A general magnetic-energy-based torque estimator: validation via a permanent-magnet motor drive

This paper describes the use of the current–flux-linkage ($i{-}psi$ ) diagram to validate the performance of a general magnetic-energy-based torque estimator. An early step in the torque estimation is the use of controller duty cycles to reconstruct the average phase-voltage waveform during each pulsewidth-modulation (PWM) switching period. Samples over the fundamental period are recorded for the estimation of the average torque. The fundamental period may not be an exact multiple of the sample time. For low speed, the reconstructed voltage requires additional compensation for inverter-device losses. Experimental validation of this reconstructed waveform with the actual PWM phase-voltage waveform is impossible due to the fact that one is PWM in nature and the other is the average value during the PWM period. A solution to this is to determine the phase flux-linkage using each waveform and then plot the resultant $i{-}psi$ loops. The torque estimation is based on instantaneous measurements and can therefore be applied to any electrical machine. This paper includes test results for a three-phase interior permanent-magnet brushless ac motor operating with both sinusoidal and nonsinusoidal current waveforms

SENSORLESS SPEED CONTROL OF THE DIRECT CURRENT MOTORS

In this paper, a new speed control algorithm for a permanent magnet DC motor which does not require implementation of the angular speed sensor is presented. Three steps are performed to develop the control system: design of speed tracking control algorithm assuming the speed measurement; design of speed observer; design of sensorless speed control algorithm based on the principle of separation. Information about speed is taken from the speed observer using the motor current value. The stability of the composite system dynamics consisting of three subsystems (the speed regulation loop, current regulation loop, and speed observer) is analyzed. The feedback gains tuning procedure for decoupling of three subsystems is given. The simulation results show that the dynamic performance of the designed system is similar to the performance of the system with angular speed measurement. The resulting closed-loop system has structural robustness properties with respect to parametric and coordinate disturbances. References 12, figures 2

Fast determination of moment of inertia of permanent magnet synchronous machine drives for design of speed loop regulator

This paper proposes a novel method for the fast determination of moment of inertia of permanent magnet synchronous machine drive systems. It is based on the use of sinusoidal perturbation signals and can determine the combined moment of inertia within one sinusoidal cycle of perturbation while the influence of viscous friction is eliminated during the modeling process. It does not need the aid of complex system identification algorithms, and thanks to the elimination of influence of viscous friction, the proposed scheme shows higher accuracy than the conventional method without taking into account. Furthermore, its accuracy is also competitive with the conventional method using complex system identification algorithms, for example, the model reference adaptive system. Besides, the performance of designed speed regulators using the estimated mechanical parameters and the influence of mismatching of mechanical parameters are also investigated

Robust Load Disturbance Torque Estimation for a Permanent Magnet DC Motor Drive System

Direct current motors are an integral part of many systems. An important factor in the design of these systems is the disturbance torque on the motor\u27s shaft. This disturbance torque can negatively affect the performance of the motor and the overall system. Knowledge of the disturbance can aid in compensating for these negative effects, which enhances the robustness of the system to changes in the load. Estimation has become a feasible means of acquiring the value of such a disturbance. Various methods for the design of a robust disturbance torque estimator are presented here. The designs are robust in the sense that the estimation is insensitive to the presence of model uncertainties and/or noise. The estimators are designed to estimate both constant and non-constant, low-frequency disturbance torques. The designs are tested using a permanent magnet DC motor. An in-line torque sensor is used for validation

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

Control para máquinas de CA de imanes permanentes con FEM arbitraria, sin sensores mecánicos

