Military Vehicles Research Articles

Design and analysis of a hybrid electric powertrain for military tracked vehicles

Electrification of military vehicles offers the potential for extended stealth operation, enhanced vehicle performance, and onboard electric power. This study proposes a hybrid electric powertrain for a military tracked vehicle with hybrid energy storage (battery and capacitor) and multi-speed transmission. Initially, component sizing of the proposed powertrain and a series hybrid electric powertrain was done based on power and torque analysis of vehicle performance requirements on different operating terrains. A rule-based control strategy was then developed for the proposed powertrain to maintain high performance as well as reduce energy losses. The performance of the proposed powertrain and the series configuration was evaluated using AVL Cruise software over synthesized drive cycles that represent the real-world activities of military tracked vehicles. Comparative analysis during component sizing showed that the proposed powertrain provides a reduction in powertrain mass by 389 kg (2.72%). From the performance analysis, it was observed that the fuel economy of the proposed powertrain improved by almost 30.27% as compared to the series configuration while maintaining vehicle performance.

C-shaped split ring resonator type metamaterial antenna design using neural network

A C-shaped split ring resonator-based metamaterial (MTM) structure placed on a patch antenna is proposed. An artificial neural network (ANN) is applied to design and determine dimensions of an MTM structure that is similar to those used in wireless communication systems, such as Wi-Fi and WiMax, as well as in military vehicles and space stations. The proposed microstrip antenna interacts with the MTM-based structures to improve the reflection coefficient (S11) and quality factor. The design of the proposed structure is optimized for this purpose in accordance with the ANN studies in the related literature. Both simulation and experimental studies show that ANN calculated MTM antennas improved the quality factor, which is calculated as 230 at 5.18 GHz. The simulated S11 is verified by experiment to show the integrity of the proposed work.

Validation of two reconfigurable wheel-track testbeds for military vehicles

The National Robotics Engineering Center has conceived a novel system that is able to reconfigure from a track to a wheel while in motion. The purpose of this device is to combine the benefits of wheels and tracks to provide performance optimization on a variety of terrain. The first stage of development resulted in two benchtop prototypes: one to test a transition from rotating hub to rotating tread and another to test a constantly-oriented shape transition from circle to triangle. This paper documents the testing of these devices including current draw, temperature change, and braking characteristics. Through experimentation with the first testbed, desired speed was shown to be consistent within +/−6% when transitioning between wheel and track modes at an approximated ground speed between 5 and 35 km/h while transitioning in 5 to 60 seconds. Testing on the second system identified asymmetry in testbed construction and showed consistent loading patterns throughout a 42 mm-change in sprocket position between wheel and track mode while transitioning between 10 and 50 mm/s. The evaluation of these testbeds informed the design of the next process of the reconfigurable wheel-track project, which resulted in a larger prototype capable of propelling a small ground vehicle.

Review on self-inflation tire system

Self-Inflation Tire (SIT) System works with the combination of Mechanical Engineering, Electronic control unit (ECU), Electronic Engineering &Pneumatic control unit (PCU)). The primary job of self-inflation tire is to properly inflate the tire according to the recommended tire pressure; which eventually improves the overall tire life. SIT is designed for the small puncture and slow leakages. Leakages and punctures tend to decrease the recommended tire pressure slowly which is dangerous for the tire as well as vehicle. Self-inflation tires maintains the tire pressure at proper or required level. SIT does not need the extra time from the driver for filling the air pressure in tire, it can be implemented within few seconds. Self-inflation tires are mostly useful in commercial application, military vehicles and in luxury cars. With the push of a button the user or driver can inflate or deflate the tire within few seconds, this paper will discuss its advantages and disadvantages which justifies this system.

Multilevel Design of Sandwich Composite Armors for Blast Mitigation using Bayesian Optimization and Non-Uniform Rational B-Splines

