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Yield potential was predicted and mapped for three corn fields in Central Illinois, using digital aerial color infrared images. Three methods, namely statistical (regression) modeling, genetic algorithm optimization and artificial neural networks, were used for developing yield models. Two image resolutions of 3 and 6 m/pixel were used for modeling. All the models were trained using July 31 image and tested using images from July 2 and August 31, all from 1998. Among the three models, artificial neural networks gave best performance, with a prediction error less than 30%. The statistical model resulted in prediction errors in the range of 23 to 54%. The lower resolution images resulted in better prediction accuracy compared to resolutions higher than or equal to the yield resolution. Images after pollination resulted in better accuracy compared to images before pollination.

Data obtained when harvesting with a combine equipped with a yield monitor were used to develop yield maps. A prototype yield monitor was developed that uses a combination of light emitters and receivers mounted in a rectangular frame. The monitor was mounted in the combine in the top of the clean grain elevator. As grain flows through the monitor, a voltage change proportional to light reduction was recorded. This voltage was then correlated to grain flow rate. At the same time, site-specific location was recorded using the global positioning satellites (GPS) system. The location data, yield monitor output, cutting width, and combine forward speed were stored in a spreadsheet format. The data were then used to prepare the yield maps.

With COSMOsim, OTSL is looking to better virtually recreate diverse driving conditions to enable safe and accurate verifications at a point when autonomous driving continues to move toward practical use around the world.

To investigate the feasibility of various test procedures to determine aerodynamic performance for the Phase 2 Greenhouse Gas (GHG) Regulations for Heavy-Duty Vehicles in the United States, the US Environmental Protection Agency commissioned, through Southwest Research Institute, constant-speed torque tests of several heavy-duty tractors matched to a conventional 53-foot dry-van trailer. Torque was measured at the transmission output shaft and, for most tests, also on each of the drive wheels. Air speed was measured onboard the vehicle, and wind conditions were measured using a weather station placed along the road side. Tests were performed on a rural road in Texas. Measuring wind-averaged drag from on-road tests has historically been a challenge. By collecting data in various wind conditions at multiple speeds over multiple days, a regression-based method was developed to estimate wind-averaged drag with a low precision error for multiple tractor-trailer combinations.

Through this work, Wind River and Airbiquity look to enable secure and intelligent software updates and data management for these vehicles through over-the-air (OTA) programming technology. The work may also lead to similar solutions for traditional aerospace and unmanned aircraft system (UAS) industries.

September 17-19, 2019 │ Garden Grove, CA, USA

September 17-19, 2019 │ Garden Grove, CA, USA

This SAE standard presents the basic information required for the design and manufacture of a wheel chock.

The EU Commission's “Clean Power for Transport” initiative aims to break the EU's dependence on imported oil whilst promoting the use of alternative fuels to reduce greenhouse gas emissions. Among the options considered is the use of liquefied natural gas (LNG) as a substitute for diesel in long haul trucks. It is interesting to ask how the lifecycle greenhouse gas (GHG) emissions of LNG compare with conventional diesel fuel for this application. The LNG available in Europe is mainly imported. This paper considers the “well-to-tank” emissions of LNG from various production routes, including: gas production, treatment and liquefaction, shipping to Europe, terminal, distribution and refuelling operations. “Tank-to-Wheel” emissions are considered for a range of currently-available engine technologies of varying efficiency relative to diesel.

The environmental impact from herbicide utilization has been well documented in recent years. The reduction in weed control with out a viable alternative will likely result in decreased per acre production and thus higher unit production cost. The potential for selective herbicide application to reduce herbicide usage and yet maintain adequate weed control has generated significant interest in different forms of remote sensing of agricultural crops. This research evaluated the color co-occurrence texture analysis technique to determine its potential for utilization in crop groundcover identification. A program termed GCVIS (Ground Cover VISion) was developed to control an ATT TARGA 24 frame grabber; and generate HSI color features from the RGB format pixel data, HSI CCM matrices and the co-occurrence texture feature data.

The challenges of climate change and energy security require a continuous effort toward reduction of global environmental pollution and fossil oil consumption. To meet greenhouse gas (GHG) emission targets and to decrease oil dependency, overall energy consumption of vehicles must be substantially reduced.

Few previous publications investigate the possibility of combining multiple waste heat sources in a combustion engine waste heat recovery system. A waste heat recovery system for a HD truck diesel engine is evaluated for utilizing multiple heat sources found in a conventional HD diesel engine. In this type of engine more than 50% of heat energy goes futile. The majority of the heat energy is lost through engine exhaust and cooling devices such as EGRC (Exhaust gas recirculation cooler), CAC (Charge air cooler) and engine cooling. In this paper, the potential of usable heat recuperation from these devices using thermodynamic analysis was studied, and also an effort is made to recuperate most of the available heat energy that would otherwise be lost. A well-known way of recuperating this heat energy is by employing a Rankine cycle circuit with these devices as heat sources (single loop or dual loop), and thus this study is focused on using a Rankine cycle for the heat recovery system.

