Speed control of universal motor

Imran, Omar A.; Abed, Wisam Najm Al-Din; Jbarah, Ali N.

doi:10.11591/ijpeds.v10.i1.pp41-47

Cited by 6 publications

(4 citation statements)

References 11 publications

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“…In many engineering applications, using DC (Direct Current) motors under speed control configuration is a common requirement [1,2] because DC motors can provide a high starting torque and are suitable for speed control. Many speed control strategies have been developed for these motors, for example, a modified PI (Proportional-Integral) speed controller was developed in [3], and a comparison between a fuzzy logic and a PID (Proportional-Integral-Derivative) controller for a universal DC motor was reported in [4].…”

Section: Introductionmentioning

confidence: 99%

Predictive Speed Control of a DC Universal Motor Applied to Monitor Electric Vehicle Batteries

et al. 2023

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This article deals with the design of a simple predictive control algorithm applied to a bidirectional DC-DC power converter for the angular speed control of a DC motor. We used the dynamics of a DC motor but mathematically reduced them to arrive at a simple model that is ideal for our purpose, not only to meet the control objective but also to generate reliable data for further analysis. This predictive control approach is based on the discrete time mathematical model of a DC motor. A huge capacitor to emulate an electric vehicle battery was then successfully connected to our experimental platform. Due to the robustness of the proposed control algorithm, the same predictive control scheme provided sufficient information to monitor the battery’s state. On this basis, and due to the system’s efficiency, it was possible to configure a fault detection scheme in our electric car battery emulator using only classical statistical tools. A PIC18F252 microcontroller was used in our experimental platform to implement our predictive control algorithm. It was then appropriately coupled to the power electronics required by the DC-DC converter to drive the DC motor. Our experimental results proved the excellent performance of the control method and also of the health monitoring system. On the other hand, the main difficulty in achieving our main goal was the realization of discrete control, which had to be as simple as possible while maintaining the control objective and while also being capable of generating reliable data for the health monitoring stage. Thus, the primary contribution of this work was the development of the predictive control of the speed of a universal motor, followed by the modification of the experimental design to simulate an electric car battery and the introduction of a novel statistical method for fault detection.

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Section: Introductionmentioning

confidence: 99%

Predictive Speed Control of a DC Universal Motor Applied to Monitor Electric Vehicle Batteries

et al. 2023

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“…Indeed, the characteristics of this latter are directly related to the autonomy of the vehicle. Despite this, several models ignore this critically important part of the traction system model [1][2][3]. Currently, many researchers are interested in predicting traction battery performance.…”

Section: Introductionmentioning

confidence: 99%

Electric vehicle battery SOC estimation under different speed references

Jebahi¹,

Fatma²,

Aloui³

2022

E3S Web Conf.

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The present work aims to improve the traction chain system of a leisure electric vehicle equipped with a Li-S battery. For that, an equivalent circuit model of the battery was developed and implanted in the traction chain model in order to investigate the autonomy of the electric vehicle under different drive-cycles. The obtained results show a good quality of the studied vehicle in terms of autonomy and energy consumption.

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“…So, it is necessary to search about the simplest, fastest, and efficiently covering the search-space algorithm. Literature review: recently, researchers focus on controller tuning based on various meta-heuristic optimization algorithms [13]- [16]. The literature review below shows the researcher's interest in the utilization of the new nature-inspired techniques for traditional controller tuning for BLDC motor speed control schemes.…”

Section: Introductionmentioning

confidence: 99%

Sensored speed control of brushless DC motor based salp swarm algorithm

Abed

Imran²,

Abdullah³

2022

IJECE

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<p>This article uses one of the newest and efficient meta-heuristic optimization algorithms inspired from nature called salp swarm algorithm (SSA). It imitates the exploring and foraging behavior of salps in oceans. SSA is proposed for parameters tuning of speed controller in brushless DC (BLDC) motor to achieve the best performance. The suggested work modeling and control scheme is done using MATLAB/Simulink and coding environments. In this work, a 6-step inverter is feeding a BLDC motor with a Hall sensor effect. The proposed technique is compared with other nature-inspired techniques such as cuckoo search optimizer (CSO), honey bee optimization (HBO), and flower pollination algorithm (FPA) under the same operating conditions. This comparison aims to show the superiority features of the proposed tuning technique versus other optimization strategies. The proposed tuning technique shows superior optimization features versus other bio-inspired tuning methods that are used in this work. It improves the controller performance of BLDC motor. It refining the speed response features which results in decreasing the rising time, steady-state error, peak overshoot, and settling time.</p>

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Speed control of universal motor

Cited by 6 publications

References 11 publications

Predictive Speed Control of a DC Universal Motor Applied to Monitor Electric Vehicle Batteries

Predictive Speed Control of a DC Universal Motor Applied to Monitor Electric Vehicle Batteries

Electric vehicle battery SOC estimation under different speed references

Sensored speed control of brushless DC motor based salp swarm algorithm

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