Sensorless Permanent Magnet Research Articles

Design and Implementation of Improved Gate Driver Circuit for Sensorless Permanent Magnet Synchronous Motor Control

Reliable motor control is important for electric vehicle applications. The control process requires accurate measurements of the current and rotor position information to establish correct motor control design, particularly in sensorless permanent magnet synchronous motor control systems. Practical issues regarding the motor control circuit, such as the effects of parasitic element behavior on the switching components in the insulated gate bipolar transistor-driven inverter, were discussed in this study. It analyzed the effects of parasitic elements that can cause the ringing of switching losses and affect the spike of the signal in the motor current, which must be avoided in the implementation of motor control. The gate driver circuit topology was improved to reduce this effect in motor control devices. The proposed gate driver circuit design with the ringing suppression circuit configuration achieved good performance by keeping the signal spike at less than 10% in the motor current. Furthermore, a signal spike or noise was not observed in the estimation results of rotor position when using current information as the parameter control process. Both conditions were verified by experiments on the designed motor control devices. Under these conditions, signal precision can be achieved in motor control.

A review of sensorless permanent magnet synchronous motors with adaptive observer

A review of sensorless permanent magnet synchronous motors with adaptive observer

Design of sensorless permanent magnet synchronous motor controller based on improved sliding mode observer

Because PMSM needs to install a position sensor in practical application, and the buffeting issue in sensorless control stems from an old SMO (sliding mode observer), an improved SMO is proposed. Stemming from the improvement of the switching function and low-pass filter of the traditional SMO, the chattering problem of the conventional SMO is optimized. Considering the reality that the traditional PI control strategy unable to respond accurately and quickly in the case of current coupling, the current complete decoupling integrates the traditional PI control method is adopted. It can speed up system response and improve system performance. The experimental consequence demonstrates that the improved SMO can effectively restrain the chattering phenomenon and realize the fast and precise control of the PMSM.

Three‐phase current reconstruction method for permanent magnet synchronous motor based on current transformer sensors

AbstractThe position sensorless permanent magnet synchronous motor (PMSM), with its simple structure, is applied in the aerospace field with high reliability requirements. To drive PMSM safely, the three‐phase current measured from the driver needs to be isolated for the closed‐loop control. And then, the accuracy current measurement is crucial for achieving optimal motor performance. In the paper, current transformer (CT) with centre taps is employed to isolate and measure the high‐frequency current of the inverter switch. Additionally, an algorithm is proposed to reconstruct the switch current into the low‐frequency phase current. Subsequently, the measuring method and the algorithm are applied to an inverter platform, which drives a 100W PMSM. Finally, the reconstructed phase current waveform is compared with the measured phase current waveform, and the experimental results show that the above method is effective and feasible.

Sequence-Separation Complex-Vector Observer in Sensorless PMSM Drives for BEMF Trajectory Optimization

The back-electromotive force (BEMF)-based position estimation is attractive for sensorless permanent magnet synchronous motor (PMSM) drives. However, it shows weak robustness against the low-frequency disturbance induced by the practical nonideal conditions. This results in the trajectory deviation of the estimated BEMF, causing apparent position estimation error. To address this problem, this paper proposed a sequence-separation complex vector observer to optimize the trajectory of the estimated BEMF. First, a sequence separation structure is designed to remove the response of the equivalent negative sequence disturbance at the operation frequency. On this basis, the speed-adaptive disturbance compensation law is added into the observer to force the center of the estimated BEMF converging to the original point. Compared with the conventional method, the studied BEMF observer can ensure accurate position estimation by optimizing the trajectory of estimated BEMF. Finally, the studied algorithm is experimentally verified on a 2.2kW ARM-based PMSM platform.

Multi-Optimization Objective Online Tracking-Based Parameter Self-Tuning Method for Sensorless PMSM Drives

It is important to optimize control parameters for the high-performance operation of position sensorless permanent magnet synchronous motor (PMSM) drives. In this article, a multi-optimization objective online tracking (MOOT)-based parameter self-tuning method is proposed to improve the sensorless control performance when the high-frequency signal injection (HFSI) method is used, which involves both offline and online stages. By the parameter self-learning and the model analysis, the injection signal, the position observer, the speed, and current regulators are preliminarily designed offline to ensure that the system can start smoothly. Based on the parameter characteristics analysis, an adaptive law with the speed ripple and torque ripple as the optimization index is designed to realize the online tracking of control and observation parameters. To solve the issues of tuning delay and mistuning, a moving window-based error detection strategy is investigated, which improves the parameter self-tuning speed and accuracy. The proposed method can improve the steady- and transient-state performance and realize the sensorless debug-free operation for HFSI-based method. The effectiveness is verified by experiments on a 2.2-kW PMSM drive platform.

