Stator Resistance Research Articles

Rotor Speed and Load Torque Estimations of Induction Motors via LSTM Network

Abstract In this study, a long short-term memory (LSTM) based estimator using rotating axis components of the stator voltages and currents as inputs is designed to perform estimations of rotor mechanical speed and load torque values of the induction motor (IM) for electrical vehicle (EV) applications. For this aim, first of all, an indirect vector controlled IM drive is implemented in simulation to collect both training and test datasets. After the initial training, a fine-tuning process is applied to increase the robustness of the proposed LSTM network. Furthermore, the LSTM parameters, layer size, and hidden size are also optimised to increase the estimation performance. The proposed LSTM network is tested under two different challenging scenarios including the operation of the IM with linear and step-like load torque changes in a single direction and in both directions. To force the proposed LSTM network, it is also tested under the variation of stator and rotor resistances for the both-direction scenario. The obtained results confirm the highly satisfactory estimation performance of the proposed LSTM network and its applicability for the EV applications of the IMs.

Electrical Parameter Estimation Method for Surface-Mounted Permanent Magnet Synchronous Motors Considering Voltage Source Inverter Nonlinearity

This paper proposes an electrical parameter estimation method for permanent magnet synchronous motors (PMSMs) considering the voltage source inverter (VSI) nonlinearity. Accurate parameters are essential for high-performance control of PMSMs. Therefore, numerous studies have been conducted to obtain accurate parameters. However, the VSI nonlinearity causes voltage distortion, which causes parameter-estimation errors. To address this problem, this paper presents a solution using the double-frequency double-amplitude (DFDA) injection method based on the high-frequency (HF) injection method. The proposed method is a practical and novel method using simple mathematical calculations that takes into account VSI nonlinearity without using nonlinearity-compensation methods. It increases the accuracy and reduces the resistance-estimation step by simultaneously estimating the stator resistance and inductance. To demonstrate the efficacy and practicability of the proposed method, it was experimentally verified on a 400 W surface-mounted PMSM. The proposed method can simultaneously estimate the stator resistance and inductance with high accuracy within a short time and can, therefore, be applied to PMSM drives in various industries, such as robotics.

Introducing Improved Iterated Extended Kalman Filter (IIEKF) to Estimate the Rotor Rotational Speed, Rotor and Stator Resistances of Induction Motors

This paper introduces the Improved Iterated Extended Kalman Filter (IIEKF) for estimating the rotational speed, rotor resistance, and stator resistance of three-phase induction motors (IMs). Two state-space models for estimating the variables are presented. An optimal estimation of rotational speed is obtained by introducing a data fusion approach. The effectiveness of the IIEKF in comparison with the Extended Kalman Filter (EKF), using experimental data and in a wide range of operating conditions, is shown.

Offline Measurement of Stator Resistance and Inverter Voltage Drop Using Least Squares

Modern industrial and commercial electrical drives are typically designed to control motors of different types, operating under scalar, field-oriented or direct torque control. These drives execute various algorithm such as sensorless control, temperature monitoring, etc., which require the knowledge of motor drive parameters. In order to do this, the inverters allow data to be input manually or execute self-commissioning routines before running the motor. The parameters necessary for proper operation include motor phase resistance and inverter voltage drop, which are especially important in low-speed range. This paper presents an offline technique for estimation of mentioned parameters, which can be obtained with enough precision for the overwhelming majority of applications. The proposed algorithm consequently injects DC-current of several levels into the stator of a motor, measuring the corresponding voltages. Each pair of current and voltage is a point in the voltage current characteristic of motor drive, thus set of these points maybe approximated with a first order polynomial using least squares method. The parameters of polynomial are desired inverter voltage drop and phase resistance. The experimental section analyzes estimation errors and their dependence on the number of injected levels, their values and filtering capability of measuring algorithm. After that, the authors give suggestions on algorithm parameters selection, depending on the demanded precision. Finally, the authors demonstrate a mass-producing dishwasher motor drive, which adopted this technique.

