Sensorless Algorithm Research Articles

Fuzzy compensation of model predictive control for PMSMs with external disturbances

In some high-speed scenarios, encoders may prove ineffective in providing real-time feedback, thereby increasing the installation and maintenance costs of Permanent Magnet Synchronous Motors (PMSMs). Consequently, the development of sensorless algorithms for medium and high-speed scenarios will enhance the practical applicability of PMSMs. In contrast to the angle estimation scheme for a rotated coordinate system, model predictive control (MPC) commences from the stationary coordinate system to explore Lyapunov stability and directly derive speed and angle based on the stability condition. The primary advantage of this approach lies in its ability to mitigate the accumulation of observation angle iteration errors, while simultaneously simplifying stability conditions. Furthermore, it is important to note that uncertain factors will significantly impede the performance of PMSMs. Subsequently, various fuzzy schemes are introduced to mitigate the impact of uncertain factors in the sensorless mode, and a rigorous proof is provided for the relationship between the fuzzy error and current error. Furthermore, a comprehensive analysis of controller stability conditions is conducted. Ultimately, experimental results demonstrate that the proposed fuzzy compensations effectively counteract external disturbances.

An Adaptive Delay Compensated Position Sensorless PMBLDC Motor Drive With Regenerative Braking for LEV Application

This paper deals with a new terminal voltage-based rotor position sensorless algorithm of permanent magnet brushless DC (PMBLDC) motor with adaptive phase angle compensation along with regenerative braking technique for light electric vehicle (LEV) application. Removal of Hall-Effect sensors from PMBLDC motor reduces the circuit complexity and makes the motor drive system robust and compact. Back EMF based position estimation of PMBLDC motor suffers poor accuracy at low speed. In this paper, position sensorless operation is achieved at very low speed below 100rpm. Position estimation of PMBLDC motor suffers with commutation error due to several factors like non-ideal back EMF, lowpass filter used, unbalanced DC bus voltage etc. An adaptive phase angle compensation strategy is developed to mitigate this issue, considering a generalized nonideal commutation case. This method is suitable for compensation of commutation error during variable speeds over a wide speed range, which is required for EV application. Moreover, the compensation method works with motor parameters variation as well. The proposed drive topology extends the vehicle's driving range with solar PV integration and energy regeneration algorithm. The system is simulated and experimentally validated in real case scenarios.

Sensorless Control With Switching Frequency Square Wave Voltage Injection for SPMSM With Low Rotor Magnetic Anisotropy

High-frequency signal injection sensorless algorithms are widely studied and used for rotor angle estimation in PMSM at low speed or standstill. One of the main drawbacks of such methods is the acoustic noise connected to the voltage injection. In order to minimize this problem, it is advisable to increase the frequency of the injected signal. Thus, many studies focus on square-wave injection at the switching frequency, which is the maximum theoretical frequency. Since these methods exploit the rotor magnetic anisotropy, it is relatively easy to use them in interior PMSMs, where the rotor anisotropy is high. On the contrary, it is hard to exploit them in surface PMSMs, which have an almost symmetric rotor, although a low rotor magnetic anisotropy is still present. In this paper, a sensorless algorithm with switching frequency square-wave injection is developed for surface PMSMs. To increase the signal-to-noise ratio, current oversampling is exploited. The benefits of such a technique are demonstrated with experimental results on a 2 Nm SPMSM.

Fault-Tolerant Self-Tuning Control for Three-Phase Three-Level T-Type Rectifier

This paper proposes a sensorless self-tuning control algorithm for a three-phase T-type rectifier. The proposed sensorless algorithm consists of three layers including an observer, which estimates grid voltages or currents based on the Kalman filter algorithm (KFA), an online estimator, which estimates the state-space matrix parameters, and a linear quadratic tracker (LQT), which is the main controller in this study. On the other hand, the performance of the LQT depends on the gains that need to be adjusted according to the system parameters, which is a challenge. To overcome this problem, a self-tuning method based on recursive least square algorithm (RLSA) is also proposed to tune the gains of LQT online. An experimental prototype is established, and the results, including the steady-state and dynamic performances, are carried out and presented to validate the effectiveness of the proposed controller.

