and speed estimation based on high-frequency (HF) injection techniques generally employs two parts after the signal injection: signal processing/heterodyning process and tracking. This article proposes significant improvements for these two parts. First, the low-pass filters used in the classical heterodyning process of HF injection techniques are removed, which leads to the proposal of a novel heterodyning process in order to improve the estimation procedure in terms of delays, cost/complexity of implementation, and harmonics. Second, an independent machine parameters estimation based on step-by-step sliding mode observer using only the sign of the rotor position estimation error is developed. Thanks to this observer, the tuning of position, speed, and acceleration observer gains is achieved in a decoupled manner, which ensures states convergence separately in finite time. Third, the machine acceleration is estimated to improve the estimation procedure in transient modes. These contributions enhance significantly the estimation procedure in all operating ranges. A comparative study of the robustness/performance of the proposed strategy and classical tracking algorithms is carried out. Both simulations and experimental tests on an IPMSM rig are conducted in the framework of electric propulsion benchmark used in automotive applications, showing good agreement with the expected results.

High-Precision Rotor Position Correction Strategy for High-Speed Permanent Magnet Synchronous Motor Based on Resolver

A high-precision rotor position correction strategy for a 2.5 kW@10 000 r/min permanent magnet synchronous motor (PMSM) based on the resolver is proposed in this article. The resolver as the rotor position sensor for PMSM has the advantage of long service life and high anti-interference. However, it is common that the unbalance amplitude of the resolver signal and the nonideal resolver-to-digital converter cause the rotor position estimation error. To solve these problems, a self-adaption rotor position correction strategy is proposed. First, the relationship between the q-axis current and the rotor position estimation error is analyzed. The error from estimate and the imbalances of the resolver-to-digital converter circuit are decoupled. Then, a rotor position correction strategy based on self-adaption controller is presented, and the self-adaption controller can compensate the estimation error both from unbalance amplitude of the resolver signal and the nonideal resolver-to-digital converter. Finally, the effectiveness and feasibility of the correction strategy are verified by the experiments on a 2.5 kW@10 000 r/min PMSM platform.

The Rotor Position Estimation Error Improved Method for Sensorless Starting Control of Brushless Synchronous Machine

This article proposed a sensorless starting control method for the brushless synchronous machine with the indirectly injected high-frequency signal, where the high-frequency signals are injected into the stator windings of the main exciter instead of the main generator. The impact of the nonlinear links of the rotary rectifier and various filters on the rotor position estimation error during the asynchronous demodulation method is analyzed in detail. Since the phase delay of the bandpass filter and the low-pass filter will deteriorate the zero-crossing points of the envelope curve, the signal restoration module could not restore the sinusoidal envelope curve accurately, then, the estimated rotor position error is expanded with the increasing of rotor speed in the starting process. Therefore, a novel mathematical analysis method with fewer filters for the rotor position demodulation is presented to improve the estimated rotor position error compared to the traditional method, and the feasibility and effectiveness of the proposed method are verified by the comparison of the simulation and experimental results.

Correction of Rotor Position Estimation Error for High-Speed Permanent Magnet Synchronous Motor Sensorless Drive System Based on Minimum-Current-Tracking Method

This article focuses on the issue of the rotor position estimation error correction for high-speed permanent magnet synchronous motor sensorless drive system. First, a rotor position estimator is designed. Then the estimation error caused by different kinds of nonideal factors is analyzed in detail. Estimation error results in larger amplitude of the stator current, the larger loss, and the degradation of the output torque. To eliminate the estimation error, a novel correction method based on the “minimu-current-tracking (MCT)” method is proposed in this article. The main idea of the proposed method is to obtain the minimum amplitude of the stator current adaptively through the MCT algorithm. The estimation error can be reduced to zero by correcting the compensation factor of the designed position estimator and observing the amplitude of stator current until the amplitude converges to the minimum value. The proposed method has two advantages: 1) the estimation error caused by no matter which kind of nonideal factor can be completely corrected; 2) no sensitive parameters are required in the proposed method. Finally, sufficient simulated results and experimental results verify the effectiveness of the proposed MCT-based method.

A resilient adaptive sliding mode observer for sensorless AC salient pole machine drives based on an improved HF injection method

In high frequency (HF) injection methods, classical tracking algorithms are used to estimate the rotor position for sensorless alternating current (AC) salient pole machines. These algorithms were dependent on AC machine inductances which are characterized by their large variations. To overcome this dependency, a new approach based on using only the sign of the rotor position estimation error (instead of using rotor position estimation error) is proposed. This approach has also the advantage of removing the low-pass filter (LPF) used to separate the HF component from the rotor position information. Consequently, only the first order sliding mode observer can be employed to estimate the rotor position, as only the sign of the rotor position estimation error is known. To avoid the well known chattering phenomena of this observer, an adaptive step-by-step sliding mode observer is proposed as an alternative solution to estimate the rotor position of the machine. The stability study of the proposed observer is analyzed both in transient/steady state ranges and a procedure for gains tuning is then given. The performance of the proposed algorithm is tested on simulation and experimentally in the framework of a representative small-scale electric propulsion benchmark, used in automotive applications. Moreover, a comparison study is conducted with respect to some existing tracking algorithms in order to illustrate the well-founded of the designed algorithm.

Sliding-Mode Sensorless Control of PMSM With Inverter Nonlinearity Compensation

In this paper, a robust adaptive sliding-mode observer (SMO) is designed based on the surface permanent-magnet synchronous machine (SPMSM) model in rotor reference frame ( $\gamma \delta $ -axis), and an online inverter nonlinearity identification and compensation method is proposed. In order to reduce the chattering of the SMO, an adaptive law is presented to help estimate the back electromotive forces of an SPMSM; thus, smaller gains can be set for switching functions of the SMO. The small-signal model of the proposed sensorless scheme is derived for analyzing the steady-state and dynamic behavior of the sensorless scheme. Voltage distortion, caused by nonlinear characteristics of switching devices, not only causes (6 k ± 1)th harmonics in phase currents but also leads to a rotor position estimation error. The equivalent amplitude of the voltage distortion can be identified based on the derived small-signal model of the proposed sensorless scheme. To improve the accuracy of the estimated voltage distortion, a recursive restricted total least squares is applied to obtain the estimated amplitude of the voltage distortion. Experimental results validate the proposed sensorless control scheme and its effectiveness.