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The purpose of this paper is to optimize the design and power management control fuel cell/supercapacitor and fuel cell/battery hybrid electric vehicles and to provide a comparative study between the two configurations.

In hybrid electric vehicles (HEVs), the power flow control and the powertrain component sizing are strongly related and their design will significantly influence the vehicle performance, cost, efficiency and fuel economy. Hence, it is necessary to assess the power flow management strategy at the powertrain design stage in order to minimize component sizing, cost, and the vehicle fuel consumption for a given driving cycle. In this paper, the PSO algorithm is implemented to optimize the design and the power management control of fuel cell/supercapacitor (FC/SC) and fuel cell/battery (FC/B) HEVs for a given driving cycle. The powertrain and the proposed control strategy are designed and simulated by using MATLAB/Simulink. In addition, a comparative study of fuel cell/supercapacitor and fuel cell/battery HEVs is analyzed and investigated for adequately selecting of the appropriate HEV, which could be used in industrial applications.

The results have demonstrated that it is possible to significantly improve the hydrogen consumption in fuel cell hybrid electric vehicles (FCHEVs) by applying the PSO approach. Furthermore, by analyzing and comparing the results, the FC/SC HEV has slightly higher fuel economy than the FC/B HEV.

The addition of electrical energy storage such as supercapacitor or battery in fuel cell‐based vehicles has a great potential and a promising approach for future hybrid electric vehicles (HEV). This paper is mainly focused on the optimal design and power management control, which has significant influences on the vehicle performance. Therefore, this study presents a modified control strategy based on PSO algorithm (CSPSO) for optimizing the power sharing between sources and reducing the components sizing. Furthermore, an interleaved multiple‐input power converter (IMIPC) is proposed for fuel cell hybrid electric vehicle to reduce the input current/output voltage ripples and to reduce the size of the passive components with high efficiency compared to conventional boost converter. Meanwhile, the fuel economy is improved. Moreover, a comparative study of FC/SC and FC/B HEVs will be provided to investigate the benefits of hybridization with energy storage system (ESS).

The purpose of this paper is the investigation of a new coordinated switching strategy to improve the transient performance of a fuel cell (FC)- supercapacitor (SC) electric vehicle. The proposed switching strategy protects FCs from large currents drawn during abrupt power variations. Furthermore, it compensates the poor FC transient response and suppresses the transient ripples occurring during power source switching instants.

Coordinated power source switching is achieved using three different transition functions. Vehicle model is fractioned into computational and console subsystems for its simulation using real time (RT) LAB simulator. Blocs containing coordination switching strategy, power sources models and their power electronics interface are placed in the computational subsystem that will be executed, in RT, on one of real time laboratory simulator central processing unit cores.

Coordination switching strategy resulted in reducing transient power ripples by 90% and direct current (DC) bus voltage fluctuations by 50%. Switching through transition functions compensated the difference between FC and SC transient responses responsible for transient power ripples. Among the three proposed transition functions, linear transition function resulted in the best transient performances.

The proposed coordinated switching strategy allows the control of the switching period duration. Furthermore, it enables the choice of adequate transition functions that fit the dynamics of power sources undergoing transition. Also, the proposed switching technique is simple and does not require the knowledge of system parameters or the complex control models.

The electric vehicle has been viewed as a technological solution to the dual plagues of dwindling fossil fuel supplies and pollutant emissions from gasoline powered vehicles. Futurists see a world where most personal transportation is electrically powered with energy supplied by tomorrow's power plants. In that future world, automobile power sources — representing millions of uncontrollable sources of pollution and energy waste — are consolidated into fewer, manageable, generators in fixed locations. With fixed and relatively few sources of pollution, resources can be better focused to provide clean, inexpensive energy for transportation. Many people share this vision of the future but few have been able to see how it can be brought into existence. Initial attempts have focused on legislation to stimulate the development of this market. As with any new technology, the electric vehicle field has developed its own terminology. For purposes of clarity throughout mis paper please bear in mind the following definitions.

