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Deformation Resistance Welding (DRW) is a process that employs resistance heating to raise the temperature of the materials being welded to the appropriate forging range, followed by shear deformation which increases the contacting surface area of the materials being welded. Because DRW is a new process, it became desirable to establish variable selection strategies which can be integrated into a production procedure. A factorial design of experiment was used to examine the influence of force, number of pulses, and weld cycles (heating/cooling time ratio) on the DRW process. Welded samples were tensile tested to determine their strength. Once tensile testing was complete, the resulting strengths were observed and compared to corresponding percent heat and percent reduction in thickness. Tensile strengths ranged from 107 kN to 22.2 kN. A relationship between the maximum current and the weld variables was established.

Most of the prior work on active mounting systems has been conducted in the context of a single degree-of-freedom even though the vehicle powertrain is a six degree-of-freedom isolation system. We seek to overcome this deficiency by proposing a new six degree-of-freedom analytical model of the powertrain system with a combination of active and passive mounts. All stiffness and damping elements contain spectrally-varying properties and we examine powertrain motions when excited by an oscillating torque. Two methods are developed that describe the mount elements via a transfer function (in Laplace domain). New analytical formulations are verified by comparing the frequency responses with numerical results obtained by the direct inversion method (based on Voigt type mount model). Eigensolutions of a spectrally varying mounting system are also predicted by new models.

Modern passenger cars are being equipped with advanced driver assistance systems such as lane departure warning, collision avoidance systems, adaptive cruise control, etc. Testing for operation and effectiveness of these warning systems involves interaction between vehicles. While dealing with multiple moving vehicles, obtaining discriminatory results is difficult due to the difficulty in minimizing variations in vehicle separation and other parameters. This paper describes test strategies involving an automated test driver interacting with another moving vehicle. The autonomous vehicle controls its state (including position and speed) with respect to the target vehicle. Choreographed maneuvers such as chasing and overtaking can be performed with high accuracy and repeatability that even professional drivers have difficulty achieving. The system is also demonstrated to be usable in crash testing.

Following many accidents, one of the involved vehicles is found with partial or total separation of one of its wheels. In many such cases, forensic evidence on the wheel, and/or on some surface struck by the wheel, provide direct evidence that the wheel separation resulted from the impact. However, in some cases such direct evidence is not as obvious or cannot be identified. In those cases, it is often asserted that before the accident occurred one of the involved vehicles might have undergone a sudden loss of control as a result of a spontaneous partial or total wheel separation. This paper examines the response of rear wheel drive vehicles when there is a failure involving a ball joint on the front suspension as the vehicle is traveling along a roadway. The design of the front suspension is analyzed to determine the expected effects of such failure on the wheel geometry and on the interaction between the tires and the pavement.

This paper discusses the development of the 1997 Jeep Cherokee model for the National Advanced Driving Simulator's planned vehicle dynamics software, NADSdyna. Recursive rigid body formalism called the Real Time Recursive Dynamics (RTRD) developed by the University of Iowa is used to model the front and rear suspension mechanisms. To complement vehicle dynamics for simulator applications, subsystems that include tires, aerodynamics, powertrain, brake, and steering are added to the rigid body dynamics model. These models provide high fidelity driving realism to simulate severe handling maneuvers in real time. The soundness of the model does not only depend on the mathematics of the model, but also on the validity of the parameters. Therefore, this paper discusses thoroughly the methodology of parameters estimation. A generic model of cruise control is included.

The paper discusses the development of a vehicle dynamics model and model validation of the 2003 Ford Expedition in CarSim. The accuracy of results obtained from simulations depends on the realism of the model which in turn depends on the measured data used to define the model parameters. The paper describes the tests used to measure the vehicle data and also gives a detailed account of the methodology used to determine parameters for the CarSim Ford Expedition model. The vehicle model was validated by comparing simulation results with experimental testing. Bounce and Roll tests in CarSim were used to validate the suspension and steering kinematics and compliances. Field test data of the Sine with Dwell maneuver was used for the vehicle model validation. The paper also discusses the development of a functional electronic stability control system and its effect on vehicle handling response in the Sine with Dwell maneuver.

The paper discusses the development of a model of the 2003 Ford Expedition using ADAMS View and its validation with experimental data. The front and rear suspensions are independent double A-arm type suspensions modeled using rigid links and ideal joints. The suspension springs and shock absorbers are modeled as force elements. The plots comparing the experimental tests and the simulation results are shown in this paper. Quasi-static roll and bounce tests are used to validate the suspension characteristics of the model while the Sine with Dwell and Slowly Increasing Steer maneuvers are used to validate the vehicle handling and tire-road interaction characteristics of the model. This paper also details the incorporation of an ESC model, originally developed by Kinjawadekar et al. [2] for CarSim, with the ADAMS model. The ESC is modeled in Simulink and co-simulated with the ADAMS vehicle model. Plots validating the ESC model with experimental data are also included.

