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The purpose of this paper is to make a quantitative comparison between induction machine (IM) and interior permanent magnet machine (IPM) for electric vehicle applications, in terms of electromagnetic performance and material cost.

The analysis of IM is based on an analytical method, which has been validated by test. The analysis of IPM is based on finite element analysis. The popular Toyota Prius 2010 IPM is adopted directly, and the IM is designed with the same stator outer diameter and stack length as Prius 2010 IPM for a fair comparison.

The torque capability of IM is lower than IPM for low electric loading and competitive to IPM for high electric loading. The maximum torque/power-speed characteristic of IM is competitive to IPM; while the rated torque/power-speed characteristic of IM is poorer than IPM. The power factor of IM is competitive and even better than IPM for high electric loading in low-speed region. The torque ripple of IM is comparable to IPM for high electric loading and much lower than IPM for low electric loading. The overall efficiency of IM is lower than IPM, and the maximum efficiency of copper squirrel cage IM is approximately 2-3 percent lower than IPM. The material cost of IM is about half of IPM when IM and IPM are designed with the same stator outer diameter and stack length.

The electromagnetic performances and material costs of IM and IPM are quantitatively compared and discussed.

The purpose of this paper is to minimize the optimization parameter number of synchronous reluctance machine (SynRM) and permanent magnet (PM) assisted SynRM, and compare their relative merits with interior permanent magnet (IPM) machine for electric vehicle applications, in terms of electromagnetic performance and material cost.

The analysis of electromagnetic performance is based on finite element analysis, by using software MAXWELL. The genetic algorithm is utilized for optimization.

The rotor design of SynRM can be significantly simplified by imposing some reasonable conditions. The number of rotor design parameters can be reduced to three. The electromagnetic performance of SynRM is much poorer than that of IPM, although the material cost is much cheaper, approximately one-third of IPM. The ferrite-SynRM is competitive and even better than IPM especially for high electric loading, in terms of torque capability, torque-speed characteristic, power factor, threshold speed and efficiency. In addition, ferrite-assisted SynRM has great advantage over IPM in material cost, 55 percent cheaper. The performance of NdFeB-assisted SynRM is close to IPM in terms of torque capability, torque-speed characteristic, power factor, torque ripple and efficiency. The material cost of NdFeB-assisted SynRM is ∼25 percent lower than IPM.

Some conditions, which can simplify the optimization of SynRM rotor, are discussed. The electromagnetic performances and material costs of SynRM, ferrite-assisted, NdFeB-assisted SynRMs and IPM are quantitatively compared and discussed.

The purpose of this paper is to propose a permanent magnet-assisted synchronous reluctance machine (PMASynRM) using ferrite magnets with the same power density as rare-earth PM synchronous motors used in Toyota Prius 2010.

A novel rotor structure with rectangular PMs is discussed with respect to the demagnetization of ferrite magnets and mechanical strength. Some electromagnetic characteristics including torque, output power, loss and efficiency are calculated by 2D finite element analysis.

The results of the analysis show that a high power density and high efficiency for PMASynRM can be achieved using ferrite magnets.

This paper proposes a novel rotor structure of PMASynRM with low-cost ferrite magnets that achieves high power density as permanent machines with rare-earth PMs.

Online web searches have played crucial roles in influencing consumers’ purchasing decisions. Web search traffic information enables researchers and practitioners to better understand consumers in terms of their preferences and interests, among other things. The purpose of this paper is to use web search traffic information provided by Google Trends to derive relationships among product brands as well as those between product brands and product attributes to propose a method to enhance the visibility of consumer brand positioning.

This study builds upon the interesting observation that consumers’ behavior in performing simultaneous searches, or searches including two or more keywords, can be converted into data indicating relationships among brands as well as those between brands and their attributes. The study focuses on the cases of hybrid cars and tablet PCs, and applies a social network analysis method to identify these relationships. Time series information on web search traffic is used because it can track these two product groups from the early stages to the present. This step is completed to verify the changes in the status of each brand and in their relationships that occurred in consumers’ minds over time.

Results show that consumers’ web search behaviors reveal the brand positioning and brand-attribute associations in their minds. Specifically, using consumers’ simultaneous search data, the authors derived relationships among brands (brand-brand network) from consumers’ behaviors of searching simultaneously for two brands and the relationships between brands and attributes (brand-product attributes network) from consumers’ behavior of searching simultaneously for a specific brand and certain product attributes.

Theoretically, this study verifies that consumers’ web search traffic information can be used to microscopically identify the positions of individual brands and their relationships in the minds of consumers. Regarding practical applications, this study proposes a method that can be used by companies to track how consumers perceive their brands by performing a simple and cost-effective analysis using the free search traffic information provided by Google.

The decade from 2000 until 2010 was a turbulent time for Toyota Motor Company. The carmaker came under significant criticism from the United States government, consumers throughout the world, and media critics amid allegations of poor quality control and vehicle safety concerns. Problems with accelerators and brake systems were found on several of its most popular models, a situation initially exacerbated by the slow and somewhat tentative response from top management. Toyota was accused of not addressing early warning signs that appeared several years before the crisis received intense negative publicity. Toyota struggled to retain the confidence of consumers and governmental regulators, eventually recalling approximately eight million automobiles.

