Sensorless finite-control set model predictive control for IPMSM drives

This paper investigates the feasibility of a sensorless field oriented control (FOC) combined with a finite control set model predictive current control (FCS-MPC) for an interior permanent magnet synchronous motor (IPMSM). The use of a FCS-MPC makes the implementation of most of the existing sensorless techniques difficult due to the lack of a modulator. The proposed sensorless algorithm exploits the saliency of the motor and the intrinsic higher current ripple of the FCS-MPC to extract position and speed information using a model-based approach. This method does not require the injection of additional voltage vectors or the periodic interruption of the control algorithm and consequently it has no impact on the performance of the current control. The proposed algorithm has been tested in simulation and validated on an experimental set-up, showing promising results

GFTSM-based Model Predictive Torque Control for PMSM Drive System With Single Phase Current Sensor

Copyright © 2017 Acta Automatica Sinica. All rights reserved. A global fast terminal sliding mode (GFTSM)-based model predictive torque control (MPTC) strategy is developed for permanent magnet synchronous motor (PMSM) drive system with only one phase current sensor. Generally two phase-current sensors are indispensable for MPTC. In response to only one phase current sensor available and the change of stator resistance, a novel adaptive observer for estimating the remaining two phase currents and time-varying stator resistance is proposed to perform MPTC. Moreover, in view of the variation of system parameters and external disturbance, a new GFTSM-based speed regulator is synthesized to enhance the drive system robustness. In this paper, the GFTSM, based on sliding mode theory, employs the fast terminal sliding mode in both the reaching stage and the sliding stage. The resultant GFTSM-based MPTC PMSM drive system with single phase current sensor has excellent dynamical performance which is very close to the GFTSM-based MPTC PMSM drive system with two-phase current sensors. On the other hand, compared with proportional-integral (PI)-based and sliding mode (SM)-based MPTC PMSM drive systems, it possesses better dynamical response and stronger robustness as well as smaller total harmonic distortion (THD) index of three-phase stator currents in the presence of variation of load torque. The simulation results validate the feasibility and efiectiveness of the proposed scheme

Rotor-position detection in permanent-magnet wheel motor to ensure smooth startup from standstill

In this paper, an innovative rotor-position-detection method for a permanent-magnet wheel motor (PMWM) that operates from standstill to low speed is presented. The neutral voltage, which is sensed through phaseshifted pulse width modulation, overcomes the limitations of the conventional back electromotive force (EMF)-based position-detection method, which is more suitable for high-speed operation. In addition, a technique that ensures a transition between the two position-detection methods is presented to cover the full speed range. Computer simulations are employed to design and assess the neutral-voltage-based and EMF-based position-detection methods. The results of the position detection and angle error are presented starting from standstill to low speed. A step current (iq) corresponding to motor torque demand is applied for the starting process in the two position-detection methods. The experimental studies of the new position-detection method are conducted. The method is successfully applied to drive a 60-kW PMWM that operates from standstill to high speed. This demonstrates the effectiveness and performance of the presented method

Dynamic performance evaluation of sensorless permanent magnet synchronous motor drives with reduced current sensors

A novel position sensorless PMSM (Permanent Magnet Synchronous Motor) drive that uses only a DC-link current sensor is presented in this paper. This concept is already known, but several new implementation details are shown in the paper. The proposed drive system is simple and can be implemented using a low-cost control hardware. The dynamic performance of the proposed drive is evaluated and compared with the performance of position sensorless and full sensored drives

Sensorless Passive Control Algorithms for Medium to High Power Synchronous Motor Drives

