Brushed DC Motor Research Articles

Design, implementation, and application of 150-degree commutation VSI to improve speed range of sensored BLDC motor.

Permanent magnet brushless dc (BLDC) motors are very convenient for many applications such as industrial, medical, robotic, aerospace, small electric vehicles, and home applications because of their inherent satisfying dynamic characteristics. There are numerous studies about these motors and their control schemes such as sensorless control and different speed and torque control schemes. All electric motors need commutation in order to produce speed and torque. Commutation in brushed DC motors is performed by means of a brush and collector. In BLDC motors, commutation is provided electronically in contrast to the brushed dc motors. In BLDC motors, motor phase windings are energized according to the information of the rotor position by inverter transistors. Rotor position information is used for commutation. Therefore, rotor position information is required to produce speed and torque for BLDC motors. The easiest and cheapest way to obtain rotor position information is to use Hall-effect or optical sensors. BLDC motor manufacturers generally produce BLDC motors equipped with three Hall-effect position sensors. Having three position sensors on BLDC motors provides six-step commutation which ensures two phase windings are energized in each moment. The third phase is empty. In this study, all phase windings are energized in the same time. This commutation method is twelve-step or 150 degrees commutation. So that more speed can be achieved from the same BLDC motor by comparison with six-step commutation. In this paper, both six-step and twelve-step commutation methods applied to the same BLDC motor and obtained experimental results from this study were presented, examined, and discussed.

Model Verification For A Brushed DC Motor Running In Closed Loop With Speed Feedback

In this study, a closed loop speed control of a permanent magnet brushed dc motor is developed. In the first part of the study, the model of the dc motor is obtained and used to simulate a closed loop speed control system using Matlab/Simulink. In the second part, ED laboratory dc motor set is used to implement the simulated system experimentally. The data obtained from experimental study is used to verify simulation results.

Torque measurement method based on the Lorentz force law for miniature DC motor

This paper describes a torque measurement method for a miniature DC motor. The measurement principle is the Lorentz force law, that is, the equivalence in power between the electromagnetic torque and the motional electromotive force. The test bench that embodies the measurement needs no torque meter. Only a set of the same motors under test are sufficient, except for a digital oscilloscope, a DC power supply, and several resistors. The intrinsic measurement error related to the measurement principle is formulated by an equivalent circuit analysis of the DC brush motor. In addition, the superficial measurement error due to unevenness in electrical or mechanical characteristics between the two motors is clarified from the analysis. These measurement errors are experimentally evaluated for miniature DC motors on the market and the measurement accuracy is discussed. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Lap time simulation and design optimisation of a brushed DC electric motorcycle for the Isle of Man TT Zero Challenge

ABSTRACTThis works regards the design of an electric motorcycle for the annual Isle of Man TT Zero Challenge. Optimal control theory was used to perform lap time simulation and design optimisation. A bespoked model was developed, featuring 3D road topology, vehicle dynamics and electric power train, composed of a lithium battery pack, brushed DC motors and motor controller. The model runs simulations over the entire or of the Snaefell Mountain Course. The work is validated using experimental data from the BX chassis of the Brunel Racing team, which ran during the 2009 to 2015 TT Zero races. Optimal control is used to improve drive train and power train configurations. Findings demonstrate computational efficiency, good lap time prediction and design optimisation potential, achieving a 2 minutes reduction of the reference lap time through changes in final drive gear ratio, battery pack size and motor configuration.

Online Fault Diagnosis of Motor Bearing via Stochastic-Resonance-Based Adaptive Filter in an Embedded System

Digital signal processing algorithms are widely adopted in motor bearing fault diagnosis. However, most algorithms are developed on desktop platforms, and their focus is on the analysis of offline captured signals. In this paper, a simple and easily implemented algorithm running on an embedded system is proposed for the online fault diagnosis of motor bearing. The core part of the algorithm is a stochastic-resonance-based adaptive filter that realizes signal denoising and adaptation of the filter coefficient. Processed by the filter, the period of the purified signal is obtained, and then the fault type of the motor bearing is identified. The proposed method has distinct merits, such as low computational cost, online implementation, contactless measurement, and availability for various speed motors. This paper provides a simple, flexible, and effective solution for conducting motor bearing diagnosis on an embedded/portable device. The algorithm proposed is validated by a brushless dc motor and a brushed dc motor fabricating with defective/healthy support bearings.

