A Novel Method for Sensorless Speed Detection of Brushed DC Motors

Vázquez-Sánchez, Ernesto; Sottile, J.; Gómez-Gil, Jaime

doi:10.3390/app7010014

Cited by 18 publications

(7 citation statements)

References 26 publications

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“…It can be compared to a sensor having a low number of references about the rotor speed per one rotation. The value of the threshold speed for controlling the motor speed appropriately depends on the motor construction parameters from Equation (9). For example, motors with a larger number of commutator segments provide enough information about the rotor speed also at the low speeds.…”

Section: Resultsmentioning

confidence: 99%

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Sensorless Speed Control of Brushed DC Motor Based at New Current Ripple Component Signal Processing

et al. 2021

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Signal processing of the brushed DC motor current was developed in this paper to obtain information about a rotor speed from a measured motor current. The brushed DC motor current contains a signal with a frequency proportional to the rotor speed. This signal is the outcome of a commutation process occurring in the brushed DC motor, and it is called a ripple component. Since the number of ripples in the measured motor current per one rotation is constant, the rotor speed can be estimated. A discrete bandpass filter with a floating bandwidth was developed as the main part of signal processing. This new interpretation of the bandpass filter was used to extract a frequency of the ripple component from the measured motor current. This frequency was used to acquire information about the estimated rotor speed. The estimated speed was set as a feedback value to a cascade control structure to provide sensorless speed control. The advantages and limitations of this approach are presented in this paper. Based on simulations and experimental results, it was confirmed that the proposed sensorless speed control is robust, accurate, and works precisely in a wide range of speeds.

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Section: Resultsmentioning

confidence: 99%

“…Another approach [9] used the spectral components of the motor current. This method is also useful for the brushed DC motors with a large number of coils where the ripple component is almost negligible.…”

Section: Introductionmentioning

confidence: 99%

Sensorless Speed Control of Brushed DC Motor Based at New Current Ripple Component Signal Processing

et al. 2021

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“…The system's response is simulated and analyzed using MATLAB/SIMULINK, with the PID controller being tuned and evaluated on the Simulink platform. This study addresses the tuning and operational principles of the PID controller, and the results of the experiments are detailed and analyzed in prior studies [15][16][17][18]. The regulation of numerous systems is crucial for achieving the desired performance level and has been extensively explored in various control strategies, as discussed in references [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Tuning of PID Controller for Speed Control of DC-Motor by using Generalized Regression Neural Network and Invasive Weed Optimization

Hilal,

Haider TH. Salim ALRikabi,

Ibtisam A. Aljazaery

2023

ejuow

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The Generalized Recurrent Neural Network (GRNN) and Invasive Weed Optimization (IWO) algorithms are two powerful techniques that can be used to optimize motor drive speed. GRNN is a type of artificial neural network designed to process time-series data, while IWO is a metaheuristic optimization technique inspired by the behavior of invasive weed species. To optimize motor drive speed using GRNN and IWO algorithms, data on motor performance over time must be collected and used to train a GRNN model that can predict future motor performance based on past performance. By optimizing the parameters of the GRNN model, the optimal combination of parameters can be found to maximize motor efficiency and performance while minimizing energy consumption and wear and tear on the motor. The objective of this study is to regulate the speed of a Per Magnetic DC (PMDC) motor with high precision and rapid response using a GRNN/IWO controller. The IWO-GRNN controller exhibits superior damping response and reduced overshoot in comparison to conventional GRNN controllers. Additionally, the drive current limiting mechanism ensures that the motor operates within its rated continuous current limit during continuous operation. The IWO-tuned single-loop GRNN controller outperforms the single-loop GRNN controller when tuned. The GRNN-IWO controller provides excellent damping response and minimal overshoot, enabling faster control response of the DC motor, with an accuracy of 98.85% compared to MATLAB-tuned IWO.

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“…Most control systems used in automation and robotics require the measurement of the angular rotational velocity of a motor using a sensorless approach [ 1 ], using internal sensors [ 2 , 3 ], or using external rotary encoders [ 4 ]. The low-cost standard defined by the industry is an external rotary encoder based on a rotating magnet ring with two, four, six, or more alternating poles attached to the rotating shaft and one, two, or three fixed Hall-effect digital sensors.…”

Section: Introductionmentioning

confidence: 99%

Improving the Angular Velocity Measured with a Low-Cost Magnetic Rotary Encoder Attached to a Brushed DC Motor by Compensating Magnet and Hall-Effect Sensor Misalignments

Palacín

Martínez

2021

Sensors

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This paper proposes a method to improve the angular velocity measured by a low-cost magnetic rotary encoder attached to a brushed direct current (DC) motor. The low-cost magnetic rotary encoder used in brushed DC motors use to have a small magnetic ring attached to the rotational axis and one or more fixed Hall-effect sensors next to the magnet. Then, the Hall-effect sensors provide digital pulses with a duration and frequency proportional to the angular rotational velocity of the shaft of the encoder. The drawback of this mass produced rotary encoder is that any structural misalignment between the rotating magnetic field and the Hall-effect sensors produces asymmetric pulses that reduces the precision of the estimation of the angular velocity. The hypothesis of this paper is that the information provided by this low-cost magnetic rotary encoder can be processed and improved in order to obtain an accurate and precise estimation of the angular rotational velocity. The methodology proposed has been validated in four compact motorizations obtaining a reduction in the ripple of the estimation of the angular rotational velocity of: 4.93%, 59.43%, 76.49%, and 86.75%. This improvement has the advantage that it does not add time delays and does not increases the overall cost of the rotary encoder. These results showed the real dimension of this structural misalignment problem and the great improvement in precision that can be achieved.

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A Novel Method for Sensorless Speed Detection of Brushed DC Motors

Cited by 18 publications

References 26 publications

Sensorless Speed Control of Brushed DC Motor Based at New Current Ripple Component Signal Processing

Sensorless Speed Control of Brushed DC Motor Based at New Current Ripple Component Signal Processing

Tuning of PID Controller for Speed Control of DC-Motor by using Generalized Regression Neural Network and Invasive Weed Optimization

Improving the Angular Velocity Measured with a Low-Cost Magnetic Rotary Encoder Attached to a Brushed DC Motor by Compensating Magnet and Hall-Effect Sensor Misalignments

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