High-Frequency Injection Angle Self-Adjustment Based Online Position Error Suppression Method for Sensorless PMSM Drives

In the high-frequency (HF) signal injection based position sensorless permanent magnet synchronous motor (PMSM) drives, there is an estimated position error caused by the cross-saturation effect and other factors. In order to suppress the position error, an HF injection angle self-adjustment based online suppression method is proposed in this letter. By tracking the sign of the increment of the absolute back electromotive force in the estimated frame, the criterion of the HF injection angle self-adjustment can be determined online and the position error can be mitigated effectively. This method can avoid the offline measurement or the variation of the operating state, which has a satisfactory suppression effect for the position error under different operating conditions. The effectiveness is verified by experiments on a 2.2-kW PMSM drive platform.

Research on compound control strategy of sensorless permanent magnet synchronous motor

Research on compound control strategy of sensorless permanent magnet synchronous motor

Research on compound control strategy of sensorless permanent magnet synchronous motor

Research on compound control strategy of sensorless permanent magnet synchronous motor

Self-Balancing Control of Yarn Number Based on a Novel Sensorless PMSM Speed Drive System

The performance of the motor drive system is responsible for the yarn feeding quality of the weft accumulator. The existing motor drive systems have problems such as slow start–stop and poor dynamic response performance, resulting in slow yarn tracking speed and low precision of the weft accumulator. This article proposes a new self-balancing yarn number control method based on a novel sensorless permanent magnet synchronous motor (PMSM) speed drive system. The novel sensorless PMSM speed drive system is constructed to improve the dynamic response performance of PMSM by integrating an improved sliding mode observer, a simplified initial position detection method, and a new hybrid control method. The self-balancing yarn number closed-loop control method is proposed based on a pseudoderivative feedback controller to improve the response speed and accuracy of yarn feeding. The general design principle is given, and various tests are carried out. The results show that the proposed drive system has characteristics of a fast start–stop and high dynamic response, which can meet the high-response and high-precision yarn feeding requirements of the weft accumulator.

Adaptive Quasi-Proportional-Resonant Observer-Based Rotor Position Estimation for Sensorless PMSM Drives

It is important to improve the accuracy of rotor position estimation for the high-performance operation of position sensorless permanent magnet synchronous motor (PMSM) drives. To mitigate the position harmonic error caused by the nonideal factors in high-frequency signal injection based methods, an adaptive quasi-proportional-resonant rotor position observer (AQPRO) for sensorless PMSM drives is proposed in this article. The AQPRO can track the estimation error and generate the compensation value, which can realize online suppression for position error. By analyzing the stability and the influence of parameters of the proposed position observer on the suppression performance, a proportional-resonant gain self-tuning strategy is investigated to improve the suppression effect of the position harmonic error for different loads and speeds. The influence of self-tuning regulator parameters is modeled and analyzed in detail. The proposed method does not require offline detection and has a strong suppression ability for different harmonic error components. The effectiveness is verified by experiments on a 2.2-kW PMSM drive platform.

Adaptive Iterative Learning Control-Based Rotor Position Harmonic Error Suppression Method for Sensorless PMSM Drives

Accurate rotor position estimation is important to ensure the high-performance operation of position sensorless permanent magnet synchronous motor (PMSM) drives. To suppress the estimated rotor position harmonic error (ERPHE) caused by inverter nonlinearities, flux spatial harmonics, and the current measurement error in high-frequency signal injection-based schemes, an adaptive iterative learning control-based online suppression method is proposed in this article. This method constructs a P-type iterative learning rotor position observer with the forgetting factor to obtain the tracking error and generate the compensation value in real time. The stability, the convergence, and the parameter sensitivity of this observer are analyzed in detail. To improve the suppression effect of the ERPHE for different loads and speeds, an iterative learning gain self-tuning strategy is investigated. The proposed method does not require the offline detection and the discrimination of harmonic frequencies, which has strong suppression ability for different harmonic error components. The effectiveness is verified by experiments on a 2.2-kW interior PMSM drive platform.