This research focused on developing a methodology for a vehicle dynamics model of a passenger vehicle outfitted with an aftermarket Automated Driving System software package using only literature and track based results. This package consisted of Autoware.AI (Autoware ®) operating on Robot Operating System 1 (ROS™) with C++ and Python ®. Initial focus was understanding the basics of ROS and how to implement test scenarios in Python to characterize the control systems and dynamics of the vehicle. As understanding of the system continued to develop, test scenarios were adapted to better fit system characterization goals with identification of system configuration limits. Trends from on-track testing were identified and paired with first-order linear systems to simulate physical vehicle responses to given command inputs. Sub-models were developed and simulated in MATLAB ® with command inputs from on-track testing.

Typical factors that contribute to the coast down characteristics of a vehicle include aerodynamic drag, gravitational forces due to slope, pumping losses within the engine, frictional losses throughout the powertrain, and tire rolling resistance. When summed together, these reactions yield predictable deceleration values that can be related to vehicle speeds. This paper focuses on vehicle decelerations while coasting with a typical medium-sized SUV. Drag factors can be classified into two categories: (1) those that are caused by environmental factors (wind and slope) and (2) those that are caused by the vehicle (powertrain losses, rolling resistance, and drag into stationary air). The purpose of this paper is to provide data that will help engineers understand and model vehicle response after loss of engine power.

The severity of an impact in terms of the acceleration in the occupant compartment is dependent not only on the change in vehicle velocity, but also the time for the change in velocity to occur. These depend on the geometry and stiffness of both the striking vehicle and struck object. In narrow-object frontal impacts, impact location can affect the shape and duration of the acceleration pulse that reaches the occupant compartment. In this paper, the frontal impact response of a full-sized pickup to 10 mile per hour and 20 mile per hour pole impacts at the centerline and at a location nearer the frame rails is compared using the acceleration pulse shape, the average acceleration in the occupant compartment, and the residual crush. A bilinear curve relating impact speed to residual crush is developed.

The tractor trailer models discussed in this paper were for a real-time hardware-in-the-loop (HIL) simulation to test heavy truck electronic stability control (ESC) systems [1]. The accuracy of the simulation results relies on the fidelity and accuracy of the vehicle parameters used. However in this case where hardware components are part of the simulation, their accuracy also affects the proper working of the simulation and ESC unit. Hence both the software and hardware components have to be validated. The validation process discussed in this paper is divided into two sections. The first section deals with the validation of the TruckSim vehicle model, where experimental data is compared with simulation results from TruckSim. Once the vehicle models are validated, they are incorporated in the HIL simulation and the second section discusses the validation of the whole HIL system with ESC.

The aim of this paper is to describe a unified approach to modeling the energy efficiency and power flow characteristics of energy storage and energy conversion elements used in hybrid vehicles. Hybrid vehicle analysis and design is concerned with the storage of energy in three domains - chemical, mechanical, and electrical - and on energy conversions between these domains. The paper presents the physical and mathematical basis of this modeling approach, as well as a modular simulator that embodies the same basic principles. The use of the simulator as an analysis tool is demonstrated through the conceptual design of a sport-utility hybrid drivetrain.

Autonomous vehicle technology has been developing rapidly in recent years. Vehicle parametric uncertainty in the vehicle model, variable time delays in the CAN bus based sensor and actuator command interfaces, changes in vehicle sped, sensitivity to external disturbances like side wind and changes in road friction coefficient are factors that affect autonomous driving systems like they have affected ADAS and active safety systems in the past. This paper presents a robust control architecture for automated driving systems for handling the abovementioned problems. A path tracking control system is chosen as the proof-of-concept demonstration application in this paper. A disturbance observer (DOB) is embedded within the steering to path error automated driving loop to handle uncertain parameters such as vehicle mass, vehicle velocities and road friction coefficient and to reject yaw moment disturbances.

Typically, the combustion analysis for S.I. engines is limited to the determination of the apparent heat release from in-cylinder pressure measurements, effectively using a single zone approach with constant properties determined at some average temperature. In this paper, we follow an approach consistent with the engine modeling approach (i.e., reverse modeling) to extract heat release rate from combustion pressure data. The experimental data used here solely consists of quantities measured in a typical engine dynamometer tests, namely the crank-angle resolved cylinder pressure, as well as global measurements of the A/F ratio, engine speed, load, EGR, air mass flow rate and temperature and exhaust emissions. We then perform a two-zone, crank-angle resolved analysis of the pressure data using variable composition and properties.

