110 research outputs found

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

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    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

    State-of-art on permanent magnet brushless DC motor drives

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    Permanent magnet brushless DC (PMBLDC) motors are the latest choice of researchers due to their high efficiency, silent operation, compact size, high reliability and low maintenance requirements. These motors are preferred for numerous applications; however, most of them require sensorless control of these motors. The operation of PMBLDC motors requires rotor-position sensing for controlling the winding currents. The sensorless control would need estimation of rotor position from the voltage and current signals, which are easy to be sensed. This paper presents a state of art on PMBLDC motor drives with emphasis on sensorless control of these motors

    Load Disturbance Torque Estimation for Motor Drive Systems with Application to Electric Power Steering System

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    Motors are widely used in industries due to its ability to provide high mechanical power in speed and torque applications. Its flexibility to control and quick response are other reasons for its widespread use. Disturbance torque acting on the motor shaft is a major factor which affects the motor performance. Considering the load disturbance torque while designing the control for the motor makes the system more robust to load changes. Most disturbance observers are designed for steady state load conditions. The observer designed here considers a general case making no assumptions about the load torque dynamics. The observer design methods to be used under different disturbance conditions are also discussed and the performances compared. The designed observer is tested in a Hardware-in-Loop (HIL) setup for different load conditions. A motor load torque estimation based Fault Tolerant Control (FTC) is then designed for an Electric Power Steering (EPS) system

    Hybrid Sensorless Field Oriented and Direct Torque Control for Variable Speed Brushless DC Motors

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    The objective of this thesis is to design a hybrid sensorless closed-loop motor controller using a combination of Field-Oriented Control (FOC) and Direct Torque Control (DTC) for brushless DC motors used in multi-rotor aerial vehicles. The primary challenge is the wide range of desired working speeds, which can quickly vary from low speed to high speed. For this range, the control approach must be efficient, effective, and low-cost in order to provide fast response times during initial startup, steady-state, and transient operation. Additional design challenges include minimal response time to desired speed changes and small steady-state speed errors. Finally, the control approach must be robust to motor parameter uncertainties or variations and the operation of the final design must be robust to measurement noise

    High performance position control for permanent magnet synchronous drives

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    In the design and test of electric drive control systems, computer simulations provide a useful way to verify the correctness and efficiency of various schemes and control algorithms before the final system is actually constructed, therefore, development time and associated costs are reduced. Nevertheless, the transition from the simulation stage to the actual implementation has to be as straightforward as possible. This document presents the design and implementation of a position control system for permanent magnet synchronous drives, including a review and comparison of various related works about non-linear control systems applied to this type of machine. The overall electric drive control system is simulated and tested in Proteus VSM software which is able to simulate the interaction between the firmware running on a microcontroller and analogue circuits connected to it. The dsPIC33FJ32MC204 is used as the target processor to implement the control algorithms. The electric drive model is developed using elements existing in the Proteus VSM library. As in any high performance electric drive system, field oriented control is applied to achieve accurate torque control. The complete control system is distributed in three control loops, namely torque, speed and position. A standard PID control system, and a hybrid control system based on fuzzy logic are implemented and tested. The natural variation of motor parameters, such as winding resistance and magnetic flux are also simulated. Comparisons between the two control schemes are carried out for speed and position using different error measurements, such as, integral square error, integral absolute error and root mean squared error. Comparison results show a superior performance of the hybrid fuzzy-logic-based controller when coping with parameter variations, and by reducing torque ripple, but the results are reversed when periodical torque disturbances are present. Finally, the speed controllers are implemented and evaluated physically in a testbed based on a brushless DC motor, with the control algorithms implemented on a dsPIC30F2010. The comparisons carried out for the speed controllers are consistent for both simulation and physical implementation

    Harjattoman tasavirtamoottorin arviointi opto-mekaanisessa paikkasäätösovelluksessa

