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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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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

Auxiliary power system is an indispensable part of the train; the auxiliary systems of both electric locomotives and EMUs mainly are powered by one of the two ways, which are either from auxiliary windings of traction transformers or from DC-link voltage of traction converters. Powered by DC-link voltage of traction converters, the auxiliary systems were maintained of uninterruptable power supply with energy from electric braking. Meanwhile, powered by traction transformers, the auxiliary systems were always out of power while passing the neutral section of power supply grid and control system is powered by battery at this time.

Uninterrupted power supply of auxiliary power system powered by auxiliary winding of traction transformer was studied. Failure reasons why previous solutions cannot be realized are analyzed. An uninterruptable power supply scheme for the auxiliary systems powered by auxiliary windings of traction transformers is proposed in this paper. The validity of the proposed scheme is verified by simulation and experimental results and on-site operation of an upgraded HXD3C type locomotive. This scheme is attractive for upgrading practical locomotives with the auxiliary systems powered by auxiliary windings of traction transformers.

This scheme regenerates braking power supplied to auxiliary windings of traction transformers while a locomotive runs in the neutral section of the power supply grid. Control objectives of uninterrupted power supply technology are proposed, which are no overvoltage, no overcurrent and uninterrupted power supply.

The control strategies of the scheme ensure both overvoltage free and inrush current free when a locomotive enters or leaves the neutral section. Furthermore, this scheme is cost low by employing updated control strategy of software and add both the two current sensors and two connection wires of hardware.

The present study provides a comprehensive review of the advancements in five active heating modes for cold-proof clothing as of 2021. It aims to evaluate the current state of research for each heating mode and identify their limitations. Further, the study provides insights into the optimization of intelligent temperature control algorithms and design considerations for intelligent cold-proof clothing.

This article presents a classification of active heating systems based on five different heating principles: electric heating system, solar heating system, phase-change material (PCM) heating system, chemical heating system and fluid/air heating system. The systems are analyzed and evaluated in terms of heating principle, research advancement, scientific challenges and application potential in the field of cold-proof clothing.

The rational utilization of active heating modes enhances the thermal efficiency of cold-proof clothing, resulting in enhanced cold-resistance and reduced volume and weight. Despite progress in the development of the five prevalent heating modes, particularly with regard to the improvement and advancement of heating materials, the current integration of heating systems with cold-proof clothing is limited to the torso and limbs, lacking consideration of the thermal physiological requirements of the human body. Additionally, the heating modes of each system tend to be uniform and lack differentiation to meet the varying cold protection needs of various body parts.

The effective application of multiple heating modes helps the human body to maintain a constant body temperature and thermal equilibrium in a cold environment. The research of heating mode is the basis for realizing the temperature control of cold-proof clothing and provides an effective guarantee for the future development of the intelligent algorithms for temperature control of non-uniform heating of body segments.

The integration of multiple heating modes ensures the maintenance of a constant body temperature and thermal balance for the wearer in cold environments. The research of heating modes forms the foundation for the temperature regulation of cold-proof clothing and lays the groundwork for the development of intelligent algorithms for non-uniform heating control of different body segments.

The present article systematically reviews five active heating modes suitable for use in cold-proof clothing and offers guidance for the selection of heating systems in future smart cold-proof clothing. Furthermore, the findings of this research provide a basis for future research on non-uniform heating modes that are aligned with the thermal physiological needs of the human body, thus contributing to the development of cold-proof clothing that is better suited to meet the thermal needs of the human body.

The purpose of this paper is to present an economic–statistical design (ESD) for the Bayesian X‾ control chart based on predictive distribution with two types of informative and noninformative prior distributions.

The design used in this study is based on determining the control chart of the predictive distribution and then its ESD. The new proposed cost model is presented by considering the conjugate and Jeffrey's prior distribution in calculating the expected total cycle time and expected cost per cycle, and finally, the optimal design parameters and related costs are compared with the fixed ratio sampling (FRS) mode.

Numerical results show decreases in costs in this Bayesian approach with both Jeffrey's and conjugate prior distribution compared to the FRS mode. This result shows that the Bayesian approach which is based on predictive density works better than the classical approach. Also, for the Bayesian approach, however, there is no significant difference between the results of using Jeffrey's and conjugate prior distributions. Using sensitivity analysis, the effect of cost parameters and shock model parameters and deviation from the mean on the optimal values of design parameters and related costs have been investigated and discussed.

This research adds to the body of knowledge related to quality control of process monitoring systems. This paper may be of particular interest to quality system practitioners for whom the effect of the prior distribution of parameters on the quality characteristic distribution is important.

economic statistical design (ESD) of Bayesian control charts based on predictive distribution is presented for the first time.