Hybrid Active Flux Observer to Suppress Position Estimation Error for Sensorless IPMSM Drives

Harmonics and drifts are found in the position estimation errors of high-frequency signal injection (HFI) methods. To suppress the position estimation error, a hybrid active flux observer with disturbance rejection for both HFI method and model-based method is proposed. It fuses the position information from traditional HFI method and model-based method as the input of a disturbance observer, the estimated disturbance output can compensate measurement error for the two methods. Then a reduced-order natural speed observer is connected in a cascaded form to reject motor mechanical disturbance by estimating the load torque. Besides, a stator resistance identification algorithm is proposed, which is proved stable near zero frequency under persistent excitation condition. A tuning guideline for the whole algorithm is elaborated based on a rigorous stability analysis. Effective experiments and simulations verify the feasibility of the proposed scheme on a 0.75-kW interior permanent magnet synchronous motor drive platform.

Time-Optimal Current Control of Synchronous Motor Drives

We are concerned with the problem of fast and accurate tracking of currents in the general synchronous drive. The problem becomes complicated with decreasing available voltage, which is common in high-speed and field weakening regimes. The existing time-optimal controllers rely on a simplified model, ignoring stator resistance and differences in inductances. We derive a solution for the general model considering all parameters and show how the parameters affect the current trajectory. One simplifying assumption had to be made, but we show in simulation that it has a negligible impact on accuracy. The simplification allowed for the design of a feed-forward controller that has a low computational cost and can be easily implemented in realtime. We provide experimental validation of the controller on the developed IPMSM drive prototype of the rated power of 4.5 kW using conventional industrial DSP. The controller is compared to conventional PI and deadbeat solutions, demonstrating that the time-optimal controller can reach the required setpoint four times faster than the competitors at the field weakening regime of the drive. The proposed feed-forward control can be seen as a universal building block that can be combined with existing feedback controllers and observers and thus incorporated into existing control solutions.

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.

Performance Analysis of 3 Phase Induction Motor Against Loading Using the Power Simulator (PSIM) Application

Three-phase induction motors are the most widely used type of motor in industry, induction motors are widely used as prime movers to turn loads on production machines in the industrial world. The output of a three-phase induction motor is the amount of torque to move the load. If the load torque carried by the three-phase induction motor is greater, then the three-phase induction motor will not rotate. And if the load torque carried by a three-phase induction motor is too small, this is considered excessive. In this analysis the method used by the author is the experimental method of analysis using the Power Simulator application with load data and induction motor data. Based on the analysis, it was found that Istart and Inominal on a 15 kW induction motor have different values ​​according to the torque value used, so the torque value is directly proportional to the Istart value. Meanwhile, Istart induction motors 15 kW 894.324 (15 N.m), 894.149 (25 N.m), 894.159 (60 N.m) and 45 kW induction motors 355.15 (25 N.m), 355.172 (60 N.m), 355.172 (80 N.m) and induction motors 55 kW 337.743 (30N.m), 337.76 (50N.m) and 337.761 (100N.m) Reaches 80% of full speed, torque is at its highest “pull-out torque”) and current starts to fall and is at full speed, or synchronous speed, torque and stator currents drop to zero, it can be concluded that the greater the value of the stator resistance, the smaller the value of the starting current.
 
 Keywords: Induction Motor, Torque, PSIM

Design and Xilinx Virtex-field-programmable gate array for hardware in the loop of sensorless second-order sliding mode control and model reference adaptive system–sliding mode observer for direct torque control of induction motor drive

This article aims first to propose an improved space vector modulation–direct torque control in order to enhance the induction motor performance using: (1) a super-twisting controller and (2) a novel model reference adaptive system based on a sliding mode observer. Second, due to the complexity of the suggested control algorithm, this article deals also with a hardware implementation on a field-programmable gate array board. Indeed, the field-programmable gate array is mainly chosen to reduce the execution time, thanks to its parallel processing which significantly improves the quality of the control system by reducing the sampling period, and consequently the delays in the control loop. Besides, the super-twisting controller is proposed to enhance the speed regulation loop which is a second-order sliding mode control technique that uses a continuous control law to prevent the chattering phenomenon induced by the first-order sliding mode control technique. Moreover, the high performance control requires information about the rotor speed which can be obtained by a sensor. Generally, the use of the speed sensor increases the system cost and size, and reduces its system reliability. Therefore, a combination between a model reference adaptive system observer and a sliding mode observer is suggested for speed estimation and overcoming the sensitivity of the classical model reference adaptive system observer against uncertainties and stator resistance variations. The performance of the proposed space vector modulation--direct torque control--super-twisting controller with the model reference adaptive system--sliding mode observer algorithm of an induction motor is verified through simulation, hardware co-simulation and experimental validation utilizing a field-programmable gate array Virtex-5-ML507 board. The performance of the suggested sensorless control method is compared also with other recent published schemes.