DTC-SVM οf Sensorless Five-phase Induction Machine Using Extended Kalman Filter

This work relates to the study of direct torque control based on space vector modulation applied on five-phase induction machine. It is well established that the conventional direct torque control using hysteresis comparators suffers from high torque ripples and variable switching frequency. The most common solution to those problems is the use of space vector modulation. In the other hand, this paper aims also to design an extended Kalman filter observer for speed/flux estimation, which improves not only the control performances by using a sensorless algorithm but also can lower the cost and increase the reliability of the system. Both theoretical principle and simulation results of the sensorless control method of multiphase drive will be conducted to verify the effectiveness of the proposed control approach.

A sensorless, physiologic feedback control strategy to increase vascular pulsatility for rotary blood pumps

Continuous flow rotary blood pumps (RBP) operating clinically at constant rotational speeds cannot match cardiac demand during varying physical activities, are susceptible to suction, diminish vascular pulsatility, and have an increased risk of adverse events. A sensorless, physiologic feedback control strategy for RBP was developed to mitigate these limitations. The proposed algorithm used intrinsic pump speed to obtain differential pump speed (ΔRPM). The proposed gain-scheduled proportional-integral controller, switching of setpoints between a higher pump speed differential setpoint (ΔRPMHr) and a lower pump speed differential setpoint (ΔRPMLr), generated pulsatility and physiologic perfusion, while avoiding suction. The switching between ΔRPMHr and ΔRPMLr setpoints occurred when the measured ΔRPM reached the pump differential reference setpoint. In-silico tests were implemented to assess the proposed algorithm during rest, exercise, a rapid 3-fold pulmonary vascular resistance increase, rapid change from exercise to rest, and compared with maintaining a constant pump speed setpoint. The proposed control algorithm augmented aortic pressure pulsatility to over 35 mmHg during rest and around 30 mmHg during exercise. Significantly, ventricular suction was avoided, and adequate cardiac output was maintained under all simulated conditions. The performance of the sensorless algorithm using estimation was similar to the performance of sensor-based method. This study demonstrated that augmentation of vascular pulsatility was feasible while avoiding ventricular suction and providing physiological pump outflows. Augmentation of vascular pulsatility can minimize adverse events that have been associated with diminished pulsatility. Mock circulation and animal studies would be conducted to validate these results.

Overview of Fundamental Frequency Sensorless Algorithms for AC Motors: A Unified Perspective

This article uses the active flux concept to review fundamental frequency sensorless algorithms for both induction and permanent magnet motors in one framework. Fundamentally, sensorless torque estimation can be directly solved using voltage-current model (VM) estimator or indirectly solved using current-speed model (CM) estimator. The latter turns the torque estimation problem into a speed estimation problem. The stator flux in VM and the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$d$ </tex-math></inline-formula> -axis angle in CM are deemed as the two sets of original states for the sensorless drive. Through the change of states, the direct torque estimation can be realized via observer designs, whereas the speed dependency in the dynamics of the unknown state [e.g., active flux and electromotive force (emf)] gives rise to a class of speed estimation methods, known as model reference adaptive system (MRAS). The idea of a general speed observer is proposed to summarize various separate speed estimation methods needed for direct torque estimation. It is suggested to adopt inherently sensorless designs such that two-way coupling between torque estimation and speed estimation is avoided. For induction motors, it turns out that the unmodeled voltage in the active flux dynamics reveals current flowing in rotor bars and can be further modeled, for which the solutions to regeneration instability problem are discussed, and change of states is recommended to attain global stability. Finally discussed are the results of the slow reversal test, where local weak observability of ac motors can be potentially preserved.

Sensorless DTC-SVM applied to an induction motor controlled by a three-level inverter using SMSFO

