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1 – 10 of 73
Article
Publication date: 1 February 2024

Gerasimos G. Rigatos, Pierluigi Siano, Mohammed S. Al-Numay, Bilal Sari and Masoud Abbaszadeh

The purpose of this article is to treat the nonlinear optimal control problem in EV traction systems which are based on 5-phase induction motors. Five-phase permanent magnet…

Abstract

Purpose

The purpose of this article is to treat the nonlinear optimal control problem in EV traction systems which are based on 5-phase induction motors. Five-phase permanent magnet synchronous motors and five-phase asynchronous induction motors (IMs) are among the types of multiphase motors one can consider for the traction system of electric vehicles (EVs). By distributing the required power in a large number of phases, the power load of each individual phase is reduced. The cumulative rates of power in multiphase machines can be raised without stressing the connected converters. Multiphase motors are also fault tolerant because such machines remain functional even if failures affect certain phases.

Design/methodology/approach

A novel nonlinear optimal control approach has been developed for five-phase IMs. The dynamic model of the five-phase IM undergoes approximate linearization using Taylor series expansion and the computation of the associated Jacobian matrices. The linearization takes place at each sampling instance. For the linearized model of the motor, an H-infinity feedback controller is designed. This controller achieves the solution of the optimal control problem under model uncertainty and disturbances.

Findings

To select the feedback gains of the nonlinear optimal (H-infinity) controller, an algebraic Riccati equation has to be solved repetitively at each time-step of the control method. The global stability properties of the control loop are demonstrated through Lyapunov analysis. Under moderate conditions, the global asymptotic stability properties of the control scheme are proven. The proposed nonlinear optimal control method achieves fast and accurate tracking of reference setpoints under moderate variations of the control inputs.

Research limitations/implications

Comparing to other nonlinear control methods that one could have considered for five-phase IMs, the presented nonlinear optimal (H-infinity) control approach avoids complicated state-space model transformations, is of proven global stability and its use does not require the model of the motor to be brought into a specific state-space form. The nonlinear optimal control method has clear implementation stages and moderate computational effort.

Practical implications

In the transportation sector, there is progressive transition to EVs. The use of five-phase IMs in EVs exhibits specific advantages, by achieving a more balanced distribution of power in the multiple phases of the motor and by providing fault tolerance. The study’s nonlinear optimal control method for five-phase IMs enables high performance for such motors and their efficient use in the traction system of EVs.

Social implications

Nonlinear optimal control for five-phase IMs supports the deployment of their use in EVs. Therefore, it contributes to the net-zero objective that aims at eliminating the emission of harmful exhaust gases coming from human activities. Most known manufacturers of vehicles have shifted to the production of all-electric cars. The study’s findings can optimize the traction system of EVs thus also contributing to the growth of the EV industry.

Originality/value

The proposed nonlinear optimal control method is novel comparing to past attempts for solving the optimal control problem for nonlinear dynamical systems. It uses a novel approach for selecting the linearization points and a new Riccati equation for computing the feedback gains of the controller. The nonlinear optimal control method is applicable to a wider class of dynamical systems than approaches based on the solution of state-dependent Riccati equations.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 43 no. 1
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 21 March 2023

Manikandan R. and Raja Singh R.

The purpose of this paper is to prevent the destruction of other parts of a wind energy conversion system because of faults, the diagnosis of insulated-gate bipolar transistor…

Abstract

Purpose

The purpose of this paper is to prevent the destruction of other parts of a wind energy conversion system because of faults, the diagnosis of insulated-gate bipolar transistor (IGBT) faults has become an essential topic of study. Demand for sustainable energy sources has been prompted by rising environmental pollution and energy requirements. Renewable energy has been identified as a viable substitute for conventional fossil fuel energy generation. Because of its rapid installation time and adaptable expenditure for construction scale, wind energy has emerged as a great energy resource. Power converter failure is particularly significant for the reliable operation of wind power conversion systems because it not only has a high yearly fault rate but also a prolonged downtime. The power converters will continue to operate even after the failure, especially the open-circuit fault, endangering their other parts and impairing their functionality.

