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In alignment with the U.S. Army's Climate Strategy and the broader trend in automotive technology, there is a strategic shift towards electrification and hybridization of the vehicle fleet. While a major goal of this effort is to mitigate the carbon footprint of the U.S. Army's vehicle operations, this transition also presents an opportunity to harness advancements in automotive electrification. Among the key vehicles in focus are tactical wheeled vehicles, which provide military forces with versatile and rugged transportation solutions for various combat scenarios, ensuring mobility, protection, and adaptability on the battlefield. This study investigates the potential of electrified tactical wheeled vehicles by conducting a survey involving a diverse group of vehicle operators across various ranks within the U.S. Army.

In recent years, the increasing complexity of modern aerospace systems has driven the rapid adoption of robust Model-Based Systems Engineering (MBSE). MBSE is a development methodology centered around computational models, which are instrumental in supporting the design and analysis of intricate systems. In this context, the Architecture Analysis and Design Language (AADL) and Systems Modeling Language (SysML) are two prominent modeling languages for specifying and analyzing the structure and behavior of a cyber-physical system. Both languages have their own specific use cases and tool environments and are typically employed to model different aspects of system design. Although multiple software tools are available for transforming models from one language to another, their effectiveness is limited by fundamental differences in the semantics of each language.

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.

Success in metal additive manufacturing (AM) relies on the optimization of a large set of process parameters to achieve materials whose properties and performance meet design and safety requirements. Despite continuous improvements in the process over the years, the quality of AM parts remains a major concern for manufacturers. Today, researchers are starting to move from discrete geometry-dependent build parameters to continuously variable or dynamically changing parameters that are geometry- and scan-path aware. This approach has become known as “feedforward control.” Process Control for Defect Mitigation in Laser Powder Bed Fusion Additive Manufacturing discusses the origins of feedforward control, its early implementations in AM, the current state of the art, and a path forward to its broader adoption. Click here to access the full SAE EDGETM Research Report portfolio.

Traditional ground vehicle architectures comprise of a chassis connected via passive, semi-active, or active suspension systems to multiple ground wheels. Current design-optimizations of vehicle architectures for on-road applications have diminished their mobility and maneuverability in off-road settings. Autonomous Ground Vehicles (AGV) traversing off-road environments face numerous challenges concerning terrain roughness, soil hardness, uneven obstacle-filled terrain, and varying traction conditions. Numerous Active Articulated-Wheeled (AAW) vehicle architectures have emerged to permit AGVs to adapt to variable terrain conditions in various off-road application arenas (off-road, construction, mining, and space robotics). However, a comprehensive framework of AAW platforms for exploring various facets of system architecture/design, analysis (kinematics/dynamics), and control (motions/forces) remains challenging.

This work covers the historical development of Built-In-Test (BIT) for fiber optic interconnect links for aerospace applications using Optical Time Domain Reflectometry (OTDR) equipped transceivers. The original failure modes found that installed fiber optic links must be disconnected before diagnosis could begin, often resulting in “no fault found” (NFF) designation. In fact, the observed root cause was that most (85%) of the fiber optic link defects were produced by contamination of the connector end faces. In March of 2006, a fiber optics workshop was held with roughly sixty experts from system and component manufacturers to discuss the difficulties of fiber optic test in aerospace platforms. During this meeting it was hypothesized that Optical Time Domain Reflectometry (OTDR) was feasible using an optical transceiver transmit pulse as a stimulus. The time delay and amplitude of received reflections would correlate with the position and severity of link defects, respectively.

We describe how we apply the SAE AS 5506 Architecture and Analysis Design Language (AADL) [4] to reason about contextual and architectural concerns for cyber security. A system’s cyber security certification requires verification that the system’s cyber security mechanisms are correct, non-bypassable, and tamper-resistant. We can verify correctness by examining the mechanism itself, but verifying the other qualities requires us to examine the context in which that mechanism resides. Understanding that context and validating the system’s evolving design against that context is an objective for the Architecture Centric Virtual Integration Process (ACVIP), an AADL-based approach to model and detect system design defects before they become too costly to fix. We describe our work to apply AADL to assess non-bypassability and tamper-resistance. The results of our research - tool plugins for cyber security architectural validation - support system developers today in their ACVIP activities.

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.

As the complexity of systems expands with increasing emphasis for digital transformation, the aerospace industry is generating big data to meet customer requirements. The ability to that data to solve challenging problems is limited by many factors, including the capabilities of current classical computing systems. Impact of Quantum Computing in Aerospace discusses how quantum computing systems offer (possibly quadratic to exponentially) greater computational power over classical computers. The power of quantum computing is tremendous and has many potential impacts on the aerospace industry; however, there are also many unsettled topics surrounding the future of the technology. Click here to access the full SAE EDGETM Research Report portfolio.

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.