This study is focused on the definition of sensorless algorithms for Surface-Mounted Permanent Magnet Synchronous Motors (SM-PMSM) and Electrically Excited Synchronous Motors (EESM). Even if these types of motors are rather different from a constructive point of view, they have some common issues regarding sensorless drives. Indeed, SM-PMSMs, which are usually used for low-medium power applications, have a low rotor anisotropy, therefore it is complicated to use sensorless active methods (which are based on high-frequency voltage injection), due to the low signal to noise ratio. On the other hand, active methods on high-power EESM have the drawback of high torque ripple. For these reasons, both for SM-PMSM and EESM, it is interesting to define and use sensorless passive algorithms (i.e., based on observers and estimators). The drawback of such algorithms is that their performance deteriorates significantly in the low-speed region. The aim of this thesis is to define a robust sensorless passive algorithm that could work in a wide speed region and that could start the motor from standstill even with a high load torque. The initial objective of the work is to find, among the various algorithms proposed in the technical literature, the most promising one. For this purpose, four different algorithms are selected. They are chosen considering the most recent articles presented in the technical literature on high reputable journals. Since many improvements are proposed in the literature for the different algorithms, the most recent ones are candidates for being the ones with higher performance. Even if the experimental tests of the four different algorithms are shown in the literature, it is difficult to evaluate a priori which offers the best performance. As a matter of facts, for each algorithm different tests are carried out (e.g., different speed and torque profiles). In addition to that, motor sizing and features are different. Moreover, the test bench characteristics can significantly affect sensorless performance. As an example, inverter features and non-linearities (e.g., switching frequency, dead times, parasitic capacitance) and current measures (e.g., noise, linearity, bias) play a key role in the estimation of rotor position. The added value of this thesis is to perform a fair comparison of the four algorithms, performing the same tests with the same test bench. Additional tests are performed on the most performing algorithm. Even if this sensorless technique is already proposed in the technical literature, a methodology for observer gain tuning is not shown, which is proposed, instead, in this thesis. Moreover, the algorithm is enhanced by adding a novel management of direct axis current, which ensures the stability during fast transient from medium-high speed to low speed. The algorithm is tested with different test benches in order to verify the control effectiveness in various operating conditions. As a matter of facts, it is tested at first in the University of Genoa PETRA Lab on two different test benches. The first test bench is composed of two coupled motors, in which the braking motor could realize different torque profiles (linear torque, quadratic torque and constant torque), whereas in the second test bench the motor is coupled with an air compressor, which is a demanding load since high and irregular torque is applied at standstill. After the test at the University of Genoa, the algorithm is implemented in Phase Motion Control and Physis drive and tested on a six-meter diameter fan. Regarding the EESMs, for these type of motor is necessary to estimate the stator flux amplitude and angle. Indeed, the stator angle is usually used to perform the Park transformations in the FOC scheme and the stator flux amplitude is used to control the excitation current. In this study, the RFO is adapted for estimating the stator flux of an EESM. Regarding the control for EESM, it is tested on a simulative model for high-power motors provided by NIDEC ASI and tested on a small-scale test bench at the University of Genoa

Current commutation and control of brushless direct current drives using back electromotive force samples

