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The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

A system was developed which provides nutrients and water to plants while maintaining good aeration at the roots and preventing water from escaping in reduced gravity. The nutrient solution is circulated through porous tubes under negative pressure and moves through the tube wall via capillary forces into the rooting matrix, establishing a non-saturated condition in the root zone. Tests using prototypes of the porous tube water and nutrient delivery system indicate that plant productivity in this system is equivalent to standard soil and solution culture growing procedures. The system has functioned successfully in short-term microgravity during parabolic flight tests and will be flown on the space shuttle. Plants are one of the components of a bioregenerative life support system required for long duration space missions.

Identifying edge cases for designed algorithms is critical for functional safety in autonomous driving deployment. In order to find the feasible boundary of designed algorithms, simulations are heavily used. However, simulations for autonomous driving validation are expensive due to the requirement of visual rendering, physical simulation, and AI agents. In this case, common sampling techniques, such as Monte Carlo Sampling, become computationally expensive due to their sample inefficiency. To improve sample efficiency and minimize the number of simulations, we propose a tailored active learning approach combining the Support Vector Machine (SVM) and the Gaussian Process Regressor (GPR). The SVM learns the feasible boundary iteratively with a new sampling point via active learning. Active Learning is achieved by using the information of the decision boundary of the current SVM and the uncertainty metric calculated by the GPR.

Farm workers experience a very high incidence of injuries leading to physical and cognitive (strokes, TBI) disabilities. Since 1991, the AgrAbility Project 2 and its staff have provided direct assistance and education to many U.S. farmers and farm workers. If farmers, ranchers or farm workers who become disabled continue to be employed in agriculture, often their agricultural operation must be modified and/or agricultural machinery must be modified or adaptive equipment purchased to meet their new needs. Some common tractor modifications include operator lifts, hand controls, added/modified steps and handrails, automated hitches, and custom seating. Some modifications are commercially available but others are done on an individual need basis. AgrAbility staff would welcome the opportunity to work closer with farm equipment manufacturers to create modifications that would make farming and ranching easier and safer for all.

We present an approach in which an open-source software infrastructure is used for testing the behavior of autonomous vehicles through computer simulation. This software infrastructure is called CAVE, from Connected Autonomous Vehicle Emulator. As a software platform that allows rapid, low-cost and risk-free testing of novel designs, methods and software components, CAVE accelerates and democratizes research and development activities in the field of autonomous navigation.

The adaptation to changes in human operator dynamics and changes in working environment dynamics can be an important issue in designing high performance telerobotic systems. This paper describes an approach to force control in telerobotic hand systems in which model reference adaptive control techniques are used to adapt to changes in human operator and working environment dynamics. The techniques have been applied to force-reflective control of a single degree-of-freedom telerobotic gripper system at Wisconsin Center for Space Automation and Robotics (WCSAR). This adaptive gripping system is described in the paper along with results of experiments with human subjects in which the performance of the adaptive system was analysed and compared to the performance of a conventional non-adaptive system. These experiments emphasized adaptation to changes in compliance of gripped objects and adaptation to the on-set of human operator fatigue.

Using a low-speed high-torque (LSHT) pump/motor to provide the speed range and torque for a hydrostatic automobile offers a number of advantages over using a high-speed low-torque pump/motor, combined with a gear reducer. However, there appear to be no LSHT units commercially available that have true variable displacement capability. Because of this void, a variable displacement pump/motor has been designed and built that could provide a direct drive for each wheel of a hydrostatic automobile. The unit uses some components such as the cylinder block, piston and modified rotating case from a commercially available radial piston pump/motor. Initial preliminary testing of the pump/motor indicates that it has good efficiency and performance characteristics, and, with further development should be very attractive for automotive use. This paper focuses on the design and kinematics of the device.

There is significant potential for connected and autonomous vehicles to impact vehicle efficiency, fuel economy, and emissions, especially for hybrid-electric vehicles. These improvements could have large-scale impact on oil consumption and air-quality if deployed in large Mobility-as-a-Service or ride-sharing fleets. As part of the US Department of Energy's current Advanced Vehicle Technology Competition (AVCT), EcoCAR: The Mobility Challenge, Mississippi State University’s EcoCAR Team is redesigning and doing the development work necessary to convert a conventional gasoline spark-ignited 2019 Chevy Blazer into a hybrid-electric vehicle with SAE Level 2 autonomy. The target consumer segments for this effort are the Mobility-as-a-Service fleet owners, operators and riders. To accomplish this conversion, the MSU team is implementing a P4 mild hybridization strategy that is expected to result in a 30% increase in fuel economy over the stock Blazer.

