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Article
Publication date: 7 November 2016

Sajid Hussain and David Lowther

The losses incurred in ferromagnetic materials under PWM excitations must be predicted accurately to optimize the design of modern electrical machines. The purpose of this…

Abstract

Purpose

The losses incurred in ferromagnetic materials under PWM excitations must be predicted accurately to optimize the design of modern electrical machines. The purpose of this paper is to employ mathematical hysteresis models (i.e. classical Preisach model) to predict iron losses in electrical steels under PWM excitation without compromising the computational complexity of the model.

Design/methodology/approach

In this paper, a novel approach based on the dynamic inverse Preisach model is proposed to model the iron losses. The PWM magnetic flux density waveform is decomposed into its harmonic component using Fourier series and a weighted Everett function is computed based on these harmonic components. The Preisach model is applied for the given flux waveform and results are validated against the measurements.

Findings

The paper predicts the total iron loss by computing a weighted Everett function based on the harmonics present in PWM waveform. Moreover, it formulates the possibility of utilizing the classical Preisach model to predict iron losses under PWM excitation.

Research limitations/implications

The approach is still limited in terms of its application at high frequencies. This work may eventually lead toward the accurate prediction of iron loss under PWM excitation in electromagnetic machine design.

Practical implications

The paper provides a simple approach applying the Preisach model for the prediction of iron losses under PWM excitation. The proposed approach does not require additional experimental data beyond B-H loops measured under sinusoidal excitation.

Originality/value

A novel approach is presented to incorporate the frequency dependence into a static inverse Preisach model. The approach extends the ability of the static Preisach model to compute total iron loss under PWM excitation using a weighted Everett function.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 35 no. 6
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 21 October 2019

Oszkár Bíró, David Lowther and Piergiorgio Alotto

Abstract

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 38 no. 5
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 4 September 2017

Min Li, Mohammad Hossain Mohammadi, Tanvir Rahman and David Lowther

Manufacturing processes, such as laminations, may introduce uncertainties in the magnetic properties of materials used in electrical machines. This issue, together with…

Abstract

Purpose

Manufacturing processes, such as laminations, may introduce uncertainties in the magnetic properties of materials used in electrical machines. This issue, together with magnetization errors, can cause serious deterioration in the performance of the machines. Hence, stochastic material models are required for the study of the influences of the material uncertainties. The purpose of this paper is to present a methodology to study the impact of magnetization pattern uncertainties in permanent magnet electric machines.

Design/methodology/approach

The impacts of material uncertainties on the performances of an interior permanent magnet (IPM) machine were analyzed using two different robustness metrics (worst-case analysis and statistical study). In addition, two different robust design formulations were applied to robust multi-objective machine design problems.

Findings

The computational analyses show that material uncertainties may result in deviations of the machine performances and cause nominal solutions to become non-robust.

Originality/value

In this paper, the authors present stochastic models for the quantification of uncertainties in both ferromagnetic and permanent magnet materials. A robust multi-objective evolutionary algorithm is demonstrated and successfully applied to the robust design optimization of an IPM machine considering manufacturing errors and operational condition changes.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 36 no. 5
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 4 September 2017

Mohammad Hossain Mohammadi, Tanvir Rahman and David Lowther

This paper aims to propose a numerical methodology to reduce the number of computations required to optimally design the rotors of synchronous reluctance machines (SynRMs…

Abstract

Purpose

This paper aims to propose a numerical methodology to reduce the number of computations required to optimally design the rotors of synchronous reluctance machines (SynRMs) with multiple barriers.

Design/methodology/approach

Two objectives, average torque and torque ripple, have been simulated for thousands of SynRM models using 2D finite element analysis. Different rotor topologies (i.e. number of flux barriers) were statistically analyzed to find their respective design correlation for high average torque solutions. From this information, optimal geometrical constraints were then found to restrict the design space of multiple-barrier rotors.

Findings

Statistical analysis of two considered SynRM case studies demonstrated a design similarity between the different number of flux barriers. Upon setting the optimal geometrical constraints, it was observed that the design space of multiple-barrier rotors reduced by more than 56 per cent for both models.

Originality/value

Using the proposed methodology, optimal geometrical constraints of a multiple-barrier SynRM rotor can be found to restrict its corresponding design space. This approach can handle the curse of dimensionality when the number of geometric parameters increases. Also, it can potentially reduce the number of initial samples required prior to a multi-objective optimization.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 36 no. 5
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 7 January 2020

David Lowther, Vahid Ghorbanian, Mohammad Hossain Mohammadi and Issah Ibrahim

The design of electromagnetic systems for a variety of applications such as induction heating, electrical machines, actuators and transformers requires the solution of a…

Abstract

Purpose

The design of electromagnetic systems for a variety of applications such as induction heating, electrical machines, actuators and transformers requires the solution of a multi-physics problem often involving thermal, structural and mechanical coupling to the electromagnetic system. This results in a complex analysis system embedded within an optimization process. The appearance of high-performance computing systems over the past few years has made coupled simulations feasible for the design engineer. When coupled with surrogate modelling techniques, it is possible to significantly reduce the wall clock time for generating a complete design while including the impact of the multi-physics performance on the device.

Design/methodology/approach

An architecture is proposed for linking multiple singe physics analysis tools through the material models and a controller which schedules the execution of the various software tools. The combination of tools is implemented on a series of computational nodes operating in parallel and creating a “super node” cluster within a collection of interconnected processors.

Findings

The proposed architecture and job scheduling system can allow a parallel exploration of the design space for a device.

