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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.

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.

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.

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.

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.

This paper aims to deal with direct torque controller when the five-phase induction motor drive in faulty operation. Precisely, open-phase fault condition is contemplated. Also, the DTC is combined with a speed-adaptive variable-structure observer based on sliding mode observer.

Two novel features are presented. First, the concept of the virtual voltage vector is presented, which eliminates low-frequency harmonic currents and simplifies analysis. Second, speed information is introduced into the selection of the inverter states.

Direct torque control (DTC) is largely used in traditional three-phase drives as a backup to rotor-stator flux-oriented methods. The classic DTC strategy was primarily designed on the base of hysteresis controllers to control two independent variables (speed, torque and flux). Due to the additional degrees of freedom offered by multiphase machine, extensive works have been extended on the ensemble five-phase drives in healthy operation. In addition, the ability to continue the operation in faulty conditions is considering one of the main advantages of multiphase machines. One can find in the literature different approaches treating this subject. The applicability of DTC after the appearing of a fault has not been enclosed in the literature.

Theoretical development is presented in details followed by simulation results using Matlab/Simulink to analyze the performance of the drive, comparing with the behavior during healthy situation.

The purpose of this study is to analyze whether negotiators stick to one single negotiation style or whether their styles vary during the negotiation process. The paper seeks to identify different combinations of phase-specific negotiation styles and investigates the relationship between these combinations and negotiation performance and satisfaction.

The study is based on a large online negotiation simulation that allows a phase-specific analysis of negotiation styles via an elaborate coding scheme.

The findings reveal that negotiators generally do not limit themselves to a single negotiation style. Instead, they vary their style in the course of different negotiation phases. The authors distinguish between five distinct phase-specific negotiation style patterns that differ with regard to their impact on negotiation performance but not negotiation satisfaction.

The study demonstrates that a phase-specific analysis of negotiation styles allows deeper insights into a negotiator’s style behavior. For future studies, the authors recommend taking a phase-specific view when analyzing negotiation styles.

Negotiation practitioners get to know different phase-specific negotiation style patterns and get insights into which pattern is the most promising for negotiation performance. As a result, they can acquire this phase-specific negotiation style pattern to enhance their performance.

The paper contributes to existing negotiation style literature, because it is the first to analyze negotiation styles from a phase-specific point of view.

Existing conceptual, empirical and case studies evidence suggests that manufacturing industries find the joint implementation of Kaizen philosophy initiatives. However, the existing practices rarely demonstrated in a single framework and implementation procedure in a structure nature. This paper, therefore, aims to develop, validate and practically test a framework and implementation procedure for the implementation of integrated Kaizen in manufacturing industries to attain long-term improvement of operational, innovation, business (financial and marketing) processes, performance and competitiveness.

The study primarily described the problem, extensively reviewed the current state-of-the-art literature and then identified a gap. Based on it, generic and comprehensive integrated framework and implementation procedure is developed. Besides, the study used managers, consultants and academics from various fields to validate a framework and implementation procedure for addressing business concerns. In this case, the primary data was collected through self-administered questionnaire, and 244 valid questionnaires were received and were analyzed. Furthermore, the research verified the practicability of the framework by empirically exploring the current scenario of selected manufacturing companies.

The research discovered innovative framework and six-phase implementation procedure to fill the existing conceptual gap. Furthermore, the survey-based and exploratory empirical analysis of the research demonstrated that the practice of the proposed framework based on structured procedure is valued and companies attain the middling improvements of productivity, delivery time, quality, 5S practice, waste and accident rate by 61.03, 44, 52.53, 95.19, 80.12, and 70.55% respectively. Additionally, the companies saved a total of 14933446 ETH Birr and 5,658 M² free spaces. Even though, the practices and improvements vary from company to company, and even companies unable to practice some of the unique techniques of the identified CI initiatives considered in the proposed framework.

All data collected in the survey came from professionals working for Ethiopian manufacturing companies, universities and government. It is important to highlight that n = 244 is high sample size, which is adequate for a preliminary survey but reinforcing still needs further survey in terms of generalization of the results since there are hundreds of manufacturing companies, consultants and academicians implementing and consulting Kaizen. Therefore, a further study on a wider Ethiopian manufacturing companies, consultants and academic scale would be informative.

