Speed Sensorless Induction Motor Research Articles

Wide-Speed Range Stability Improvement of Speed-Sensorless Induction Motor Drives Based on Orthogonality Voltage-Model Observer

Wide-Speed Range Stability Improvement of Speed-Sensorless Induction Motor Drives Based on Orthogonality Voltage-Model Observer

Novel Advanced Artificial Neural Network-Based Online Stator and Rotor Resistance Estimator for Vector-Controlled Speed Sensorless Induction Motor Drives

This paper presents a new approach for the online estimation of stator and rotor resistance of induction motors for speed sensorless vector-controlled drives, using feed-forward artificial neural networks with advanced adaptive learning rates. For the rotor resistance estimation, a neural network model based on rotor speed and stator currents is developed. The rotor flux linkages acquired from the voltage model are compared with the neural network model. The feed-forward neural network employs an adaptive learning rate as the function of the obtained error during training for quick convergence with minimal estimation error. A two-layered neural network model based on the stator voltage and current equations is developed for the stator resistance estimation. The d-q axes stator currents obtained from the developed model are compared with the acquired d-q axes stator currents. For the fast convergence with minimal estimation error, an adaptive learning rate as the function of error is adopted during training. Furthermore, the neural network estimates the induction motor’s speed. The simulation and experimental results justify that the developed algorithms track variation in the resistances quickly and precisely along with the speed as compared with the conventional constant learning rate algorithm, leading to reliable operation of the drive.

Predictive Compensation-Based Harmonics Suppression for Speed-Sensorless Induction Motor Drives With Improved Feedback Gains

Predictive Compensation-Based Harmonics Suppression for Speed-Sensorless Induction Motor Drives With Improved Feedback Gains

Adaptive High Gain Observer Based MRAS for Sensorless Induction Motor Drives

Because of their advantages, speed sensorless induction motor drives have received a lot of attention in the academic and industrial communities over the last decade. Despite the recent developments in this area, the performance of sensorless variable-speed IM drives in ultra-low and zero electrical rotor speeds and regeneration mode remains a big challenge. To obtain acceptable results under unobservable conditions, an adaptive high gain observer-based MRAS speed estimator is proposed in this paper. The stability analysis of the proposed algorithm is proved using the Lyapunov stability theorem. Moreover, the efficiency and feasibility of the proposed estimator are verified by comparative experiments.

Discrete Sliding-Mode-Based MRAS for Speed-Sensorless Induction Motor Drives in the High-Speed Range

By combining the high robustness of sliding-mode observer (SMO) with the adaptability of model reference adaptive system (MRAS), the sliding-mode-based MRAS can improve the speed estimation performance of speed-sensorless induction motor (IM) drives. However, the analysis of this paper shows that there exists a mismatch problem between the fixed-value of SMO gains and the variable stability boundary which changes with IM operation speed, resulting in speed estimation performance degradation or even instability in high-speed range. To cope with this problem, a discrete SMO is proposed to expand the effective operation range of sliding-mode-based MRAS. First, a discrete terminal SMO with modified observer structure is designed for rotor flux estimation. Then, a variable gain is designed to ensure the SMO stability in high-speed range, and avoid the chattering caused by gain value overestimation. Compared with existing sliding-mode-based MRAS, the studied method can improve the stability and accuracy of speed estimation in high-speed range. Finally, the experimental results from a 3.7kW IM test bench can confirm the validness of studied speed estimation scheme.

Graphical Multiple-Error Feedback Matrix Design for Stability and Robustness Enhancement of Speed-Sensorless Induction Motor Drives

For speed-sensorless induction motor (IM) drives, the feedback matrix is a significant technique to enhance the stability in low-speed regenerating region. However, further analyzes show it has difficulty for existing methods in maintaining the stability and robustness with parameter uncertainties. To cope with this problem, in this article, a graphical design method of multiple-error feedback matrix (ME-FBM) is presented for adaptive full-order observer. First, the flux error is introduced by projection of current error. Adopting flux error and current error, the ME-FBM is graphically developed to satisfy the stability necessary condition by reconstructing the stability function. As a result, the unstable region is eliminated during low-speed regenerating mode. On this basis, the gains of ME-FBM is graphically selected to reduce the error of estimated rotor flux and improve the robustness against parameter uncertainties at low-stator frequencies. Finally, the effectiveness of proposed ME-FBM is verified on a 2.2 kW IM experimental setup.