Game-changing opportunities abound for the application of vehicle health management (VHM) across multiple transportation-related sectors, but key unresolved issues continue to impede progress. VHM technology is based upon the broader field of advanced analytics. Much of traditional analytics efforts to date have been largely descriptive in nature and offer somewhat limited value for large-scale enterprises. Analytics technology becomes increasingly valuable when it offers predictive results or, even better, prescriptive results, which can be used to identify specific courses of action. It is this focus on action which takes analytics to a higher level of impact, and which imbues it with the potential to materially impact the success of the enterprise. Artificial intelligence (AI), specifically machine learning technology, shows future promise in the VHM space, but it is not currently adequate by itself for high-accuracy analytics.

Mobile heavy article tilter and positioner (HATP) is special purpose vehicle designed to level, articulate and positioning of very heavy load within the accuracy of arc minutes and in a stipulated time in fully auto mode. HATP system uses sophisticated electronic controller system to carry out required task in auto mode. This electronic controller system comprises of various types of electronic hardware, software, sensors and actuators. As this system is dealing with heavy load, any failure in any of subsystem of HATP can result into catastrophe. Therefore active and passive safety measure at various levels must be incorporated into system which firstly prevents the failure and reduce the effect of failure. The safety system for HATP system has been divided in three major levels: 1. Access level safety 2. Operational safety 3. Preventive safety. All three levels of safety is incorporated at appropriate subsystem based on Risk Priority Number (RPN) and failure mode effect analysis.

During Operation Iraqi Freedom and Operation Enduring Freedom, improvised explosive devices were used strategically and with increasing frequency. To effectively design countermeasures for this environment, the Department of Defense identified the need for an under-body blast-specific Warrior Injury Assessment Manikin (WIAMan). To help with this design, information on Warfighter injuries in mounted under-body blast attacks was obtained from the Joint Trauma Analysis and Prevention of Injury in Combat program through their Request for Information interface. The events selected were evaluated by Department of the Army personnel to confirm they were representative of the loading environment expected for the WIAMan. A military case review was conducted for all AIS 2+ fractures with supporting radiology. In Warfighters whose injuries were reviewed, 79% had a foot, ankle or leg AIS 2+ fracture. Distal tibia, distal fibula, and calcaneus fractures were the most prevalent.

The EuroSID-2re (ES-2re) Anthropomorphic Test Device (ATD) commonly known as the crash test dummy is also used in the military domain to assess the risk of injury of armored vehicles occupants from lateral impact. The loading conditions range from low velocity - long duration impacts (4 m/s - 50 ms) similar to the automotive domain, to high velocity - short duration impacts (28 m/s - 3 ms) corresponding to cases where the panel deforms under an explosion. The human shoulder response to lateral impact was investigated at bounds of the loading condition spectrum previously mentioned, and also at intermediate conditions (14 m/s - 9 ms) in previous studies. The aim of the current study is to provide additional insight at the intermediate loading conditions which are not found in the literature.

Abstract - The Warrior Injury Assessment Manikin (WIAMan) was developed to assess injury in Live Fire Test and Evaluation (LFTE) and laboratory development tests of vehicles and vehicle technologies subjected to underbody blast (UBB) loading. While UBB events impart primarily vertical loading, the occupant location in the vehicle relative to the blast can result in some inherent non-vertical, or off-axis loading. In this study, the WIAMan Technology Demonstrator (TD) was subjected to 18 tests with a 350g, 5-ms time duration drop tower pulse using an original equipment manufacturer (OEM) energy attenuating seat in four conditions: purely vertical, 15° forward tilt, 15° rearward tilt, and 15° lateral tilt to simulate the partly off-axis loading of an UBB event. The WIAMan TD showed no signs of damage upon inspection. Time history data indicates the magnitude, curve shape, and timing of the response data were sensitive to the off-axis loading in the lower extremity, pelvis, and spine.

The advancement of both sensory and unmanned technology, combined with increased utilization of autonomous platforms in complex teaming scenarios, has created a need for practical design space exploration tools to aid in the synthesis of effective System-of-Systems (SoS). The presented work describes a modular, flexible, and extensible framework, referred to herein as the Technologies and Teaming Evaluation (TATE) framework, for straightforward identification of high-quality SoS, which may include both manned and autonomous elements, through quantitative evaluation of system-level and SoS-level attributes against a set of user-defined reference tasks.

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.

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.

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.

Under body blast (UBB) loading to military transport vehicles is known to cause foot-ankle fractures to occupants due to energy transfer from the vehicle floor to the feet of the soldier. The soldier posture, the proximity of the event with respect to the soldier, the personal protective equipment (PPE) and age/sex of the soldier are some variables that can influence injury severity and injury patterns. Recently conducted experiments to simulate the loading environment to the human foot/ankle in UBB events (~5ms rise time) with variables such as posture, age and PPE were used for the current study. The objective of this study was to determine statistically if these variables affected the primary injury predictors, and develop injury risk curves. Fifty below-knee post mortem human surrogate (PMHS) legs were used for statistical analysis. Injuries to specimens involved isolated and multiple fractures of varying severity.