PurposeThe direct torque control (DTC) of induction motor (IM) drive is featured by high ripples in the electromagnetic torque and stator flux profiles because they are controlled by two hysteresis regulators. Furthermore, the machine flux is not directly measurable. Hence, it is better to reconstitute it from the instantaneous electrical equations of the machine. Once the stator flux is estimated, we can guarantee a reliable sensorless DTC control. Thus, the purpose of this research work is to ensure fast response and full reference tracking of the IM under sensorless DTC strategy with desired dynamic behavior and low ripple levels.Design/methodology/approachIn this work, an improved DTC strategy, which is DTC_SVM_3L, is suggested. The first step of the designed approach is to substitute the conventional inverter feeding the motor with a three-level inverter because it guarantees reduced switching losses, improved quality of voltage waveform and low-current total harmonic distortion rate. The second aim of this paper is to make the IM operate at a constant switching frequency by using the nearest three vectors-based space vector modulation (SVM) technique rather than hysteresis controllers. The third objective of this study is to conceive a sliding-mode stator flux observer, which can improve the control performances by using a sensorless algorithm to get an accurate estimation, and consequently, increase the reliability of the system and decrease the cost of using sensors. The stability of the proposed observer is demonstrated based on the Lyapunov theory. To overcome the load change disturbance in the proposed DTC control strategy, this paper exhibits a comparative assessment of four speed regulation methods: classical proportional and integral (PI) regulator, fuzzy logic PI controller, particle swarm optimization PI controller and backstepping regulator. The entire control algorithm was tested under different disturbances such as stator resistance and load torque variations.FindingsIt was ascertained that the IM, controlled with three-level inverter, exhibits good performances under the proposed DTC-SVM strategy based on a sliding-mode observer. The robustness of the suggested approach against parameter variations is also proved.Originality/valueThe theoretical development of the proposed control strategy is thoroughly described. Then, simulations using Matlab/Simulink software are launched to investigate the merits of the sensorless DTC-SVM command of three-level inverter-fed IM drive with different speed regulators.

Surface Permanent Magnet Synchronous Motors’ Passive Sensorless Control: A Review

Sensorless control of permanent magnet synchronous motors is nowadays used in many industrial, home and traction applications, as it allows the presence of a position sensor to be avoided with benefits for the cost and reliability of the drive. An estimation of the rotor position is required to perform the field-oriented control (FOC), which is the most common control scheme used for this type of motor. Many algorithms have been developed for this purpose, which use different techniques to derive the rotor angle from the stator voltages and currents. Among them, the so-called passive methods have gained increasing interest as they do not introduce additional losses and current distortion associated instead with algorithms based on the injection of high-frequency signals. The aim of this paper is to present a review of the main passive sensorless methods proposed in the technical literature over the last few years, analyzing their main features and principles of operation. An experimental comparison among the most promising passive sensorless algorithms is then reported, focusing on their performance in the low-speed operating region.

Sensorless DPCC of PMLSM Using SOGI-PLL-Based High-Order SMO With Cogging Force Feedforward Compensation

In order to reduce the adverse effect of the large thrust ripple of permanent magnet linear synchronous motor (PMLSM) on mover position estimation accuracy and solve the sliding mode chattering problem of the traditional sensorless algorithm based on sliding mode observer (SMO), this article proposes a systematic method to solve above issues. First, the high-order SMO method is used to suppress harmonic generation from the source of sliding mode chattering. Second, an adaptive filter based on a second-order generalized integrator (SOGI) is constructed to filter out the harmonics. Then, the normalized quadrature phase-locked loop (PLL) method is used to realize the closed-loop extraction of position information. Finally, the deadbeat predictive current control (DPCC) with the current feedforward compensation strategy is proposed to further improve the dynamic performance and mover position estimation accuracy. The simulation model and experimental platform are built. The simulation analyses and test results show that the proposed method has a better performance than conventional techniques.

Experimental Low-Speed Performance Evaluation and Comparison of Sensorless Passive Algorithms for SPMSM

Sensorless algorithms for PMSM have achieved an increasing interest in the technical literature. They can be divided into active methods and passive methods. Active methods exploit rotor anisotropy by injecting high voltage frequency signals, whereas passive methods are based on observers. Even if passive methods do not have the drawbacks of active methods – acoustic noise, torque ripple and harmonic distortion - their effectiveness is reduced in the low speed region. For this reason, active methods are usually used at low speed and the motor control switches to passive methods in the high-speed region. Since high frequency injection is associated to many drawbacks, the aim of passive methods is to work at lower speed as possible or, ideally, to be able to start directly the motor. That is particularly true for Surface-Mounted PMSM: since they have a low anisotropy, high frequency injection should be particularly elevate to achieve sufficient signal-to-noise ratio. It is difficult to compare the performance of passive algorithms proposed in the technical literature since experimental tests have been done with different conditions: motors, inverter features, measurements, type of tests, etc. In this paper, five different sensorless passive algorithms for Surface-Mounted PMSM, selected among the most promising algorithms available in the technical literature, are compared, performing the same tests on the same experimental setup, to achieve a fair comparison and establishing the most performing one.

