Sensorless Speed Estimation Research Articles

Reduced Sensor-Based PMSM Driven Autonomous Solar Water Pumping System

The nonlinear <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V–I</i> characteristic of solar cell, calls for the use of maximum power point tracking (MPPT) method in order to obtain optimum power from solar photovoltaic (PV) array. Conventional MPPT methods require one voltage and one current sensor. This paper proposes a novel single sensor-based MPPT technique for a PV array fed water pumping using a permanent magnet synchronous motor (PMSM) drive. As the use of encoders, is not preferred for submersible water pumping, this paper uses a sensorless speed and position estimation for speed control of PMSM. The estimation of rotor speed and position, is achieved through the estimation of stator flux from voltages and currents in stationary reference frame. As the conventional flux estimators suffer from the problems, such as saturation, dc drift, and distortion, this paper proposes a mix multi-resonant structure for flux estimation. A sensorless speed control decreases the cost and improves the reliability of the solar water pumping system. The energy extracted from the PV array, is used to drive the PMSM, which rotates the pump coupled to it. Suitability of the proposed system is demonstrated under varying insolation conditions through a prototype developed in the laboratory and utilizing a digital signal processor (dSPACE-1202) for controlling the SWP system.

MRAS-Based Speed Estimation of Induction Motor Drive Utilizing Machines' d- and q-Circuit Impedances

This paper proposes a new model reference adaptive system (MRAS) for the sensorless speed estimation of field-oriented induction motor (IM) drive utilizing d - and q -circuits effective impedances. The functional quantity of the MRAS, in this context, is the difference between the stator d - and q -circuits' effective working impedances. This unique structure does not require any flux computation while estimating speed. Moreover, the formulation is free from any resistance terms. The proposed estimator performs satisfactorily at all the operating points and exhibits stability in all the four quadrants of the drive's operation. The relevant stability and sensitivity studies, in this regard, are done in MATLAB/Simulink. Furthermore, the controller performance is validated experimentally by dSPACE-1103-based IM drive setup.

Adaptive Observer of Resistance in Sensorless Estimation of Speed and Position in Brushless DC Electric Motor

Abstract Estimating the speed and position using measurable electrical parameters would allow establishment of sensorless control systems for brushless DC motors, without the need to use expensive sensors for the rotor position and speed. When the motor is running, it heats up and the stator resistance rises. This heat-dependent change needs to be reflected in the observer, as it would produce an error in rated speed and position. An adaptive algorithm can compensate for the change of resistance as a disturbing effect of the motor heating. The adaptive algorithm for estimating the resistance is synthesized using the function of Lyapunov. This article is useful for estimation of brushless electric motor speed and position with observer. It contains simulations with an adaptive observer of resistance for sensorless estimation of speed and position in brushless DC motor through measurement of voltage and current.

Sensorless DTC of BDFRG using LMS algorithm for wind energy conversion systems

This paper presents a new sensorless speed and secondary winding resistance estimation technique for brushless doubly fed reluctance generator (BDFRG) using least mean square (LMS) algorithm. Detailed mathematical derivation of the algorithm is explained and simulation results in MATLAB Simulink are shown for sensorless direct torque control (DTC) of BDFRG using LMS algorithm. A comparison to traditional speed estimation technique for BDFRG using primary winding flux linkage formula in stationary frame is then held to show the advantages of this proposed technique over the traditional method of speed estimation. Power electronics of the drive system is also simulated to consider effect of harmonics injected by electronic switches on both algorithms.

Sensorless DTC of BDFRG using LMS algorithm for wind energy conversion systems

This paper presents a new sensorless speed and secondary winding resistance estimation technique for brushless doubly fed reluctance generator (BDFRG) using least mean square (LMS) algorithm. Detailed mathematical derivation of the algorithm is explained and simulation results in MATLAB Simulink are shown for sensorless direct torque control (DTC) of BDFRG using LMS algorithm. A comparison to traditional speed estimation technique for BDFRG using primary winding flux linkage formula in stationary frame is then held to show the advantages of this proposed technique over the traditional method of speed estimation. Power electronics of the drive system is also simulated to consider effect of harmonics injected by electronic switches on both algorithms.

An approximate high gain observer for speed-sensorless estimation of induction motors

Rotor speed estimation for induction motors is a key problem in speed-sensorless motor drives. This paper performs nonlinear high gain observer design based on the full-order model of the induction motor. Such an effort appears non-trivial due to the fact that the full-model at best admits locally a non-triangular observable form &#x0028 NTOF &#x0029, and its analytical representation in the NTOF can not be obtained. This paper proposes an approximate high gain estimation algorithm, which enjoys a constructive design, ease of tuning, and improved speed estimation and tracking performance. Experiments demonstrate the effectiveness of the proposed algorithm.