Observer-based fuzzy adaptive fault-tolerant nonlinear control for uncertain strict-feedback nonlinear systems with unknown control direction and its applications

This paper proposes a new nonlinear control scheme incorporating a state observer, a fuzzy neural network (FNN) and a new Nussbaum function for strict-feedback nonlinear systems by considering several challenges. These challenges are external disturbances, uncertain dynamics, unmeasured states, constrained input, unknown control direction, singularity issue, and actuator’s faults of different types. The scheme uses approximations of the unknown system’s dynamics provided by the FNN, the system’s states variables estimation provided by a model-free high-gain observer, and the control direction provided by the Nussbaum function. Compared to existing schemes, in addition to the fact that the new scheme can tackle simultaneously all the aforementioned challenges with better tracking performances, it also cancels the assumption about the positive definiteness of the control gain function found in many works. Thus, the scheme suites for more applications as it can be applied in cases where the control gain can be either semi-negative/negative-definite, semi-positive/positive-definite. Furthermore, the knowledge of the bounds for uncertain dynamics, actuation faults, FNN approximation errors and external disturbances is not required as it is for many other schemes. The effectiveness of the scheme is illustrated by its successful application to three examples, which are the pitch angle control for a Boeing 747-100/200 represented by the ultimate approximate nonlinear longitudinal model over up-and-away flight regime, the trajectory tracking control of a one-link manipulator actuated by a brush DC (BDC) motor, and the position tracking control for an inverted pendulum.

Adaptive homo‐backstepping tracking control for strict‐feedback systems in presence of unknown dead‐zones

SummaryAn adaptive homo‐backstepping control for nonlinear strict‐feedback systems subjected to unknown actuator dead‐zone and disturbance is investigated. A sliding‐mode‐based integral filter is constructed and used to approximate the desired feedback control in the backstepping‐like recursive design technique. Subsequently, the problem of “explosion of complexity” is solved by obviating the analytic derivatives deduction for virtual control in the conventional backstepping technology. The actuator dead‐zone dynamic is modeled as the combination of a line and a disturbance‐like term, which makes the controller design simpler. The interconnected control module and filter module in the resulting closed‐loop system satisfy the input‐to‐state practically stability‐modularity condition, provided that the small‐gain theorem is exploited to ensure the stability of closed‐loop system. The proposed approach cannot only mitigate the effect of dead‐zone but also solve the problem of explosion of complexity in the previous literature. Numerical simulations performed on a manipulator with a brushed DC motor are introduced to illustrate the effectiveness of underlying control scheme.

A MRAC Principle for a Single-Link Electrically Driven Robot with Parameter Uncertainties

In this paper, a model reference adaptive control (MRAC) principle for a one-degree-of-freedom rigid-link electrically driven robot is presented. The proposed control methodology addresses the problem of trajectory tracking with parameter uncertainties in the dynamic model of the system and proposes adaptation laws for the electrical and mechanical parameters. Closed-loop stability is rigorously discussed, proving that the tracking error trajectories converge to the origin exponentially. With the aim of performing experimental comparisons, two control schemes are also revisited theoretically and experimentally: one is an algorithm previously reported in the literature and the other is an adaptive controller derived under the assumption that the electrical dynamics of the actuator are negligible. All the discussed controllers have been implemented in an experimental setup consisting in a rigid-link robot actuated with brushed DC motor. The comparison indicates that better results are obtained with the new MRAC scheme.

A Novel Method for Sensorless Speed Detection of Brushed DC Motors

Many motor applications require accurate speed measurement. For brushed dc motors, speed can be measured with conventional observers or sensorless observers. Sensorless observers have the advantage of not requiring any external devices to be attached to the motor. Instead, voltage and/or current are measured and used to estimate the speed. The sensorless observers are usually divided into two groups: those based on the dynamic model, and those based on the ripple component. This paper proposes a method that measures the current of brushed dc motors and analyses the position of its spectral components. From these spectral components, the method estimates the motor speed. Three tests, performed each with the speeds ranging from 2000 to 3000 rpm either at constant-speed, at slowly changing speeds, or at rapidly changing speeds, showed that the average error was below 1 rpm and that the deviation error was below 1.5 rpm. The proposed method: (i) is a novel method that is not based on either the dynamic model or on the ripple component; (ii) requires only the measurement of the current for the speed estimation; (iii) can be used for brushed dc (direct current) motors with a large number of coils; and (iv) achieves a low error in the speed estimation.

