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This paper presents a feedback linearization control technique as applied to a Roll Simulator. The purpose of the Roll Simulator is to reproduce in-field rollovers of ROVs and study occupant kinematics in a laboratory setting. For a system with known parameters, non-linear dynamics and trajectories, the feedback linearization algorithm cancels out the non-linearities such that the closed-loop dynamics behave in a linear fashion. The control inputs are computed values that are needed to attain certain desired motions. The computed values are a form of inverse dynamics or feed-forward calculation. With increasing system eigenvalue, the controller exhibits greater response time. This, however, puts a greater demand on the translational actuator. The controller also demonstrates that it is able to compensate for and reject a disturbance in force level.

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.

The main objective of this paper is to simulate the springback using combined kinematic/isotropic hardening model. Material parameters in the hardening model are identified by an inverse method. Three-point bending test is conducted on 6022-T4 aluminum sheet. Punch stroke, punch load, bending strain and bending angle are measured directly during the tests. Bending moments are then computed from these measured data. Bending moments are also calculated based on a constitutive model. Material parameters are identified by minimizing the normalized error between two bending moments. Micro genetic algorithm is used in the optimization procedure. Stress-strain curves is generated with the material parameters found in this way, which can be used with other plastic models. ABAQUS/Standard 5.8, which has the combined isotropic/kinematic hardening model, is used to simulate draw-bend of 6022-T4 series aluminum sheet. Absolute springback angles are predicted very accurately.

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.

A technique has been developed to study the effects of the vehicle interior on the performance of child safety seats. Child safety seat sled tests are used to define the kinematics of the seat and child in a crash situation. Computer animation of this motion is superimposed on the motion of the actual vehicle crash tests giving an estimation of the kinematics of the child and child seat in a real crash situation. The significance of the vehicle interior and the interference of the vehicle interior with the child's kinematics is presented within the computer animation. The analysis is conducted using a single child restraint device in multiple seating conditions within a single vehicle.

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.