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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.

Investigating the impact of Gasoline fuel on diesel engine performance and emission is very important for military heavy- duty combat vehicles. Gasoline has great potential as alternative fuel due to rapid depletion of petroleum reserves and stringent emission legislations, under multi fuel strategy program for military heavy- duty combat vehicle. There is a known torque, horsepower and fuel economy penalty associated with the operation of a diesel engine with Gasoline fuel. On the other hand, experimental studies have suggested that Gasoline fuel has the potential for lowering exhaust emissions, especially NOx, CO, CO2, HC and particulate matter as compared to diesel fuel. Recent emission legislations also restrict the total number of nano particles emitted in addition to particulate matter, which has adverse health impact.

This document has been declared "CANCELLED" as of July 2008 and has been superseded by PRI AC7102/1. By this action, this document will remain listed in the Numerical Section of the Aerospace Standards Index noting that it is superseded by PRI AC7102/1. Cancelled specifications are available from SAE.

This Aerospace Standard (AS) establishes the requirements for suppliers of Nonconventional Machining Services to be accredited by the National Aerospace and Defense Contractors Accreditation Program (NADCAP). NADCAP accreditation is granted in accordance with SAE AS7003 after demonstration of compliance with the requirements herein. The requirements may be supplemented by additional requirements specified by the NADCAP Nonconventional Machining and Surface Enhancement (NMSE) Task Group. Using the corresponding Audit Criteria (PRI AC7116) will ensure that accredited Nonconventional Machining suppliers meet all of the requirements in this standard and all applicable supplementary standards. The purpose of this audit program is to assess a supplier's ability to consistently provide a product or service that conforms to the technical specifications and customer requirements.

This Aerospace Standard (AS) is to be used as a supplement to SAE AS7109. In addition to the requirements contained in AS7109, the requirements contained herein shall apply to suppliers seeking NADCAP Coatings accreditation who are engaged in thermal spray.

Abstract The objective of this article is to evaluate the effects of different blast protective modules to military vehicle structures and occupants. The dynamic responses of the V-shape integral basic armor, the add-on honeycomb sandwich structure module, and the anti-shock seat-dummy system were simulated and analyzed. The improvements of occupant survivability by different protective modules were compared using occupant injury criteria. The integral armored cab can maintain the integrity of the cab body structure. The add-on honeycomb sandwich armor reduces the peak structural deformation and velocity of the cab floor by 34.9% and 47.4%, respectively, compared with the cab with integral armors only. The integral armored cab with the anti-shock seat or the honeycomb sandwich structures reduces the occupant shock responses below the injury criteria. For different blast threat intensities, the selection of appropriate protective modules can meet protection requirements.

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 The advancement in vision sensors and embedded technology created the opportunity in autonomous vehicles to look ahead in the future to avoid potential obstacles and steep regions to reach the target location as soon as possible and yet maintain vehicle safety from rollover. The present work focuses on developing a nonlinear model predictive controller (NMPC) for a high-speed off-road autonomous vehicle, which avoids undesirable conditions including stationary obstacles, moving obstacles, and steep regions while maintaining the vehicle safety from rollover. The NMPC controller is developed using CasADi tools in the MATLAB environment. The CasADi tool provides a platform to formulate the NMPC problem using symbolic expressions, which is an easy and efficient way of solving the optimization problem. In the present work, the vehicle lateral dynamics are modeled using the Pacejka nonlinear tire model.

This Aerospace Standard (AS) is to be used as a supplement to SAE AS7109. In addition to the requirements contained in AS7109, the requirements contained herein shall apply to suppliers seeking NADCAP Coatings accreditation who are engaged in stripping of coated material.

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.

This SAE Standard covers engine military oils suitable for lubrication of reciprocating internal combustion engines of both spark-ignition and compression-ignition types, and for power transmission fluid applications in combat/tactical service equipment (see 7.1). This document is equivalent to MIL-PRF-2104G when all requirements are met.

The objective of this study was to optimize the occupant restraint systems for a light tactical vehicle in frontal crashes. A combination of sled testing and computational modeling were performed to find the optimal seatbelt and airbag designs for protecting occupants represented by three size of ATDs and two military gear configurations. This study started with 20 sled frontal crash tests to setup the baseline performance of existing seatbelts, which have been presented previously; followed by parametric computational simulations to find the best combinations of seatbelt and airbag designs for different sizes of ATDs and military gear configurations involving both driver and passengers. Then 12 sled tests were conducted with the simulation-recommended restraint designs. The test results were further used to validate the models. Another series of computational simulations and 4 sled tests were performed to fine-tune the optimal restraint design solutions.

A full-system, end-to-end blast modeling and simulation of vehicle underbody buried blast events typically includes detailed modeling of soil, high explosive (HE) charge and air. The complex computations involved in these simulations take days to just capture the initial 50-millisecond blast-off phase, and in some cases, even weeks. The single most intricate step in the buried blast event simulation is in the modeling of the explosive loading on the underbody structure from the blast products; it is also one of the most computationally expensive steps of the simulation. Therefore, there is significant interest in the modeling and simulation community to develop various methodologies for fast running tools to run full simulation events in quicker turnarounds of time.

Frequently, a choice between system concepts must be made on the basis of something other than a detailed evaluation of the design effectiveness of these systems. This paper develops a rudimentary analysis process for use in addressing this problem.

This document has been declared "CANCELLED" as of June 2017. By this action, this document will remain listed in the Numerical Section of the Aerospace Standards Index. Cancelled specifications are available from SAE.

After manufacture, every military vehicle experiences a unique history of dynamic loads, depending on loads carried, missions completed, etc. Damage accumulates in vehicle structures and components accordingly, leading eventually to failures that can be difficult to anticipate, and to unpredictable consequences for mission objectives. The advent of simulation-based fatigue life prediction tools opens a path to Digital Twin based solutions for tracking damage, and for gaining control over vehicle reliability. An incremental damage updating feature has now been implemented in the Endurica CL fatigue solver with the aim of supporting such applications for elastomer components. The incremental updating feature is demonstrated via the example of a simple transmission mount component. The damage state of the mount is computed as it progresses towards failure under a series of typical loading histories.

As powertrain hybridization technologies are becoming popular, their application for heavy-duty military vehicles is drawing attention. An intelligent design and operation of the energy management system (EMS) is important to ensure that hybrid military vehicles can operate efficiently, simultaneously maximize fuel economy and minimize monetary cost, while successfully completing mission tasks. Furthermore, an integrated EMS framework is vital to ensure a functional vehicle power system (VPS) to survive through critical missions in a highly stochastic environment, when needed. This calls for situational awareness and dynamic system reconfiguration capabilities on-board of the military vehicle. This paper presents a new energy management and control (EMC) framework based on holistic situational awareness (SA) and dynamic reconfiguration of the VPS.

Tradespace analysis is used to define the characteristics of the solution space for a vehicle design problem enabling decision-makers (DMs) to evaluate the risk-benefit posture of a vehicle design program. The tradespace itself is defined by a set of functional objectives defined by vehicle simulations and evaluating the performance of individual design solutions that are modeled by a set of input variables. Of special interest are efficient design solutions because their perfomance is Pareto meaning that none of their functional objective values can be improved without decaying the value of another objective. The functional objectives are derived from a combination of simulations to determine vehicle performance metrics and direct calculations using vehicle characteristics. The vehicle characteristics represent vendor specifications of vehicle subsystems representing various technologies.