Control of PMSM Based on Switched Systems and Field-Oriented Control Strategy

Starting from the problem of studying the parametric robustness in the case of the control of a permanent magnet-synchronous motor (PMSM), although robust control systems correspond entirely to this problem, due to the complexity of the algorithms of the robust type, in this article the use of switched systems theory is proposed as a study option, given the fact that these types of systems are suitable both for the study of systems with variable structure and for systems with significant parametric variation under conditions of lower complexity of the control algorithms. The study begins by linearizing a PMSM model at a static operating point and continues with a systematic presentation of the basic elements and concepts concerning the stability of switched systems by applying these concepts to the control system of a PMSM based on the field-oriented control (FOC) strategy, which usually changes the value of its parameters during operation (stator resistance Rs, stator inductances Ld and Lq, but also combined inertia of PMSM rotor and load J). The numerical simulations performed in Simulink validate the fact that, for parametric variations of the PMSM structure, the PMSM control switched systems preserve qualitative performance in terms of its control. A series of Matlab programs are presented based on the YALMIP toolbox to obtain Pi matrices, by solving Lyapunov–Metzler type inequalities, and using dwell time to demonstrate stability, as well as the qualitative study of the performance of PMSM control switched systems by presenting in phase plane and state space analysis of the evolution of state vectors: ω PMSM rotor speed, iq current, and id current.

Performance of a Vector-Controlled PMSM Drive without Using Current Sensors

The current sensorless vector-controlled permanent-magnet synchronous motor (PMSM) drive using a single sensor (i.e., speed sensor) is presented in this work. The current sensors are removed, and the estimated currents are used to close the current loop to minimize the drive cost and make it fault-tolerant against current sensor failure. A classical vector-control PMSM drive requires at least three sensors, i.e., two current sensors and one speed/position sensor. This paper presents a new current estimation technique that is free from inverter switching states, an integrator, and differentiator terms. The drive is suitable for retrofit applications, as it does not require any additional hardware. The reference voltages (vds and vqs) are used to estimate the rotor reference frame currents (i.e., iqs and ids). The presented algorithm depends on the stator resistance (Ɍs). The online Ɍs estimation algorithm is used for compensation to overcome the effect of the Ɍs on the estimated currents. The sensitivity analysis for the currents against the speed is verified and presented. The speed loop is closed with actual speed information, which will try to maintain the reference speed under any circumstances. The proposed current sensorless PMSM drive was validated using MATLAB/Simulink and also verified on a hardware prototype. The presented technique was verified for various operation conditions, and some of the extensive results are presented.

Second-Order ESO-Based Current Sensor Fault-Tolerant Strategy for Sensorless Control of PMSM With B-Phase Current

Usually, two-phase current sensors are required to realize sensorless control of permanent magnet synchronous motor (PMSM). However, once the phase current sensor fails, the whole system will not work. In this article, a novel second-order extended state observer (SO-ESO) based current sensor fault-tolerant strategy for realizing PMSM sensorless control and multiparameter identification is proposed, which can significantly improve the system reliability. When a fault occurs in the A-C two-phase current sensor, the proposed scheme uses only a B-phase current sensor to estimate the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> - <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> axis stator current and time varying resistance, achieving a high-performance sensorless control function. In order to reduce the chattering of the system, a sigmoid function is introduced in the SO-ESO. In addition, an SO-ESO based parallel speed and multiparameter identification scheme are proposed by using two model reference adaptive system observer (MRASO). The first MRASO is designed based on super twisting algorithm with a corrective feedback loop and is used for estimating rotor speed and position. The second MRASO only needs to identify inductance and permanent flux because the stator resistance is estimated by SO-ESO. The second MRASO and SO-ESO updates the three identified electrical parameters (i.e., stator resistance, inductance, and permanent flux) and estimated currents to the first MRASO to achieve high robustness sensorless control. The relevant results show that the scheme gives good results, and the system has good dynamic performance and better fault tolerance.

