Vector-controlled Permanent Magnet Synchronous Motor Research Articles

Controller design using PSO and WOA algorithm for enhanced performance of vector-controlled PMSM drive

ABSTRACT This study presents the tuning strategy of PI controllers gain parameters to improve the performance of vector-controlled permanent magnet synchronous motor drive. In the proposed work PI controller parameters are optimized using Particle Swarm Optimization (PSO) and Whale Optimisation Algorithm (WOA). Nonlinear programming techniques, namely PSO and WOA optimisation, are employed to enhance the convergence rate of speed, torque, and flux errors using an offline tuning method. The simulation results of speed, torque, and flux show that the transient and steady state responses have been greatly improved and verified for different operating conditions. It has been observed that the quality of stator current, developed output voltage of inverter, and ripples in electromagnetic torque are also improved, which shows the feasibility and accuracy of the proposed method.

Classification of Optoelectronic Rotary Encoder Faults Based on Deep Learning Methods in Permanent Magnet Synchronous Motor Drive System

This article presents the classification of optoelectronics encoder faults in a permanent magnet synchronous motor (PMSM) drive system. This paper proposes the deep neural networks (DNNs) speed sensor faults classification application in the vector-controlled PMSM drive. This approach to the issue has not been discussed in the literature before. This work presents a solution based on early detection with the use of the model reference adaptive system (MRAS) estimator and fault classification based on artificial intelligence. The innovative nature of this work is also due to the simulation of speed sensor damage using the developed optoelectronics encoder model in the Matlab/Simulink environment. This work is focused on simulation studies, which have been supported by experimental results obtained on the MicroLabBox platform. This article compares two structures of deep neural networks in fault detection. The results were also compared with previous experimental studies on the classification of speed sensor failures using shallow neural networks.

Modeling and Analysis of Time Response Parameters of a PMSM-Based Electric Vehicle with PI and PID Controllers

This paper presents the mathematical modeling of a vector-controlled Permanent Magnet Synchronous Motor (PMSM) drive with either a Proportional Integral (PI) controller or a Proportional Integral Derivative (PID) controller as a propulsion system for an Electric Vehicle (EV). Most commercial drives use a standard PI controller as a speed regulator. The vector control system model consists of the PMSM, a PWM inverter, the speed controller, and vehicle dynamics for speed control. The performance analysis of the drive is evaluated under transient conditions for settling time, rise time, steady state error of speed, and the vehicle’s acceleration at the wheel axle for specifically designated values validated by MATLAB/Simulink.

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.

Vector-Controlled Permanent Magnet Synchronous Motor Drive with Reduced Current Sensor

Vector-Controlled Permanent Magnet Synchronous Motor Drive with Reduced Current Sensor

Adaptive Speed Estimation with Genetic Algorithm for Vector-controlled Permanent Magnet Synchronous Motor Drive

Adaptive Speed Estimation with Genetic Algorithm for Vector-controlled Permanent Magnet Synchronous Motor Drive

Design and Analysis of Current Sensor Fault Detection Mechanisms for PMSM Drives Based on Neural Networks

This paper describes a vector-controlled Permanent Magnet Synchronous Motor (PMSM) drive system with the current sensor fault detection mechanism. In general, the control structure is based on the well-known Field Oriented Control (FOC) algorithm. The structure is equipped with an additional algorithm for current sensor fault detection based on a neural network. The presented control structure is able to detect typical current sensor faults, such as lack of signal, intermittent signal, variable gain and signal noise. The application of the NN detector guarantees a faster detection of the sensor fault than classical detectors based on algorithmic methods or logical systems. This work focuses on presenting the methodology of designing detectors and their analysis, based solely on simulation analysis. The simulation results, conducted in the Matlab/Simulink environment, are presented for the above-mentioned faults in phase A and phase B for different speed conditions.

