Search Results

An existing tire model was investigated for additional normal load-dependent characteristics to improve the large truck simulations developed by the National Highway Traffic Safety Administration (NHTSA) for the National Advanced Driving Simulator (NADS). Of the existing tire model coefficients, plysteer, lateral friction decay, aligning torque stiffness and normalized longitudinal stiffness were investigated. The findings of the investigation led to improvements in the tire model. The improved model was then applied to TruckSim to compare with the TruckSim table lookup tire model and test data. Additionally, speed-dependent properties for the NADS tire model were investigated (using data from a light truck tire).

The single-parameter, in-process monitor and automatic control systems for the resistance spot welding process have been studied by many investigators. Some of these have already been commercialized and used by sheet metal fabricators. These control systems operate primarily on one of the three process parameters: maximum voltage or voltage drop, dynamic resistance, or thermal expansion between electrodes during nugget formation. Control systems based on voltage or dynamic resistance have been successfully implemented for industrial applications. A great amount of experience on these two control methods has been accumulated through trial-and-error approaches. The expansion-based control system is not commonly utilized due to lack of experience and understanding of the process. Since the expansion displacement between electrodes during welding responds directly to the weld nugget formation, this control parameter provides a better means to produce more precise spot welds.

Conductive heat resistance seam welding (CHRSEW) is a new process developed at Edison Welding Institute for creating butt joints on aluminum sheet. The process uses conventional resistance seam welding equipment, and takes advantage of steel cover sheets on either side of the intended joint. Resulting joints are fusion in character, and can be manufactured at very high welding speeds (∼ 3 to 4 m/min). In this study, the conductive heat resistance seam welding process was extended to some new applications. These included joining a 7075-T6 alloy, and a dissimilar thickness 1- to 2-mm 5754 configuration. The former is generally considered unweldable by fusion methods, and is of considerable interest for aerospace applications. The latter is representative of a tailor welded blank for automotive applications. Resulting welds were evaluated using metallurgical examinations and mechanical testing.

Recent studies in sheet metal forming, conducted at universities world wide, emphasize the development of computer aided techniques for process simulation. To be practical and acceptable in a production environment, these codes must be easy to use and allow relatively quick solutions. Often, it is not necessary to make exact predictions but rather to establish the influence of process variables upon part quality, tool stresses, material flow, and material thickness variation. In cooperation with its industrial partners, the ERC for Net Shape Manufacturing of the Ohio State University has applied a number of computer codes for analysis and design of sheet metal forming operations. This paper gives a few selected examples taken from automotive applications and illustrates practical uses of computer simulations to improve productivity and reduce tool development and manufacturing costs.

This paper presents the details of the model for the physical steering system used on the National Advanced Driving Simulator. The system is basically a hardware-in-the-loop (steering feedback motor and controls) steering system coupled with the core vehicle dynamics of the simulator. The system's torque control uses cascaded position and velocity feedback and is controlled to provide steering feedback with variable stiffness and dynamic properties. The reference model, which calculates the desired value of the torque, is made of power steering torque, damping function torque, torque from tires, locking limit torque, and driver input torque. The model also provides a unique steering dead-band function that is important for on-center feel. A Simulink model of the hardware/software is presented and analysis of the simulator steering system is provided.

Automated driving has become a very promising research direction with many successful deployments and the potential to reduce car accidents caused by human error. Automated driving requires automated path planning and tracking with the ability to avoid collisions as its fundamental requirement. Thus, plenty of research has been performed to achieve safe and time efficient path planning and to develop reliable collision avoidance algorithms. This paper uses a data-driven approach to solve the abovementioned fundamental requirement. Consequently, the aim of this paper is to develop Deep Reinforcement Learning (DRL) training pipelines which train end-to-end automated driving agents by utilizing raw sensor data. The raw sensor data is obtained from the Carla autonomous vehicle simulation environment here. The proposed automated driving agent learns how to follow a pre-defined path with reasonable speed automatically.