Brushless DC machines (BLDC) are widely used in home, automotive, aerospace and military applications. The reason of this interest in different industries in this type of machine is due to their significant advantages. Brushless DC machines have a high power density, simple construction and higher efficiency compared to conventional AC and DC machines and lower cost comparing to permanent magnet AC synchronous machines. The phase currents of a BLDC machine have to commutate properly which is realised by using power semiconductors. For a proper commutation the rotor position is often obtained by an auxiliary instrument, mostly an arrangement of three Hall-effect sensors with 120 spatial displacement. In modern and cost-effective BLDC drives the focus is on replacing the noise sensitive and less reliable mechanical sensors by numerical algorithms, often referred to as sensorless or self-sensing methods. The advantage of these methods is the use of current or voltage measurements which are usually available as these are required for the control of the drive or the protection of the semiconductor switches. Avoiding the mechanical position sensor yields remarkable savings in production, installation and maintenance costs. It also implies a higher power to volume ratio and improves the reliability of the drive system. Different self-sensing techniques have been developed for BLDC machines. Two algorithms are proposed in this thesis for self-sensing commutation of BLDC machines using the back-EMF samples of the BLDC machine. Simulations and experimental tests as well as mathematical analysis verify the improved performance of the proposed techniques compared to the conventional back-EMF based self-sensing commutation techniques. For a robust BLDC drive control algorithm with a wide variety of applications, load torque is as a disturbance within the control-loop. Coupling the load to the motor shaft may cause variations of the inertia and viscous friction coefficient besides the load variation. Even for a drive with known load torque characteristics there are always some unmodelled components that can affect the performance of the drive system. In self-sensing controlled drives, these disturbances are more critical due to the limitations of the self-sensing algorithms compared to drives equipped with position sensors. To compensate or reject torque disturbances, control algorithms need the information of those disturbances. Direct measurement of the load torque on the machine shaft would require another expensive and sensitive mechanical sensor to the drive system as well as introducing all of the sensor related problems to the drive. An estimation algorithm can be a good alternative. The estimated load torque information is introduced to the self-sensing BLDC drive control loop to increase the disturbance rejection properties of the speed controller. This technique is verified by running different experimental tests within different operation conditions. The electromagnetic torque in an electrical machine is determined by the stator current. When considering the dynamical behaviour, the response time of this torque on a stator voltage variation depends on the electric time constant, while the time response of the mechanical system depends on the mechanical time constant. In most cases, the time delays in the electric subsystem are negligible compared to the response time of the mechanical subsystem. For such a system a cascaded PI speed and current control loop is sufficient to have a high performance control. However, for a low inertia machine when the electrical and mechanical time constants are close to each other the cascaded control strategies fail to provide a high performance in the dynamic behavior. When two cascade controllers are used changes in the speed set-point should be applied slowly in order to avoid stability problems. To solve this, a model based predictive control algorithm is proposed in this thesis which is able to control the speed of a low inertia brushless DC machine with a high bandwidth and good disturbance rejection properties. The performance of the proposed algorithm is evaluated by simulation and verified by experimental results as well. Additionally, the improvement on the disturbance rejection properties of the proposed algorithm during the load torque variations is studied. In chapters 1 and 2 the basic operation principles of the BLDC machine drives will be introduced. A short introduction is also given about the state of the art in control of BLDC drives and self-sensing control techniques. In chapter 3, a model for BLDC machines is derived, which allows to test control algorithms and estimators using simulations. A further use of the model is in Model Based Predictive Control (MBPC) of BLDC machines where a discretised model of the BLDC machine is implemented on a computation platform such as Field Programmable Gate Arrays (FPGA) in order to predict the future states of the machine. Chapter 4 covers the theory behind the proposed self-sensing commutation methods where new methodologies to estimate the rotor speed and position from back-EMF measurements are explained. The results of the simulation and experimental tests verifies the performance of the proposed position and speed estimators. It will also be proved that using the proposed techniques improve the detection accuracy of the commutation instants. In chapter 5, the focus is on the estimation of load torque, in order to use it to improve the dynamic performance of the self-sensing BLDC machine drives. The load torque information is used within the control loop to improve the disturbance rejection properties of the speed control for the disturbances resulting from the applied load torque of the machine. Some of the machine parameters are used within speed and load torque estimators such as back-EMF constant Ke and rotor inertia J. The accuracy with which machine parameters are known is limited. Some of the machine parameters can change during operation. Therefore, the influence of parameter errors on the position, speed and load torque is examined in chapter 5. In Chapter 6 the fundamentals of Model based Predictive Control for a BLDC drive is explained, which are then applied to a BLDC drive to control the rotor speed. As the MPC algorithm is computationally demanding, some enhancements on the FPGA program is also introduced in order to reduce the required resources within the FPGA implementation. To keep the current bounded and a high speed response a specific cost function is designed to meet the requirements. later on, the proposed MPC method is combined with the proposed self-sensing algorithm and the advantages of the combined algorithms is also investigated. The effects of the MPC parameters on the speed and current control performance is also examined by simulations and experiments. Finally, in chapter 7 the main results of the research is summarized . In addition, the original contributions that is give by this work in the area of self-sensing control is highlighted. It is also shown how the presented work could be continued and expanded