<div class="section abstract"><div class="htmlview paragraph">In regions at war, the increasing use of improvised explosive devices (IEDs) is the main threat against military vehicles. Large cabin”s penetrations and high gross accelerations are primary threats against the occupants” survivability. The occupants” survivability under an IED event largely depends on the design of the vehicle armor. Under a blast load, a vehicle armor should maintain its structural integrity while providing low cabin penetrations and low gross accelerations. This investigation employs Bayesian global optimization (BGO) and non-uniform rational B-splines (NURBS) to design sandwich composite armors that simultaneously mitigate the cabin”s penetrations and the reaction force at the armor”s supports. The armors are made of four layers: steel, carbon fiber reinforced polymer (CFRP), aluminum honeycomb, and CFRP. BGO is a methodology to solve optimization problems that require the evaluation of expensive black-box functions such as the finite element (FE) simulations of the vehicle armor under a blast event. BGO has two main components: the surrogate model of the black-box function and the acquisition function that guides the optimization. In this study, the surrogate models are Gaussian processes and the acquisition function is the multi-objective expected improvement function. NURBS generate the armor”s shape. The numerical examples show three alternatives to optimize the armor at two levels: (1) thicknesses of the sandwich”s layers and (2) the armor”s shape. The three design alternatives differ in the number of optimized levels and the optimization approach (sequential or simultaneous). The results show that the simultaneous optimization of the thicknesses of the sandwich”s layers and the armor”s shape is the most effective approach to design vehicle armors for blast mitigation.</div></div>

Unstructured with a Point: Validation and Robustness Evaluation of Point-Cloud Based Path Planning

<div class="section abstract"><div class="htmlview paragraph">Robust autonomous navigation in unstructured environments is an unsolved problem and critical to the operation of autonomous military and rescue ground vehicles. Two-dimensional path planners operating on occupancy grids or costs maps can produce infeasible paths when the operational area includes complex terrain. Recently, sample-based path planners that plan on LiDAR-acquired point-cloud maps have been proposed. These approaches require no discretization of the operational area and provide direct pose estimation by modeling vehicle and terrain interaction. In this paper, we show that direct sample-based path planning on point clouds is effective and robust in unstructured environments. Robustness is demonstrated by completing a system parameter sensitivity analysis of the system in an Unreal simulation environment and partnered with field validation.</div></div>

Analysis of mechanical characteristics of inserts supporting run-flat tire during pressure relief

Inserts supporting run-flat tire is an important guarantee for safety, mobility and trafficability of military wheeled vehicles. The mechanical characteristics in the process of pressure relief is an important factor that affects the driving ability of vehicles. In order to study the change law, the large deflection and nonlinear finite element model of run-flat tire was established based on simulation using ABAQUS, and the accuracy of the model was verified by tire load characteristic test. The change law of tire displacement and contact pressure under different inflation pressures was studied and compared with normal tire. The results show that under the rated load, there is a significant piecewise nonlinear characteristic between the displacement and tire inflation pressure. When the insert is involved in the load bearing, the radial stiffness of the tire significantly increases. In the process of pressure relief, the maximum contact pressure of the tire extends from the center of the contact impression to both ends. When the tire inflation pressure is reduced to 25·kPa, the central pressure of the tread gradually increases, and the phenomenon of tread warpage is improved, which enhances the distribution uniformity of the contact pressure in the pressure relief and zero-pressure conditions.

Functional availability studies of military vehicles in terms of operation intensity.

Keeping vehicles technically suitable is strictly dependent on the intensity and nature of the damage. Determining the factors influencing functional availability comes down to investigating the causes of vehicle damage. Studies and analysis of the results have confirmed that functional availability for military vehicles can be estimated, taking into account vehicle intensity and reliability. The intensity of use may be taken into account by appropriate selection of layer tests, classified by intensity of use and by observing changes in functional availability with an increase in the number of trips, reflecting the intensity of use. Studies have found that the intensity of use in the range of average intensity of use of military vehicles does not significantly differentiate the level of availability.

COVID catalyst: telemedicine in rheumatology protects patient care beyond just the pandemic

During January 2021, rheumatologic care in Washington DC was affected by both the peak of the COVID-19 pandemic in the United States as well as a deadly insurrection and attack on the US Capitol. As rheumatologists practicing a few blocks from the White House, the authors discuss the crucial role that telemedicine served in delivering healthcare to patients with rheumatic diseases during and after the attack on the US Capitol as threats of violence, physical barriers, military vehicles, and armed troops challenged traditional means of caring for patients. The authors also discuss the role for telemedicine in safely providing future healthcare delivery.