Parameter independent speed estimation technique for PMSM drive in electric vehicle

This paper presents a simple parameter independent speed estimation algorithm for vector-controlled permanent magnet synchronous motor (PMSM) drive. The speed estimation algorithm is formed using modified X-MRAS (modified fictitious quantity model reference adaptive system), independent of machine parameter, integrator, and differentiator terms. Any variation in the machine parameters will not affect the presented speed/position estimation algorithm. The speed sensorless method makes the drive more compact, reliable, reduces the cost, and mitigates environmental issues. The functional quantity of modified X-MRAS is developed using rotor reference frame voltages and currents. The proposed speed estimator is found to be stable in all the four quadrants of operation. This algorithm performs satisfactorily for variable speed and load operations. The proposed algorithm is verified through computer-based simulation using the MATLAB/SIMULINK platform and supported with experimental validation through the PMSM laboratory-developed prototype using the dSPACE-1104.

A Novel SVPWM Scheme for Field-Oriented Vector-Controlled PMSM Drive System Fed by Cascaded H-Bridge Inverter

In the motor drive system fed by multilevel inverter, the problems such as the complexity of reference voltage synthesis, high common mode voltage (CMV), and high switching loss are usually the obstacles to the practical application. In order to reduce the computational complexity and improve the performance of permanent magnet synchronous motor (PMSM), a novel space vector pulsewidth modulation scheme, which is practical and independent of level number is proposed for PMSM vector control. First, the space vector plane is redivided, and the coordinates of the nearest three vectors and their duty cycles can be obtained directly by determining the location of reference vector, which simplifies the calculation and does not need any iterative algorithm. Then, the optimal switching state and switching sequence are selected online so as to ensure the minimum switching loss under the premise of minimum CMV. This article provides an original method and new idea for motor drive system fed by multilevel inverter. Finally, the practicability and validity of the proposed method are verified by simulation and experiment.

A New Stator Resistance Estimation Technique for Vector-Controlled PMSM Drive

This article presents new stator resistance (R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> ) estimation techniques for a vector-controlled permanent magnet synchronous motor (PMSM) drive. These techniques give the indirect measurement of the temperature rise in the stator. An accurate estimation of the R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> will help in the condition monitoring of the PMSM machine. The various R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> estimation techniques proposed in this article are formulated using the model reference adaptive system (MRAS). Out of the various methods proposed, Þ - MRAS performs better than the remaining stator resistance estimation techniques since this is independent of the integrator, differentiator, and speed; offers robust and dynamic performance in all four modes of operation, including zero speed. The stability and sensitivity analysis is further carried out to ensure the robustness of the proposed estimation techniques. The proposed stator resistance estimation techniques are simulated in MATLAB/Simulink and experimentally validated through a dSPACE-1104-based laboratory prototype.

A New Diagnostic Algorithm for Multiple IGBTs Open Circuit Faults by the Phase Currents for Power Inverter in Electric Vehicles

In order to simplify the application and improve diagnostic speed of the diagnostics, a novel method to diagnose multiple open circuit faults in insulated gate bipolar transistors (IGBTs) by three-phase currents for power inverter in electric vehicles is presented. The summation of currents with semi-period phase-difference is described in diagnostic variables with exploration of the current information in faulty condition. In contrast with plentiful existing methods which rely on the motor models and control parameters, this algorithm merely requires phase currents. Meanwhile, the normalized way based on the absolute phase currents and variable parameter moving average method are applied to improve the diagnostic speed and independence of load variation, which contributes to the real-time application in the electric vehicles. Experimental results, using a vector-controlled permanent magnet synchronous motor (PMSM) and digital signal processor MC56F8346, are presented to verify the algorithm effectiveness, showing many features, such as applicability for multiple open circuit faults, well-robustness against false alarms, briefness and agility for the diagnosis function.