En este trabajo de tesis se proponen nuevas soluciones a dos problemáticas de control de máquinas de corriente alterna con imanes permanentes: la minimización del ripple de par y la eliminación de sensores mecánicos de posición y/o velocidad. Para minimizar el ripple de par, producido por formas de onda de fem inducida no sinusoidales ni trapezoidales, se propone una nueva técnica para realizar la regulación de las corrientes de la máquina, basado en las ideas de control vectorial, lo que permite realizar el control de corriente en variables continuas del mismo modo que para máquinas sinusoidales. Con el fin de eliminar los sensores de posición y/o velocidad en el control de máquinas con forma de onda de fem arbitraria, se proponen dos nuevas estrategias, basadas en observadores de estado, que permiten estimar la fem inducida de la máquina, y a partir de ella obtener la velocidad y/o la posición del rotor. Una de las propuestas incluye una aproximación por series de Fourier de las formas de onda de la fem, que permite modelar máquinas con cualquier forma de onda de fem inducida. La segunda propuesta emplea un observador de orden reducido combinado con un observador de alta ganancia. Además, para compensar las perturbaciones producidas por el par de carga desconocido, se propuso extender el vector de estados para estimar dicho par de carga. El principal aporte de este trabajo radica en el uso de observadores que no se limitan únicamente a máquinas con fem sinusoidal o trapezoidal. Se presentan resultados de simulación y experimentales que validan las estrategias propuestas.New solutions for two permanent magnet AC machines control issues are proposed in this thesis. These issues are: ripple torque minimization and elimination of mechanical speed and/or position sensors. In order to minimize the ripple torque that is produced by neither sinusoidal nor trapezoidal induced emf, a new current control technique is proposed. The proposal is based on vector control ideas, and it allows to perform the current control in DC variables, in the same way as in sinusoidal PM machines. Two new reduced-order state-observer based strategies are proposed with the aim of eliminating position and/or speed sensor, for the control of arbitrary emf waveform machines. The proposals allow the estimation of machine induced emf. Rotor speed and/or position can be obtained from the estimated emf. One of the proposals includes a Fourier series approximation of the induced emf waveform that allows the modeling of machines with any emf waveform. The second one employs a reduced order observer combined with a high gain observer. In addition, a state vector extension is proposed for load torque estimation, in order to compensate the perturbations produced by the unknown load. The most important contribution of this work is the use of observers that are not limited only to sinusoidal or trapezoidal emf machines. Simulation and experimental results that validate the proposed strategies are presented.Facultad de Ingenierí

Disturbance torque estimation in a sensorless dc drive

The estimation of the disturbance torque in a sensorless DC motor drive is carried out by extending the classical observer theory. Three estimation schemes are formulated according to the representation of the disturbance torque and the processing of the observer states. In addition to the disturbance torque, all the schemes deliver an estimation of the motor speed. Steady-state accuracy and dynamics of the schemes are first determined in nominal conditions, identifying the scheme with the best performance. The effects of variations in the motor parameters are then analyzed, with the finding that a proper modeling of the motor makes the steady-state estimation of the disturbance torque insensitive to any variation. As a test, the schemes are applied to a sensorless DC motor drive for both compensating for the disturbance torque and closing the speed loop. The responses obtained with the best-performance scheme are reporte

Contribución en el ámbito de la tecnología sensorless para la detección de la velocidad y posición en motores dc monitorizando únicamente la corriente: mejora de la precisión, minimización del coste computacional y aplicabilidad a motores de alta potencia

Actualmente en muchas aplicaciones es necesario conocer la velocidad y posición de un motor. Esto puede ser conseguido mediante observadores convencionales como son encoders, tacómetros o resolvers, o mediante observadores sensorless. Los observadores sensorless son técnicas que miden la tensión y/o la corriente y estiman la velocidad y posición. En motores DC, los observadores sensorless se dividen en tres grupos, los basados en el modelo dinámico, los basados en la componente ripple y los basados en la combinación del modelo dinámico y la componente ripple. Este trabajo presenta tres nuevos métodos donde cada uno de ellos presenta una mejora frente a los observadores sensorless existentes que monitorizan únicamente la corriente para la estimación de la velocidad y/o posición. El primer método funciona en motores dc de baja potencia, se basa en la componente ripple e intenta minimizar el efecto del ruido. El segundo método funciona en motores DC de baja potencia, se basa en la componen ripple e intenta minimizar el coste computacional. El tercer método funciona en motores DC de alta potencia, en este caso una nueva teoría sobre las componentes espectrales de la corriente ha sido desarrollada, y en esta teoría se basa para realizar la estimación. Finalmente los tres métodos han sido testeados y medida su precisión dando como resultado que tienen una precisión aceptable.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería Telemátic