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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.

Machine operators rely on intuition and experience to evaluate vehicle performance. As we increasingly turn to automation, it is important to automatically evaluate sensor data and system performance. Fuzzy logic allows us to take advantage of domain knowledge to evaluate data and to describe a system linguistically. In this paper, two automated fuzzy evaluation systems are described. In the first, a fuzzy quality module evaluates output from a simulated noisy sensor. In the second system, a fuzzy quality module evaluates the output from a machine vision system. Results from both systems indicate that fuzzy logic was able to accurately categorize the output in support of machinery decision making for automated control.

This paper describes a practical and efficient approach for determining complete transient, as well as steady state response of tractor-trailer air brake systems by recording pushrod displacement and air brake service line pressure as a function to time. The test hardware utilizes easy to fabricate “clip on” transducers to measure pushrod stroke length. Data acquisition is via LABVIEW‚. All transducers are easy to temporarily affix to any tractor- trailer and require no alteration to the vehicle. A complete system check takes less time than manually measuring pushrod stroke as required under FMCSA. This system with one treadle application and release gives digital timing and displacement history of all brakes. Useful information includes: application and release profiles (pushrod velocity), shoe compliance upon seating and crack pressure release points for both tractor and trailer relay valves.

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 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.

Site-Specific Crop Management (SSCM) involves use of automated seeders and chemical applicators to make spatially-variable applications to agricultural fields. Soil productivity is spatially variable and thus, SSCM provides an opportunity to reduce total applications of seed and fertilizer without reducing crop yields. Also, more complete crop use of fertilizers with SSCM could reduce the potential for environmental contamination. A key element in SSCM is a Field Information System (FIS) for preparing application maps to control application rates.

This paper describes and discusses a computer model that can be used to predict the hydraulic pump requirements of an excavator necessary to meet the specified productivity levels for a given set of design conditions. The model predicts the hydraulic cylinder flow rates, pressures, and power necessary to sustain a given work cycle. The study compares the results from a simulation of the excavator with actual test data obtained from a test vehicle taken during a typical work cycle.

A normally aspirated, four-stroke diesel engine was tested under operation with two alcohol containing fuel blends. The fuels contained ethanol, butanol, heavy virgin distillate, diesel Nos. 2 and 4, and a cetane improver. The proportions of the components were selected to give blends with properties within the range of diesel No. 2. The final blends contained 25 and 43.7 percent alchohols. Test results showed a loss in power due to the reduced heating value of the blends, and some deterioration of performance at light loads. At intermediate to heavy loads, satisfactory performance was obtained.