Natural Speed Observer for Nonsalient AC Motors

This letter addresses experimental validation of the reduced-order natural speed observer design for position sensorless drive with nonsalient permanent magnet synchronous motor. The natural speed observer and the active flux estimator are connected in a cascaded fashion, which results in a simple sensorless algorithm that needs only to tune one bandwidth parameter for flux estimation and one bandwidth parameter for speed observation. Experimental results of high speed reversal test, zero speed stopping test, and slow speed reversal test are included, where the practice of applying nonzero <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$d$</tex-math></inline-formula> -axis current at zero speed has shown to be effective for loaded zero speed stopping test, but it causes zero-speed locked-up at slow speed reversal with acceleration rate of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rm \text{50}\,r/\text{min}/s$</tex-math></inline-formula> . Four remedies are compared to improve the slow speed reversal test and the proposed method gives almost ramp actual speed waveform, nondiverging <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$q$</tex-math></inline-formula> -axis current and smooth transition in position waveform during slow zero speed crossing. A new dynamic expression of the active flux is proposed and with the aid of the active flux concept, the proposed sensorless algorithm is also applicable to various types of ac motors.

Control technology and development status of flywheel energy storage system

Flywheel energy storage technology has attracted more and more attention in the energy storage industry due to its high energy density, fast charge and discharge speed, long service life, clean and pollution-free characteristics. It is wwidely used in uninterruptible power system, grid frequency modulation, energy recovery and reuse and other fields. With the development of flywheel rotor materials, motors, bearings and control technology, flywheel energy storage technology has been greatly developed. Introducing the basic structure of the flywheel energy storage system in the above three applications. Typical charge-discharge control strategies are given for the three sensor-less algorithms of model reference adaptive control, sliding mode observer andextended Kalman filter, which are suitable for flywheel energy storage devices.

State-Space Approach for SPMSM Sensorless Passive Algorithm Tuning

Sensorless algorithms for Permanent Magnet Synchronous Motors (PMSM) have achieved increasing interest in the technical literature over the last few years. They can be divided into active methods and passive methods: the first inject high-frequency signals exploiting rotor anisotropy, whereas the second are based on observers. Recently, a sensorless control based on a rotor flux observer has been presented in the technical literature, which gives very accurate results in terms of rotor position estimation and robustness. In this paper, the aforementioned observer is considered and a procedure for choosing stabilizing gains of the observer is proposed. The contribution of the paper is three-fold: the mathematical modelling of the rotor flux observer, the methodology for the definition of the observer gains, and the presentation of the experimental results.

Rotor Position Recognition Technology of Permanent Magnet Linear Synchronous Motor Based on Sliding Mode Observer

Position sensorless control system of permanent magnet linear synchronous motor has some advantages: simple structure, easy maintenance, high efficiency, good speed performance, etc. This paper designed a position sensorless control system of permanent magnet linear synchronous motor based on sliding mode observer, namely taking advantage of a sensorless algorithm to estimate the pole position and speed. Firstly, the principle of sliding mode control and basic conditions which need to achieve are analyzed. And then, a sliding mode observer of the permanent magnet linear synchronous motor sensorless control system is designed. The related simulation model is built to study the effect of sliding mode observer for rotor position accuracy. The simulation model is implemented to build models of permanent magnet linear synchronous motor vector control system based on sliding mode observer and simulate the control performance of position sensorless control. In the last part, the feasibility of the design scheme is verified by analysis of simulation results.

Implementation of sensorless speed control of synchronous reluctance motor using extended Kalman filter

This paper presents an extended Kalman filter (EKF) based sensorless speed control which was performed for controlling a synchronous reluctance motor (SynRM). Maximum torque per ampere (MTPA) control strategy was used to obtain a maximum electromagnetic torque with lowest current for the motor. In this study, all control parameters were optimized using a particle swarm optimization (PSO) algorithm to achieve the lowest control speed error and the lowest amplitude stator currents with low total harmonic distortion (THD). Also, the optimization was able to achieve the minimum difference between d-q axes currents. The motor was controlled without using a shaft sensor which plays an important role in rotor synchronization. A TMS320F28379D was used as a dual-core microcontroller capable of performing 32-bit floating point operations at 200 MHz operating frequency. The speed estimation algorithm was operated on the other core while the speed control and switching algorithms were operated on the first core. The sampling time for both cores was set to 80us. These two cores were communicated over an internal memory of the microcontroller. Experimental results for both MTPA and EKF-based sensorless algorithms were presented in the paper.

