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The EcoCAR Challenge team at The Ohio State University has designed an extended-range electric vehicle capable of 50 miles all-electric range via a 22 kWh lithium-ion battery pack, with range extension and limited parallel operation supplied by a 1.8 L dedicated E85 engine. This vehicle is designed to drastically reduce fuel consumption, while meeting Tier II Bin 5 emissions standards. This vehicle design is implemented in a GM crossover utility vehicle as part of the EcoCAR Challenge. This paper explains the implementation of the vehicle's control strategy in order to maintain high efficiency and improve drivability. The vehicle control strategy employs both distinct operating modes and an Equivalent Consumption Minimization Strategy (ECMS) to find the most efficient operating point. The ECMS strategy does an online search for the most efficient torque split in order to meet the driver's command.

This paper describes a method to evaluate vehicle stability and controllability when the vehicle operates in the nonlinear range of lateral dynamics. The method is applied to open-loop steering maneuvers as well as closed-loop path-following maneuvers. Although path-following maneuvers are more representative of real world driving intent, they are usually considered inappropriate for objective assessment because of repeatability and accuracy issues. The automated test driver (ATD) can perform path-following maneuvers accurately and with good repeatability. This paper discusses the usefulness of application of the automated test drivers and path-following maneuvers. The dynamic mode of instability is not directly obtained from measurable outputs such as yawrate and lateral acceleration as in open-loop maneuvers. A few metrics are defined to quantify deviation from desired or ideal behavior in terms of observed “unexpected” lateral force and moment.

In crashes between heavy trucks and light vehicles, most of the fatalities are the occupants of the light vehicle. A reduction in heavy truck stopping distance should lead to a reduction in the number of crashes, the severity of crashes, and consequently the numbers of fatalities and injuries. This study made use of the National Advanced Driving Simulator (NADS). NADS is a full immersion driving simulator used to study driver behavior as well as driver-vehicle reactions and responses. The vehicle dynamics model of the existing heavy truck on NADS had been modified with the creation of two additional brake models. The first was a modified S-cam (larger drums and shoes) and the second was an air-actuated disc brake system. A sample of 108 CDL-licensed drivers was split evenly among the simulations using each of the three braking systems. The drivers were presented with four different emergency stopping situations.

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.

This paper discusses techniques for estimating steering feel performance measures for on-center and off-center driving. Weave tests at different speeds are used to get on-center performances for a 1994 Ford Taurus, a 1998 Chevrolet Malibu, and a 1997 Jeep Cherokee. New concepts analyzing weave tests are added, specifically, the difference of the upper and lower curves of the hysteresis and their relevance to driver load feel. For the 1997 Jeep Cherokee, additional tests were done to determine steering on-center transition properties, steering flick tests, and the transfer function of handwheel torque feel to handwheel steering input. This transfer function provides steering system stiffness in the frequency domain. The frequency domain analysis is found to be a unique approach for characterizing handwheel feel, in that it provides a steering feel up to maximum steering rate possible by the drivers.

This paper presents a real-time steering system torque feedback model used in the National Advanced Driving Simulator (NADS). The vehicle model is based on real-time recursive multi-body dynamics augmented with vehicle subsystems models including tires, power train, brakes, aerodynamics and steering. The steering system feel is of paramount importance for the fidelity of the simulator. The driver has to feel the appropriate torque as he/she steers the vehicle. This paper presents a detailed mathematical model of the steering physics from low-speed stick-slip to high-speed states. On-center steering weave handling and aggressive lane change inputs are used to validate the basic mathematical predictions. This validation is objective and open loop, and was done using field experiments.

Sixty test participants each drove an instrumented vehicle over a prescribed route that included highway and city street segments. Drivers included equal numbers of males and females, and equal numbers of individuals in Younger (18 to 25 years of age), Middle (35 to 45 years of age), and Older (55 to 65 years of age) age groups. Test participants drove on weekdays (Monday through Thursday), in good weather, and during both rush and non-rush hour morning or afternoon periods. Approximately 6,600 vehicle miles of travel on public roads were recorded. Car following range and range rate, travel speed, and driver eye glances were measured to examine driver eye glance behavior during car following. Results indicate the conditions in car following when drivers looked away from the road ahead, the distribution of glance durations when looking away, and the distribution of where drivers looked away from the road ahead.

To address the limitations of traditional data acquisition systems, The National Highway Traffic Safety Administration (NHTSA) has developed a system called the Micro Data Acquisition System (Micro-DAS). The system is very small and can be installed into a variety of vehicles in a short time period. It's video recording system is capable of collecting over 22 hours of full-motion video and data acquisition is triggered based on user created events. Using these features the system allows information on driver behavior and performance, vehicle performance, and roadway environments to be recorded in-situ, ensuring real world data collection without concerns associated with vehicle familiarity or researcher presence.

As Intelligent Transportation Systems (ITS) become more prevalent, the need to archive data from field tests becomes more critical. These data can guide the design of future systems, provide an information conduit among the many developers of ITS, enable comparisons across locations and time, and support development of theoretical models of driver behavior. The National Highway Traffic Safety Administration (NHTSA) is interested in such an archive. While a design for an ITS data archive has not yet been developed, NHTSA has supported the enhancement of the Test Planning, Analysis, and Evaluation System (Test PAES), originally developed by Calspan SRL Corporation for the U. S. Air Force Armstrong Laboratory, for possible use in such an archive. On a single screen, Test PAES enables engineering unit data, audio, and video, as well as a vehicle animation, to be time synchronized, displayed simultaneously, and operated with a single control.

A number of automotive diagnostic equipment and procedures have evolved over the last two decades, leading to two generations of on-board diagnostic requirements (OBDI and OBDII), increasing the number of components and systems to be monitored by the diagnostic tools. The goal of On-Board Diagnostic is to alert the driver to the presence of a malfunction of the emission control system, and to identify the location of the problem in order to assist mechanics in properly performing repairs. The aim of this paper is to suggest a methodology for the development of an Integrated Powertrain Diagnostic System (EPDS) that can combine the information supplied by conventional tailpipe inspection programs with onboard diagnostics to provide fast and reliable diagnosis of malfunctions.

The state of Ohio has recognized the importance and potential impact of Intelligent Vehicle-Highway Systems (IVHS) to its citizens and business enterprises. In response to the identified need, a small group of individuals representing Federal and state government, academia, and the private sector have worked together over the past year to initiate a statewide IVHS effort. This initiative is referred to as IVHS~Ohio. The objective of the effort is to "coordinate and foster a public, private, and academic partnership to make the urban and rural surface transportation system in the state of Ohio significantly safer, more effective, and more efficient by accelerating the identification, development, integration, and deployment of IVHS technologies." A May 1993 symposium was attended by over 220 people from government, academia, and the private sector. The result was a unanimous decision to establish a statewide IVHS program.

The objective of this paper is to develop a self-tuning optimal control of an active suspension. An active suspension composed of an identifier and a controller is proposed in this paper. Although control strategies on active (or semi-active) suspensions have been investigated during the past few decades, some problems are not well understood yet. One of them arising from the ride control of an active suspension is that when the weight and the moments of inertia of the sprung mass are varied, the feedback gains of the controller should vary with the variation of parameters accordingly. Therefore, the identifier is proposed before the controller is designed. In the real situations, the parameter variation may occur when loadings on vehicles vary - either from passengers or payloads, especially, in the case of loading on a truck. An identification structure using parallel model reference adaptive system (MRAS) is proposed to identify the true parameters.