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    This thesis evaluates the applicability of a micro-sized brushless direct current (DC) mo- tor in an opto-mechanical positioning application. Brushless DC motors are electronically commutated motors that use permanent magnets to produce the airgap magnetic field. The motor is powered through an inverter or switching power supply which produces an AC electric current to drive each phase of the motor. Optimal current waveforms are determined by the motor controller based on the desired torque, speed or position requirements. The benefits of a brushless motor over conventional brushed DC motors are a high power to weight ratio, low noise and a long operating life. The purpose of this thesis is to find out the performance potential of such motors and determine methods to achieve it. Firstly, a motor model and an exact motor classification is presented. A literature review is made to discuss state of the art control methods and hardware configurations for dynamic position control. Based on the literature review, a control scheme with field-oriented control based torque control and cascaded PI controlled speed and position loops was selected for further evaluation. Experimental positioning tests were executed for two motors with different power transmission setups. Tests were performed with both, a hardware and software implemented, motor controllers. Results show promising performance. It was shown that the required acceleration is feasible with both, geared and direct drive, transmissions. Field-oriented control was shown as a well performing method to control torque but special caution was needed to implement a reliable position sensing solution in a small size as the control algorithm is intolerant for inaccurate and noisy position data. The conventional PI based position controller was effective in cases with no feedback related harmonics or motor related torque ripple but was not capable in handling ripple caused by a non-ideal system. Quality variances were seen between motors which were originated from mechanical defects and non-idealities in the stator structure. Further research is needed to achieve a better settling performance through filtering undesired feedback harmonics, better tuning and thus minimizing undesired vibrations.Tämän diplomityön tarkoituksena on arvioida pienikokoisen harjattoman tasavirtamoottorin soveltuvuutta opto-mekaaniseen paikkasäätösovellukseen. Harjattomat tasavirtamoottorit ovat elektronisesti ohjattuja moottoreita, joissa ilmavälin magneettivuo luodaan kestomagneeteilla. Moottorille syötetään virtaa taajuusmuuttajalta, joka muodostaa halutunlaisen vaihtovirran jokaiselle moottorin vaiheelle. Syötettävää virtaa ohjataan moottorinohjaimelta määritettyjen vääntö-, nopeus- ja paikkavaatimusten perusteella. Harjattoman DC-moottorin edut verrattuna perinteiseen harjalliseen DC-moottoriin ovat hyvä teho-painosuhde, hiljainen käyntiääni ja pitkä käyttöikä. Diplomityön tavoitteena on kartoittaa kyseisen moottorityypin suorituskyky paikkasäädössä ja tutkia keinoja saavuttaa haluttu taso. Alan tutkimuksessa ja kirjallisuudessa tunnettuja suorituskykyisiä säätömenetelmiä ja laite- sekä komponenttikokoonpanoja on koostettu kirjallisuuskatsauksessa. Tämän perusteella kokeellisiin testeihin valittiin säätöarkkitehtuuri vektorisäätöön perustuvalla virransäädöllä sekä PI-pohjaisilla nopeus- ja paikkasäätimillä. Kokeellisilla paikoitustesteillä arvioitiin kahden moottorin suorituskykyä erilaisilla voimansiirtovaihtoehdoilla. Testit suoritettiin sekä ohjelmistopohjaisella että sovelluskohtaiseen mikropiiriin toteutetulla laitepohjaisella säätimellä. Tulokset osoittavat että vaaditun kiihtyvyyden saavuttaminen on mahdollista sekä vaihteellisella että suoravetoisella voimansiirrolla. Vektorisäätö osoittautui suorituskykyiseksi virransäätömenetelmäksi, mutta moottorin asentomittauksen luotettava toteutus vaati erityishuomiota, sillä vektorisäätöalgoritmi on herkkä paikkadatan tarkkuudelle. PI-säätimillä toteutettu paikkasäätö osoittautui toimivaksi, mutta herkäksi moottorin epäideaalisuuksille sekä häiriöille takaisinkytkennässä. Moottoreiden välillä havaittiin laatueroja mekaanisissa toleransseissa ja staattorin rakenteessa. Lopullisen asettumisajan saavuttaminen vaatii lisätutkimusta. Erityishuomiota on kiinnitettävä harmonisten komponenttien suodattamiseen sekä systeemin säätöön, jotta ei-toivotut värinät saadaan minimoitua

    Fault diagnosis and fault tolerant control of multiphase voltage source converters for application in traction drives