Precision concurrent speed and position tracking of brushed dc motors using nonlinear time-frequency control

Brushed DC motors are essential components in a wide range of applications in which their unique benefits are explored. However, their being inherently nonlinear and sensitive to system based uncertainties such as load variation and process noise has made improving the precision control of brushed DC motors a challenging task. To mitigate such negative effects that invariably undermine motor stability and controllability, a novel wavelet-based nonlinear time-frequency control scheme viable for the concurrent speed and position tracking of brushed DC motors is presented. The control approach has its basis in discrete wavelet transformation and adaptive control. Considering system response in the wavelet domain allows the true dynamics of the system as delineated by both the time and frequency information of the response to be faithfully resolved without being distorted or misinterpreted. By employing adaptive theory, the undesirable features typical of nonlinear brushed DC motor systems such as being highly unstable and energy inefficient are also properly addressed. The validity of the controller design are demonstrated by evaluating its performance and the power requirement against PID control and fuzzy logic control in mitigating the speed, position, and armature voltage responses of a permanent magnet brushed DC motor under severe system uncertainties. The proposed nonlinear controller is shown to be accurate, robust, energy efficient, low in power requirement, and easy to switch between speed and position control.

Elbow Joint Rehabilitation Device

Stroke is a brain disease, which it causes spasticity and may occurs muscle weakness and also joint stiffness. Besides that, joint stiffness also will occur after joint trauma and with the Continuous passive motion (CPM) exercise, the joint stiffness can be reduces and also maintain the range of motion (ROM) of the joint. Elbow Joint Rehabilitation Device provides Continuous passive motion (CPM) exercises to the patients who have elbow injury or elbow that has undergone surgical procedure and Neurological problems such as stroke and traumatic brain injuries which effected on the elbow. The purpose of this project is to upgrade the existing Elbow Joint Rehabilitation Device to more comfortable to use, more lightly in weight to be handle and carry, and also can operate in DC rechargeable batteries. To develop this project, brushed DC motor is use to move the arm/elbow joint with controllable speed and the degree of movement by using PIC microcontroller (Programmable Interface Controllers). Furthermore, a rechargeable battery is added on the device which to able the device operates in DC power supply. To conduct this project, data collection, testing and data analysis for the stroke and elbow joint injury patients. As a result, we’ll find out the effectiveness of the device to the stroke and elbow injury patient.

モータ一体型リニア振動アクチュエータの実験的検証

We propose a linear oscillatory actuator that converts rotational motion into linear motion using brushed DC motors. In this study, we verify the operating principle and characteristics of this actuator through FEM analysis and dynamic simulation. Additionally, we verify the validity of the analysis results through experiments on a prototype.

ACCIONAMENTOS DE RELUCTANCIA AUTOCONMUTADOS CON CONTROL DE PAR PARA DIRECCIÓN ASISTIDA ELECTRICA

Nowadays, the power steering is a standard device in commercial vehicles. The electric power steering is becoming an alternative to the traditional hydraulic power steering. Right now, the electric drive commonly used in this application is the DC brush motor drive. Today, different electric drives are seen as a future option but the best candidate seems to be the permanent magnet synchronous motor drive. However due to its constructive simplicity, absence of permanent magnets and fault tolerance the switched reluctance motor drive is an alternative that should not be ignored. In this article a switched reluctance motor drive is presented for a rack-type electric power steering for midsize cars with a rack force 10 kN. The drive consists of a switched reluctance motor of four-phase with 8 stator poles and 6 rotor poles fed through an electronic power converter with Power MOSFETs switches, an incremental encoder and digital torque control to minimize torque ripple and to mitigate disturbances that appear when clearing a fault and the drive works with one or two open phases. The drive has been built and tested in the laboratory and experimental results have confirmed its suitability as a drive for power steering.

Intelligent Sensor Based Bayesian Neural Network for Combined Parameters and States Estimation of a Brushed DC Motor

The objective of this paper is to develop an Artificial Neural Network (ANN) model to estimate simultaneously, parameters and state of a brushed DC machine. The proposed ANN estimator is novel in the sense that his estimates simultaneously temperature, speed and rotor resistance based only on the measurement of the voltage and current inputs. Many types of ANN estimators have been designed by a lot of researchers during the last two decades. Each type is designed for a specific application. The thermal behavior of the motor is very slow, which leads to large amounts of data sets. The standard ANN use often Multi-Layer Perceptron (MLP) with Levenberg-Marquardt Backpropagation (LMBP), among the limits of LMBP in the case of large number of data, so the use of MLP based on LMBP is no longer valid in our case. As solution, we propose the use of Cascade-Forward Neural Network (CFNN) based Bayesian Regulation backpropagation (BRBP). To test our estimator robustness a random white-Gaussian noise has been added to the sets. The proposed estimator is in our viewpoint accurate and robust.

Sensorless speed measurement for brushed DC motors

This study describes two new methods of sensing the speed of a pulse-width modulation-driven brushed DC motor based on measuring the inductive spikes generated when the motor is turned off. The research has studied the relationship between the rise time or duration of the inductive spike, and the motor current and speed. Computationally inexpensive algorithms have been developed that use either rise time or duration to estimate speed. The algorithms have been implemented on an inexpensive microprocessor and show a speed error of approximately 10% over most of the motor's range of operation. The spike rise time implementation requires an analog-to-digital converter (ADC) as found in many microprocessors, while the spike duration implementation requires only a single digital input thus reducing the cost of the controlling microprocessor. This work has shown that sensorless speed measurement can be based on the inductive spike and has also raised future research questions, such as to the best way to optimise the speed measurement in dynamic situations, and measurement errors to be expected in a mass production environment.