A laboratory experiment is designed to examine the clunk phenomenon. A static torque is applied to a driveline system via the mass of an overhanging torsion bar and electromagnet. Then an applied load may be varied via attached mass and released to simulate the step down (tip-out) response of the system. Shaft torques and torsional and translational accelerations are recorded at pre-defined locations. The static torque closes up the driveline clearances in the pinion/ring (crown wheel) mesh. With release of the applied load the driveline undergoes transient vibration. Further, the ratio of preload to static load is adjusted to lead to either no-impact or impact events. Test A provides a ‘linear’ result where the contact stiffness does not pass into clearance. This test is used for confirming transient response and studying friction and damping. Test B is for mass release with sufficient applied torque to pass into clearance, allowing the study of the clunk.

The 2nd Automotive CFD Prediction workshop (AutoCFD2) was organized to improve the state-of-the-art in automotive aerodynamic prediction. It is the mission of the workshop organizing committee to drive the development and validation of enhanced CFD methods by establishing publicly available standard test cases for which high quality on- and off-body wind tunnel test data is available. This paper reports on the AutoCFD2 workshop for the Ford DrivAer test case. Since its introduction, the DrivAer quickly became the quasi-standard for CFD method development and correlation. The Ford DrivAer has been chosen due to the proven, high-quality experimental data available, which includes integral aerodynamic forces, 209 surface pressures, 11 velocity profiles and 4 flow field planes. For the workshop, the notchback version of the DrivAer in a closed cooling, static floor test condition has been selected.

The Ohio State University Center for Intelligent Transportation Research (CITR) has developed three automated vehicles demonstrating advanced cruise control, automated steering control for lane keeping, and autonomous behavior including automated stopping and lane changes in reaction to other vehicles. Various sensors were used, including a radar reflective stripe system and a vision based system for lane position sensing, a radar system and a scanning laser rangefinding system for the detection of objects ahead of the vehicle, and various supporting sensors including side looking radars and an angular rate gyroscope. These vehicles were demonstrated at the National Automated Highway System Consortium (NAHSC) 1997 Technical Feasibility Demonstration in a scenario involving mixed autonomous and manually driven vehicles. This paper describes the demonstration, the vehicle sensing, control, and computational hardware, and the vehicle control software.

This research was performed using a designed experiment to evaluate the loss of dry surface braking performance and stability that could be associated with the disablement of specific brake positions on a tractor-semitrailer. The experiment was intended to supplement and update previous research by Heusser, Radlinski, Flick, and others. It also sought to establish reasonable limits for engineering estimates on stopping performance degradation attributable to partial or complete brake failure of individual S-cam air brakes on a class 8 truck. Stopping tests were conducted from 30 mph and 60 mph, with the combination loaded to GCW (80,000 lb.), half-payload, and with the flatbed semitrailer unladen. Both tractor and semitrailer were equipped with antilock brakes. Along with stopping distance, brake pressures, longitudinal acceleration, road wheel speed, and steering wheel position and effort were also recorded.

This paper discusses the improvement of a heavy truck anti-lock brake system (ABS) model currently used by the National Highway Traffic Safety Administration (NHTSA) in conjunction with multibody vehicle dynamics software. Accurate modeling of this complex system is paramount in predicting real-world dynamics, and significant improvements in model accuracy are now possible due to recent access to ABS system data during on-track experimental testing. This paper focuses on improving an existing ABS model to accurately simulate braking under limit braking maneuvers on high and low-coefficient surfaces. To accomplish this, an ABS controller model with slip ratio and wheel acceleration thresholds was developed to handle these scenarios. The model was verified through testing of a Class VIII 6×4 straight truck. The Simulink brake system and ABS model both run simultaneously with TruckSim, with the initialization and results being acquired through Matlab.

This paper describes the mechanical design of a Suspension Parameter Identification Device and Evaluation Rig (SPIDER) for wheeled military vehicles. This is a facility used to measure quasi-static suspension and steering system properties as well as tire vertical static stiffness. The machine operates by holding the vehicle body nominally fixed while hydraulic cylinders move an “axle frame” in bounce or roll under each axle being tested. The axle frame holds wheel pads (representing the ground plane) for each wheel. Specific design considerations are presented on the wheel pads and the measurement system used to measure wheel center motion. The constraints on the axle frames are in the form of a simple mechanism that allows roll and bounce motion while constraining all other motions. An overview of the design is presented along with typical results.