Next-generation NATO reference mobility model complex terramechanics – Part 1: Definition and literature review

The US army along with NATO member and partner nations’ militaries need an accurate software tool for predicting ground vehicle mobility (such as speed-made-good and fuel-consumption) on world-wide terrains where military vehicles may be required to operate. Currently, the NATO Reference Mobility Model (NRMM) is the only NATO recognized tool for assessing ground vehicle mobility. NRMM was developed from the 1960s to the 1980s and relies on steady-state empirical formulas which may not be accurate for new military ground vehicles. A NATO research task group (RTG-248) was established from 2016 to 2018 to develop the NG-NRMM (next-generation NRMM) software tool requirements and an NG-NRMM prototype which uses high-fidelity “simple” or “complex” terramechanics models for the terrain/soil along with modern 3D multibody dynamics software tools for modeling the vehicle. NG-NRMM Complex Terramechanics (CT) models are those that utilize full 3D soil models capable of predicting the 3D soil reaction forces on the vehicle surfaces (including tires, tracks, legs, and under body) and the 3D flow and deformation of the soil including both elastic and plastic deformation under any 3D loading condition. In Part 1 of this paper, an overview of the full spectrum of terramechanics models from the highest fidelity to the lowest fidelity is presented along with a literature review of CT ground vehicle mobility models.

Specimen-specific fracture risk curves of lumbar vertebrae under dynamic axial compression

Underbody blast attacks of military vehicles by improvised explosives have resulted in high incidence of lumbar spine fractures below the thorocolumbar junction in military combatants. Fracture risk curves related to vertical loading at individual lumbar spinal levels can be used to assess the protective ability of new injury mitigation equipment. The objectives of this study were to derive fracture risk curves for the lumbar spine under high rate compression and identify how specimen-specific attributes and lumbar spinal level may influence fracture risk. In this study, we tested a sample of three-vertebra specimens encompassing all spinal levels between T12 to S1 in high-rate axial compression. Each specimen was tested with a non-injurious load, followed by a compressive force sufficient to induce vertebral body fracture. During testing, bone fracture was identified using measurements from acoustic emission sensors and changes in load cell readings. Following testing, the fractures were assessed using computed tomographic (CT) imaging. The CT images showed isolated fractures of trabecular bone, or fractures involving both cortical and trabecular bone. Results from the compressive force measurements in conjunction with a survival analysis demonstrated that the compressive force corresponding to fracture increased inferiorly as a function of lumbar spinal level. The axial rigidity (EA) measured at the mid-plane of the centre vertebra or the volumetric bone mineral density (vBMD) of the vertebral body trabecular bone most greatly influenced fracture risk. By including these covariates in the fracture risk curves, no other variables significantly affected fracture risk, including the lumbar spinal level. The fracture risk curves presented in this study may be used to assess the risk of injury at individual lumbar vertebra when exposed to dynamic axial compression.

A Novel Pseudonym Assignment and Encryption Scheme for Preserving the Privacy of Military Vehicles

In this digital era, security has become one of the important topics of concern, and things become more critical for military vehicles where safety plays a vital role. In this paper, we have discussed a pseudonym-based approach that preserves the real identity of military vehicles. This paper also focuses on military vehicles’ location privacy by deploying a novel pseudonym assignment and encryption schemes. The proposed security scheme is based on a hybrid approach of matrix array symmetric key and the intelligent water drop scheme. After implementing the proposed security scheme, each military vehicle will obtain its pseudonym for hiding their original identities. The proposed algorithm effectively manages pseudonym generation and change requests for the local region and inter-region environment. The proposed security scheme not only provides secure communication and preservation of location privacy of military vehicles but also ensures their security against various attacks. Finally, the time efficiency of proposed algorithms is obtained for both local and inter-region requests. Comparative analysis shows that the proposed scheme is more efficient than other existing techniques.

Optimization of vehicle protection components based on reliability

In order to improve the bottom protection capability of military vehicles, a reliable optimization method was proposed for the design of vehicle protection components. In the traditional optimization process, if the uncertainty of design variables is not considered, the performance of design objectives will fluctuate or even fail. In this paper, multi-objective reliability optimization was introduced into the optimization of explosion protection. The surrogate model with the highest accuracy was constructed and chosen after the design variables were selected through experimental design and sensitivity analysis. The reliability optimization of the protection components was achieved by the multi-objective genetic algorithm. Eventually, through experiment and simulation verification, the optimized protective components met the requirements of protection and lightweight, and the reliability was improved, which can provide reference for the subsequent design and production of protective components.