This work is very important for Kaizen professionals in the manufacturing industry, academic and government but in particular for senior management and leadership teams. Aside from the main findings on framework development, there is some strong evidence that practice of Kaizen resulted in achieving quantitative (monetary and non-monetary) and qualitative results. Thus, senior management teams should use this research out to practice and analyze the effect of Kaizen on their own organizations. Within the academic community, this study is one of the first focusing on development, validating and practically testing and should aid further study, research and understanding of Kaizen in manufacturing industries.

So far, it is rare to find preceding studies proposed, validated and practically test an integrated Kaizen framework with the context of manufacturing industries. Thus, authors understand that this is the very first research focused on the development of the framework for manufacturing industries continuously to be competitive and could help managers, institutions, practitioners and academicians in Kaizen practice.

The essential investments in new product development (NPD) made by industrial companies entail effective management of NPD activities. In this context, performance measurement is one of the means that can be employed in the pursuit of effectiveness.

According to most textbooks, the widely accepted Booz, Allen and Hamilton (BAH) conceptual framework is supposedly the best way to go through the new product development process. That is, the textbooks imply that companies will achieve the best results if they follow the BAH conceptual framework. The authors studied ten new products to identify how marketing research was utilized during their development and introduction. The actual “practice” of marketing research usage was then compared with the BAH framework. The comparison showed that marketing research usage in practice was noticeably different from the usage implied by the BAH conceptual framework, thus suggesting that the latter does not hold up perfectly. The authors offer some suggestions as to when the conceptual framework for marketing research usage should be modified, and what the nature of those modifications might be.

The paper examined the nature of information technology (IT) outsourcing decision making and developed a theoretical framework consisting of five phases of decision making. The phases augmented those of Simon and consisted of intelligence, analysis and planning, strategy selection, action, and evaluation and monitoring. Australia's largest organisations and government agencies were surveyed by questionnaire to establish the importance of tasks and subtasks to be performed when completing each of the five phases. Participants possessed high experiences with IT in general and IT outsourcing in particular. When the importance of phases vis‐à‐vis each other were established, the action phase and evaluation and monitoring phase were found to be more significant than the other phases. For the action phase, which was statistically the most significant phase, the tasks of selecting an IT‐outsourcing vendor and determining a suitable IT‐outsourcing contract were dominant and strongly correlated. Findings from the study should help organisations identify and therefore better manage critical decision‐making activities during IT outsourcing particularly those related to vendors and contracts.

Literature, spanning industrial organization and strategic management disciplines, uses variance decomposition to understand the relative importance of firm, industry and business group effects in shaping profitability variations. Some literature analyzes firm profitability under transition to liberalization. Previous research has taken a static before-and-after view on institutional change. This paper aims to focus on the dynamic process of liberalization in India, analyzing how different institutional regime changes alter firm behavior leading to changes in profitability patterns.

Based on a panel data set of several thousand Indian firms, spanning the 26-year period between 1980-1981 and 2005-2006, the authors determine the relative importance of firm, industry and business group effects in explaining manufacturing firms’ profitability variances across different institutional phases. The authors evaluate three propositions that help assess transition dynamics between phases. They determine the quantum of catch-up or falling behind by firms.

Different industries emerge as profitability leaders, as the economy progresses through different liberalization phases. Business groups that have been more effective in resource appropriation, rent-seeking, politician management and non-market activities in a controlled regime are replaced as profit leaders by those that, in a free-market economy, can be capable of intra-business resource allocation tasks and leveraging corporate capabilities.

The approach demonstrates how to analyze the underlying detailed structure of firm-level data, and performance outcomes, to derive nuanced interpretation of factors giving rise to the effects that explain profitability variances, and how to assess the way these effects behave over time. The dynamic evidence-based approach highlights what factors matter, where, when and why, in influencing profitability variances, which are a key dimension of industrial and economic performance.