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    There is an increasing demand for vehicles with less environmental impact and higher fuel efficiency. To meet these requirements, the transportation electrification has been introduced in both academia and industry during last years. Electric vehicle (EV) and hybrid Electric vehicle (HEV) are two practical examples in transportation systems. The typical power train in the EVs consists of three main parts including energy source, power electronics and an electrical motor. Regarding the machine, permanent magnet (PM) motors are the dominant choice for light duty hybrid vehicles in industry due to their higher efficiency and power density. In order to operate the power train, the electrical machine can be supplied and controlled by a voltage source inverter (VSI). The converter is subjected to various fault types. According to the statistics, 38% of faults in a motor drive are due to the power converter. On the other side, the electrical power train should meet a high level of reliability. Multiphase PM machines can meet the reliability requirements due to their fault-tolerant characteristics. The machine can still be operational with faults in multiple phases. Consequently, to realize a multiphase fault-tolerant motor drive, three main concepts should be developed including fault detection (FD), fault isolation and fault-tolerant control. This PhD thesis is therefore focused on FD and fault-tolerant control of a multiphase VSI. To achieve this research goal, the presented FD and control methods of the power converter are thoroughly investigated through literature review. Following that, the operational condition of the multiphase converter supplying the electrical machine is studied. Regarding FD methods in multiphase, three new algorithms are presented in this thesis. These proposed FD methods are also embedded in new fault-tolerant control algorithms. At the first step, a novel model based FD method is proposed to detect multiple open switch faults. This FD method is included in the developed adaptive proportional resonant control algorithm of the power converter. At the second step, two signal based FD methods are proposed. Fault-tolerant control of the power converter with the conventional PI controller is discussed. Furthermore, the theory of SMC is developed. At the last step, finite control set (FCS) model predictive control (MPC) of the five-phase brushless direct current (BLDC) motor is discussed for the first time in this thesis. A simple FD method is derived from the control signals. Inputs to all developed methods are the five-phase currents of the motor. The theory of each method is explained and compared with available methods. To validate the developed theory at each part, FD algorithm is embedded in the fault-tolerant control algorithm. Experimental results are conducted on a five-phase BLDC motor drive. The electrical motor used in the experimental results has an in-wheel outer rotor structure. This motor is suitable for electric vehicles. At the end of each part, the remarkable points and conclusions are presentedHay una creciente demanda de vehículos con menor impacto ambiental y una mayor eficiencia de combustible. Para cumplir estos requisitos, la electrificación del transporte se ha introducido en la academia y la industria en los últimos años. Vehículos eléctricos y vehículos eléctricos híbridos son dos ejemplos prácticos en los sistemas de transporte. El tren de potencia típico en los vehículos eléctricos se compone de tres partes principales, incluyendo la fuente de energía, la electrónica de potencia y un motor eléctrico. En cuanto a la máquina, de imán permanente motores son la opción dominante para vehículos híbridos ligeros en la industria debido a su mayor eficiencia y densidad de potencia. Con el fin de operar el tren de potencia, la máquina eléctrica se puede suministrar y controlado por un inversor de fuente de tensión. El convertidor se somete a diversos tipos de fallos. Según las estadísticas, 38 % de las fallas en un motor se deben al convertidor de potencia. Por otro lado, el tren de potencia eléctrica debe cumplir con un alto nivel de fiabilidad. Máquinas multifase PM pueden cumplir con los requisitos de fiabilidad debido a sus características de tolerancia a fallos. La máquina puede seguir siendo operativo con fallas en múltiples fases. En consecuencia, para realizar una unidad de motor de alta disponibilidad de múltiples fases, tres conceptos principales deben desarrollarse incluyendo la detección de fallos, el aislamiento de fallas y control tolerante a fallos. Por tanto, esta tesis doctoral se centra en la FD y control tolerante a fallos de un VSI multifase. Para lograr este objetivo la investigación, los productos alimenticios y bebidas y métodos de control que se presentan del convertidor de potencia se investigan a fondo a través de revisión de la literatura. Después de eso, se estudió la condición operativa del convertidor de múltiples el suministro de la máquina eléctrica. En cuanto a los métodos de FD en múltiples fases, tres nuevos algoritmos se presentan en esta tesis. Estos métodos FD propuestas también están integrados en los nuevos algoritmos de control con tolerancia a fallos. En el primer paso, se propone un método FD modelo novela basada detectar fallas múltiples del interruptor abierto. Este método FD está incluido en el algoritmo de control adaptativo desarrollado proporcional resonante del convertidor de potencia. En el segundo paso, se proponen dos métodos FD señal basada. Se discute el control tolerante a fallos del convertidor de potencia con el controlador PI convencional. Además, la teoría de la SMC se desarrolla. En el último paso, el control conjunto finito modelo de control predictivo del motor de cinco fases sin escobillas de corriente continua se discutió por primera vez en esta tesis. Un método FD sencilla se deriva de las señales de control. Las entradas a todos los métodos desarrollados son las corrientes de cinco de fase del motor. La teoría de cada método se explica y se compara con los métodos disponibles. Para validar la teoría desarrollada en cada parte, FD algoritmo está incorporado en el algoritmo de control tolerante a fallos. Los resultados experimentales se llevan a cabo en una unidad de motor BLDC de cinco fases. El motor eléctrico usado en los resultados experimentales tiene una estructura de rotor exterior en las cuatro ruedas. Este motor es adecuado para los vehículos eléctricos. Al final de cada parte, se presentan los puntos notables y conclusione

    Sensorless operation of permanent magnet brushless dc motor based on infinite impulse response digital filter.

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    Disertasi ini membentangkan operasi baru tanpa penderia bagi motor arus terus magnet kekal tanpa berus (BLDC) berasaskan pada penapisan digit gelombang daya gerak elektrik balik dengan menggunakan dsPIC30F6010 mikropengawal. Dari segi motor pacuan, teknik pemodulatan lebar denyut (PWM) biasanya digunakan untuk mengubah voltan yang dikenakan pada pangkalan motor supaya dapat mengendalikan kelajuan motornya. This dissertation presents a new sensorless operation for permanent magnet brushless DC motor based on digital filtering of back-EMF waveform using dsPIC30F6010 microcontroller. In motor drives, PWM technique is normally used to vary the voltage imposed on the motor terminals, and therefore controlling the speed of the motor

    Traction control in electric vehicles

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    Tese de Mestrado Integrado. Engenharia Electrotécnica e de Computadores. Área de Especialização de Automação. Faculdade de Engenharia. Universidade do Porto. 201
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