Fault Diagnosis of Induction Motor Using D-Q Simplified Model and Parity Equations

Induction motors are the horsepower in the industrial environment, and among them, 3-phase induction motors (3PIMs) stand out for their robustness and standard 3-phase power supply. In the literature, there are many approaches to diagnose faults for the nonlinear 3PIM model, and the vast majority focus on a single motor fault, although others address more faults but at the cost of greater computational complexity. In this sense, one of the methods with less computational load and early detection is the parity equation approach, which is based on analyzing the discrepancy between the input and output signals of a real process and a linear mathematical model to generate a residual signal, which contains important information about the fault and is obtained through a suitable selection of a weighting matrix W to isolate the faults as much as possible. The problem in this case study is that the 3PIM model is a nonlinear system. In this work, the fault detection method based on the parity equations approach applied in the 3PIM is explored using a simplified and proposed model of the 3PIM working in the D-Q synchronous reference frame, which is matched with the direct current motor model to guarantee both the existence of the parity space and to ensure a large set of detectable faults in the 3PIM parameters. Simulation and experimental results validate the proposed scheme and confirm a very simple set of residual equations to guarantee both early detection and a large set of detectable faults in: Stator and rotor resistances, stator and rotor inductances, as well as current, voltage, and speed sensors. Additionally, development of human machine interface (HMI) is implemented to validate the proposed scheme.

ANN Optimization of Weighting Factors Using Genetic Algorithm for Model Predictive Control of PMSM Drives

Model predictive control (MPC) has become one of the most attractive control techniques due to its outstanding dynamic performance for permanent magnet synchronous motor (PMSM) drives. However, the tuning of weighting factors for the cost function of MPC is a time-consuming procedure and weighting factors can significantly affect torque ripples of PMSM drives. For the purpose of optimizing the weighting factors in cost functions of MPC, this article proposes an artificial neural network (ANN) based method, which applies genetic algorithm as the back propagation algorithm. Since this method is trained offline, it does not increase any computation complexity of MPC. Consequently, any optimization targets that combine the performance metrics of MPC are defined and the optimal weighting factors for the given targets can be fast and precisely found through the proposed method. Besides, this method is robust to the variations of motor parameters like stator resistance and permanent magnet flux. The superiority of the proposed method over conventional ANN is evaluated by comparative simulations, in terms of current total harmonic distortion, tracking performance, and neutral-point potential balance. Finally, the feasibility and robustness of the proposed method are verified on the platform of PMSM drives fed by three-level T-type inverter.

Research on the Influence of Temperature on the Performance of Induction Motor

Background: : Induction motor plays a major role in various industries, and its importance is increasing. Due to the environmental temperature or sealed working environment, heat generation is generally severe. The heat exchange with the outside environment does not take place smoothly, and the motor temperature increases. The performance of the induction motor is also significantly influenced by the temperature. Therefore, it is necessary to study the influence of temperature on the performance of induction motor. Objective: This study aimed to analyse the influence of temperature on induction motor. At different temperatures, variation in performance parameters has been observed. Methods: Taking an 11 kW 1500r/min induction motor as an example, a two-dimensional transient electromagnetic field model was established, and the correctness of the model was verified by experiments. The motor starting performance, various losses and efficiencies under different temperatures wereestimated. Results : As the stator and rotor resistance increased, the starting current decreased by 11.99% when the internal temperature rose from 25°C to 150°C. When the internal temperature rose from 25°C to 150°C, the stator copper loss increased by 32.83%, and the rotor copper loss increased by 28.79%. However, the core loss of the motor increased by 3W, and the motor efficiency decreased by 2.12%. Conclusion: When the temperature is different, the starting torque of the motor is almost unchanged, and the starting current decreases with an increase in temperature. The stator copper loss and rotor copper loss of the motor increase with the increase in temperature, while the core loss is almost unchanged. In addition, the efficiency of the motor gradually decreases with the increase in temperature.

A Sensorless Control Strategy of Injecting HF Voltage Into d-Axis for IPMSM in Full Speed Range

This article presents a sensorless control strategy by injecting high-frequency (HF) voltage into the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> -axis for the interior permanent magnet synchronous motor (IPMSM) in the full speed range. The defined quadratic virtual back electromotive force model can be adopted in the full speed range, and thus, there is no need to design a transition algorithm from the zero–low speed to the medium–high speed. Besides, the accurate model of IPMSM is applied to eliminate the error caused by ignoring the stator resistance. Furthermore, the estimation error caused by the filter and system delay during demodulating the HF current in the conventional HF voltage injection method is avoided. Compared with the method of injecting HF voltage into the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> -axis, the proposed method has smaller torque ripple and smaller injected voltage. The effectiveness of the proposed method is verified by experimental results.

