Implementation of SiC Power Electronics for Green Energy Based Electrification of Transportation

Increase in greenhouse gas emission poses a threat to the quality of air thus threatening the future of living beings on earth. A large part of the emission is produced by transport vehicles. Electric vehicles (EVs) are a great solution to this threat. They will completely replace the high usage of hydrocarbons in the transport sector. Energy efficiency and reduced local pollution can also be expected with full implementation of electrification of transportation. However, the current grid is not prepared to take the power load of EV charging if it were to happen readily. Moreover, critics are doubtful about the long-term sustainability of EVs in terms of different supply chain issues. The first step for tackling this problem from a research perspective was to do a thorough review of the details of charging in modern day grid. The downsides and lack of futuristic vision. Findings showed that implementing end to end DC based on green energy aided by SiC power electronics. To prove the findings analysis and modelling was done for SiC based charging network. A similar approach was implemented in EV powertrain development. The implementation of SiC power electronics in charging network showed lesser losses, higher thermal conductivity, lesser charging time. The effect on long term battery health and additional circuit was also observed. The cost of production can be reduced by volume manufacturing that has been discussed. In powertrain analysis and simulation the loss and heat reduction one shown on a component-by-component basis. Therefore, this research proposes a Silicon Carbide based end to end DC infrastructure based completely on solar and wind power. The pollution will further be reduced, and energy demands will be met

Extending the solid step fixed-charge transportation problem to consider two-stage networks and multi-item shipments

This paper develops a new mathematical model for a capacitated solid step fixed-charge transportation problem. The problem is formulated as a two-stage transportation network and considers the option of shipping multiple items from the plants to the distribution centers (DC) and afterwards from DCs to customers. In order to tackle such an NP-hard problem, we propose two meta-heuristic algorithms; namely, Simulated Annealing (SA) and Imperialist Competitive Algorithm (ICA). Contrary to the previous studies, new neighborhood strategies maintaining the feasibility of the problem are developed. Additionally, the Taguchi method is used to tune the parameters of the algorithms. In order to validate and evaluate the performances of the model and algorithms, the results of the proposed SA and ICA are compared. The computational results show that the proposed algorithms provide relatively good solutions in a reasonable amount of time. Furthermore, the related comparison reveals that the ICA generates superior solutions compared to the ones obtained by the SA algorithm

Analysis of current and potential sensor network technologies and their incorporation as embedded structural system

This document provides a brief overview of the actual wireless ad hoc sensor networks technologies and standards available, especially in view of their possible implementation for shipping container protection and monitoring within the framework of the STEC Action aiming at analyzing possible technical solutions to improve the security of the millions of containers moving in and out of Europe. Examples of applications and research projects are reported from the literature to give insights on the possibility of implementation of wireless sensor networks in real world scenarios.JRC.G.5-European laboratory for structural assessmen

Joint location and inventory models and algorithms for deployment of hybrid electric vehicle charging stations.

This thesis describes a study of a novel concept of hybrid electric vehicle charging stations in which two types of services are offered: battery swapping and fast level-3 DC charging. The battery swapping and fast-charging service are modeled by using the M/G/s/s model and the M/G/s/$\infty$ model, respectively. In particular, we focus on the operations of joint battery swapping and fast charging services, develop four joint locations and inventory models: two for the deployment of battery swapping service, two for the deployment of hybrid electric vehicle charging service. The first model for each deployment system considers a service-level constraint for battery swapping and hybrid charging service, whereas the second for each deployment system considers total sojourn time in stations. The objective of all four models is to minimize total facility setup cost plus battery and supercharger purchasing cost. The service level, which is calculated by the Erlang loss function, depends on the stockout probability for batteries with enough state of charge (SOC) for the battery swapping service and the risk of running out of superchargers for the quick charging service. The total sojourn time is defined as the sum of the service time and the waiting time in the station. Metaheuristic algorithms using a Tabu search are developed to tackle the proposed nonlinear mixed-integer optimization model. Computational results on randomly generated instances and on a real-world case comprised of 714,000 households show the efficacy of proposed models and algorithms

Applications of network optimization

Includes bibliographical references (p. 41-48).Ravindra K. Ahuja ... [et al.]

Meta-heuristic approach for high-demand facility locations considering traffic congestion and greenhouse gas emission

Large facilities in urban areas, such as storage facilities, distribution centers, schools, department stores, or public service centers, typically generate high volumes of accessing traffic, causing congestion and becoming major sources of greenhouse gas (GHG) emission. In conventional facility-location models, only facility construction costs and fixed transportation costs connecting customers and facilities are included, without consideration of traffic congestion and the subsequent GHG emission costs. This study proposes methods to find high-demand facility locations with incorporation of the traffic congestion and GHG emission costs incurred by both existing roadway traffic and facility users into the total cost. Tabu search and memetic algorithms were developed and tested with a conventional genetic algorithm in a variety of networks to solve the proposed mathematical model. A case study to determine the total number and locations of community service centers under multiple scenarios in Incheon City is then presented. The results demonstrate that the proposed approach can significantly reduce both the transportation and GHG emission costs compared to the conventional facility-location model. This effort will be useful for decision makers and transportation planners in the analysis of network-wise impacts of traffic congestion and vehicle emission when deciding the locations of high demand facilities in urban areas

Research reports: 1991 NASA/ASEE Summer Faculty Fellowship Program

The basic objectives of the programs, which are in the 28th year of operation nationally, are: (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate an exchange of ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of the participants' institutions; and (4) to contribute to the research objectives of the NASA Centers. The faculty fellows spent 10 weeks at MSFC engaged in a research project compatible with their interests and background and worked in collaboration with a NASA/MSFC colleague. This is a compilation of their research reports for summer 1991

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes