Stochastic Modeling in Multibody Dynamics: Aerodynamic Loads on Ground Vehicles

2010 ◽  
Vol 5 (3) ◽  
Author(s):  
Christian Wetzel ◽  
Carsten Proppe
Keyword(s):  
Probability Density Functions ◽  
Sensitivity Analyses ◽  
Ground Vehicles ◽  
Vehicle Model ◽  
Ground Vehicle ◽  
Aerodynamic Loads ◽  
Vehicle System ◽  
Surface Method ◽  
Vehicle Systems ◽  
Reliability Methods

The influence of wind loads on the driving behavior of ground vehicles is an important economical, safety, and comfort issue. The crosswind performance is of great interest, as violent lateral winds can cause major accidents or will at least make the driver and the passengers feel very uncomfortable and insecure. In this paper, a sampling based methodology for the analysis of stochastic ground vehicle systems is presented. Starting from the well known Monte Carlo method more sophisticated reliability methods with higher efficiency are introduced and their advantages and drawbacks are critically reviewed. Furthermore, probabilistic sensitivity analyses are presented, which can be used to quantify the importance of the random variables on the response of the vehicle system. The influence of the parameters of the probability density functions is investigated by means of a novel response surface method. The mentioned approach is applied to a nonlinear road vehicle model under strong crosswind excitation for which the failure probabilities and the sensitivities are computed.

Health and Usage Monitoring Algorithm Based on Terrain Identification for Mechanical Components on an Army Ground Vehicle System

2008 ◽  
Vol 51 (2) ◽  
pp. 31-41 ◽  
Author(s):  
Richard Heine ◽  
Donald Barker
Keyword(s):  
Unit Cost ◽  
Monitoring Systems ◽  
Statistical Parameters ◽  
Ground Vehicle ◽  
Wheeled Vehicle ◽  
Vehicle System ◽  
Basic Set ◽  
Vehicle Systems ◽  
Monitoring Algorithm

The desire for enhanced functionality of Army vehicle systems has resulted in increasingly complex systems. This drive is in direct contention with another Army goal of improved reliability. Health and usage monitoring systems (HUMS) and remaining-life prognostics are being developed to address these conflicting goals. One of the major challenges of applying a HUMS to an Army wheeled vehicle system is that the development and per unit cost of the HUMS needs to be relatively low in comparison with typical high-cost applications such as aircraft. Simplified algorithms that derive terrain exposure from a basic set of sensors and estimate fatigue damage accumulated on components where loading comes primarily from terrain have been developed to meet this need. Various inputs and statistical parameters are evaluated for this model based on accuracy of terrain identification and quality of fatigue prediction on an example component. The generalized process and recommendations for application of this model to military ground vehicle systems are discussed.

Function-Oriented Material Design for Next-Generation Ground Vehicles

2003 ◽  
Author(s):  
Zheng-Dong Ma ◽  
Hui Wang ◽  
Noboru Kikuchi ◽  
Christophe Pierre ◽  
Basavaraju Raju
Keyword(s):  
Cost Effective ◽  
Material Design ◽  
Optimization Process ◽  
Ground Vehicles ◽  
Ground Vehicle ◽  
Cost Constraints ◽  
Vehicle Systems ◽  
Optimal Material ◽  
Material Layout ◽  
Oriented Material

A systematic approach, referred to as function-oriented material design (FOMD), is presented in this paper, which can be used to design materials for the specific tasks demanded of structures in future ground vehicle systems. In order to carry out the FOMD process, first the functions of a structure in the vehicle system need to be explicitly defined in a systematic way. Then these functions must be quantified, so as to define the objective and constraint functions in the optimization process. Finally, an advanced optimization process needs to be carried out, and the material layout has to be finalized by the design engineer. Typically a number of constraints, such as manufacturing and cost constraints, need to be considered in the optimal material design process. A major objective of this research is to outline these constraints, as well as to find ways to ameliorate the optimization process to produce improved, cost-effective, and manufacturable engineered materials.

