Simple Mathematical and Simulink Model of Stepper Motor

Iqteit, Nassim; Yahya, Khalid; Makahleh, Firas M.; Attar, Hani; Amer, Ayman; Solyman, Ahmed A. A.; Qudaimat, Ahmad; Tamizi, Khaled

doi:10.3390/en15176159

Cited by 8 publications

(7 citation statements)

References 20 publications

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“…State observers should form the backbone of rolling mill DTAs. Creating relatively simple object-oriented digital twins will contribute to the development of smart production and the transition of the metallurgical industry towards innovations [61][62][63][64]. Virtual models required to improve automated drives and mechatronic systems, including the described adequate two-mass model, facilitate this [65][66][67].…”

Section: Discussionmentioning

confidence: 99%

Method for Defining Parameters of Electromechanical System Model as Part of Digital Twin of Rolling Mill

Gasiyarov,

Radionov,

Loginov

et al. 2023

JMMP

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Creating digital twins of industrial equipment requires the development of adequate virtual models, and the calculation of their parameters is a complex scientific and practical problem. To configure and digitally commission automated drives, two-mass electromechanical system models are used. A promising area in which to implement such models is the development of digital shadows, namely drive position observers. Connecting virtual models for online data exchange predetermines the tightening of requirements for their parameter calculation accuracy. Therefore, developing accessible techniques for calculating electromechanical system coordinates is an urgent problem. These parameters are most accurately defined by experiments. The contribution of this paper is the proposition of a method for defining the two-mass system model parameters using the oscillograms obtained in the operating and emergency modes. The method is developed for the horizontal stand drives of a plate mill 5000 and is supported by numerical examples. The technique is universal and comprises calculating the rotating mass inertia torques, elastic stiffness and oscillation damping coefficients, and the time constants of the motor air gap torque control loop. The obtained results have been applied to the development of the elastic torque observer of the rolling stand’s electromechanical system. A satisfactory coordinate recovery accuracy has been approved for both open and closed angular gaps in mechanical joints. Recommendations are given for the use of the method in developing process parameter control algorithms based on automated drive position observers. This contributes to the development of the theory and practice of building digital control systems and the implementation of the Industry 4.0 concept in industrial companies.

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Section: Discussionmentioning

confidence: 99%

Method for Defining Parameters of Electromechanical System Model as Part of Digital Twin of Rolling Mill

Gasiyarov,

Radionov,

Loginov

et al. 2023

JMMP

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“…The BB converter's implementation and use are limited to specific applications because the output voltage is the opposite of the input voltage. As shown in Table 4 and Figure 7d, the power capacity and current/voltage ratings of the DSSB are much larger than those of the BB and SEPIC converters, and it can be used particularly with PV module arrays with higher power [21][22][23][24][25].…”

Section: Mean Value (Dc): Rms Value (Ac)mentioning

confidence: 99%

“…The AC small-signal technique is used to approximate the behavior of the converter, such as a linear time-invariant system around a certain switching cycle of the switches as the operating point of interest. This AC small-signal principle enables the DSSB duty cycle representations through open-loop and closed-loop transfer functions [25][26][27][28].…”

