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Virtual reality is an emerging technology with the potential for many engineering applications including machinery simulation. In this paper the writers describe the hardware and software components of a virtual reality system that simulates machinery. They detail the flow of information that occurs in this system and discuss the functioning of an existing system at the National Center for Supercomputing Applications (NCSA) located at the University of Illinois at Urbana-Champaign. Finally, they describe potential uses of virtual reality in product design, manufacturing, training and marketing.

Camless actuation offers programmable flexibility in controlling engine valve events. However, a full range of engine benefits will only be available, if the actuation system can control lift profile characteristics within a particular lift event. Control of the peak value of valve lift is a first step in controlling the profile. The paper presents an adaptive feedback control of valve lift for a springless electrohydraulic valvetrain. The adaptive control maintains peak value of lift in presence of variations in engine speed, hydraulic fluid temperature and manufacturing variability of valve assemblies. The control design includes a reduced-order model of the system dynamics. Experimental results show dynamic behavior under various operating and environmental conditions and demonstrate advantages of adaptive control over the non-adaptive type.

The development of automated guidance for agricultural tractors has addressed several basic and applied issues of agricultural equipment automation. Basic analyses have included the dynamics of steering systems and posture sensors for guidance. Applied issues have evaluated the potential of several commercial sensing systems and a commercial mechanical guidance system. A research platform has been developed based on a Case 7220 Magnum1 2-wheel drive agricultural tractor. An electrohydraulic steering system was used and characterized in support of automated guidance control. Posture sensing methods were developed using GPS, geomagnetic direction sensors (GDS), inertial, and machine vision sensing systems. Sensor fusion of GPS-inertial-machine vision and GPS-GDS-machine vision provided the most flexible and accurate guidance and capable for operation under dynamically changing field conditions.

A dynamic model for the springless electrohydraulic valvetrain has been developed. The model speeds up the valvetrain development process by simulating effects of parameter changes, thus minimizing the number of hardware variations. It includes dynamic characteristics of check valves that enable energy recovery, hydraulic snubbers that limit seating velocity of the engine valves, and leakage in the control solenoids. A good match of the experimental data has been obtained for a single valve system, and the model calibration and validation have been completed. The known parameters are used together with some unknown calibration constants which have been tuned to match the experimental data. The simulation results for a twin valve system are also presented. The model applications for system performance analysis and for the closed-loop control of the engine valve lift are described. The cyclic variability of the experimental data is also discussed.

Neural networks are massively parallel computational models for knowledge representation and information processing. The capabilities of neural networks, namely learning, noise tolerance, adaptivity, and parallel structure make them good candidates for application to a wide range of engineering problems including diagnostics problems. The general approach in developing neural network based diagnostic methods is described through a case study. The development of an acoustic wayside train inspection system using neural networks is described. The study is aimed at developing a neural network based method for detection defective wheels from acoustic measurements. The actual signals recorded when a train passes a wayside station are used to develop a neural network based wheel defect detector and to study its performance. Signal averaging and scoring techniques are developed to improve the performance of the constructed neural inspection system.

This paper describes a ‘toolbox’ for modeling liquid cooling system networks within vehicle thermal management systems. Components which can be represented include pumps, coolant lines, control valves, heat sources and heat sinks, liquid-to-air and liquid-to-refrigerant heat exchangers, and expansion tanks. Network definition is accomplished through a graphical user interface, allowing system architecture to be easily modified. The elements of the toolbox are physically based, so that the models can be applied before hardware is procured. The component library was coded directly into MATLAB / SIMULINK and is intended for control system development, hardware-in-the-loop (HIL) simulation, and as a system emulator for on-board diagnostics and controls purposes. For HIL simulation and on-board diagnostics and controls, it is imperative that the model run in real-time.

A reconfigurable control system is an intelligent control system that detects faults within the system and adjusts its performance automatically to avoid mission failure, save lives, and reduce system maintenance costs. The concept was first successfully demonstrated by NASA between December 1989 and March 1990 on the F-15 flight control system (SRFCS), where software was integrated into the aircraft's digital flight control system to compensate for component loss by reconfiguring the remaining control loop. This was later adopted in the Boeing X-33. Other applications include modular robotics, reconfigurable computing structure, and reconfigurable helicopters. The motivation of this work is to test such control system designs for future long term space missions, more explicitly, the automation of life support systems.

Control system design is one of the most critical issues for implementation of intelligent vehicle systems. Wide ranged fundamental research has been undertaken in this area and the safety issues of the fully automated vehicles are clearly recognized. Study of vehicle performance constrains is essential for a good understanding of this problem. This paper discusses safety issues of heavy-duty vehicles under automatic steering control. It focuses on the analysis of the effect of tire force saturation. Vehicle handling characteristics are also analyzed to improve understanding of the truck dynamics and control tasks. A simple differential brake control is formulated to show its effect of on reducing trailer swing.

Aircraft incidents and accidents in icing are often the result of degradation in performance and control. However, current ice sensors measure the amount of ice and not the effect on performance and control. No processed aircraft performance degradation information is available to the pilot. In this paper research is reported on a system to estimate aircraft performance and control changes due to ice, then use this information to automatically operate ice protection systems, provide aircraft envelope protection and, if icing is severe, adapt the flight controls. Key to such a safety system would be he proper communication to, and coordination with, the flight crew. This paper reviews the basic system concept, as well as the research conducted in three critical areas; aerodynamics and flight mechanics, aircraft control and identification, and human factors.

Automotive software complexity has been growing rapidly with time. The demand for automation in automotive segment including autonomous automobiles and software based products has caught the attention of researchers. Hence, it is necessary to check the complexity of automotive software and their reliability growth. Testing in the field of software artifact is resource intensive exercise. If project managers are able to put forward testing activities well then the testing resource consumptions may be much more resource/cost efficient. Reliability can be estimated during testing phase of software using software reliability growth models (SRGMs). A software package Computer Aided Software Reliability Estimation (CASRE) has many important SRGMs. These SRGMs are based on Non-Homogeneous Poisson Process (NHPP), Markov process or Bayesian models.

This paper presents system identification methods of using both frequency and time domain analyses to estimate system parameters for a nonlinear electrohydraulic (E/H) tractor steering system. The frequency domain method identified parameters of the system using a linear model with a nonlinear gain function. The time domain method identified those parameters using a discrete time expression. A method of multiple models was used to represent the nonlinear system for both frequency and time domain analyses. Simulation and test results showed that the modified identification method could satisfactorily identify the parameters of the nonlinear E/H tractor steering system.

The US Army uses a light tactical High-Mobility Multi-Purpose Wheeled Vehicle (HMMWV) which, due to the amount of armor added, requires air conditioning to keep its occupants comfortable. The current system uses R134a in a dual evaporator, remote-mounted condenser, engine-driven compressor system. This vehicle has been adapted to use an environmentally friendly refrigerant (carbon dioxide) to provide performance, efficiency, comfort and logistical benefits to the Army. The unusual thermal heat management issues and the fact that the vehicle is required to operate under extreme ambient conditions have made the project extremely challenging. This paper is a continuation of work presented at the SAE Alternate Refrigerants Symposium held in Phoenix last June [1].