Stray flux-based rotation angle measurement for bearing fault diagnosis in variable-speed BLDC motors

Angle of rotation is a key parameter in motor fault diagnosis under varying speed conditions, and is usually measured by an optical encoder. However, the use of encoders is intrusive and in many scenarios its signal is difficult to access due to technical or commercial reasons. In this study, a novel rotation angle measurement method based on stray flux analysis is proposed and applied to bearing fault diagnosis of brushless direct-current (BLDC) motors. The measurement accuracy of the proposed method is comparable to that from an encoder. The developed method is flexible, noninvasive, and nondestructive. It is easy to implement and eliminates the need for long cables and access of the motor control system. The proposed method can be extended to the diagnosis of motor electrical and drive faults. If implemented with an Internet of Things (IoT) or a hand-held device, it can further improve the reliability of sensorless motor drive systems in industrial automation so as to meet Industry 4.0 requirements

Position-sensing by ZCP Filter for 3-Phase Sinusoidal BLDC Motor Controller

Department of Electrical EngineeringIn this thesis, studied is a ZCP (Zero Crossing Point) filter scheme along with slow start-up initial driving method for sensor-less 3-phase sinusoidal BLDC (Brush-Less DC Motor) controller. ZCP filter is a key IP block to detect the rotor position of the BLDC motor and control the driving transistors of an inverter. A traditional 3-phase sinusoidal BLDC motor uses 3 hall sensors to detect the rotor position to control the motor speed. In this case, hall sensors are installed inside a BLDC motor. But it often causes reliability problem in automotive applications due to malfunction of the sensor. Therefore, sensor-less BLDC motor becomes more desirable and the position detection scheme replacing the hall sensor is key area of research. The proposed digital ZCP filter for the rotor position detection alone with a slow start-up initial driving is implemented by digital logic designed by using Verilog HDL. Also, SPWM (Sinusoidal Pulse Width Modulation) sensor-less BLDC motor controller is designed by Verilog HDL. All function is implemented and verified by using a FPGA.ope

Medição indireta de torque e velocidade angular de motor de corrente contínua sem escovas

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Mecânica, Florianópolis, 2016.Em algumas aplicações de motores, como compressores herméticos de refrigeração, torque e velocidade angular são grandezas que podem oscilar significativamente durante uma revolução do eixo. A determinação dessas variações é de grande importância para assegurar eficiência ao motor e, no caso dos compressores, garantir conforto acústico ao usuário final. Quando o motor é interior a um invólucro selado, a determinação dessas grandezas por meio de instrumentação convencional é inviável e a obtenção delas a partir de variáveis externas se torna uma opção atraente. Resultados disponíveis na literatura indicam que é possível determinar o torque e a velocidade angular indiretamente em diferentes tipos de motores associados a compressores herméticos, entre eles os motores de corrente contínua sem escovas, que são alimentados por conversores eletrônicos. Neste trabalho, apresentase proposta de solução para determinação de torque e velocidade angular do motor de corrente contínua sem escovas a partir dos valores de tensão e correntes obtidas junto a tais conversores. Na proposta, baseada na modelagem matemática do motor de corrente contínua sem escovas, a tensão induzida é variável subjacente à estimação das grandezas de interesse, fazendo-se necessário obtê-la para qualquer posição angular do rotor. A avaliação dos valores estimados por meio da solução proposta demanda o desenvolvimento de uma bancada com características peculiares. Tal bancada deve possibilitar, de forma inédita, gerar e medir oscilações de torque com frequência igual à frequência rotacional, bem como medir a velocidade angular e tensão induzida do motor de corrente contínua sem escovas. A avaliação da solução proposta é feita pela comparação dos valores estimados com valores de referência obtidos em medição direta das variáveis nessa bancada. Tais testes mostraram a viabilidade da solução para todas as variáveis estimadas, com curvas de tendência de tensão induzida e velocidade angular que se assemelham às de referência.Abstract : In some electrical motors applications such as hermetic refrigeration compressors, torque and angular rate are quantities that can fluctuate significantly during an axis revolution. The determination of these variations is of great importance to ensure efficiency to the motor and, in the case of compressors, to guarantee acoustic comfort to the end user. When the motor is inside a sealed enclosure, the determination of these quantities by means of conventional instrumentation is impracticable and obtaining them from external variables becomes an attractive option. Results available in the literature indicate that it is possible to determine the torque and angular rate indirectly in different types of motors associated with hermetic compressors, among them the brushless DC motors, which are fed by electronic converters. In this work, we propose a solution for determination of torque and angular rate of the BLDC from the voltage and current values obtained with such converters. In the proposal, based on the mathematical modeling of the BLDC, the back electromotive force is variable underlying the estimation of the quantities of interest, making necessary to obtain it for any angular position of the rotor. The evaluation of the estimated values through the proposed solution demands the development of a bench with peculiar characteristics. Such a bench should enable, in a novel way, to generate and measure torque oscillations with frequency equal to the rotational frequency, as well as to measure the angular rate and induced voltage of the BLDC. The evaluation of the proposed solution is made by comparing the estimated values with reference values obtained in direct measurement of the variables in this bench. These tests showed the viability of the solution for all the estimated variables, with curves of back electromotive force and angular rate that resemble those of the reference

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