A brief review of carbon nanotube reinforced metal matrix composites for aerospace and defense applications

The aerospace and defense industry's intense desire is to revamp the performance characteristics of space shuttle vehicles, military tanker vehicles by continuously driving the production of advanced materials with remarkable properties. Thus, the need for high strength and lower weight metals are increasing rapidly in these industries. In this view, many research works on composites have been proved, especially metal matrix composites (MMCs). Carbon nanotubes (CNTs) are rolled-up graphene sheets with superior mechanical, thermal, and electrical properties attracted by many researchers in fabrication with MMCs. Metal matrix composites are developed in making space shuttle components and jet engine parts due to their higher specific strength and wear resistance. Numerous experimental investigations were performed on CNT reinforced MMCs in the making of structural components in aerospace and military vehicles, but the challenge still exists in many factors such as the production of complex structural components with optimistic performance, poor scattering of CNT in MMCs due to the formation of agglomeration and to retain nanoscale properties in large fraction. The aim of this review is to discuss about the development of MMCs in aerospace and military applications, the importance of CNTs in the field of the aviation industry, challenges in aerospace and defense sectors, and highlighting the importance of various processing techniques adopted in the development of CNT reinforced MMCs.

Preface

International Conference “Actual Issues of Mechanical Engineering–2020” was successfully held at Admiral Makarov State University of Maritime and Inland Shipping (Saint-Petersburg, Russia) on 27-29 October, 2020. Because of the travel restrictions and to avoid public gathering, it was decided to hold the conference online. This gave participants from across Russia an opportunity to present their reports despite the lockdown. The geography of AIME–2020 includes the researchers from Moscow, Saint Petersburg, Ufa, Irkutsk, Nizhniy Novgorod, Rostov, Bryansk and other Russian cities.AIME–2020 became a scientific forum to discuss various issues of mechanical engineering, such as: automotive and locomotive engineering, farming machinery, water transport, special purpose civil and military vehicles. Researchers and practitioners presented their papers on construction equipment, reaction engines, power and heat generators, machinery manufacturing automation, and machinery lifecycle management. After careful reviewing, 80 papers were accepted for publication.Due to the complicated epidemiological situation and the travel restrictions applied by the Russian Government, the conference was held remotely. The work of the sections was organized in a video conference mode, where the most relevant reports selected by the organizing committee of the conference were presented using the Cisco Webex platform (https://www.webex.com/downloads.html). The traditional 15-minute time limit on speeches was preserved. The attendance for virtual participation without the report and without the opportunity to participate in discussion with the voice was free of charge. However, all participants could take their part in the discussion via moderators.List of Editorial Board, Programme Committee and Organizing committee are available in the pdf.

The Impact of the Accuracy of Terrain Surface Data on the Navigation of Off-Road Vehicles

Current soil and surface data are not detailed enough to obtain accurate analyses of cross-country movement. The reason for the research presented in this article was the absence of a methodology for the synthetic assessment of the influence of the terrain surface on the movement of military vehicles. The study is based on analyses of data and information sources of soils and surface conditions primarily with the aim to determine their reliability, availability and precision when used for analyses of terrain traversability by off-road vehicles. The key method to achieve the set objective is the employment of tractive charts of military vehicles and utilized coefficients, the coefficient of rolling resistance and the coefficient of adhesion. Input data and information is tested with a comparative method of cross-country movement analyses. Conversion of soil and surface types to tractive chart coefficients is currently not optimal. For the most part, evaluation of soil type is very inaccurate with a wide range of possible values. Results of the analysis propose developing a methodology of evaluating surface and soils for vehicle traversability.

Adaptive 3D Imaging for Moving Targets Based on a SIMO InISAR Imaging System in 0.2 THz Band