The flexible mode transitions, multiple power sources and system uncertainty lead to challenges for mode transition control of four-wheel-drive hybrid powertrain. Therefore, the purpose of this paper is to improve dynamic performance and fuel economy in mode transition process for four-wheel-drive hybrid electric vehicles (HEVs), overcoming the influence of system uncertainty.

First, operation modes and transitions are analyzed and then dynamic models during mode transition process are established. Second, a robust mode transition controller based on radial basis function neural network (RBFNN) is proposed. RBFNN is designed as an uncertainty estimator to approximate lumped model uncertainty due to modeling error. Based on this estimator, a sliding mode controller (SMC) is proposed in clutch slipping phase to achieve clutch speed synchronization, despite disturbance of engine torque error, engine resistant torque and clutch torque. Finally, simulations are carried out on MATLAB/Cruise co-platform.

Compared with routine control and SMC, the proposed robust controller can achieve better performance in clutch slipping time, engine torque error, vehicle jerk and slipping work either in nominal system or perturbed system.

The mode transition control of four-wheel-drive HEVs is investigated, and a robust controller based on RBFNN estimation is proposed. Compared results show that the proposed controller can improve dynamic performance and fuel economy effectively in spite of the existence of uncertainty.

This chapter explains how electric driving has been transforming car mobility in The Netherlands since 1990, highlighting the role of a specific Dutch policy mix as direct factor, and the conditions through which this policy mix came about as indirect factors. The analysis is based on triangulation of findings from three methods: (1) discourse analysis of national newspapers and online blogs to understand the changing meanings of car mobility as well as changing stakeholder competences; (2) interview analysis with Dutch stakeholders to understand policy effects as well as their changing competences; and (3) analysis of relevant documents that provide the numbers of vehicles sold, implemented infrastructures and policy instruments. The study describes market changes in terms of ‘reconfiguring’ (entangled) practices of Dutch motorists, vehicle manufacturers and policy-makers, constituted by the (changing) relations between meanings, materialities, competences and policy incentives. The analysis finds a gradual reconfiguration of car mobility in three stages: The hegemony of Internal Combustion Engine (ICE) mobility (1990–2008), Surge in Plug-in Hybrid Electric Vehicle (HEV) mobility (2009–2015), and Surge in full-electric mobility (2016–2020). The analysis shows that the specific Dutch policy incentives were critical to orchestrating the co-evolution of ICE-based and electric mobility towards low-carbon alternatives, that is, towards more electrification. The policy mix was adapted in three successive steps, in which inconsistencies towards electric mobility (e-mobility) were solved, entailing three distinct reconfiguration pathways in each period. The relatively strong policy incentives for e-mobility in The Netherlands can be explained by the absence of an established car industry as well as particular air quality challenges in cities (triggering local support for the provision of charging infrastructure). The conclusion includes policy recommendations for countries that seek to promote e-mobility, although further research should clarify how contextual differences require specific elements in the policy mix.

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.

Fractional slot permanent magnet (PM) brushless machines having concentrated non‐overlapping windings have been the subject of research over last few years. They have already been employed in the commercial hybrid electric vehicles (HEVs) due to high‐torque density, high efficiency, low‐torque ripple, good flux‐weakening and fault‐tolerance performance. The purpose of this paper is to overview recent development and research challenges in such machines in terms of various structural and design features for electric vehicle (EV)/HEV applications.

In the paper, fractional slot PM brushless machines are overviewed according to the following main and sub‐topics: first, machine topologies: slot and pole number combinations, all and alternate teeth wound (double‐ and single‐layer windings), unequal tooth structure, modular stator, interior magnet rotor; second, machine parameters and control performance: winding inductances, flux‐weakening capability, fault‐tolerant performance; and third, parasitic effects: cogging torque, iron loss, rotor eddy current loss, unbalanced magnetic force, acoustic noise and vibration.

Many fractional slot PM machine topologies exist. Owing to rich mmf harmonics, fractional slot PM brushless machines exhibit relatively high rotor eddy current loss, potentially high unbalanced magnetic force and acoustic noise and vibration, while the reluctance torque component is relatively low or even negligible when an interior PM rotor is employed.