Section: Ac Small-signal Analysis Techniquementioning

confidence: 99%

A New Double-Switch SEPIC-Buck Topology for Renewable Energy Applications

Emar,

Issa,

Kanaker

et al. 2024

Energies

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In addition to their conventional use in electric motor drives, DC-DC converters have a variety of other uses, such as energy storage, energy conversion, cyber security systems, uninterruptible power supplies, and renewable energy systems. An innovative DC-DC converter is suggested in this article. Designing a new, high-gain DC-DC converter scheme known as a double-switch SEPIC-buck converter (DSSB) is possible after making some adjustments to the SEPIC converter that is currently known in accordance with accepted techniques. The output voltage magnitude of the proposed converter is either larger than or less than the input voltage magnitude and is the same sign as the input voltage. According to the theoretical and analytical study that has been supported by the real-world application, high voltage gain, low switching stress, and low inductor current ripple are the main characteristics of the proposed DSSB converter. The related small-signal model was also used to build the closed-loop system. The frequency response and output voltage behavior were investigated when the input source voltage abruptly changed as a step function. Based on the comparison study with other DC-DC converters, the DSSB converter outperforms currently known DC-DC converters such as Buck, SEPIC, Boost, Buck-Boost, and other SEPIC converter topologies in terms of voltage gain, harmonic content, normalized current ripple, dynamic performance, and efficiency. Additionally, the frequency response and control of the proposed converter using an alternate current (AC), small-signal, analysis-based, current-mode control technique are both provided. Thus, the DSSB is regarded as safe in overcurrent situations because of the small-signal analysis with the current control strategy. As a result of the verification of the proposed control technique, the resistance to changes in the DSSB parameters, improved dynamic performance, and higher control accuracy are further advantages of current-mode control based on small-signal analysis over other control approaches (PI controllers). Finally, the experimental and simulation results from Simplorer 7 and MATLAB/Simulink are used to validate the findings of the analytical and comparative investigation.

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“…where a and b are the two phases, v (V) and i (A) denote voltage and current, R (Ω) and L (H) represent resistance and inductance, and the ψ (Wb) values are the mutual flux linkages. The mutual flux linkages ψ a = ψ m cos(pΘ) and ψ b = ψ m sin(pΘ) in phase a and b, respectively are given by Iqteit et al [46], where p is the number of pole pairs and Θ is the rotor angular displacement or step angle, measured in degrees. Substituting the expressions for ψ a and ψ b into Equation ( 9) and performing the well-known D-Q transformation gives…”

Section: Inlet Ddrvmentioning

confidence: 99%

An Optimized Artificial Neural Network Model of a Limaçon-to-Circular Gas Expander with an Inlet Valve

Hossain,

Sultan,

Phung

et al. 2024

Thermo

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In this work, an artificial neural network (ANN)-based model is proposed to describe the input–output relationships in a Limaçon-To-Circular (L2C) gas expander with an inlet valve. The L2C gas expander is a type of energy converter that has great potential to be used in organic Rankine cycle (ORC)-based small-scale power plants. The proposed model predicts the different performance indices of a limaçon gas expander for different input pressures, rotor velocities, and valve cutoff angles. A network model is constructed and optimized for different model parameters to achieve the best prediction performance compared to the classic mathematical model of the system. An overall normalized mean square error of 0.0014, coefficient of determination (R2) of 0.98, and mean average error of 0.0114 are reported. This implies that the surrogate model can effectively mimic the actual model with high precision. The model performance is also compared to a linear interpolation (LI) method. It is found that the proposed ANN model predictions are about 96.53% accurate for a given error threshold, compared to about 91.46% accuracy of the LI method. Thus the proposed model can effectively predict different output parameters of a limaçon gas expander such as energy, filling factor, isentropic efficiency, and mass flow for different operating conditions. Of note, the model is only trained by a set of input and target values; thus, the performance of the model is not affected by the internal complex mathematical models of the overall valved-expander system. This neural network-based approach is highly suitable for optimization, as the alternative iterative analysis of the complex analytical model is time-consuming and requires higher computational resources. A similar modeling approach with some modifications could also be utilized to design controllers for these types of systems that are difficult to model mathematically.

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Simple Mathematical and Simulink Model of Stepper Motor

Cited by 8 publications

References 20 publications

Method for Defining Parameters of Electromechanical System Model as Part of Digital Twin of Rolling Mill

Method for Defining Parameters of Electromechanical System Model as Part of Digital Twin of Rolling Mill

A New Double-Switch SEPIC-Buck Topology for Renewable Energy Applications

An Optimized Artificial Neural Network Model of a Limaçon-to-Circular Gas Expander with an Inlet Valve

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