Instant Closing of Permanent Magnet Synchronous Motor Control Systems at Open-Loop Start

Nowadays, position sensorless permanent magnet synchronous motor drives are gaining popularity quite rapidly, and have become almost standard in many applications such as compressors, high speed pumps, etc. All of these drives involve estimators to calculate the speed and the position of the rotor, which are necessary for proper operation of vector control. While these estimators, with the exception of injection-based ones, work well in the middle and high-speed ranges, they cannot operate at low speeds. In order to overcome this problem, sensorless control systems include different starting techniques, with the most popular being open-loop starting. In this approach, the motor is accelerated in open-loop mode until it reaches the speed where estimator operates stably, then the control system is closed. However, the weakest point of this method is the technology of closing the system, which typically creates transients and can even be the cause of loss of stability. This paper proposes a method for instant and seamless transition from open-loop to closed loop which works perfectly under different load conditions. Other starting techniques are considered and compared with the proposed method.

Online Temperature Identification Strategy for Position Sensorless PMSM Drives With Position Error Adaptive Compensation

For the position sensorless permanent magnet synchronous motor (PMSM) drive system, the online identification of temperature is of great significance for safe operation. Generally, the motor temperature can be obtained directly from the stator resistance, the identification of which is, however, affected by the position estimation error of sensorless control. In order to deal with this problem, a stator temperature identification method for the interior PMSM is proposed with the position error adaptive compensation. The influence of position error on the stator resistance and temperature identification is analyzed and then compensated based on the minimum current vector online tracking (MCVOT) scheme for improving the identification precision. For further improving the accuracy and the convergence rate of MCVOT, a current vector angle tracking strategy based on the adaptive variable tracking step value is adopted in the rotating reference frame. The validity of the proposed method is verified on two experimental platforms.

Static-Errorless Position Estimation for Sensorless PMSM Drives With Enhanced Robustness Against the Full-Frequency Domain Disturbance

The back-electromotive force (BEMF) model-based position estimation is attractive for sensorless permanent magnet synchronous motor (PMSM) drives. However, the conventional method cannot ensure the robustness against the full-frequency domain disturbance, which results in the position estimation error. To address this problem, this article proposed a static-errorless position estimation strategy for sensorless PMSM drives. First, a second-order BEMF observer is proposed to achieve the bandpass characteristics for the simultaneous elimination of dc error and high-frequency noise. Second, a speed-adaptive notch filter-based phase-locked loop is presented to suppress the fluctuation caused by the medium-frequency harmonics. Compared with the conventional method, the studied static-errorless position estimation strategy shows strong robustness against disturbance in the full-frequency range. This ensures the finite-time convergence of position estimation. Finally, the studied algorithm is experimentally verified on a 4.4 kW ARM-based PMSM platform.

Mixed Fault Classification of Sensorless PMSM Drive in Dynamic Operations Based on External Stray Flux Sensors.

This paper aims to classify local demagnetisation and inter-turn short-circuit (ITSC) on position sensorless permanent magnet synchronous motors (PMSM) in transient states based on external stray flux and learning classifier. Within the framework, four supervised machine learning tools were tested: ensemble decision tree (EDT), k-nearest neighbours (KNN), support vector machine (SVM), and feedforward neural network (FNN). All algorithms are trained on datasets from one operational profile but tested on other different operation profiles. Their input features or spectrograms are computed from resampled time-series data based on the estimated position of the rotor from one stray flux sensor through an optimisation problem. This eliminates the need for the position sensors, allowing for the fault classification of sensorless PMSM drives using only two external stray flux sensors alone. Both SVM and FNN algorithms could identify a single fault of the magnet defect with an accuracy higher than 95% in transient states. For mixed faults, the FNN-based algorithm could identify ITSC in parallel-strands stator winding and local partial demagnetisation with an accuracy of 87.1%.