Design/methodology/approach

The most widely used signal processing methods for locating open-switch faults in power devices are the short-time Fourier transform and wavelet transform (WT) – based on time–frequency analysis. To increase their effectiveness, these methods necessitate the intensive use of computational resources. This study suggests a fault detection technique using empirical mode decomposition (EMD) that examines the phase currents from a power inverter. Furthermore, the intrinsic mode function’s relative energy entropy (REE) and simple logical operations are used to locate IGBT open switch failures.

Findings

The presented scheme successfully locates and detects 21 various classes of IGBT faults that could arise in a two-level three-phase voltage source inverter (VSI). To verify the efficacy of the proposed fault diagnosis (FD) scheme, the test is performed under various operating conditions of the power converter and induction motor load. The proposed method outperforms existing FD schemes in the literature in terms of fault coverage and robustness.

Originality/value

This study introduces an EMD–IMF–REE-based FD method for VSIs in wind turbine systems, which enhances the effectiveness and robustness of the FD method.

Open Access
Article
Publication date: 23 May 2023

Roland Ryndzionek, Michal Michna, Filip Kutt, Grzegorz Kostro and Krzysztof Blecharz

The purpose of this paper is to provide an analysis of the performance of a new five-phase doubly fed induction generator (DFIG).

Abstract

Purpose

The purpose of this paper is to provide an analysis of the performance of a new five-phase doubly fed induction generator (DFIG).

Design/methodology/approach

This paper presents the results of a research work related to five-phase DFIG framing, including the development of an analytical model, FEM analysis as well as the results of laboratory tests of the prototype. The proposed behavioral level analytical model is based on the winding function approach. The developed DFIG model was used at the design stage to simulate the generator’s no-load and load state. Then, the results of the FEM analysis were shown and compared with the results of laboratory tests of selected DFIG operating states.

Findings

The paper provides the results of analytical and FEM simulation and measurement tests of the new five-phase dual-feed induction generator. The use of the MATLAB Simscape modeling language allows for easy and quick implementation of the model. Design assumptions and analytical model-based analysis have been verified using FEM analysis and measurements performed on the prototype. The results of the presented research validate the design process as well as show the five-phase winding design advantage over the three-phase solution regarding the control winding power quality.

Research limitations/implications

The main disadvantage of the winding function approach-based model development is the simplification regarding omitting the tangential airgap flux density component. However, this fault only applies to large airgap machines and is insignificant in induction machines. The results of the DFIG analyses were limited to the basic operating states of the generator, i.e. the no-load state, the inductive and resistive load.

Practical implications

The novel DFIG with five phase rotor control winding can operate as a regular three-phase machine in an electric power generation system and allows for improved control winding power quality of the proposed electrical energy generation system. This increase in power quality is due to the rotor control windings inverter-based PWM supply voltage, which operates with a wider per-phase supply voltage range than a three-phase system. This phenomenon was quantified using control winding current harmonic analysis.

Originality/value

The paper provides the results of analytical and FEM simulation and measurement tests of the new five-phase dual-feed induction generator.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 42 no. 4
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 29 April 2022

Taposh Kumar Roy and Md Habibullah

Predictive current control (PCC) of three-to-five-phase direct matrix converters (DMCs) is computationally expensive. For this reason, this study aims to consider a reduced number…

60

Abstract

Purpose

Predictive current control (PCC) of three-to-five-phase direct matrix converters (DMCs) is computationally expensive. For this reason, this study aims to consider a reduced number of switching states of DMC in PCC algorithm to predict the control objectives, such as output current control and input reactive power control.

Design/methodology/approach

The switching sequences which yield the voltage vectors of variable amplitude at a constant frequency in space are considered for the prediction and optimization step of PCC algorithm. For the selected voltage vectors, the phase angles of the output vectors are independent on the phase angles of the input vectors. In a three-to-five-phase DMC, there are 243 valid switching states. Among the switching states, only 91 states are considered using the aforementioned concept of variable amplitude output at a constant frequency. This reduced number of switching states simplifies the computational complexity of MPC based current control of three-to-five-phase DMC.

Findings

The computational complexity of the proposed PCC based DMC is lower than the all 243 vectors based PCC. The current total harmonic distortion, transient current response and input reactive power control for the simplified 91 vector based PCC are similar to the all 243 vectors based PCC.