Nearly a third of the fuel energy is wasted through the exhaust of a vehicle. An efficient waste heat recovery process will undoubtedly lead to improved fuel efficiency and reduced greenhouse gas (GHG) emissions. Currently, there are multiple waste heat recovery technologies that are being investigated in the auto industry. One innovative waste heat recovery approach uses Thermoacoustic Converter (TAC) technology. Thermoacoustics is the field of physics related to the interaction of acoustic waves (sonic power) with heat flows. As in a heat engine, the TAC produces electric power where a temperature differential exists, which can be generated with engine exhaust (hot side) and coolant (cold side). Essentially, the TAC converts exhaust waste heat into electricity in two steps: 1) the exhaust waste heat is converted to acoustic energy (mechanical) and 2) the acoustic energy is converted to electrical energy.

The China Automotive Technology and Research Center Co., Ltd. (CATARC), TÜV SÜD Group, and Shanghai SH Intelligent Automotive and International Transportation Innovation Center (ITIC) have joined with SAE International to establish the International Alliance for Mobility Testing and Standardization (IAMTS).

Computer algorithms were developed for generating the guidance parameters necessary to steer an agricultural tractor. A variety of field operations were considered in order that the guidance program be suited for general applications including travel in curved rows and following a single edge. Testing of the guidance algorithm was performed in the laboratory using simulated and videotaped images of rowcrops and tilled soil. From the images, yaw angle change of the tractor, direction value and offset error were computed. Prediction of the direction value and offset error compared well to measured values. Accuracy of the direction value was within +/- 0.5 degrees while the offset error was within +/- 0.05 meters. Good performance was observed for straight and curved rows as well as following a single edge.

The existing instrumentation of a soil bin was retrofitted with virtual instrumentation techniques to achieve improved repeatability and more precise measurements. Current-loop sensors were added to the prime mover for improved speed control. Soil preparation operations were instrumented to determine penetrometer forces as a function of soil penetration depth, soil surface smoothness, compaction force, and soil surface elevation. Test hitch-points for agricultural implements were instrumented with wheatstone bridge force transducers. Implement depth was found with ratiometric linear transducers. Distance and speed determinations utilized an optical encoder with a resolution of 3.0 × 10-4 m. Temperature measurements were also recorded with solid state current transducers.

Vermeer concept targets autonomous baling

Three-dimensional models of real world terrain have application in a variety of tasks, but digitizing a large environment poses constraints on the design of a 3D scanning system. We have developed a Mobile Scanning System that works within these constraints to quickly digitize large-scale real world environments. We utilize a mobile platform to move our sensors past the scene to be digitized - fusing the data from cm-level accuracy laser range scanners, positioning and orientation instruments, and high-resolution video cameras - to provide the mobility and speed required to quickly and accurately model the target scene.

The SAE J1939 communications network is developed for use in heavy-duty environments and suitable for horizontally integrated vehicle industries. The SAE J1939 communications network is applicable for light-duty, medium-duty, and heavy-duty vehicles used on-road or off-road, and for appropriate stationary applications which use vehicle derived components (e.g., generator sets). Vehicles of interest include, but are not limited to, on-highway and off-highway trucks and their trailers, construction equipment, and agricultural equipment and implements. SAE J1939-71 Vehicle Application Layer is the SAE J1939 reference document for the conventions and notations that specify parameter placement in PGN data fields, the conventions for ASCII parameters, and conventions for PGN transmission rates. This document previously contained the majority of the SAE J1939 data parameters and messages for information exchange between the ECU applications connected to the SAE J1939 communications network.

The SAE J1939 communications network is developed for use in heavy-duty environments and suitable for horizontally integrated vehicle industries. The SAE J1939 communications network is applicable for light-duty, medium-duty, and heavy- duty vehicles used on-road or off-road, and for appropriate stationary applications which use vehicle derived components (e.g., generator sets). Vehicles of interest include, but are not limited to, on-highway and off-highway trucks and their trailers, construction equipment, and agricultural equipment and implements. SAE J1939-71 Vehicle Application Layer is the SAE J1939 reference document for the conventions and notations that specify parameter placement in PGN data fields, the conventions for ASCII parameters, and conventions for PGN transmission rates. This document previously contained the majority of the SAE J1939 data parameters and messages for information exchange between the ECU applications connected to the SAE J1939 communications network.