In late 2009 Toyota became the subject of media and U.S. government scrutiny after multiple deaths and injuries were attributed to accidents resulting from the unintended and uncontrolled acceleration of its cars. Despite Toyota's voluntary recall of 4.2 million vehicles for floor mats that could jam the accelerator pedal and a later recall to increase the space between the gas pedal and the floor, the company insisted there was no underlying defect and defended itself against media reports and regulatory statements that said otherwise. As the crisis escalated, Toyota was further criticized for its unwillingness to share information from its data recorders about possible problems with electronic throttle controls and sticky accelerator pedals, as well as braking problems with the Prius. By the time Toyota Motor Company president Akio Toyoda apologized in his testimony to the U.S. Congress, Toyota's stock price had declined, in just over a month, by 20 percent---a $35 billion loss of market value.

Understand the strategic and reputational nature of crises Recognize the challenges of managing a crisis Learn the requirements for building trust in a crisis Understand the challenges of managing a crisis that may not be the company's fault Identify the strategic business problem in a crisis Understand how corporate structure may help or hinder effective crisis management Understand the media landscape and its impact on crisis management

The paper aims to propose a reinterpretation of corporate apologia and social legitimacy from theoretical perspectives of phenomenology and Foucault's theory of discipline.

The reinterpretation proposed in this paper is based on diagnostic theories aimed at making improvements by guiding practice in a determinate direction and by providing a basis for criticizing practice. The author also provides examples of adequate and inadequate corporate apologia along with the theoretical framework proposed in this paper.

Besides shouldering responsibility corporations cannot help becoming disciplined subjects in order to re‐establish legitimacy with the public.

The paper proposes a view of corporate apologia as self‐discipline for corporations that have undergone mishaps in order to reestablish legitimacy. Some examples of Japanese multinational corporations, such as Toyota and Toshiba, are included to contextualize abstract ideas.

The purpose of this paper is to probe the potentials of computational intelligence (CI) and bio-inspired computational tools for designing a hybrid framework which can simultaneously design an identifier to capture the underlying knowledge regarding a given plug-in hybrid electric vehicle’s (PHEVs) fuel cost and optimize its fuel consumption rate. Besides, the current investigation aims at elaborating the effectiveness of Pareto-based multiobjective programming for coping with the difficulties associated with such a tedious automotive engineering problem.

The hybrid intelligent tool is implemented in two different levels. The hyper-level algorithm is a Pareto-based memetic algorithm, known as the chaos-enhanced Lamarckian immune algorithm (CLIA), with three different objective functions. As a hyper-level supervisor, CLIA tries to design a fast and accurate identifier which, at the same time, can handle the effects of uncertainty as well as use this identifier to find the optimum design parameters of PHEV for improving the fuel economy.

Based on the conducted numerical simulations, a set of interesting points are inferred. First, it is observed that CI techniques provide us with a comprehensive tool capable of simultaneous identification/optimization of the PHEV operating features. It is concluded that considering fuzzy polynomial programming enables us to not only design a proper identifier but also helps us capturing the undesired effects of uncertainty and measurement noises associated with the collected database.

To the best knowledge of the authors, this is the first attempt at implementing a comprehensive hybrid intelligent tool which can use a set of experimental data representing the behavior of PHEVs as the input and yields the optimized values of PHEV design parameters as the output.

Under the condition of small data set, a prediction model of motor magnetic field is established based on deep learning method. This paper aims to complete the magnetic field prediction quickly and accurately.

An improved Linknet model is proposed to predict the motor magnetic field. This is a digital twin technology, which can predict the function values of other points according to the function values of typical sampling points. The results of magnetic field distribution are represented by color images. By predicting the pixels of the image, the corresponding magnetic field distribution is obtained. The model not only considers the correlation between pixels but also retains the spatial information in the original input image and can well learn the mapping relationship between motor structure and magnetic field.

The model can speed up the calculation while ensuring the accuracy and has obvious advantages in large-scale calculation and real-time simulation.

Under the condition of small data set, the model can well learn the mapping relationship between motor structure and magnetic field, so as to complete the magnetic field prediction quickly and accurately. In the future, according to the characteristics of magnetic field distribution, it will lay a foundation for solving the problems of rapid optimization, real-time simulation and physical field control of electrical equipment.

The purpose of this paper is to examine the effects of the #MeToo movement in the work environment of professional football organizations in Spain. It also explores the current situation of the professional career of women working in this industry to know if the opportunities are equal for men and women to reach management or executive positions.

From a gender approach and considering gender as a social structure (Risman, 2004), the authors are going to analyse men and women’s professional careers in football organizations from a three-dimensional gender perspective (individual, interactional and institutional). The objective is twofold: to know the effect of the #MeToo movement in these organizations; and also to know the opinion of both men and women of these organizations concerning gender influence for women’s career progression. The methodology implemented in this investigation is qualitative; 24 in-depth interviews (12 men and 12 women) have been carried out with professionals from different executive positions in both football clubs and organizations.

The gender approach improves current knowledge about women’s roles in the football industry. The exploratory analysis of the results shows that although the #MeToo phenomenon is relatively known it has had an indirect impact in Spanish football, where its consequences have not been as visible as in other sectors.

The paper provides an exploratory approach by analysing the effects of the #MeToo movement in the football sector, an area where almost no previous research has been done. Also, it presents the main factors that influence women’s professional careers in this sector and the significance of the recent #MeToo phenomenon in the football industry.