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Abstract TOC

The second-life use of batteries from electric vehicles (EV) represents an excellent and cost-effective option for energy storage applications, including the control of fluctuations in energy supply and demand or in combination with solar photovoltaic and wind turbine. Indeed, these batteries are normally replaced from EV use before the end of their service life, when they still have 70-80% of the original capacity. Depending on the cell chemistry and the specific design, such batteries can still be employed in less stressful applications than the automotive one, including commercial, residential, and industrial applications. With the aim to promote the transition to a circular closed-loop economy for spent traction batteries, this study consists in a systematic literature review of available options for reusing EV batteries as a storage system in a factory environment, highlighting benefits and critical aspects.

This document is divided into five parts. The first part deals with flotation analysis features and definitions to acquaint the engineer with elements common to the various methods and the meanings of the terms used. The second part identifies and describes current flotation analysis methods. Due to the close relationship between flotation analysis and runway design, methods for the latter are also included in this document. As runway design criteria are occasionally used for flotation evaluation, including some for runways built to now obsolete criteria, a listing of the majority of these criteria constitutes the third part. The fourth part of this document tabulates the most relevant documents, categorizing them for commercial and civil versus military usage, by military service to be satisfied, and by type of pavement. This document concludes with brief elaborations of some concepts for broadening the analyst’s understanding of the subject.

Engineering Events staff at SAE International in Warrendale, Pennsylvania, have extended the call for abstracts through September 21 for the organization’s AeroTech aerospace and defense technology conference, which will take place at the Fort Worth Convention Center in Fort Worth, Texas, March 14-16, 2023. Visit the AeroTech call for abstracts page for more information and to get started.

Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.

SAE International is inviting global participation in its AeroTech® aerospace and defense technology conference and exhibition, which is for the first time co-located with ASM International’s AeroMat, at the Pasadena Convention Center in Pasadena, California, March 15 through 17, 2022.

Abstract Autonomy has the potential to make the most radical impact by significantly reducing the number of soldiers in harm’s way and changing the military paradigm. Benefits of autonomy to improve the Army’s mission capabilities and the rapid evolution of military systems exerts pressure to develop these systems quickly. Since the associated technological development is highly fast paced and stochastic, approaches that develop systems for stochastic future scenarios are required. In this article we present a vision for the autonomous high-mobility military systems for that future. We discuss the ramifications of autonomy in five areas: (1) fleet organization, (2) physical attributes of high-mobility military systems, (3) individual behaviors of autonomous assets, (4) interactions between humans and autonomous systems, and (5) operation and teaming strategies. We present the future vision, implications, requirements, and technological challenges for each of the five areas.

Abstract This article investigates the fuel savings potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the lithium-ion battery pack in the hybrid configuration. The powertrain supervisory control optimization determines the most efficient way to split the power demand between the battery pack and the engine. Despite the available design and control optimization techniques, a generalized mathematical formulation and solution approach for combined design and control optimization is still missing in the literature. This article intends to fill that void by proposing a unified framework to simultaneously optimize both the battery pack size and power split control sequence. This is achieved through a combination of genetic algorithm (GA) and Pontryagin’s minimum principle (PMP) where the design parameters are integrated into the Hamiltonian function.

This paper investigates the fuel saving potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the Lithium-ion battery pack in the hybridized configuration. On the other hand, the powertrain supervisory control optimization finds the most efficient way to split power demands between the battery pack and the engine. Most of the previous literatures implement them separately. In contrast, combining the sizing and energy management problem into a single optimization problem produces the global optimal solution. This study proposes a novel unified framework to couple Genetic Algorithm (GA) with Pontryagin’s Minimum Principle (PMP) to determine the battery pack sizing and the power split control sequence simultaneously.