Model reference adaptive system based sensorless speed estimation of brushless doubly‐fed reluctance generator for wind power application

Brushless doubly-fed reluctance generator (BDFRG) is drawing a growing attention of research over the traditional doubly-fed induction generator in variable speed application like wind power generation nowadays, due to its brushless structure. In this work, the applicability of different model reference adaptive system (MRAS) based sensorless speed estimation techniques for BDFRG in wind power application is explored. The MRAS estimators developed, in this context, are based on active power, reactive power and fictitious quantity. All these schemes are implemented under primary field orientation using machine secondary winding quantities as the functional variables. Matlab/Simulink study and hardware test results under variable wind speed (between cut-in and rated speed) are presented for the aforementioned speed estimation techniques. Furthermore, to ensure the robustness of the drive system, stability study using Popov's criteria for hyperstability and sensitivity analyses is presented.

An Improved Speed Sensorless Control Strategy for Linear Induction Machines Based on Extended State Observer for Linear Metro Drives

This paper proposes an improved systematic approach for sensorless speed estimation and controller design of a linear induction machine (LIM) for linear metro drives. A novel speed estimation method based on the extended state observer is developed to improve the dynamic speed estimation response. In contrast to the conventional proportional-integral speed adaptive mechanism based only on the LIM electromagnetic model, this new speed estimation method incorporates both the electromagnetic and mechanical models such that it can estimate the LIM speed and load resistance at the same time. A new speed controller incorporating the disturbance observer based control algorithm is developed to strengthen the speed tracking ability and suppress the disturbance of load variation. Having fewer parameters, it brings great convenience to the drive system parameter setting and tuning. The performance of the proposed method is numerically simulated and experimentally verified.

Speed Estimation Based on Rotor Slot Harmonics in Multiphase Induction Machines Under Open-Phase Fault

Multiphase (i.e., with more than three phases) induction machines (MIMs) are particularly attractive for safety-critical applications, because they are able to operate under open-phase fault. On the other hand, algorithms for sensorless speed estimation are of great interest, since, e.g., they improve reliability and decrease cost and maintenance. Among these methods, the approach based on rotor slot harmonics (RSHs) is especially popular, due to advantages such as its independence from time-varying parameters (e.g., resistances and inductances). In healthy machines, usually the fundamental or any given harmonic component has ideally equal magnitude in all stator phases. The previous RSH-based techniques rely on this characteristic. Conversely, under open-phase fault there is current imbalance. Moreover, due to the postfault strategies for optimum current reference generation, such imbalance varies with the load. Thus, the existing RSH-based methods are not suitable for open-phase fault, and alternative ones should be developed. This paper addresses the sensorless speed estimation based on RSHs for MIMs under open-phase fault. The main RSHs obtained in faulty situations are studied. Then, accordingly, a speed estimation technique for MIMs under open-phase fault is developed, able to work with good accuracy despite the variable current imbalance. Finite-element and experimental results are provided.

Hybrid Computational Mechanical Sensorless Fuzzified Technique for Speed Estimation of Permanent Magnet Direct Current Brushed Motor

This paper proposes a novel fuzzified mechanical sensorless speed estimation technique for permanent magnet direct current (PMDC) brushed motor operated with pulse width modulation (PWM) based terminal voltage. For replacement of conventional mechanical speed sensors, few mechanical sensorless speed estimation techniques have been reported recently in the field of PMDC brushed motor. In this paper, a novel technique is applied over a recently reported semianalytical dynamic time-domain PMDC brushed motor model incorporating space-domain effects, namely slotting effect and commutation phenomenon to simulate the proposed estimation process. Ripple and back electromotive force based standalone estimation approaches are hybridized in order to eliminate uncertainties in all regions of estimation. In this paper, a discrete fuzzified hybrid speed estimation model has been proposed with adequate dynamic simulation responses. Further the proposed discrete speed estimation model has been applied experimentally over a PWM-driven 24-V, 12-teeth, 100-W PMDC brushed motor and various dynamic real-time responses have been compared with conventionally captured speed samples to validate the proposed model.

Sensorless Control of IM Based on Stator-Voltage MRAS for Limp-Home EV Applications

This paper proposes a novel sensorless speed estimation for an induction motor (IM) based on a new stator-voltage model reference adaptive system (Vs-MRAS) scheme. This is utilized for torque-controlled drive (TCD) based on indirect rotor field oriented control technique in limp-home mode operation of electric vehicles (EV) applications. The Vs-MRAS scheme uses the error between the reference and estimated stator-voltage vectors and estimates the synchronous speed. Unlike existing MRAS schemes, the proposed sensorless scheme does not require the measured nominal values of stator resistance, stator inductance, and rotor resistance. This scheme is insensitive to variations of the aforementioned parameters. Moreover, using the proposed scheme eliminates the need for slip calculation. The proposed scheme is implemented and experimentally tested in a lab environment, on a 19-kW IM, and also applied on an electric golf buggy, powered by a 5-kW IM. The experimental results show that the proposed scheme is immune to parameter variations and is consistent in vehicle-starting from standstill and hill-starting tests. This scheme is also free from drift problems associated with a pure integration and is stable in the field weakening region. The test-drive results from the golf buggy confirm suitability of the proposed Vs-MRAS scheme over a wide range of speeds for the purpose of TCD in EV applications.