In this paper, a new front end converter (FEC) topology has been proposed for the switched reluctance (SR) motor drive. This study aims to present the performance analysis of FEC-based SR motor drive using various types of control schemes like conventional proportional integral (PI) controller, fuzzy logic controller (FLC) and fuzzy-tuned proportional integral controller (Fuzzy-PI).

The proposed FEC-based SR motor drive with various control strategies is derived for the torque ripple minimization and speed control.

The steady state and the dynamic response of the FEC-based SR motor drive are analyzed using three different controllers under change in speed and loading conditions. The Fuzzy-PI-based control scheme improves the dynamic response of the system when compared with the FLC and the conventional PI controller.

The hardware prototype has been implemented for the FEC-based SR motor drive by using the Xilinx SPARTAN 6 FPGA processor. The experimental verification has been conducted and the results have been measured under steady state and dynamic conditions.

The purpose of this paper aims to design a robust wind turbine emulator (WTE) based on a three-phase induction motor (3PIM).

The 3PIM is driven by a soft voltage source inverter (VSI) controlled by a specific space vector modulation. By adjusting the appropriate vector sequence selection, the desired VSI output voltage allows a real wind turbine speed emulation in the laboratory, taking into account the wind profile, static and dynamic behaviors and parametric variations for theoretical and then experimental analysis. A Mexican hat profile and a sinusoidal profile are therefore used as the wind speed system input to highlight the electrical, mechanical and electromagnetic system response.

The simulation results, based on relative error data, show that the proposed reactive power control method effectively estimates the flux and the rotor time constant, thus ensuring an accurate trajectory tracking of the wind speed for the wind emulation application.

The proposed architecture achieves its results through the use of mathematical theory and WTE topology combine with an online adaptive estimator and Lyapunov stability adaptation control methods. These approaches are particularly relevant for low-cost or low-power alternative current (AC) motor drives in the field of renewable energy emulation. It has the advantage of eliminating the need for expensive and unreliable position transducers, thereby increasing the emulator drive life. A comparative analysis was also carried out to highlight the online adaptive estimator fast response time and accuracy.

Worldwide, companies are interested in improving processes and reaching high levels of quality through the adoption of various systems. For example, they implement quality management methodologies, such as Lean, with the aim of reducing waste and cost. In the food sector, however, companies also adopt food safety management systems, such as BRC (British Retail Consortium), destined to comply with the standards of hygiene, food safety and quality systems. Interestingly, both Lean and BRC seek to boost quality. Thus, both should be able to work as a single system and cooperate to add value to a company without duplicating efforts. By solving the problems in the bag sealing process of an Ecuadorian company through the implementation of Lean tools incorporated in the steps of the DMAIC methodology (define-measure-analyze-improve-control), and then framing a cooperation matrix of Lean tools and BRC clauses, this paper seeks to demonstrate their feasible cooperation.

One of the most well-known methodologies for process improvement is the DMAIC methodology. Through the sequence of the DMAIC steps, the main problem of an Ecuadorian company that produces flexible packaging for food was identified. With the voice of the customer (VOC) from historical customer surveys of the company, the common issues were found. Similarly, historical data of non-conformities required by ISO-9001: 2015 provided insightful information for this phase. In order to measure the current quantitative state of the processes, a VSM (value stream map) was jointly employed with an operator balance chart. Data was collected during the whole operational month. Having this quantitative data, and with the ideas generated from the Kaizen events, improvement initiatives were analyzed and proposed. The proposed solutions involve production and maintenance teams. After some tests, it was verified that all these improvements had had a positive impact on the company. Finally, it was analyzed that Lean tools can collaborate and also be used as proof for BRC requirements. Thus, a correlation matrix between them was built, which demonstrates cooperation between both systems.

The results of this study indicate that Lean can cooperate in the pursuit of the BRC Standard for food packaging companies. This is shown through the case study of the Ecuadorian company, which implemented Lean tools and reduced its costs by shortening lost time and reducing set up time in the machines employed to cut and seal bags. Additionally, overall equipment effectiveness (OEE) from machines 1 and 2 rose their values considerably. Since BRC is a certifiable standard, it contains clauses that must be achieved in order to get the certification. By using Lean tools, it was possible to comply with some of the clauses of the BRC standard. A matrix was built so that it could be identified that Lean tools can work together with BRC, and thus, reduce costs and waste, while simultaneously complying with the safety and quality standards that the standard guarantees.