Sliding mode control rotor flux MRAS based speed sensorless induction motor traction drive control for electric vehicles

<abstract><p>Climate change has highlighted a need to transition to more sustainable forms of transportation. Electric vehicles (EVs) and hybrid electric vehicles (HEVs) offer a promising alternative to conventional gasoline powered vehicles. However, advancements in power electronics and advanced control systems have made the implementation of high performance traction drives for EVs and HEVs easy. In this paper, a novel sliding mode control model reference adaptive system (SMC-MRAS) speed estimator in traction drive control application is presented. However, due to the unpredictable operational uncertainties of the machine parameters and unmodelled non-linear dynamics, the proportional-integral (PI)-MRAS may not produce a satisfactory performance. The Proposed estimator eliminates the PI controller employed in the conventional MRAS. This method utilizes two loops and generates two different error signals from the rotor flux and motor torques. The stability and dynamics of the SMC law are obtained through the Lyapunov theory. The potential of the proposed SMC-MRAS methodology is simulated and experimentally validated for an electric vehicle application. Matlab-Simulink environment is developed and proposed scheme is employed on indirect vector control method. However, for the experimental validation, the dSPACE 4011 R & D controller board was utilized. Furthermore, the SMC-MRAS performance is differentiated with PI-MRAS for speed regulation performance, tracking and estimation error, as well as the fast minimization of the error signal. The results of the proposed scheme illustrate the enhanced speed estimation, load disturbance rejection ability and fast error dynamics.</p></abstract>

Current Sensor Fault-Tolerant Control for Speed-Sensorless Induction Motor Drives Based on the SEPLL Current Reconstruction Scheme

In speed-sensorless-controlled induction motor (IM) drives, current sensors are important but prone to failure, which may significantly degrade control performance. In view of this, this paper proposes a current sensor fault-tolerant control (FTC) scheme for speed-sensorless IM drives. In the proposed current sensor FTC scheme, a single-phase enhanced phase-locked loop (SEPLL) is implemented to reconstruct the faulty phase current without the use of the estimated speed or rotor position. With this, the undesired coupling effects caused by the introduction of estimated speed or estimated position are avoided. Afterwards, with the well-reconstructed current, satisfactory speed and current estimation performance are achieved by the sliding mode observer (SMO) under a current sensor fault. By doing so, the single-phase-current sensor speed-sensorless control of the IM drives can be achieved. A series of experimental tests are executed to verify the effectiveness of the proposed current sensor FTC scheme.

An Adaptive Active Disturbance Rejection Control Strategy for Speed-Sensorless Induction Motor Drives

Speed-sensorless control of induction motor drives based on the extended state observer (ESO) attracts much popularity due to its key characteristics, e.g., satisfactory estimation performance, and high robustness against disturbances. However, the conventional ESO generally uses fixed high gains to achieve fast convergence. This may bring about the concern of noise sensitivity. Moreover, a proportional-integral (PI)-type speed controller is mostly adopted in speed-sensorless control of induction motor drives, which may cause unsatisfactory system dynamics. To address these, an adaptive active disturbance rejection control (ADRC) strategy is proposed for speed-sensorless induction motor drives in this article. In this scheme, a third-order adaptive ESO (AESO) is first used to estimate the speed, the phase, and the overall disturbance. Then, a speed controller based on the state error feedback control rate (SEFCR) is designed to improve system dynamics. In practice, disturbances like dc offsets may further challenge estimation performance, and hence, a closed-loop flux observer (CLFO) is employed to deal with this issue. Additionally, a parameter sensitivity analysis of the CLFO is also provided to evaluate the performance of the proposed scheme. Finally, extensive experimental tests have been carried out to validate the effectiveness of the proposed.

Virtual voltage vector based predictive current control of speed sensorless induction motor drives

Nowadays, predictive current control (PCC) strategy has been recognized as a promising option for the control of electric drives for their control flexibility, fast dynamic response and weighting factorless structure of objective function. However, such kinds of conventional control strategies make drives to suffer from the ingress of significant harmonics in stator current, increasing further the steady state flux ripple followed by a noticeable torque ripple. To ameliorate these aforementioned shortcomings of conventional scheme, the present work employs the concept of virtual voltage vector (V3) in PCC strategy. The mathematical steps of the proposed V3PCC make the scheme more frontward in delay compensation, and also less parameter sensitive than the conventional one. As a baseline for the performance analysis, the present V3PCC is compared with a weighting factorless V3 based predictive flux control (PFC) scheme in induction motor (IM) drive. A speed adaptive flux observer is considered for the speed estimation purpose in both the control schemes. The performance of both the sensorless schemes for IM drive are analysed in MATLAB/Simulink, and also experimentally verified in a 2.2 kW IM drive test bench.