Real-Time Parameter Estimation Study for Inertia Properties of Ground Vehicles

2013 ◽  
Vol 60 (1) ◽  
pp. 7-21 ◽  
Author(s):  
Jeremy Kolansky ◽  
Corina Sandu
Keyword(s):  
Probability Density ◽  
Real Time ◽  
Adaptive Filtering ◽  
A Posteriori ◽  
Ground Vehicles ◽  
Vehicle Model ◽  
Time Step ◽  
Ground Vehicle ◽  
Generalized Polynomial ◽  
Inertia Properties

Vehicle parameters have a significant impact on handling, stability, and rollover propensity. This study demonstrates two methods that estimate the inertia values of a ground vehicle in real-time. Through the use of the Generalized Polynomial Chaos (gPC) technique for propagating the uncertainties, the uncertain vehicle model outputs a probability density function for each of the variables. These probability density functions (PDFs) can be used to estimate the values of the parameters through several statistical methods. The method used here is the Maximum A-Posteriori (MAP) estimate. The MAP estimate maximizes the distribution of P(β | z) where β is the vector of the PDFs of the parameters and z is the measurable sensor comparison. An alternative method is the application of an adaptive filtering method. The Kalman Filter is an example of an adaptive filter. This method, when blended with the gPC theory is capable at each time step of updating the PDFs of the parameter distributions. These PDF’s have their median values shifted by the filter to approximate the actual values.

Using Modeling and Simulation to Evaluate Traction of Track Vehicles

2000 ◽  
Author(s):  
David D. Gunter ◽  
Michael D. Letherwood
Keyword(s):  
Dynamic Performance ◽  
Vehicle Design ◽  
Ground Vehicles ◽  
Ground Vehicle ◽  
Us Army ◽  
3 Dimensional ◽  
Tractive Effort ◽  
The Us ◽  
Vehicle Systems ◽  
Time Required

Abstract The US Army Tank-automotive and Armaments Command (TACOM) has the mission of procuring and managing the US Army’s fleet of wheeled and tracked vehicles. TACOM’s Tank Automotive Research, Development and Engineering Center (TARDEC) provides engineering and scientific support directed at maximizing the capability of all Department of Defense (DOD) ground vehicle systems and ensuring the safety of their personnel. In order to reduce the time required to deploy troops and equipment, engineers and scientists at TARDEC have been investigating modifications to ground vehicles that lead to overall increases in performance, especially in the areas of off-road mobility, and on-road stability and handling. This paper describes an effort to assess the dynamic performance of a track laying (tracked) Recovery Vehicle towing a disabled tracked vehicle whose weight is approximately equal to that of the Recovery Vehicle. Specifically, this paper will describe techniques employed to develop a 3-dimensional dynamic model of the vehicle combination, and apply the model to evaluate towing performance of the recovery vehicle. It also describes measures aimed at minimizing incidences of jackknifing when braking on downhill slopes, as well as vehicle design modifications that were modeled and simulated in efforts to reduce the combination’s jackknife vulnerability. These modifications included tow bar schemes that locked-out inter-vehicle yaw, and external surge brakes mounted on the towed vehicle. Techniques used to model and simulate the tractive effort available to the Recovery Vehicle on varied soil types are described as are analyses used to determine the combination’s ability to climb grades. Vehicle modifications aimed at increasing the tractive effort available, such as tow bar pitch orientation and track shoe geometry changes are also described.

Applications of Artificial Neural Networks on Ground Vehicle Systems - Modeling and Diagnostics: A Literature Survey

2008 ◽  
Author(s):  
Ming Cao
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
System Modeling ◽  
Ground Vehicles ◽  
Dynamics Modeling ◽  
Ground Vehicle ◽  
Vehicle System ◽  
Powertrain System ◽  
Vehicle Rollover ◽  
Artificial Neural

This study reviews progresses on the application of Artificial Neural Networks (ANNs) in ground vehicle system modeling and diagnostics since 1997. Fundamentals of ANN-based system modeling are laid out, and utilized to frame the review. Areas covered in this research include modeling of vehicle components, prediction of vehicle dynamics, modeling of safety-related driver behaviors and prediction of vehicle rollover, as well as vehicle system prognostics. As this review shows, most applications addressed powertrain system and its components (includes engine, transmission parts such as friction components etc.). Besides characterizing different ANN modeling / prognostic techniques for ground vehicle applications, this study also points out future directions in this area, and serves as the foot step for the future applications of ANNs in ground vehicles.

A Methodology for the Test Design and Evaluation of Human Whole-Body Vibration in Ground Vehicle Systems

1989 ◽  
Vol 33 (18) ◽  
pp. 1192-1196
Author(s):  
Ellen C. Haas
Keyword(s):  
Whole Body Vibration ◽  
International Standards ◽  
Whole Body ◽  
Test Design ◽  
Exposure Limits ◽  
Ground Vehicle ◽  
Body Vibration ◽  
Exposure Limit ◽  
Vehicle Systems ◽  
Iso 2631