Terahertz (THz) imaging technology has received increased attention in recent years and has been widely applied, whereas the three-dimensional (3D) imaging for moving targets remains to be solved. In this paper, an adaptive 3D imaging scheme is proposed based on a single input and multi-output (SIMO) interferometric inverse synthetic aperture radar (InISAR) imaging system to achieve 3D images of moving targets in THz band. With a specially designed SIMO antenna array, the angular information of the targets can be determined using the phase response difference in different receiving channels, which then enables accurate tracking by adaptively adjusting the antenna beam direction. On the basis of stable tracking, the high-resolution imaging can be achieved. A combined motion compensation method is proposed to produce well-focused and coherent inverse synthetic aperture radar (ISAR) images from different channels, based on which the interferometric imaging is performed, thus forming the 3D imaging results. Lastly, proof-of-principle experiments were performed with a 0.2 THz SIMO imaging system, verifying the effectiveness of the proposed scheme. Non-cooperative moving targets were accurately tracked and the 3D images obtained clearly identify the targets. Moreover, the dynamic imaging results of the moving targets were achieved. The promising results demonstrate the superiority of the proposed scheme over the existing THz imaging systems in realizing 3D imaging for moving targets. The proposed scheme shows great potential in detecting and monitoring moving targets with non-cooperative movement, including unmanned military vehicles and space debris.

Radar HRRP Target Recognition Based on Dynamic Learning with Limited Training Data

For high-resolution range profile (HRRP)-based radar automatic target recognition (RATR), adequate training data are required to characterize a target signature effectively and get good recognition performance. However, collecting enough training data involving HRRP samples from each target orientation is hard. To tackle the HRRP-based RATR task with limited training data, a novel dynamic learning strategy is proposed based on the single-hidden layer feedforward network (SLFN) with an assistant classifier. In the offline training phase, the training data are used for pretraining the SLFN using a reduced kernel extreme learning machine (RKELM). In the online classification phase, the collected test data are first labeled by fusing the recognition results of the current SLFN and assistant classifier. Then the test samples with reliable pseudolabels are used as additional training data to update the parameters of SLFN with the online sequential RKELM (OS-RKELM). Moreover, to improve the accuracy of label estimation for test data, a novel semi-supervised learning method named constraint propagation-based label propagation (CPLP) was developed as an assistant classifier. The proposed method dynamically accumulates knowledge from training and test data through online learning, thereby reinforcing performance of the RATR system with limited training data. Experiments conducted on the simulated HRRP data from 10 civilian vehicles and real HRRP data from three military vehicles demonstrated the effectiveness of the proposed method when the training data are limited.

Sizing and Siting of Energy Storage Systems in a Military-Based Vehicle-to-Grid Microgrid

Due to the absence of utility power grid infrastructure in remote military bases, on-site diesel generators serve as the primary sources for power demands. Increasing efficiency and preventing frequent startup/shutdown operations of on-site diesel generators are therefore becoming a critical issue for reducing fuel cost. Application of vehicle-to-grid technology in a military-based microgrid embodies potential for significant fuel economy benefits since on-board vehicle generators and energy storage units can serve as mobile power sources that provide higher flexibility for supplying power demands. In addition, energy storage system integration is considered as an alternative solution for increasing on-site diesel generators efficiency and lessening their startup/shutdown operations. This article proposes a three-stage planning procedure for identifying the optimal locations and capacities of energy storage systems, considering multiple operating scenarios via stochastic programming. Note that on-site diesel generators and on-board vehicle generators support plug-and-play functionality, meaning their startup/shutdown operations can be decided in real time. Furthermore, network-constrained ac unit commitment model is used to optimize operation of microgrids. It is assumed that in the tested microgrid systems, several tactical military vehicles with on-board generators and energy storage units are deployed as alternative power sources. The economic merits of vehicle-to-grid implementation and energy storage system integration in a military-based microgrid are validated in the numerical studies.

Development of an empirical relation to assess soil spatial variability for off-road trafficability using terrain similarity analysis & geospatial data

ABSTRACT Soils trafficability is measure of soil strength required to support the manoeuvring of military vehicles. Trafficability can be measured with the tests performed using cone penetrometer and moisture metre to understand the complexity of phenomenon. Empirical relation can be developed through the outcomes of these tests. This empirical relation can be used in tandem with geospatial data to understand the heterogeneous soil behaviour and its impact on trafficability. Further, it will enhance the remote sensing data capability to assess the trafficability in inaccessible areas. In this study, a numerical approach is described in which geo-parameters like land use, soil, elevation and moisture are quantified using various data sources such as remote sensing and ground survey information. Terrain similarity analysis was performed to find analogous soil patches of homogenous nature. The aim of this paper is to outline a procedure, which will be useful for off-road trafficability studies. The current advancement in remote sensing technologies and ground survey from digital equipment was used to have better accuracy of results along with better understanding of utilization of geo-spatial data. It will pave the way to analyse the terrain suitability for off-road trafficability operation.