Stability Analysis and Trajectory Design of a Nonlinear Switching System for Speed Sensorless Induction Motor Drive

For wide-speed range operation of speed sensorless induction motor drives (SSIMD), the stable operation at low synchronous speed range (including zero synchronous speed) is a great challenge. Virtual voltage injection method is found efficient to overcome this challenge. However, the injected virtual voltage into observer results in the estimated speed error, it is reasonable to rely upon this method only when the performance of traditional SSIMD is poor, i.e., at low speed range. At middle and high speed ranges, virtual voltage injection method cannot meet the high-accuracy requirement of speed estimation in industrial application. For wide-speed range operation of SSIMD, a necessary switching system is proposed in this article to meet the stability requirement and accuracy requirement at the same time. The input-state stability theory is adopted to verify the stability of switching method, because the switching system is a nonlinear and strong coupling system. Then the switching trajectory is optimized for smooth and fast switching transition. Finally, the effectiveness and feasibility of the proposed method are verified by experimental results.

Predictive Torque Control Strategy for Speed Adaptive Flux Observer Based Sensorless Induction Motor Drive in Flux-Weakening Region

In general, flux-weakening operation of induction motor (IM) drive to achieve control above the rated speed is challenging. The challenge further aggravates if the drive becomes speed sensorless. This article primarily focuses on the flux-weakening operation of adaptive flux observer-based speed sensorless IM drive working under a promising predictive torque control (PTC) regime. The flux-weakening operation, in this case, is more challenging because of the involvement of additional unavoidable estimation strategies essential for PTC algorithm, thereby further deteriorating drive's performance in the flux-weakening region if not addressed suitably. In this article, a simple flux and torque scaling factor-based approach is introduced in the PTC algorithm of the adopted sensorless IM drive to improve the performance in flux-weakening region. The drive's performance in terms of speed tracking is thoroughly investigated in MATLAB/Simulink. Moreover, stability study in the entire operating range has also been done in the same environment. Experimental results demonstrating the speed of operation up to 3.5 times the base speed as obtained with 2.2 kW IM drive interfaced with dSPACE ds1103 controller are also presented in this article.

A novel FPGA‐Based Bi input‐reduced order extended Kalman filter for speed‐sensorless direct torque control of induction motor with constant switching frequency controller

This study proposes an FPGA-based hardware in the loop (HIL) emulator for speed-sensorless of induction motor (IM) constant switching frequency controller-based direct torque control (CSFC-DTC) with a novel bi input-reduced order extended Kalman filter (BI-ROEKF). The full precision single floating point numbers in the IEEE 754 standard are used during the implementation of the HIL emulator which contains closed-loop speed-sensorless drive system of IM on the Xilinx Virtex XC5VLX-110T ML506 FPGA board. In this HIL emulator of speed-sensorless IM drive system, stator stationary axis components of stator flux, rotor mechanical angular speed, load torque, stator and rotor resistances are estimated with the novel BI-ROEKF which is proposed for the first time in the literature. The proposed BI-ROEKF is created by applying two different non-linear and linear system input functions obtained from two different IM models to the single reduced order extended Kalman filter (ROEKF) algorithm. Thus, the order and the computational burden of the EKF are reduced. The HIL emulator of the speed-sensorless drive system of IM is implemented on FPGA using the advantage of hand-written VHDL on getting an optimal logical design to reduce the sampling time which directly effects the estimation performance of the model-based estimator like the novel BI-ROEKF and hence the control performance of drive system. The estimation performance of the novel BI-ROEKF is tested with speed-sensorless CSFC-DTC IM drive system under different challenging scenarios in HIL emulator. Thus, the control and the implementation performances of digitalised emulator are tested. Finally, the estimation and control performance results and the execution time of the each part of the proposed HIL emulator of the speed-sensorless BI-ROEKF-based CSFC-DTC of the IM are presented.

Particle swarm optimization-based stator resistance observer for speed sensorless induction motor drive

This paper presents a different technique for the online stator resistance estimation using a particle swarm optimization (PSO) based algorithm for rotor flux oriented control schemes of induction motor drives without a rotor speed sensor. First, a conventional proportional-integral controller-based stator resistance estimation technique is used for a speed sensorless control scheme with two different model reference adaptive system (MRAS) concepts. Finally, a novel method for the stator resistance estimation based on the PSO algorithm is presented for the two MRAS-type observers. Simulation results in the Matlab/Simulink environment show good adaptability of the proposed estimation model while the stator resistance is varied to 200% of the nominal value. The results also confirm more accurate stator resistance and rotor speed estimation in comparison with the conventional technique.

Enhanced Low-Frequency Ride-Through for Speed-Sensorless Induction Motor Drives With Adaptive Observable Margin

For speed-sensorless induction motor (IM) drives, the observability of rotor speed is still a challenging problem under steady-state operations at low synchronous frequencies. To cope with this problem, an enhanced magnetizing current-oriented low-frequency ride-through method is proposed for adaptive full-order observers to ensure the observability of rotor speed. The adaptive changes of magnetizing current reference are generated to maintain the speed observable margin near zero synchronous frequency. Compared with existing methods, it avoids the noises caused by direct rotor flux reference calculation. In addition, the feedback matrix is employed to narrow the unstable regenerating region, and enlarge the observable margin. Addressing the detailed implementation, the analyses are provided with respect to output torque constraint, magnetizing current selection, and observability. Finally, the effectiveness of proposed method is validated on a 2.2 kW IM experimental bench during low-frequency ride-through.