The Buckeye Bullet set domestic as well as international speed records for electric vehicles in 2004. The next generation of land speed vehicle from Ohio State called the Buckeye Bullet 2 (henceforth the BB2) will again challenge and hopefully achieve several new speed records. The Buckeye Bullet suspension worked relatively well but was found to not be quite optimal for the vehicle. The purpose of the work outlined here was to develop a new front and rear suspension for the BB2 that would be an improvement over the suspension of the original Bullet. Previous to the start of this work part of the suspension had already been designed in the form of an upright/control arm setup. This paper works on taking the suspension to completion from this point of design. Work done includes developing the final design, determining suspension parameters, building an ADAMS model, and testing the ADAMS model.

Heavy trucks are involved in many accidents every year and Electronic Stability Control (ESC) is viewed as a means to help mitigate this problem. ESC systems are designed to reduce the incidence of single vehicle loss of control, which might lead to rollover or jackknife. As the working details and control strategies of commercially available ESC systems are proprietary, a generic model of an ESC system that mimics the basic logical functionality of commercial systems was developed. This paper deals with the study of the working of a commercial ESC system equipped on an actual tractor trailer vehicle. The particular ESC system found on the test vehicle contained both roll stability control (RSC) and yaw stability control (YSC) features. This work focused on the development of a reliable RSC software model, and the integration of it into a full vehicle simulation (TruckSim) of a heavy truck.

Resistance welding control systems utilizing secondary current feedback receive widespread utilization both in Europe and Japan. However, these types of control systems are only beginning to be used in any extended basis in this country. Currently, two variants of these systems are available; so called “self-teaching” systems, and “learning curve” systems. Either system has been shown to be capable of providing a stable secondary resistance welding current within two cycles. Recent work has indicated, however, that the self-teaching type control systems may be adversely affected by non-optimum set-up conditions, particularly poor fit-up and the introduction of organics (sealers or adhesives) at the faying surface. This work examines the performance of learning curve type constant current control systems under these adverse set-up conditions. Six conditions were selected for study; three degrees of progressively poorer fit-up, with and without an organic sealer.

Springback affects the dimensional accuracy and final shape of stamped parts. Accurate prediction of springback is necessary to design dies that produce the desired part geometry and tolerances. Springback occurs after stamping and ejection of the part because the state of the stresses and strains in the deformed material has changed. To accurately predict springback through finite element analysis, the material model should be well defined for accurate simulation and prediction of stresses and strains after unloading. Despite the development of several advanced material models that comprehensively describe the Bauschinger effect, transient behavior, permanent softening of the blank material, and unloading elastic modulus degradation, the prediction of springback is still not satisfactory for production parts. Dies are often recut several times, after the first tryouts, to compensate for springback and achieve the required part geometry.

Many automotive production plants are using various prepulse schedules for resistance spot welding thin gauge galvanized steel. The claimed reasons are that wider current range and longer electrode life are obtainable in comparison to the conventional schedule. However, data to support this are not available. The objective of this program was to determine the effect of prepulsation on spot weldability of galvanized steel. In this work, several prepulse resistance spot welding schedules were evaluated in two full factorial experiments. The effect of the number of prepulse cycles, the prepulse heat level and the effect of cool time were studied in detail. Weldability was evaluated using an electrode life test procedure in which the current range was periodically examined over the life of the electrodes. Generally, the results indicate that prepulsation has a negative effect on the resistance spot weldability of thin gauge galvanized steel.

This paper details the advancements and outcomes of the NEXTCAR (Next-Generation Energy Technologies for Connected and Automated on-Road Vehicles) program, an initiative led by the Advanced Research Projects Agency-Energy (ARPA-E). The program focusses on harnessing the full potential of Connected and Automated Vehicle (CAV) technologies to develop advanced vehicle dynamic and powertrain control technologies (VD&PT). These technologies have shown the capability to reduce energy consumption by 20% in conventional and hybrid electric cars and trucks at automation levels L1-L3 and by 30% L4 fully autonomous vehicles. Such reductions could lead to significant energy savings across the entire U.S. vehicle fleet.

Aluminum alloys are increasingly utilized in automotive body panels and crash components to reduce weight. Accurately assessing formability of the sheet metal can reduce design iteration and tooling tryouts to obtain the desired geometry in aluminum stampings. The current ISO forming limit curve (FLC) procedure is a position dependent technique which produces the FLC based on extrapolation at the crack location. As aluminum sheet metal use increases in manufacturing, accurate determination of the forming limits of this material will be necessary prior to production. New time dependent methods using digital imaging correlation (DIC) account for variations in material behavior by continuously collecting strain data through the material necking point. This allows more accurate FLC determination that is necessary for efficient design in the automotive stamping industry.