Implementation of reactive power‐based MRAS for sensorless speed control of brushless doubly fed reluctance motor drive

The present work introduces the concept of classical reactive power (Q)-based model reference adaptive system (MRAS) for the speed estimation and control of low-cost BDFR motor drive. The reasons behind such choice for this drive's control are: (i) MRAS-based controllers can inherently take care of the machine parameter variations which had been a challenging issue with the other available sensorless speed estimation strategies and (ii) the employment of Q as a functional candidate inevitably makes the formulation immune to the variations in stator resistance. The experimental assessment, in this respect, confirms these claims. Furthermore, the analytical validation of Popov's hyperstability criteria on the proposed controller, confirms the drive's overall stability within the investigated speed control range. The speed control performance is examined in MATLAB/Simulink. The simulation results are further validated by a real-time implementation using dSPACE-1103-based 1.6 kW BDFR machine prototype.

Modelling, control and sensorless speed estimation of micro‐wind turbines for deployment in Antarctica

This paper presents the modelling, control and sensorless speed estimation of two micro-wind turbines deployed by the British Antarctic Survey (BAS) in Antarctica. Mathematical models for the generators attached to an Ampair 100 and Rutland 913 wind turbines and their experimental validation are given. Also, a model for the wind turbines, particularly taking into account the power coefficient Cp versus tip speed ratio λ relationship was proposed and successfully evaluated on a wind turbine emulator test rig. This paper describes an analogue speed estimator board and a Kalman filter for estimating the shaft speed. These estimators use only DC side measurements to match the characteristics of the current version of the turbine control board. The wind turbine control and speed estimators were tested on the emulator test rig using real wind data from BAS research bases in Antarctica. Using only DC side measurements leads to low computation requirements to execute the algorithms in comparison to commonly used schemes that rely on AC measurements. In addition, the estimation algorithms are based on the model of a PM generator connected to a diode rectifier, as they can be used in a wider range of applications, including DC to DC converters with MPPT algorithms based on speed measurements.

Sensorless speed estimation of permanent magnet DC brushed motor considering the effect of armature teeth–slots and commutation

This study proposes a novel technique of speed estimation for permanent magnet direct current (PMDC) brushed motor. The impact of armature teeth–slots and commutation of PMDC motor on armature current is considered in this study to estimate the speed. In many applications, speed measurement of motors is essentially required. Conventionally mechanical sensors are coupled to the motor shaft for speed measurement. Recently many sensorless methods for speed estimation of motor had been introduced. This study proposes a new method where the variation in effective magnetic path reluctance due to continuous alternation in teeth–slots positions with respect to stationery poles is considered. Combined effects of effective magnetic path reluctance variation and armature commutation cause ripple in armature current. In this study, the effect of teeth–slots in armature current is investigated using finite-element approach and also it is verified experimentally. Furthermore, an elementary circuitry is included in this study in support of the proposed method from armature current. The performed test on a 24 V–100 W brushed PMDC motor indicates that the proposed method is effective in wide range of speed estimation considering the effect of change in mechanical load or terminal voltage level.

Combined Speed and Direct Thrust Force Control of Linear Permanent-Magnet Synchronous Motors With Sensorless Speed Estimation Using a Sliding-Mode Control With Integral Action

A sliding-mode-based control scheme with integral action for combined speed and direct thrust force control of a linear permanent-magnet synchronous motor is proposed. A nonlinear state-space model for the combined dynamics of speed and thrust force as system states is utilized for the synthesis of the sliding-mode control law. Direct integral action is also included in the control law to eliminate the steady-state error in the speed tracking. The sensorless speed estimation is performed by using an adaptive flux observer with a modified dual boundary layer sliding-mode component. Lyapunov stability analysis to prove the global asymptotic stabilities of both the controller and observer is provided. The effectiveness of the proposed method is validated experimentally and demonstrates excellent transient and steady-state speed control performance.

