Design, implementation and speed estimation of three-phase 2 kW out-runner permanent magnet BLDC motor for ultralight electric vehicles

Kerem, Alper

doi:10.1007/s00202-021-01279-5

Cited by 6 publications

(5 citation statements)

References 27 publications

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“…The ANNs+(PSO-RMO) approach was designed to be able to obtain these two unique features from a single algorithm by taking advantage of the distinguishing singular characteristics of PSO and RMO, increasing system stability, more reliability and rapid forecasting studies Kerem, 2021).…”

Section: The Anns+(pso-rmo) Approachmentioning

confidence: 99%

A green energy research: forecasting of wind power for a cleaner environment using robust hybrid metaheuristic model

Kerem

Saygin

Rahmani

2021

Environ Sci Pollut Res

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Wind is a stochastic and intermittent renewable energy source. Due to it's nature, it is extremely hard to forecasting of wind power.Accurate wind power forecasting can be encouraging and motivating for investors to shed light on future uncertainties caused by global warming. Thus, CO 2 and other greenhouse gases which are harmful to the environment will not be released into the atmosphere, while generating electrical energy. This paper presents a novel precise, fast and powerful hybrid metaheuristic wind power forecasting approach based on statistical and mathematical data from real weather stations. The model was developed as a hybrid metaheuristic algorithm based on Arti cial Neural Networks (ANNs), Particle Swarm Optimization (PSO) and Radial Movement Optimization (RMO). Real-time wind data was gathered from Wind Measuring Stations (WMS) at two separate places in Burdur and Osmaniye cities, Turkey. The key contribution of this new model is the ability to perform wind power forecasting studies, without needing wind speed data, with high accuracy and rapid solutions. Also, it has been carried out wind power forecasting studies with high accuracy despite the height differences between the sensors. That is, for WMS-1 and WMS-2, it has succeeded the wind power forecasting at 61m and 60.3m using temperature (3m), humidity (3m), and pressure (3.5m) data. The performance results were presented in tables and graphs.

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Section: The Anns+(pso-rmo) Approachmentioning

confidence: 99%

A green energy research: forecasting of wind power for a cleaner environment using robust hybrid metaheuristic model

Kerem

Saygin

Rahmani

2021

Environ Sci Pollut Res

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“…The suggested Field Programmable Gate Arrays (FPGAs) are controlled directly on the inverter input power with the aid of the Dynamic Power Containment Technology (DPCT) control system [2], which is based on Dynamic Power Containment Technology (DPCT). When this occurs, the magnetic flux density, flux distribution, and torque of finite element models will only be utilized to evaluate motor performance and to analyse and approve the design of the system [3,4].…”

Section: Review Of the Literaturementioning

confidence: 99%

“…Weight and size are critical considerations, particularly in electric cars and aeroplanes and applications. As a result, brushless direct current (BLDC) motors have emerged as a viable alternative, a more efficient alternative to traditional direct current motors [4].…”

Section: Introductionmentioning

confidence: 99%

“…The improved Tunicate Swarm optimization algorithm (ITSA) was employed in this work to optimise the design, which was carried out utilizing speed and torque controllers. As a result, the best gain parameters are calculated with the aid of the intended scope function, which is necessary to increase the controller function [4,5]. These brushless DC motors have recently gained popularity among designers, who point to their benefits in terms of simplicity, high output (torque), long-term usage, and high-speed stability [6] as just a few of their many advantages.…”

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confidence: 99%

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Energy Auditing in Three-Phase Brushless DC Motor Drive Output for Electrical Vehicle Communication Using Machine Learning Technique

Ramana

Manaktala

Valarmathi³

et al. 2022

Wireless Communications and Mobile Computing

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Using predictive nonlinear optimal control, this model examines the output power of a three-phase brushless DC motor (BLDC) drive to ensure that it is stabilized (PNOC). A BLDC is a kind of electric motor that is used in a variety of applications and is one of the models of electric motors that are utilized in constant speed applications. In this motor, the movable component of the rotor created torque and the rotor rotated in a position of low reluctance; the location of the rotor is determined by the motor’s maximum inductance value. The BLDC drive controls the motor via the converter circuit, and the converter circuit ensures that the motor receives the appropriate output power. The project manager should have a thorough discussion with the team about the demagnetization of the malfunctioning BLDC motor before beginning this job. It is possible to model a machine using many existing technologies, such as electrical equivalent circuit diagram (EEC), which are based on a number of assumptions that make the analysis process or the analysis approach simpler. Despite numerical methodologies, these approach scenarios give frequency domain loop (FDL) precision frequency domain, using a suitable weight strategy to deliver high power solution creation (NM). The purpose of this essay is to integrate these two technologies in order to make contributions via the development of a new hybrid EEC-FDL model closed-loop brushless DC motor. PNOC is a driving system that uses predictive nonlinear optimal control (PNOC). The generated model is subjected to simulations under both healthy and incorrect settings, respectively. MATLAB software is utilized to construct the simulation of the control circuit, and simulation outputs are validated by experimental findings. Predictive nonlinear optimal control (PNOC) is employed to eliminate torque ripple and improve system stability.

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“…Therefore, the design methods of these machines are very close to each other. Analytical methods for the design of brushless machines are presented in references [13,14]. Numerical optimization methods with the aim of achieving the highest efficiency and limiting the torque ripple are among the topics that are considered in the field of optimal design of brushless motors.…”

Section: Introductionmentioning

confidence: 99%

Design and Manufacturing of an Outer-Rotor BLDC Motor with Integrated Sensorless Drive for Automotive Cooling Fan Applications

Deylami,

Akbari,

Emami

et al. 2024

Preprint

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Design, implementation and speed estimation of three-phase 2 kW out-runner permanent magnet BLDC motor for ultralight electric vehicles

Cited by 6 publications

References 27 publications

A green energy research: forecasting of wind power for a cleaner environment using robust hybrid metaheuristic model

A green energy research: forecasting of wind power for a cleaner environment using robust hybrid metaheuristic model

Energy Auditing in Three-Phase Brushless DC Motor Drive Output for Electrical Vehicle Communication Using Machine Learning Technique

Design and Manufacturing of an Outer-Rotor BLDC Motor with Integrated Sensorless Drive for Automotive Cooling Fan Applications

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