This paper describes the development of a more accurate shock absorber model in order to obtain better vehicle simulation results. Previous shock models used a single spline to represent shock force versus shock velocity curves. These models produced errors in vehicle simulations because the damper characteristics are better represented by the application of a hysteresis loop in the model. Thus, a new damper model that includes a hysteresis loop is developed using Matlab Simulink. The damper characteristics for the new model were extracted from measurements made on a shock dynamometer. The new model better represents experimental shock data. The new shock model is incorporated into two different lumped-parameter vehicle models: one is a three degree-of-freedom vehicle handling model and the other is a seven degree-of-freedom vehicle ride model. The new damper model is compared with the previous model for different shock mileages (different degrees of wear).

The EcoCAR 2: Plugging into the Future team at the Ohio State University is designing a Parallel-Series Plug-in Hybrid Electric Vehicle capable of 50 miles of all-electric range. The vehicle features a 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes. This is made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factor weighted fuel economy of 51 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report details the fabrication and control implementation process followed by the Ohio State team during Year 2 of the competition. The fabrication process includes finalizing designs based on identified requirements, building and assembling components, and performing extensive validation testing on the mechanical, electrical and control systems.

Process simulation for product and process design is currently being practiced in industry. However, a number of input variables have a significant effect on the accuracy and reliability of computer predictions. A study was conducted to evaluate the capability of finite element method (FEM) simulations for predicting part characteristics and process conditions in forming complex-shaped, industrial parts. In industrial applications, there are two objectives for conducting FEM simulations of the stamping process: (1) to optimize the product design by analyzing formability at the product design stage and (2) to reduce the tryout time and cost in process design by predicting the deformation process in advance during the die design stage. For each of these objectives, two kinds of FEM simulations are applied.

The fatigue performance of fillet-welded transverse attachments was compared for several procedure variants for both FCAW and SAW on ½ in. steel plates. Measurements of weld toe shape on adjacent pieces of weld indicated that smoother weld toes, as evidenced by larger weld toe radius, were correlated to improved fatigue performance for both processes. Fatigue tests conducted on 59 and 109 ksi yield strength plates did not show an effect of plate strength. Weld procedures designed to provide smooth toes, such as reduced parameter FCAW beads at horizontal weld toes and flat position FCAW at higher heat inputs, were shown to provide fatigue performances near post-weld improved fillets.

Laser welding has long been evaluated as a joining technique for galvanized steels in a lap-joint configuration in the automotive industry. However, a problem associated with the low boiling point of zinc limits the application of the laser process in a lap-joint configuration. Zinc-coatings at the interface of the two coated sheets vaporize during welding and the volume of the zinc vapor expands rapidly. The venting of the zinc vapor from the weld pool causes expulsion of the molten metal during welding and a portion of zinc vapor remains in the weld as porosity after welding. To improve the weld quality of galvanized steel, many efforts have been attempted worldwide, but limited success has been reported. Edison Welding Institute (EWI) investigated the laser weldability of galvanized steel in a lap-joint configuration with no gap using a dual beam laser welding technique.

Future SAE Level 4 and Level 5 autonomous vehicles will require novel applications of localization, perception, control and artificial intelligence technology in order to offer innovative and disruptive solutions to current mobility problems. This paper concentrates on low speed autonomous shuttles that are transitioning from being tested in limited traffic, dedicated routes to being deployed as SAE Level 4 automated driving vehicles in urban environments like college campuses and outdoor shopping centers within smart cities. The Ohio State University has designated a small segment in an underserved area of campus as an initial autonomous vehicle (AV) pilot test route for the deployment of low speed autonomous shuttles. This paper presents initial results of ongoing work on developing solutions to the localization and perception challenges of this planned pilot deployment.

The Ohio State University has fielded teams at all three of the DARPA Grand Challenge and DARPA Urban Challenge autonomous vehicle competitions, using three very different vehicle platforms. In this paper we present our experiences in these competitions, comparing and contrasting the different requirements, strategies, tasks, and vehicles developed for each challenge. We will discuss vehicle control and actuation, sensors, sensor interpretation, planning, behavior, and control generation. We will also discuss lessons learned from the engineering and implementation process for these three vehicles.