Originality/value

The originality of the work derives from the organization of the parallel computing system into a series of “super nodes” and the creation of a materials database suitable for multi-physics interactions.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 39 no. 1
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 5 March 2018

Min Li, Arber Caushaj, Rodrigo Silva and David Lowther

This paper aims to presents a novel application of neural network (NN) pattern recognition to ore rock sorting using inductive electromagnetic (EM) sensors.

Abstract

Purpose

This paper aims to presents a novel application of neural network (NN) pattern recognition to ore rock sorting using inductive electromagnetic (EM) sensors.

Design/methodology/approach

The impedance of a metallic rock can be measured with an inductive method based on Faraday’s law and eddy current theory. A virtual rock model is then created for the simulation of the EM measurements. An NN is trained to differentiate between waste and useful ore samples (containing high amount of minerals) based on the EM sensor signals produced by the rocks.

Findings

The NN solution showed high accuracy of rock classification and produced relatively robust results from signals with noise.

Originality/value

A pattern recognition NN was applied to classify low- and high-grade ore samples. It has the potential to determine the approximate amount of conductive materials inside ore rocks through multiple classes. This method can be used to improve the performance of EM-based ore sorting for mineral pre-concentration.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 37 no. 2
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 8 August 2019

Vahid Ghorbanian, Mohammad Hossain Mohammadi and David Lowther

This paper aims to propose a data-driven approach to determine the design guidelines for low-frequency electromagnetic devices.

Abstract

Purpose

This paper aims to propose a data-driven approach to determine the design guidelines for low-frequency electromagnetic devices.

Design/methodology/approach

Two different devices, a core-type single-phase transformer and a motor-drive system, are used to show the usefulness and generalizability of the proposed approach. Using a finite element solver, a large database of design possibilities is created by varying design parameters, i.e. the geometrical and control parameters of the systems. Design rules are then extracted by performing a statistical analysis and exploring optimal and sub-optimal designs considering various targets such as efficiency, torque ripple and power factor.

Findings

It is demonstrated that the correlation of the design parameters influences the way the data-driven approach must be made. Also, guidelines for defining new design constraints, which can lead to a more efficient optimization routine, are introduced for both case studies.

Originality/value

Using the proposed approach, new design guidelines, which are generally not obtainable by the classical design methods, are introduced. Also, the proposed approach can potentially deal with different parameter–objective correlations, as well as different number of connected systems. This approach is applicable regardless of the device type.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 38 no. 5
Type: Research Article
ISSN: 0332-1649

Keywords

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Article
Publication date: 15 November 2011

Min Li and David A. Lowther

Robust design is very important for manufacturers to ensure the quality of the finished product. Therefore, a robustness measure is needed for the topological design of…

Abstract

Purpose

Robust design is very important for manufacturers to ensure the quality of the finished product. Therefore, a robustness measure is needed for the topological design of electromagnetic problems which may be sensitive to parameter variations. The purpose of this paper is to propose a robust objective function for topological design problems.

Design/methodology/approach

In this paper, a robust objective function for topology optimization is defined on an uncertainty set using the worst case analysis. The robustness of a topological design is defined as the worst response due to the variations of the location of the topology change. The approach is based on the definition of a topological gradient.

Findings

The robust topology optimization (RTO) was applied to eddy current crack reconstruction problems. The numerical applications showed that this method can provide more reliable results for the reconstruction in the presence of significant noise in the measured signal.

Research limitations/implications

The RTO may be applied to some more complicated design problems; however large computational costs may result.

Originality/value

This paper has defined a robustness metric for topology design and a robust design model is proposed for topology optimization problems.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 30 no. 6
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 9 September 2013

Steven Bielby and David A. Lowther

The conventional starting point for the design of an electrical machine (or any low-frequency electromagnetic device) is known as “sizing”. In this process, a simple…

Abstract

Purpose

The conventional starting point for the design of an electrical machine (or any low-frequency electromagnetic device) is known as “sizing”. In this process, a simple magnetic circuit is used to estimate the main geometric parameters. This does not work for many devices, particularly where eddy currents and non-linearity dominate. The purpose of this paper is to investigate an approach using a neural network trained on a large database of existing designs as a general sizing system.

Design/methodology/approach

The approach is based on a combination of a radial basis function neural network and a database of stored performances of electrical machines. The network is trained based on a set of typical performance requirements for a machines design problem. The resulting design is analyzed using finite elements to determine if the design performance is acceptable.

Findings

The number of neurons in the network was varied to determine the approximation and generalization capabilities. The finite element analysis showed that the network produced initial design parameters which resulted in an appropriate performance.

Research limitations/implications

The research has looked at only one class of machine. Further work is needed on a range of machines to determine how effective the approach can be.

Practical implications

The approach can provide a good initial design and thus can reduce overall design time significantly.

Originality/value

The paper proposes a novel, fast and effective generalized approach to sizing low frequency electromagnetic devices.

Details

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, vol. 32 no. 5
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 1 September 2003

David A. Lowther

This paper discusses the possibility of automating the design of electromagnetic devices. Several paradigms currently exist to accelerate the design process, search the…

Abstract

This paper discusses the possibility of automating the design of electromagnetic devices. Several paradigms currently exist to accelerate the design process, search the design space and examine the effects of tolerances on various parameters. Amongst these are semantic networks, response surfaces, interval mathematics and sensitivity analysis. This paper explores all of these and also suggests what is needed in the future in order to create a true computer based design system.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 22 no. 3
Type: Research Article
ISSN: 0332-1649

Keywords

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