Comparison between model based and non-model based sensorless methods of brushed DC motor

Vidlak, Michal; Makyš, Pavol; Staňo, Michal

doi:10.1016/j.trpro.2021.07.059

Cited by 12 publications

(6 citation statements)

References 10 publications

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“…The model-based control utilizes a dynamic model of a DC motor and incorporates various types of model-based observers, such as a sliding or pseudo-sliding mode observer or an observer that is combined with proportional-integral (PI) control [183]. These model-based methods use a mathematical model of the motor to estimate the motor speed to control.…”

Section: Advancementsmentioning

confidence: 99%

Soft Robot Design, Manufacturing, and Operation Challenges: A Review

Ambaye,

Boldsaikhan,

Krishnan

2024

JMMP

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Advancements in smart manufacturing have embraced the adoption of soft robots for improved productivity, flexibility, and automation as well as safety in smart factories. Hence, soft robotics is seeing a significant surge in popularity by garnering considerable attention from researchers and practitioners. Bionic soft robots, which are composed of compliant materials like silicones, offer compelling solutions to manipulating delicate objects, operating in unstructured environments, and facilitating safe human–robot interactions. However, despite their numerous advantages, there are some fundamental challenges to overcome, which particularly concern motion precision and stiffness compliance in performing physical tasks that involve external forces. In this regard, enhancing the operation performance of soft robots necessitates intricate, complex structural designs, compliant multifunctional materials, and proper manufacturing methods. The objective of this literature review is to chronicle a comprehensive overview of soft robot design, manufacturing, and operation challenges in conjunction with recent advancements and future research directions for addressing these technical challenges.

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Section: Advancementsmentioning

confidence: 99%

Soft Robot Design, Manufacturing, and Operation Challenges: A Review

Ambaye,

Boldsaikhan,

Krishnan

2024

JMMP

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“…To design the optimal filter, predicting the performance of the motor is essential, and motor models serve as appropriate tools for performance prediction. In studies related to BDC motor models, there have been efforts to model BDC motors operating with PWM controllers [20], compare two motor models for speed estimation [21], and validate methods for controlling the speed of very small BDC motors using modeling [22]. However, these models have limitations as they do not include the vibration components of the motor.…”

Section: Introductionmentioning

confidence: 99%

Design of Electronic Filter for Noise and Vibration Reduction in Brushed DC Motor

Kim,

Kim

2024

Machines

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With the recent conversion of internal combustion engines to electric vehicles, new noise issues have arisen, and among them, the noise generated by internal vehicle auxiliary systems is being considered. This study introduces an electronic filter designed with a motor model featuring vibration components, aiming to minimize the noise and vibrations generated by a Brushed DC (BDC) motor commonly employed in vehicle internal systems. It introduces a method to identify the connectors and internal parameters used in the motor for the matching of the model and experimental motor, and to measure and estimate these parameters. The model is separated and executed to ensure convergence, and it is validated by comparing the analysis results with the measured values. A filter is designed using the model to reduce current oscillations in the motor, confirming a subsequent reduction in noise and vibration. This research suggests the potential to attenuate noise and vibration in already produced motors by attaching only a filter without modifying the internal motor structure. Moreover, it is anticipated that a filter can be designed to predict and mitigate the noise and vibration components of the motor based on changes in load.

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“…So the aim of this research is to analyze how accurate the LM393 Microcontroller sensor is in measuring rotation and compare it with a conventional Tachometer measuring instrument. This study is based on Michal Vidlak's [1] research, which describes the comparative calculation of rotation measurement results using the engineering model of DC motor method based on the ripple component of DC motor current. The method compares rotation measurements caused by electric current using a rotation sensor and a potentiometer.…”

Section: Introductionmentioning

confidence: 99%

RPM Measurement Comparison Using a Thermometer and Lm393 Microcontroller

Nanda,

Karyadi,

Roban

et al. 2024

MECHTA

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RPM measurement is a crucial measurement tool for assessing a machine's rotation quality and ensuring that it meets the DC motor manufacturer's specifications. The quality of rotation of electric motors and combustion motors can both be observed through RPM measurements. The precision with which the LM393 sensor measures the rotation of a DC motor engine is the problem formulation in this study. Thus, the purpose of this study is to evaluate the rotation measurement accuracy of the LM393 Microcontroller sensor and compare it to a traditional tachometer. In order to conduct rotational variations on the DC motor, the following voltages will be applied: 0.93V, 2.83V, 4.25V, 7.05V, and 9.07V. Next, a tachometer and an LM393 microcontroller are used to measure the DC motor rotation. The gathered data will be made available for verification. Based on the measurement results, the corresponding data differences are -5.560 RPM, -1.577 RPM, -2.182 RPM, -3 RPM, and 0.334 RPM. Therefore, measurement validation was done based on the disparity in readings, yielding results of 0.252%, -1.45%, 0.12%, 0.038%, and 0.0725%. Based on validation results showing a presentation of no more than 10%, the LM393 measuring tool for DC motor RPM measurement is deemed valid and suitable for use.

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Comparison between model based and non-model based sensorless methods of brushed DC motor

Cited by 12 publications

References 10 publications

Soft Robot Design, Manufacturing, and Operation Challenges: A Review

Soft Robot Design, Manufacturing, and Operation Challenges: A Review

Design of Electronic Filter for Noise and Vibration Reduction in Brushed DC Motor

RPM Measurement Comparison Using a Thermometer and Lm393 Microcontroller

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