To date, testing and evaluation of whole-body vibration in ground vehicle systems have not always fully utilized appropriate experimental design methodology, applicable statistical tests, or relevant criteria. A test design and evaluation methodology was developed to eliminate these oversights. This methodology uses inferential statistics, questionnaires, and a comparison of vibration data with representative mission scenarios. The methodology was employed in the evaluation of two alternative tracked ground vehicle designs. The independent variables were track type, terrain, vehicle speed, and crew position. The dependent variables were International Standards Organization (ISO) 2631 whole-body vibration exposure limit times at the lateral, transverse, and vertical axes. Two different multivariate analyses of variance (MANOVAs) performed on the exposure limit data indicated that all main effects, as well as several interactions, were significant (p < .01). A comparison of exposure limits to a representative mission scenario indicated that both track types would exceed ISO 2631 exposure, comfort, and fatigue limits during expected travel over cross-country terrain. Crew questionnaires also indicated crew discomfort when exposed to this type of terrain. The experiment demonstrated that the procedure was useful in helping to determine the extent that vehicle vibration permits the performance of the vehicle mission, within limits dictated by safety, efficiency, and comfort.

A Perception-Based Fuzzy Route Planing Algorithm for Autonomous Unmanned Ground Vehicles

2018 ◽  
Vol 06 (04) ◽  
pp. 251-266
Author(s):  
Phillip J. Durst ◽  
Christopher T. Goodin ◽  
Cindy L. Bethel ◽  
Derek T. Anderson ◽  
Daniel W. Carruth ◽  
...  
Keyword(s):  
Path Planning ◽  
Urban Area ◽  
Route Planning ◽  
Unmanned Ground Vehicles ◽  
Membership Functions ◽  
Ground Vehicles ◽  
Ground Vehicle ◽  
Sensor Error ◽  
Planning Algorithm ◽  
Error Costs

Path planning plays an integral role in mission planning for ground vehicle operations in urban areas. Determining the optimum path through an urban area is a well-understood problem for traditional ground vehicles; however, in the case of autonomous unmanned ground vehicles (UGVs), additional factors must be considered. For an autonomous UGV, perception algorithms rather than platform mobility will be the limiting factor in operational capabilities. For this study, perception was incorporated into the path planning process by associating sensor error costs with traveling through nodes within an urban road network. Three common perception sensors were used for this study: GPS, LIDAR, and IMU. Multiple set aggregation operators were used to blend the sensor error costs into a single cost, and the effects of choice of aggregation operator on the chosen path were observed. To provide a robust path planning ability, a fuzzy route planning algorithm was developed using membership functions and fuzzy rules to allow for qualitative route planning in the case of generalized UGV performance. The fuzzy membership functions were then applied to several paths through the urban area to determine what sensors were optimized in each path to provide a measure of the UGV’s performance capabilities. The research presented in this paper shows the impacts that sensing/perception has on ground vehicle route planning by demonstrating a fuzzy route planning algorithm constructed by using a robust rule set that quantifies these impacts.

Effect of Rear Wing on Time-Averaged Ground Vehicle Wake With Variable Slant Angle

2021 ◽  
Vol 143 (7) ◽  
Author(s):  
Md. Shehab Uddin ◽  
Fazlur Rashid
Keyword(s):  
Separation Bubble ◽  
Flow Property ◽  
Navier Stokes ◽  
Ground Vehicles ◽  
Slant Angle ◽  
Ground Vehicle ◽  
Rear Wing ◽  
Horseshoe Vortices ◽  
And Control ◽  
Ahmed Body

Abstract The slant angle plays a crucial role in the flow property of hatchback ground vehicles. An optimum slant angle is obligatory for better handling the ground vehicles when fitted with a rear wing. In this regard, the variation of time-averaged flow properties around a wing-attached hatchback ground vehicle (Ahmed body) due to a variable slant angle is accessed by this paper. The design includes a scaled Ahmed body as a reference ground vehicle and a rear wing with NACA 0018 profile. The computational studies are executed with Reynolds-averaged Navier–Stokes based k-epsilon turbulence model with nonequilibrium wall function. The vehicle's model is scaled to 75% of the actual model, and analyses are conducted with Reynolds number 2.7 × 106. After the study, it is observed that a 15 deg slant angle is the critical angle for the wing attached state in which the drag coefficient is maximum. After this angle, a sudden reduction of coefficients is observed, where 25 deg is critical for without wing condition. Besides this, the two counter-rotating horseshoe vortices in the separation bubble and side edge c-pillar vortices also behave differently due to the wing's presence. The turbulent kinetic energy variation and the variation in coefficients of surface pressure are also affected by the rear wing attachment. This paper will assist in finding the optimum slant angle for hatchback ground vehicles in the presence of a rear wing. Thus the study will help in increasing stability and control for hatchback ground vehicles.

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