Development of Integrated Softcomputing Approach for Stator Resistance Estimation of Three Phase Induction Motor

In this paper, an integrated quantum inspired GA (QGA) based generalized neural network (QGA–GNN) has been developed. The QGA–GNN is used for estimation of stator resistance of a 5 hp three phase induction motor (3Φ I.M.) under different healthy and unhealthy working conditions. The experimentation is performed in the laboratory for estimating stator winding resistance under healthy and faulty (i.e., 10, 20, 30, or 40% short circuited) conditions. The motor current and motor speed are considered as input and stator resistance as output of the proposed technique. The results obtained from QGA–GNN are compared with the ANN and GNN. QGA–GNN is giving good results under different working conditions.

An Algorithm for Estimation of Stator Resistance and Inductance of Low-Cost SMPMSM Drives

The information on stator resistance and inductance is extremely important for advanced electrical drives, which are used for tuning of position estimators, current controllers, temperature monitoring, and so on. The properly tuned control systems can provide fast response, have higher stability, and increase the efficiency of motor drives; as a result, it is of great importance at the development and tuning stages. This article proposes a simple estimation technique for surface-mounted permanent magnet synchronous motors (SMPMSMs), capable of measuring stator resistance and inductance. In order to measure the stator resistance, the developed algorithm injects two-leveled dc currents that provide information for resistance calculation. At the next stage, the estimation algorithm initiates exponential current transient, measures electric time constant of the motor, and calculates inductance. In contradiction to the conventional approach, this work composes a more detailed model of the motor and takes inverter voltage drop into account. Furthermore, this article studies several exponential transients, compares them to each other, and provides recommendations for use of each approach. Then, the proposed ideas are verified using several motors of different powers and parameters. Finally, the recommendations on application of each approach and parameter selection are provided.

An Algorithm for Offline Measurement of Motor Stator Resistance and Voltage Drop Across Inverter Switches for Washing Machine Drives

The knowledge of the exact value of motor phase resistance is extremely important for modern electrical drives, which use it for tuning of current controllers, position estimators, temperature monitoring, and so on. At the same time, the value of voltage drop across inverter switches is necessary for providing proper and efficient control, especially in the low-speed region, where the impact of system nonlinearities is significant. This article proposes a novel algorithm for the offline measurement of motor resistance and voltage drop across inverter switches, which significantly improved the performance of washing machines in open-loop starting and low-speed operation. The proposed technique uses two step injection of dc current into stator windings, which provides data for the estimation of resistance and voltage drop. This article describes traps and pitfalls on the way of implementation and tuning and provides recommendations on avoiding them. After analysis of detailed experimental results, the author gives recommendation on a selection of algorithm parameters in order to provide low estimation errors. Following successful implementation and a series of tests, this technique has been accepted for mass production and has become an inevitable part of the control system of washing machines.

Direct torque control based on second order sliding mode controller for three-level inverter-fed permanent magnet synchronous motor: comparative study

Introduction. The permanent magnet synchronous motor (PMSM) has occupied a large area in the industry because of various benefits such as its simple structure, reduced moment of inertia, and quick dynamic response. Several control techniques have been introduced for the control of the PMSM. The direct torque control strategy associated to three-level clamped neutral point inverter has been proven its effectiveness to solve problems of ripples in both electromagnetic torque and stator flux with regard to its significant advantages in terms of fast torque response. Purpose. The use of a proportional integral speed controller in the direct torque control model results in a loss of decoupling with regard to parameter fluctuations (such as a change in stator resistance value induced by an increase in motor temperature), which is a significant drawback for this method at high running speeds. Methods. That is way a second order sliding mode controller based on the super twisting algorithm (STA) was implemented instead of PI controller to achieve a decoupled control with higher performance and to insure stability while dealing with parameter changes and external disturbances. Results. The simulation results carried out using MATLAB/Simulink software show that the model of direct torque control based on a three-level inverter-fed permanent magnet synchronous motor drive has better performance with second order sliding mode speed controller than the proportional integral controller. Through the response characteristics we see greater performance in terms of response time and reference tracking without overshoots. Decoupling, stability, and convergence toward equilibrium are all guaranteed.