A phase‐shift‐free synchronous reference frame filter‐based position sensorless control method for open‐winding permanent magnet generator system

An open-winding permanent magnet generator (OWPMG) system that offers features like fewer switching devices and high integration can be used in multi-input generator systems. To achieve high-accuracy position sensorless operation for the OWPMG system, this study investigates a phase-shift-free synchronous reference frame filter (SRFF-PSF) for use in the sliding mode observer (SMO) position sensorless algorithm. The proposed SRFF-PSF can completely restore the fundamental component of back-electromotive force (EMF) without phase shift and filter out the high-order harmonics owing to the following two improvements. First, the fundamental phase lag is eliminated by removing the low-pass filter between the back-EMF and the SRFF. Second, the error iteration of the output position angle is avoided by using the synchronous angle information from an additional phase locked loop module for the coordinate transformation of the SRFF. Based on the aforementioned improvements, the proposed method can effectively solve the phase shift problem in position estimation. The correctness and effectiveness of the method are verified by the experimental results.

Control strategy to enhance pulmonary vascular pulsatility for implantable cavopulmonary assist devices: A simulation study

ObjectiveFontan failure can be potentially addressed with an implantable pump in the cavopulmonary junction (cavopulmonary assist device, CPAD) to replace the missing subpulmonary power source. Fontan pulmonary circulation lacks pulsatility due to the absence of the right ventricle, which has adverse physiological consequences. CPAD can augment pulmonary flow and improve Fontan hemodynamics. However, CPAD operating at a constant pump speed does not provide pulmonary arterial pulsatility, provide physiologic flow to match cardiac demand, or avoid suction. To overcome these limitations, a sensorless control strategy for CPAD is proposed. MethodsCPAD pump speed measurement, an intrinsic pump parameter, was used to estimate cavopulmonary pressure head (CPPH). A gain scheduled proportional-integral controller alternates CPPH between high/low setpoints (CPPHHr/CPPHLr) that generates pulsatility, while simultaneously adapting to cardiac demand and avoiding suction. Computer simulations were performed to quantify the overall performance of the proposed algorithm at rest and exercise, rapid transition from exercise to rest, and doubling of the vena caval resistance. The performance was compared against CPPH measured using pressure sensors, and a constant pump speed control strategy. ResultsThe sensorless algorithm generated a pulmonary vascular pulsatility of approximately 10 mmHg, and matched the cardiac demand at rest and exercise. The frequency of pump speed modulation was 10–15 cycles per minute and no suction was observed. Conclusion and significanceThe sensorless strategy outperformed constant CPAD speed control algorithm for improvement of pulmonary vascular pulsatility and physiologic perfusion. Further validation is needed using mock loop and animal tests.

Intelligent control of induction motor without speed sensor

&lt;p&gt;This paper presents a proposed sensorless algorithm for induction motor(IM)speed control based on artificial neural networks (ANNs).The Indirect rotor field oriented (IRFO) technique is applied to control the motor. It is designed based on the proportional-integral (PI) controller. The particle swarm optimization (PSO) algorithm is used as a good solution for the problems associated with the design of the proportional-integral (PI) controller gains.The PSO is compared with the conventional methods. The proposed controller (PSO-PI) is then integrated with the artificial neural network(ANN) speed estimator. The MATLAB/Simulink is used for the simulation of the system. The obtained simulation results for the proposed technique are very close to the actual ones.&lt;/p&gt;

Advanced speed sensorless control strategy for induction machine based on neuro-MRAS observer

High-performance field-oriented motor control requires accurate knowledge of flux and speed information. Furthermore, the elimination of sensors leads to reduced overall cost and size of the electric drive system and subsequently improving its reliability. So far, Speed sensorless control of induction motors has been faced with various techniques of speed estimation. However, the main drawbacks of these models are their insufficient performance at low speeds, along with sensitivity to parameters variation, which engenders an unsteady drive system. This paper proposes an effective sensorless indirect Field Oriented control scheme for an induction motor drive. The proposed speed observer combines artificial intelligence and model reference adaptive system (MRAS). This observer is associated with the control scheme as sensorless algorithms for rotor speed and flux estimation. This conjunction is intended to enhance the conventional MRAS performance especially in low-speed regions and reduce its sensitivity to noise and system uncertainties as well. Otherwise, the effectiveness of the proposed speed estimator is tested in simulation using Matlab/Simulink software environment. The control structure is checked in the low speed with load variation.