Sliding mode control with observer for permanent magnet synchronous machine drives

<span lang="EN-US">This <span>paper aims to develop the sliding mode control (SMC) scheme in sensorless permanent magnet synchronous machine (PMSM) drives to replace conventional proportional integral (PI) speed control. The SMC is formulated based on the integral sliding surface of the speed error. And the error is corrected based on the concept of Lyapunov stability. The SMC is designed with the load torque observer so that the disturbance can be estimated as feedback to the controller. The vector control technique which is also known as field-oriented control (FOC) is also used to split the stator current into the magnetic field generating part which is the direct axis and the torque generating part which is the quadrature axis. This can be done by using Park and Clarke transformations. The performance of the proposed SMC is tested under changes in load-torque and without load for different speed commands. The results prove that the SMC produces robust performances under variations of speeds and load disturbances. The effectiveness of the proposed method is verified and simulated by using MATLAB/SIMULINK </span>software.</span>

Multilevel Inverter fed Direct Torque and Flux Control‐Space Vector Modulation of Speed Sensorless Permanent Magnet Synchronous Motor drive with Improved Steady State and Dynamic Characteristics

AbstractIn this paper, multilevel inverter (MLI) fed direct torque and flux control with space vector modulation (DTFC‐SVM) of speed sensorless permanent‐magnet synchronous motor (PMSM) drive is proposed to improve the steady‐state and dynamic performance characteristics with less torque and flux ripples. In the DTFC‐SVM technique, the speed of PMSM drive is regulated by controlling stator flux and electromagnetic torque directly and independently. The MLIs further extend the performance characteristics of motor drive with reduced electromagnetic torque ripple and improved dynamics. Further, the robustness and reliability of drive system is improved by implementing the speed estimation control technique to eliminate the speed sensor usage. The model reference adaptive system (MRAS)‐based speed estimator is used to estimate the PMSM speed. The proposed method is simulated in MATLAB/SIMULINK environment using two‐level, three‐level, and five‐level inverter under different operating conditions, respectively. The proposed method with five‐level inverter gives very less ripples in electromagnetic torque and stator flux which consequences excellent steady‐state and dynamic performance of drive. The effectiveness and feasibility of the proposed method is validated by implementing hardware prototype and comparing simulation results with the experimental results.

Performance Analysis of Multi-Level Inverter-Fed Position Sensorless PMSM Drive Using Modified MPTC

In this article, the performance of multilevel inverter-fed position sensorless permanent magnet synchronous motor (PMSM) drive is analyzed using modified model predictive torque control (MPTC) method using two-level and three-level inverters, respectively. The MPTC method helps to control electromagnetic torque directly, which is not possible in model predictive current control, whereas the conventional model predictive torque and flux control method requires weighing factors that are similar to PI controllers used in field-oriented control or direct torque and flux control method. To simplify the control structure, most of the researchers are looking forward to weighing factorless predictive control strategies. The multilevel inverters required complex control algorithms such as space vector modulation. However, the model predictive control methods made it simple by using an embedded control structure. Furthermore, position sensorless control strategies are much needed because speed sensors are much prone to failures. Therefore, in this article, a model reference adaptive system (MRAS)–based speed sensorless approach is used to eliminate the requirement of a position sensor. The proposed multilevel inverter-fed position sensorless PMSM drive using modified MPTC is simulated in MATLAB/SIMULINK environment under different operating conditions such as under no-load, load, and change in speed. The simulation results are validated with the experimental results.

SPEED SENSORLESS CONTROL FOR PMSM DRIVES USING EXTENDED KALMAN FILTER

In this paper, Sensorless Permanent Magnet Synchronous Motor (PMSM) using Extended Kalman Filter (EKF) is presented. The previous PMSM drive uses a sensor to measure the motor’s speed. Then the idea is to replace the sensor by using sensorless drives based on the observer. For the conventional observer, it’s only good for low current and low-speed applications. Moreover, it is hard to detect the phase voltage due to the non-existence of neutral wire. Therefore, this project proposes sensorless control using an EKF. This method provides an optional estimation algorithm for the non-linear system that can produce a fast and accurate estimation of state variables. The accurate estimation will reduce the noise and ripple of the system. Additionally, the EKF do not require the information of mechanical parameters and the initial position of the rotor, making the construction is easy and simple. In this paper, the fundamental of the EKF algorithm is explained and the simulation results for different speeds and loads are presented. The noise reduction test is also conducted to measure the flux current with and without the filter. The simulation study is achieved using MATLAB/Simulink to verify the effectiveness of the proposed method. The results of the simulation show that the sensorless PMSM drives using EKF have lower overshoot and faster rise time during start-up conditions and have lower undershoot during the loaded condition. It also can be concluded that the proposed sensorless PMSM drive using EKF has good speed control accuracy and can reduce the current noise.