FPGA-based implementation of the back-EMF symmetric-threshold-tracking sensorless commutation method for brushless DC-machines

The operation of brushless DC permanent-magnet machines requires information of the rotor position to steer the semiconductor switches of the power-supply module which is commonly referred to as Brushless Commutation. Different sensorless techniques have been proposed to estimate the rotor position using current and voltage measurements of the machine. Detection of the back-electromotive force (EMF) zero-crossing moments is one of the methods most used to achieve sensorless control by predicting the commutation moments. Most of the techniques based on this phenomenon have the inherit disadvantage of an indirect detection of commutation moments. This is the result of the commutation moment occurring 30 electrical degrees after the zero-crossing of the induced back-emf in the unexcited phase. Often, the time difference between the zero crossing of the back-emf and the optimal current commutation is assumed constant. This assumption can be valid for steady-state operation, however a varying time difference should be taken into account during transient operation of the BLDC machine. This uncertainty degrades the performance of the drive during transients. To overcome this problem which improves the performance while keeping the simplicity of the back-emf zero-crossing detection method an enhancement is proposed. The proposed sensorless method operates parameterless in a way it uses none of the brushless dc-machine parameters. In this paper different aspects of experimental implementation of the new method as well as various aspects of the FPGA programming are discussed. Proposed control method is implemented within a Xilinx Spartan 3E XC3S500E board

Investigation of slim type BLDC motor drive with torque ripple minimization using abridged space-vector PWM control method

Abstract: Brushless DC (BLDC) motors are becoming an increasingly popular motor of choice for its unique characteristics. The BLDC motor drive is assumed to have trapezoidal back-electromotive force (EMF), rectangular phase currents and together produces the desired torque. However, practical back-EMF waveform might not be exactly trapezoidal because of current ripple, design considerations and manufacturing limitations. The adverse effect is the torque ripple generated due to the current ripple that causes mechanical vibration, acoustic noise and affects the accuracy of speed and position control which is not desirable in motor operation. In this paper an algorithm is developed to control and minimize the generated torque ripple using Space Vector Pulse Width Modulation (SVPWM) scheme. The efficiency improvement of slim type BLDC motor is confirmed using MATLAB environment and low cost TI Piccolo F28035 microcontroller (MC)

Design Of A Microcontroller-Based Converter For 3-Phase Brushless DC Motor Drives

Dalam aplikasi industri dan peralatan perubatan, dapat dilihat kepentingan pengawalan peralatan atau mesin dengan memantau proses keluaran dan kawalan masukan daripada komputer. In industrial application and medical devices, it can be seen that there is a need of controlling the devices or machines with observation of the output process and input control from a computer

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

A microsystem design for controlling a DC motor by pulse width modulation using MicroBlaze soft-core

This paper proposes a microsystem based on the field programmable gate arrays (FPGA) electronic board. The preliminary objective is to manipulate a programming language to achieve a control part capable of controlling the speed of electric actuators, such as direct current (DC) motors. The method proposed in this work is to control the speed of the DC motor by a purely embedded architecture within the FPGA in order to reduce the space occupied by the circuit to a minimum and to ensure the reliability of the system. The implementation of this system allows the embedded MicroBlaze processor to be installed side by side with its memory blocks provided by Xilinx very high-speed integrated circuit (VHSIC) hardware description language (VHDL), Embedded C. The control signal of digital pulse-width modulation pulses is generated by an embedded block managed by the same processor. This potential application is demonstrated by experimental simulation on the Vertix5 FPGA chip

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

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

Analysis of wavelet controller for robustness in electronic differential of electric vehicles: an investigation and numerical developments

In road transportation systems, differential plays an important role in preventing the vehicle from slipping on curved tracks. In practice, mechanical differentials are used, but they are bulky because of their increased weight. Moreover, they are not suitable for electric vehicles, especially those employing separate drives for both rear wheels. The electronic differential constitutes recent technological advances in electric vehicle design, enabling better stability and control of a vehicle on curved roads. This article articulates the modeling and simulation of an electronic differential employing a novel wavelet transform controller for two brushless DC motors ensuring drive in two right and left back driving wheels. Further, the proposed work uses a discrete wavelet transform controller to decompose the error between actual and command speed provided by the electronic differential based on throttle and steering angle as the input into frequency components. By scaling these frequency components by their respective gains, the obtained control signal is actually given as input to the motor. To verify the proposal, a set of designed strategies were carried out: a vehicle on a straight road, turning right and turning left. Numerical simulation test results of the controllers are presented and compared for robust performance and stability

Simulink modeling and design of an efficient hardware-constrained FPGA-based PMSM speed controller

The aim of this paper is to present a holistic approach to modeling and FPGA implementation of a permanent magnet synchronous motor (PMSM) speed controller. The whole system is modeled in the Matlab Simulink environment. The controller is then translated to discrete time and remodeled using System Generator blocks, directly synthesizable into FPGA hardware. The algorithm is further refined and factorized to take into account hardware constraints, so as to fit into a low cost FPGA, without significantly increasing the execution time. The resulting controller is then integrated together with sensor interfaces and analysis tools and implemented into an FPGA device. Experimental results validate the controller and verify the design

FPGA Based Control Method for Three Phase BLDC Motor

This paper introduces a good method which is helpful to assist in the design and control of cost effective, efficient Brushless Direct Current (BLDC) motors. Speed Control of BLDC motor using PIC microcontrollers requires more hardware, and with the availability of FPGA versatile features motivated to develop a cost effective and reliable control with variable speed range. In this paper, an algorithm which uses the Resolver signals captured from the motor is developed with the help of Resolver to Digital converters. The program has been written using VHDL. This program generates the firing pulses required to drive the MOSFETs of three phase fully controlled bridge converter driven by drivers. Then the program has been loaded on the Spartan- 3 FPGA device and tested on the 30V, 2000 rpm BLDC motor which can make the motor run at constant speed ranging from 10 to 2000 rpm. The proposed hardware and the program are found to be very good and efficient. The results are good compare to PIC Microcontroller based design