The Universality Analysis of Virtual Voltage Injection Method for Different Observers in Speed Sensorless IM Drives

There are three main reasons that result in unstable problem of speed sensorless induction motor drives (SSIMD): unobservable rotor speed at low speed range, unstable poles' placement of the vector control system at low speed range, and poor robustness at low speed range. If and only if these three problems are solved simultaneously, the unstable problem of SSIMD can be solved completely. There are many solutions (observers) being proposed to solve these three problems. However, these observers cannot solve three problems simultaneously. In addition, each solution does not have universality and cannot fit for different observers. There is no generic method that can be applicable to different observers and can solve three problems simultaneously by now. In this article, the universality of virtual voltage injection method is analyzed. It can be proved that virtual voltage injection is a generic, effective, and simple method that can solve three problems simultaneously and can be applicable to different observers. Finally, the feasibility is verified by experiments.

Real-Time Processor-in-Loop Investigation of a Modified Non-Linear State Observer Using Sliding Modes for Speed Sensorless Induction Motor Drive in Electric Vehicles

Tracking performance and stability play a major role in observer design for speed estimation purpose in motor drives used in vehicles. It is all the more prevalent at lower speed ranges. There was a need to have a tradeoff between these parameters ensuring the speed bandwidth remains as wide as possible. This work demonstrates an improved static and dynamic performance of a sliding mode state observer used for speed sensorless 3 phase induction motor drive employed in electric vehicles (EVs). The estimated torque is treated as a model disturbance and integrated into the state observer while the error is constrained in the sliding hyperplane. Two state observers with different disturbance handling mechanisms have been designed. Depending on, how they reject disturbances, based on their structure, their performance is studied and analyzed with respect to speed bandwidth, tracking and disturbance handling capability. The proposed observer with superior disturbance handling capabilities is able to provide a wider speed range, which is a main issue in EV. Here, a new dimension of model based design strategy is employed namely the Processor-in-Loop. The concept is validated in a real-time model based design test bench powered by RT-lab. The plant and the controller are built in a Simulink environment and made compatible with real-time blocksets and the system is executed in real-time targets OP4500/OP5600 (Opal-RT). Additionally, the Processor-in-Loop hardware verification is performed by using two adapters, which are used to loop-back analog and digital input and outputs. It is done to include a real-world signal routing between the plant and the controller thereby, ensuring a real-time interaction between the plant and the controller. Results validated portray better disturbance handling, steady state and a dynamic tracking profile, higher speed bandwidth and lesser torque pulsations compared to the conventional observer.

Open gate fault diagnosis and tolerant for voltage source inverter fed speed sensorless induction motor drive

ABSTRACT This paper presents an effective fault diagnostic and tolerant method for an open-gate fault of a three-phase inverter. The induction motor (IM) drive system is controlled by a speed sensorless indirect rotor field-oriented control (IRFOC). The proposed diagnostic method requires low computation to detect open-gate faults. This method uses a simple direct current technique based on the measured motor currents to detect faulty switch. The fault-tolerant scheme is based on changing the inverter topology from six to four switches to ensure proper operation. In the faulty case, the fault-tolerant technique disconnects the motor phase terminal from the faulty arm of the inverter and connects it to the midpoint of the DC-link via an external switch. The performance of the IM drive is investigated and analysed under normal, faulty and post-fault operations through simulation and experiment. The results demonstrate the effectiveness of the fault diagnostic and tolerant method for retaining almost the normal performance of the IM drive system.

Development of energy efficient scheme for speed sensorless induction motor drive

Development of energy efficient scheme for speed sensorless induction motor drive

Robust Stability Improvement for Speed Sensorless Induction Motor Drive at Low Speed Range by Virtual Voltage Injection

The unstable problem of speed sensorless induction motor drives (SSIMDs) at low synchronous speed range has not been solved yet. In this paper, the reason of this unstable problem is concluded as two key points: 1) there are poles of the transfer function of the SSIMD system owning positive real part at low speed range; and 2) the rotor speed is unobservable at zero synchronous speed. Correspondingly, to guarantee the stability of the SSIMD system at low speed range, the system has to achieve two conditions simultaneously: the transfer function of the SSIMD system is stable (transfer function stability (TFS) condition) and the rotor speed is observable (rotor speed observability (RSO) condition). To satisfy these two conditions, virtual voltage injection is proposed. The unstable problems can be solved by this proposed method. In addition, the robustness of the virtual voltage injection method is analyzed. When motor parameters are inaccurate, the stability of the system will not be influenced. Finally, the feasibility of the proposed method is verified by experiments.