Originality/value

A reduced number of switching sequence is considered for the prediction and optimization step of PCC algorithm. Hence, PCC algorithm can be sampled at a high frequency in real-time applications. Then, the performance of the PCC will be improved.

Details

World Journal of Engineering, vol. 20 no. 5
Type: Research Article
ISSN: 1708-5284

Keywords

Abstract

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 42 no. 4
Type: Research Article
ISSN: 0332-1649

Article
Publication date: 11 April 2023

Shailendra Kumar and Sanghamitra Choudhury

The widespread usage of artificial intelligence (AI) is prompting a number of ethical issues, including those involving concerns for fairness, surveillance, transparency…

Abstract

Purpose

The widespread usage of artificial intelligence (AI) is prompting a number of ethical issues, including those involving concerns for fairness, surveillance, transparency, neutrality and human rights. The purpose of this manuscript is to explore possibility of developing cognitive morality in AI systems.

Design/methodology/approach

This is explorative research. The manuscript investigates the likelihood of cognitive moral development in AI systems as well as potential pathways for such development. Concurrently, it proposes a novel idea for the characterization and development of ethically conscious and artificially intelligent robotic machines.

Findings

This manuscript explores the possibility of categorizing AI machines according to the level of cognitive morality they embody, and while doing so, it makes use of Lawrence Kohlberg's study related to cognitive moral development in humans. The manuscript further suggests that by providing appropriate inputs to AI machines in accordance with the proposed concept, humans may assist in the development of an ideal AI creature that would be morally more responsible and act as moral agents, capable of meeting the demands of morality.

Research limitations/implications

This manuscript has some restrictions because it focuses exclusively on Kohlberg's perspective. This theory is not flawless. Carol Gilligan, one of Kohlberg's former doctoral students, said that Kohlberg's proposal was unfair and sexist because it didn't take into account the views and experiences of women. Even if one follows the law, they may still be engaging in immoral behaviour, as Kohlberg argues, because laws and social norms are not perfect. This study makes it easier for future research in the field to look at how the ideas of people like Joao Freire and Carl Rogers can be used in AI systems.

Originality/value

It is an original research that derives inspiration from the cognitive moral development theory of American Professor named Lawrence Kohlberg. The authors present a fresh way of thinking about how to classify AI systems, which should make it easier to give robots cognitive morality.

Details

Technological Sustainability, vol. 2 no. 3
Type: Research Article
ISSN: 2754-1312

Keywords

Article
Publication date: 19 December 2023

Santosh B. Rane, Gayatri J. Abhyankar, Milind Shrikant Kirkire and Rajeev Agrawal

This article aims at - exploring and prioritizing the barriers to adoption of digitization in supply chains (SCs), categorizing them into sustainability triple bottom line (STBL…

Abstract

Purpose

This article aims at - exploring and prioritizing the barriers to adoption of digitization in supply chains (SCs), categorizing them into sustainability triple bottom line (STBL) based upon their direct impact and suggesting digital technologies to address each barrier.

Design/methodology/approach

A five-phase methodology is used which consists of an exploration of 44 barriers to the adoption of digitization in SCs, analysis of 44 barriers for mean, standard deviation and Cronbach alpha based on questionnaire-based feedback of 25 experts, extraction of 10 most significant barriers through 05 experts, followed by categorization of the barriers into STBL referring to their direct impact on STBL, prioritization of ten barriers using Fuzzy Technique for Order Performance by Similarity to Ideal Solution and recommendation of digital technologies to address each barrier.

Findings

While all the barriers considered in this study significantly impede the adoption of digitization in SCs, lack of top management commitment (B1) is found to be most crucial while lack of culture toward use of information and communication technology required for digitization (B3) has minimum impact. Large investment in digital infrastructure (B6), difficulty in integration of cyber physical systems (CPSs) on varied platforms (B8) and lack of experts having knowledge of digital technologies (B2) are equally important barriers requiring more attention while adopting digitization in SCs.

Research limitations/implications

This study is mainly based on feedback from 25 seasoned experts; a wider cross section of experts will give more insight.

Practical implications

The outcomes are very significant for organizations looking to adopt digitization in their SCs. Simultaneous consideration to all the barriers becomes impractical hence prioritization of same will be useful for the SC managers to benchmark their preparedness and decide strategies for the adoption of digitization with due consideration toward the impact of barriers on STBL. The digital technologies recommended will further aid in planning the digital strategies to address each barrier.