This research had two limitations. The first limitation is related to time. The data was collected in a month due to the project's deadline. For further research, it is recommended to increase this period of time to at least three months of production. The second limitation is related to the processes studied, which are associated with the time period. This study encompasses two major processes, which present major problems. For further investigations, longer periods of time can allow to include more processes from the company.

The implications of this project rely on the fact that the company achieved a better level of efficiency. The application of Lean tools reduces waste in the company. Basically, the waste was associated with lost time in machines 1 and 2 from the cutting and sealing processes, which was mainly produced by mechanical malfunction and inefficient maintenance. These problems had a direct relationship with the bad quality of the bags since the machines operate almost fully automatically. Additionally, mechanical problems caused by inefficient maintenance have a direct impact on quality aspects of the bag, like correct dimensions or a proper seal. Moreover, these problems generate a loss of time since the operator must stop the machine during production time in order to fix it. Machines 1 and 2 reduced their lost time drastically. Furthermore, by using Lean tools alongside the BRC methodology, the company can now reduce the resources that are destined for Lean projects and the BRC certification. Specifically, as a result, Lean tools and their documents can serve as proof of compliance with certain BRC clauses.

These improvements impact the company's profits, and therefore the workers. Since there is a significant reduction in the company's costs, and also an increment in the company's production, the company will probably require hiring new employees. In this way, more job opportunities will be generated.

The originality of this work relies on the nature of the research and the type of production facility. Previous studies have examined Lean tool applications in many settings. There are a few studies regarding the adoption of BRC standards. However, and definitely, the merge between Lean tools and a food safety management system is novel, since there are few to almost no articles that have been published using such a merge. The positive outcomes that were obtained not only prove that both methodologies are compatible, but they can also encourage further research on the applicability and functionality of merging two methodologies similar to the ones used during this research. Regarding the production facility, very few articles have been published about flexible packaging companies, and this article will help further research in this field.

This study aims to propose a tailored Lean Six Sigma framework providing an accessible Lean Six Sigma methodology for compound feed manufacturers with the aim of mitigating rising costs and increasingly complex demands from customers.

A Lean Six Sigma framework was designed combining Lean value stream mapping and Six Sigma structured problem-solving with a case study in an Irish compound feed manufacturer.

The study found that the Lean Six Sigma implementation framework provided a simplified approach, which fitted the resource availability within compound feed manufacturing.

The study is limited by the constraints of a sole case study in providing empirical evidence of the effectiveness of the framework. Nevertheless, a conceptual Lean Six Sigma model is proposed, which will assist compound feed manufacturers implementing a continuous improvement approach.

This paper proposes a simplified approach to the implementation of Lean Six Sigma in agricultural compound feed manufacturers and in small and medium-sized organisations. This is the first such study in Ireland and will add to the body of work on Lean in agriculture and aid other agri-businesses and compound feed manufacturers in understanding how Lean Six Sigma can benefit.

Managing project completion within the stipulated time is significant to all firms' sustainability. Especially for software start-up firms, it is of utmost importance. For any schedule variation, these firms must spend 25 to 40 percent of the development cost reworking quality defects. Significantly, the existing literature does not support defect rework opportunities under quality aspects among Indian IT start-ups. The present study aims to fill this niche by proposing a unique mathematical model of the defect rework aligned with the Six Sigma quality approach.

An optimization model was formulated, comprising the two objectives: rework “time” and rework “cost.” A case study was developed in relevance, and for the model solution, we used MATLAB and an elitist, Nondominated Sorting Genetic Algorithm (NSGA-II).

The output of the proposed approach reduced the “time” by 31 percent at a minimum “cost”. The derived “Pareto Optimal” front can be used to estimate the “cost” for a pre-determined rework “time” and vice versa, thus adding value to the existing literature.

This work has deployed a decision tree for defect prediction, but it is often criticized for overfitting. This is one of the limitations of this paper. Apart from this, comparing the predicted defect count with other prediction models hasn’t been attempted. NSGA-II has been applied to solve the optimization problem; however, the optimal results obtained have yet to be compared with other algorithms. Further study is envisaged.

The Pareto front provides an effective visual aid for managers to compare multiple strategies to decide the best possible rework “cost” and “time” for their projects. It is beneficial for cost-sensitive start-ups to estimate the rework “cost” and “time” to negotiate with their customers effectively.

This paper proposes a novel quality management framework under the Six Sigma approach, which integrates optimization of critical metrics. As part of this study, a unique mathematical model of the software defect rework process was developed (combined with the proposed framework) to obtain the optimal solution for the perennial problem of schedule slippage in the rework process of software development.