This is the first overview paper which systematically reviews the recent development and research challenges in fractional‐slot PM machines. It summarizes their various structural and design features for EV/HEV applications.

The purpose of this paper is to give an overview of the design issues of permanent magnet machines for the hybrid electric and plug‐in electric vehicles, including railway traction and naval propulsion.

Focus is given on both synchronous permanent magnet and reluctance machines. An overview of the design rules are provided, covering the topics of: fractional‐slot windings, fault‐tolerant configurations, flux‐weakening capability, and torque quality.

The peculiarities of these machines and the advanced design considerations to fit the automotive requirements are analyzed.

The paper includes a wide description of innovative electrical machines for electric vehicles, including not only the traction capability, but also analysis of features as weight reduction, torque ripple reduction, increase of fault tolerance, and so on.

This paper seeks to analyze consumer preferences toward fresh rabbit meat and obstacles and interest in consuming the product.

The paper uses the dual response choice experiment (DRCE) design which allows for analyzing forced and unforced options in choice experiments using the same sample. The heteroscedastic extreme‐value (HEV) model is used due to its relaxation of the restrictive assumption made in the multinomial logit model regarding the identically distributed error term across alternatives. The empirical analysis uses consumer‐level questionnaires to elicit information regarding consumer attitudes toward rabbit meat in Catalonia (Spain).

The results demonstrate a higher preference for rabbit meat from “Catalan” origin followed by higher quality certification information. Convenience and “ready‐to‐eat” products made from rabbit meat may help bolster increased consumption. An effective communication campaign is needed to educate individuals regarding the health characteristics of rabbit compared to other types of meat. Furthermore, results demonstrate that the ordering of attributes is not significantly different from forced and non‐forced choices obtained from the DRCE design. However, significant differences on the magnitude of the preferences for some attributes' levels are found.

From a methodological point‐of‐view, the study follows a similar design to the dual response choice experiments. However, the study is differentiated by asking consumers whether they are willing to buy the product. More emphasis is made on the purchasing context of the task leading consumers to focus more on their budget constraints by considering the price. The study uses the DRCE design as an alternative of the traditional single stage choice experiments. Owing to budgets constraint, the study could be improved by comparing results from both designs. At the empirical level, it would be interesting to extend the study to other geographical parts in Spain.

The study can help policy makers in stimulating demand for rabbit meat. Rabbit meat farmers in Catalonia were forced to abandon their farms due to the lack of demand. Consumption has decreased dramatically. As recommended in the paper, high quality labelling of the meat, improving the carcass format and its presentation and the healthiest characteristic of the meat could be a good way to promote and stimulate demand.

From the empirical point‐of‐view, this study, to the authors' knowledge, is the first application of CE and CV to analyze consumers' preferences towards rabbit meat. Furthermore, it is the first paper that applies the HEV model in agro‐food economics and specifically towards rabbit meat.

The purpose of this paper is the investigation of the main aspects of optimal reliability allocation with respect to the design of hybrid electric vehicles. In particular, with reference to the hybrid electric vehicle propulsion system, the problem of data uncertainty, due to a scarce knowledge of the components' reliabilities, is taken into account. This problem is crucial for new technology systems and it is faced with a Bayesian approach: components' reliabilities are considered as random variables, characterised in the paper by negative log‐gamma distributions.

The main aspects of optimal reliability allocation with the design of hybrid electric vehicles are presented, pointing out the opportunity of a reliability evaluation in the planning stage.

The topic of a series hybrid vehicle reliability is addressed, nevertheless results can be easily extended to the parallel configuration. In particular, the opportunity of a reliability evaluation of the propulsion system in the design stage is highlighted, mainly when new technology components are involved.

The value of the paper consists in the methodology allowing to express the system reliability uncertainty as a function of component uncertain data. Then, as far as concern the practical implications, the optimal allocation of the components' reliabilities can be efficiently performed, in order to minimise the system total cost respecting a prefixed value of the system reliability. In the final part of the paper, a numerical application, related to a series hybrid electric vehicle propulsion system, is presented to show the feasibility of the approach.