Selection Criteria of Multiphase Induction Machines for Speed-Sensorless Drives Based on Rotor Slot Harmonics

Multiphase (MP) induction machines (IMs) provide important advantages over three-phase (3P) ones. Sensorless speed estimation makes it possible to obtain high-performance control and monitoring without the inconveniences of speed sensors. In 3P IMs, the speed estimation methods based on rotor slot harmonics (RSHs), normally on the principal RSHs (PSHs), are well established. A difficulty of these techniques, in 3P IMs, is that RSHs are usually extremely small. Additionally, as previously assessed concerning 3P IMs, the number of rotor bars should be carefully selected; otherwise, the PSHs might not even arise in the stator current. However, no publications have addressed the magnitude of PSHs in MP IMs, in comparison to 3P ones, or selection criteria of MP IMs for speed-sensorless drives. In this paper, it is shown that in MP IMs larger (easier to detect) PSHs can be obtained, due to the low impedances in their additional stator planes, by appropriately selecting the number of bars and poles so that the PSHs are mapped into such planes. This finding is supported by newly developed stator equivalent circuits, which include the effects of rotor bars. Accordingly, criteria are presented to select MP IMs for speed-sensorless drives. Experimental and finite-element results confirm the theory.

Sensorless speed estimation in wound rotor induction machines by spectral search of the stator phase power signal

This paper investigates the feasibility of utilising the stator phase power signal to establish sensorless speed estimation schemes in wound rotor induction machines (WRIMs). To this end, the authors derive and validate closed form expressions defining the possible power signal spectral content containing rotor speed information. Based on these, two novel sensorless speed estimation techniques are proposed: the first enables supply frequency independent speed estimation in WRIM extended slip applications, while the second facilitates estimation in a wide operating speed range for scalar controlled WRIM applications based on a sliding-window search of the power spectrum. The proposed techniques are underpinned by a dichotomous search enabled spectral processing algorithm and shown to deliver an increase in attainable real-time estimation rate without compromising estimation accuracy. The performance of reported schemes is assessed and validated in real-time laboratory experiments.

Flux Based Sensorless Speed Sensing and Real and Reactive Power Flow Control with Look-up Table based Maximum Power Point Tracking Technique for Grid Connected Doubly Fed Induction Generator

This aim of this paper is to design controller for Doubly Fed Induction Generator (DFIG) converters and MPPT for turbine and a sensor-less rotor speed estimation to maintain equilibrium in rotor speed, generator torque, and stator and rotor voltages. It is also aimed to meet desired reference real and reactive power during the turbulences like sudden change in reactive power or voltage with concurrently changing wind speed. The turbine blade angle changes with variations in wind speed and direction of wind flow and improves the coefficient of power extracted from turbine using MPPT. Rotor side converter (RSC) helps to achieve optimal real and reactive power from generator, which keeps rotor to rotate at optimal speed and to vary current flow from rotor and stator terminals. Rotor speed is estimated using stator and rotor flux estimation algorithm. Parameters like tip speed ratio; coefficient of power, stator and rotor voltage, current, real, reactive power; rotor speed and electromagnetic torque are studied using MATLAB simulation. The performance of DFIG is compared when there is in wind speed change only; alter in reactive power and variation in grid voltage individually along with variation in wind speed.

Extreme learning machine approach for sensorless wind speed estimation

Precise predictions of wind speed play important role in determining the feasibility of harnessing wind energy. In fact, reliable wind predictions offer secure and minimal economic risk situation to operators and investors. This paper presents a new model based upon extreme learning machine (ELM) for sensor-less estimation of wind speed based on wind turbine parameters. The inputs for estimating the wind speed are wind turbine power coefficient, blade pitch angle, and rotational speed. In order to validate authors compared prediction of ELM model with the predictions with genetic programming (GP), artificial neural network (ANN) and support vector machine with radial basis kernel function (SVM-RBF). This investigation analyzed the reliability of these computational models using the simulation results and three statistical tests. The three statistical tests includes the Pearson correlation coefficient, coefficient of determination and root-mean-square error. Finally, this study compared predicted wind speeds from each method against actual measurement data. Simulation results, clearly demonstrate that ELM can be utilized effectively in applications of sensor-less wind speed predictions. Concisely, the survey results show that the proposed ELM model is suitable and precise for sensor-less wind speed predictions and has much higher performance than the other approaches examined in this study.

Sliding Mode Control of Induction Motor with Vector Control in Field Weakening

This paper presents a vector control sliding mode control (SMC) scheme in the field weakening (FW) region with optimal flux based algorithm. The observation of the rotor flux and stator flux components are also included. This work proves the advantages of vector controlled IM for high performance application in the industry. The vector control ability for easy FW and full voltage and current utilization of inverter fed IM to ensure a wide range of sufficient speed and torque operation was investigated in this work. In a sensorless vector controlled IM, the speed must be estimated using voltage and current components. The parameter variations is the main problem in the high speed operation of IM so that, the sensorless speed estimation through SM technique in the FW region with optimal flux measurement is presented. Space vector pulse width modulation (SVPWM) voltage source inverter is utilized in the algorithm. The simulation results shows the effectiveness of this algorithm at all speed range of operation.