Development and modification of permanent magnet brushed DC motor for hybrid photovoltaic-operated solar systems

A modified brushed permanent magnet DC (PMDC) motor has been developed and fabricated for a photovoltaic (PV)-operated solar systems. The conventional PMDC motor has been plagued with constraints, the most critical being ingestion of vapours of working fluid inside the rotor and stator, damaging the insulation of windings and forming a thin film of moisture between commutator and brushes. This flaw results into a very low mean time between failures of the motor. In the past, many attempts have been made where-in variety of seals to isolate the working fluid vapours from inner parts of motor have been tried out, but to no avail. Even Brushless DC motors have been designed in the past but their exorbitant cost makes the entire arrangement not viable economically. The modification attempted in this article overcomes the problem of working fluid ingestion inside the motor. It is found that mass flow rate of working fluid obtained at maximum peak sunshine hours is 17.5 l/min at 3030 rpm of motor driven by a PV module of 40 W at 16.20 V. This low-cost modified PMDC motor has been robust with high mean time between failures as no breakdown observed during 18 months of operation.

Braking device using counter electromotive force for the ergonomic assisted manipulation of large payloads

This paper presents a passive braking device designed to manually decelerate heavy payloads with very little effort. The device is based on the use of the counter electromotive force of a small brushed DC motor whose electrical connection is controlled using a simple handle. Three versions of the handle are proposed to activate the braking device. A dynamic model of the mechanical system is formulated and simulations are performed in order to assess the capabilities of the braking device. The simulation results are validated experimentally using a simple test bench. Finally, a full scale experimental set-up is built and results obtained with the set-up are given in order to demonstrate the effectiveness of the concept. HighlightsA passive braking device using motor back-emf for assisted payload deceleration.A dynamic model of the system and simulation results to support the concept.Experimental results on a full-scale prototype to demonstrate the effectiveness.

Implementation of PI Controller for 3ф BLDCM Drive Using FPGA

Despite the need of a complex motor controller, the simple construction of BLDC motors offers several inherent advantages not provided with brushed DC motors in terms of low inertia, high torque and a very wide speed range. The BLDC motors include, Longer service life due to a lack of electrical and friction losses and also free maintenance due to a lack of brushes and mechanical commutators. The EMI and noise are reduced because of the elimination of ionizing spikes from brushes. The control system of BLDCM is highly complex drive due to nonlinear nature. In such a system for implementing control algorithm needs high speed processor. In this work the controller Xilinx Spartan-6 FPGA is a demonstration platform intended to become familiar with the new features and availability of the Spartan-6 FPGA. The various experimental tests are carried out in 3Ф BLDCM .The experimental results are reported in order to verify the steady state, transient and robustness performance of the controller.

On the model order reduction of a direct current motor

Neglecting the armature inductance, La, is a common approach for model order reduction for a class of brush DC motors. Some authors, however, make a partial or incomplete interpretation for neglecting La, leading students to wrong results and misunderstandings. The existing conditions in the literature and in introductory control systems textbooks are either based on the time constant of the mechanical system being greatly larger than that of the electrical system, or La ≈ 0. These conditions are not supported analytically and no corresponding error analysis of any kind is provided. This paper analyzes and criticizes the eligibility of these conditions and provides an error model that corresponds to the model order reduction associated with neglecting La, and another that corresponds to neglecting the non-dominant pole. Experimental results are included to illustrate the suitability of the proposed error models and the suitability of employing such models in basic control designs.

МОДЕРНИЗАЦИЯ ПРИВОДОВ ПОДАЧ ТОКАРНЫХ СТАНКОВ С ЧПУ НА БАЗЕ МИКРОПРОЦЕССОРНОГО ЭЛЕКТРОПРИВОДА СЕРИИ CSD

This article proposes a method for modernizing feed drives of CNC lathes. The features of the application of the tracking actuator on the basis of DC brush motors for CNC lathes. The advantages of the electric servo valve to the dc drive. The features of the modernization drive supply turret CNC machine model 1B340F30 under the Department "Automated technological systems" Bryansk State Technical University. Proposed a functional block diagram of the control system drives innings this machine. Rational choice of scheme management system to avoid the effect of some factors on the accuracy of the actuator supply. The use of the electric servo valve possible to reduce the size of the drive and increase the ratio of power-to-weight.