Vector-controlled Permanent Magnet Synchronous Motor Using Indirect Matrix Converter

In this paper, the vector-controlled Permanent Magnet Synchronous Motor (PMSM) fed by Indirect Matrix Converter (IMC) is analyzed, designed, and simulated by using the IMC with Carrier Based Pulse Width Modulation (CBPWM). The CBPWM strategy is based on Space Vector Pulse Width Modulation (SVPWM) analysis, it is used to enhance the input current waveform, reduce the complexity of switching signals generation, and to solve the commutation problem. The traditional PMSM drive system is simulated for comparison with proposed drive system. The proposed drive system is compared to the traditional drive system using the Total Harmonic Distortion (THD). The comparison results show that the proposed drive system outperform the traditional drive system by THD different of 1/30 of input current and 1/1.5 of stator current, with high input power factor.

Adaptive-Linear-Neuron-Based Dead-Time Effects Compensation Scheme for PMSM Drives

This paper presents an adaptive-linear-neuron (ADALINE)-based dead-time compensation method for vector-controlled permanent-magnet synchronous motor drives. The proposed strategy is achieved by suppressing the sixth-order current harmonics in the dq-axes synchronous reference frame. Four ADALINEs are employed in the proposed algorithm. Two ADALINEs are used for estimating the sixth-order harmonic components of dq-axes currents and the other two are used for generating the dq-axes compensation voltages. The voltage compensators are self-tuned by minimizing the estimated current distortion by means of the least mean square algorithm. The proposed compensation algorithm does not require any additional hardware or complicated signal processing algorithms. Experimental results validating the proposed compensation method are also presented.

Elimination of Low-speed Vibration in Vector-controlled Permanent Magnet Synchronous Motor by Real-time Adjusted Extended Kalman Filter

The inaccuracy and delay of speed feedback cause a vibration problem when the permanent magnet synchronous motor runs at low speed. As the low-speed smoothness is a key point of many applications of the permanent magnet synchronous motor, this article solves this problem by adding a real-time adjusted extended Kalman filter to low-precision-sensor vector control. In the mathematical model, the estimated speed of the extended kalman filter is significantly impacted by the deviations of the resistance and magnetic flux rather than other parameters. Thus, under id = 0 vector control, a Rs-ψf-identifier is designed to calculate the values of the resistance and flux simultaneously with a small compensating id. This algorithm runs on the platform in real time. Finally, the experiment results validate that when the velocity reaches as low as 1 r/min, the proposed method eliminates the vibration problem in the low-precision-sensor permanent magnet synchronous motor.

A New Algorithm for Real-Time Multiple Open-Circuit Fault Diagnosis in Voltage-Fed PWM Motor Drives by the Reference Current Errors

Three-phase inverters are currently utilized in an enormous variety of industrial applications, including variable-speed ac drives. However, due to their complexity and exposure to several stresses, they are prone to suffer critical failures. Accordingly, this paper presents a novel diagnostic algorithm that allows the real-time detection and localization of multiple power switch open-circuit faults in inverter-fed ac motor drives. The proposed method is quite simple and just requires the measured motor phase currents and their corresponding reference signals, already available from the main control system, therefore avoiding the use of additional sensors and hardware. Several experimental results using a vector-controlled permanent-magnet synchronous motor drive are presented, showing the diagnostic algorithm effectiveness, its relatively fast detection time, and its robustness against false alarms.

Analysis for Fault Detection of Vector-Controlled Permanent Magnet Synchronous Motor With Permanent Magnet Defect

This paper analyzes the characteristics of a vector-controlled permanent-magnet synchronous motor (PMSM) with a permanent-magnet defect. A method for the diagnosis of the demagnetization of the permanent magnet in PMSM is proposed. In the proposed method, the magnetic field is calculated by the finite-element method, and then the flux linkage and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> axis inductances are calculated. They are introduced into the block diagram of the drive and control system. We have manufactured interior permanent-magnet motors, where one of four magnets is reduced by 10% and 20% in order to imitate the demagnetization. It is shown that the Fourier and wavelet results are in good agreement with the measured ones. This paper shows that the stator current and stator voltage using the proposed method are useful for the fault detection of demagnetized permanent magnet.