Originality/value

A unique approach to explore, analyze, prioritize and categorize the barriers to adoption of digitization in SCs is used to provide a deeper understanding of factors deterring the same. It implies that a supportive top management along with systematic allocation of finances plays a crucial role. The importance of availability of digital experts for integrating CPSs on a single platform is also highlighted. The digital technologies recommended will further assist the organizations toward adoption of digitization in SCs with due consideration to STBL.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 2 June 2023

Emad Hashiem Abualsauod

This research aims to enhance the operational excellence and continuous improvement of the retail supply chain in the Saudi Thobe Factory through an integrated approach of Six…

207

Abstract

Purpose

This research aims to enhance the operational excellence and continuous improvement of the retail supply chain in the Saudi Thobe Factory through an integrated approach of Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) with artificial intelligence (AI).

Design/methodology/approach

The study identified the tailoring department as the department with maximum defects by using voice of customer and critical to quality tools. An AI-integrated Six Sigma approach was applied to identify and eliminate nonproductive stages, and a new facility layout was designed to enhance productivity and customer satisfaction.

Findings

The use of the factor rating method and simulation using Arena software led to an improved sigma level from 1.597 to 2.237, representing an increment of about 40%. Additionally, the defects per million opportunities reduced from 461,538 to 230,769. The study can help production industry management to optimize facility layouts and improve overall production line efficiency.

Practical implications

This study addresses the lack of published research on the use of an integrated approach of Six Sigma DMAIC with AI in the retail and distribution sector of Saudi Arabia, particularly for small and medium-sized enterprises (SMEs). The study demonstrates how this approach may significantly boost SMEs’ performance and provides a basis for future research in this area.

Originality/value

This study provides a practical example of how an integrated approach of Six Sigma DMAIC with AI can be used in the retail and distribution sector of Saudi Arabia to enhance operational excellence and continuous improvement. The study highlights the potential benefits of this approach for SMEs in the region and provides a framework for future research.

Details

International Journal of Retail & Distribution Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-0552

Keywords

Article
Publication date: 28 March 2024

Elisa Gonzalez Santacruz, David Romero, Julieta Noguez and Thorsten Wuest

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework…

Abstract

Purpose

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

Design/methodology/approach

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

Findings

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

Originality/value

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

Details

The TQM Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-2731

Keywords

Article
Publication date: 23 August 2023

Kumar Srinivasan, Parikshit Sarulkar and Vineet Kumar Yadav

This article aims to focus on implementing Lean Six Sigma (LSS) in steel manufacturing to enhance productivity and quality in the galvanizing process line. In recent trends…

Abstract

Purpose

This article aims to focus on implementing Lean Six Sigma (LSS) in steel manufacturing to enhance productivity and quality in the galvanizing process line. In recent trends, manufacturing organizations have expressed strong interest in the LSS since they attempt to enhance its overall operations without imposing significant financial burdens.

Design/methodology/approach

This article used lean tools and Six Sigma's DMAIC (Define, Measure, Analyze, Improve and Control) with Yin's case study approach. This study tried to implement the LSS for the steel galvanizing process in order to reduce the number of defects using various LSS tools, including 5S, Value stream map (VSM), Pareto chart, cause and effect diagram, Design of experiments (DoE).

Findings

Results revealed a significant reduction in nonvalue-added time in the process, which led to improved productivity and Process cycle efficiency (PCE) attributed to applying lean-Kaizen techniques. By deploying the LSS, the overall PCE improved from 22% to 62%, and lead time was reduced from 1,347 min to 501 min. DoE results showed that the optimum process parameter levels decreased defects per unit steel sheet.

Practical implications

This research demonstrated how successful LSS implementation eliminates waste, improves process performance and accomplishes operational distinction in steel manufacturing.

Originality/value

Since low-cost/high-effect improvement initiatives have not been adequately presented, further research studies on adopting LSS in manufacturing sectors are needed. The cost-effective method of process improvement can be considered as an innovation.

Details

International Journal of Quality & Reliability Management, vol. 41 no. 3
Type: Research Article
ISSN: 0265-671X

Keywords

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