Permanent Magnet Synchronous Motor Drive Using Hybrid PI Speed Controller With Inherent and Noninherent Switching Functions

The performance of the fuzzy logic controller (FLC) is better under transient conditions, while that of the proportional plus integral (PI) controller is superior near the steady-state condition. The combined advantages of these two controllers can be obtained with hybrid fuzzy-PI speed controller. The computations involved with the FLC are much higher as compared to that of the PI controller. Generally, the FLC output is near the maximum permissible value at the beginning of a transient condition but reducing with the reduction in the speed error. In this paper, instead of the FLC, a fuzzy equivalent proportional (FEP) controller is used along with the PI controller to make it a hybrid PI (HPI) controller which eventually is much faster and less computation intensive. The performance of the vector-controlled permanent magnet synchronous motor drive with this HPI controller is obtained with six switching functions, namely: 1) saturation; 2) hyperbolic tangent; 3) polynomial S function; 4) output of FEP controller only; 5) output of PI controller only; and 6) combination of the outputs of both the PI and FEP controllers. From the results, it is observed that the polynomial S switching function based HPI controller is better in general for most of the performances.

Dynamic modeling of a 6-degree-of-freedom Stewart platform driven by a permanent magnet synchronous motor

For an electrical six-degree-of-freedom Stewart platform, it is difficult to compute the equivalent inertia of each motor in real time, as the inertia is time-varying. In this study, an analysis using Kane’s equation is undertaken of the driven torque of the movements of motor systems (including motor friction, movements of motor systems along with the actuators, rotation around axis of rotors and snails), as well as driven torque of the platform and actuators. The electromagnetic torque was calculated according to vector-controlled permanent magnet synchronous motor (PMSM) dynamics. By equalizing the driven torque and electromagnetic torque, a model was established. This method, taking into consideration the influence of counter electromotive force (EMF) and motor friction, could be applied to the real-time dynamic control of the platform, through which the calculation of the time-varying equivalent inertia is avoided. Finally, simulations with typically desired trajectory inputs are presented and the performance of the Stewart platform is determined. With this approach, the multi-body dynamics of the electrical Stewart platform is better understood.

Adaptive Dead-Time Compensation Strategy for Permanent Magnet Synchronous Motor Drive

This paper presents an adaptive dead-time compensation strategy to obtain fundamental phase voltage for inverter-fed vector-controlled permanent magnet synchronous motor drives. A phase dead-time compensation voltage (DTCV) to compensate the disturbance voltage due to undesirable characteristics of inverter, such as dead time, turn on/off time of switching devices, and on-voltages of switching devices and diode, is transformed into q-axis DTCV in the rotor reference frame. The relationship between q-axis DTCV and a dead-time compensation time (DTCT) is investigated. DTCT is identified online by using q-axis disturbance voltage, which is estimated by a disturbance observer. The amplitude of phase DTCV is adaptively determined according to the identified DTCT. The accuracy of identified DTCT is experimentally confirmed by calculating the mean absolute percentage error (MAPE) between calculated active power and measured one. MAPE for adaptive DTCT is within 5% at any operating point and is less than that for the fixed DTCT.

A Fast Transient-Current Control Strategy in Sensorless Vector-Controlled Permanent Magnet Synchronous Motor

This letter presents a current control technique for fast transient-current response in a sensorless vector-controlled permanent magnet synchronous motor. Pontryagin's maximum principle is employed to derive the time-optimal voltage solution. Based on this principle, the technique can guarantee the current vector transition from one operating point to another with minimum time. Compared to a proportional-integral controller, the current response by using the time-optimal controller is much faster, even under a limited dc bus voltage. Experiments are carried out to substantiate the proposed technique