Combustion under stratified operating conditions in a direct-injection spark-ignition engine was investigated using simultaneous planar laser-induced fluorescence imaging of the fuel distribution (via 3-pentanone doped into the fuel) and the combustion products (via OH, which occurs naturally). The simultaneous images allow direct determination of the flame front location under highly stratified conditions where the flame, or product, location is not uniquely identified by the absence of fuel. The 3-pentanone images were quantified, and an edge detection algorithm was developed and applied to the OH data to identify the flame front position. The result was the compilation of local flame-front equivalence ratio probability density functions (PDFs) for engine operating conditions at 600 and 1200 rpm and engine loads varying from equivalence ratios of 0.89 to 0.32 with an unthrottled intake. Homogeneous conditions were used to verify the integrity of the method.

Transient operation of automobile engines is known to contribute significantly to regulated exhaust emissions, and is also an area of drivability concerns. Furthermore, many on-board diagnostic algorithms do not perform well during transient operation and are often temporarily disabled to avoid problems. The inability to quickly and repeatedly test engines during transient conditions in a laboratory setting limits researchers and development engineers ability to produce more effective and robust algorithms to lower vehicle emissions. To meet this need, members of the Powertrain Control Research Laboratory (PCRL) at the University of Wisconsin-Madison have developed a high-bandwidth, hydrostatic dynamometer system that will enable researchers to explore transient characteristics of engines and powertrains in the laboratory.

High-resolution planar laser-induced fluorescence (PLIF) measurements were performed on the scalar field in an optical engine. The measurements were of sufficient resolution to fully resolve all of the length scales of the flow field through the full cycle. The scalar dissipation spectrum was calculated, and by fitting the results to a model turbulent spectrum the Batchelor scale of the turbulent flow was estimated. The scalar inhomogeneity was introduced by a low-momentum gas jet injection. A consistent trend was observed in all data; the Batchelor scale showed a minimum value at top dead center (TDC) and was nearly symmetric about TDC. Increasing the engine speed resulted in a decrease of the Batchelor scale, and the presence of a shroud on the intake valve, which increased the turbulence intensity, also reduced the Batchelor scale. The effect of the shrouded valve was less significant compared to the effect of engine speed.

The impingement of liquid fuels on surfaces in IC engines affects performance and emissions. To better understand liquid/solid interactions, the impact of single droplets on a healed surface was experimentally examined. The droplet impingement was photographed with a high speed cine camera to obtain a history of the hydrodynamics of the impingement process. Images obtained from the cine photography were inspected to determine hydrodynamic regimes: wetting, transition, and non-wetting, associated with the specific impingement conditions (droplet size, velocity, surface temperature, and ambient pressure). Images from selected impingement conditions were further analyzed to quantify the atomization resulting from the impingement.

Neural networks have been used for engine computations in the recent past. One reason for using neural networks is to capture the accuracy of multi-dimensional CFD calculations or experimental data while saving computational time, so that system simulations can be performed within a reasonable time frame. This paper describes three methods to improve upon neural network predictions. Improvement is demonstrated for in-cylinder pressure predictions in particular. The first method incorporates a physical combustion model within the transfer function of the neural network, so that the network predictions incorporate physical relationships as well as mathematical models to fit the data. The second method shows how partitioning the data into different regimes based on different physical processes, and training different networks for different regimes, improves the accuracy of predictions.

The University of Wisconsin - Madison Clean Snowmobile team has designed, constructed and now refined an electric snowmobile with 40 km (24 mi) range and acceleration comparable to a 75 kW (100 hp) internal-combustion-powered snowmobile. Starting with a Polaris IQ Fusion chassis, a direct-drive chain-case was engineered to couple a General Motors EV1 copper-bar rotor AC induction electric motor to the track drive shaft. The battery pack uses 104 28 V, 2.8 A-hr Lithium-Ion battery modules supplied by Milwaukee Tool to store 8.2 kW-hr of energy at a nominal voltage of 364 V. Power is transmitted to the electric motor via an Azure Dynamics DMOC445LLC motor controller. All of the components fit within the original sled envelope, leading to a vehicle with conventional appearance and a total mass of 313 kg (690 lb). The vehicle, dubbed the BuckEV, accelerates to 150 m (500 ft) in 6.9 seconds and has a top speed of 122 km/hr (76 mph) with a pass-by sound level of 55 dB.

Control of the flow of thermal energy in an air-cooled engine is important to the overall performance of the engine because of potential effects on engine performance, durability, design, and emissions. A methodology is being developed for the assessment of thermal flows in air-cooled engines, which includes the use of cycle simulation and in-cylinder heat flux measurements. The mechanism for the combination of cycle simulation, the measurement of in-cylinder heat flux and wall temperatures, and comparison of predicted and measured heat flux in the methodology is presented. The methodology consists of both simulation and experimental phases. To begin, a one-dimensional gas dynamics code (WAVE) has been used in conjunction with a detailed in-cylinder flow and combustion model (IRIS) in order to simulate engine operation in a variety of operating conditions. The methods used to apply the model to the air-cooled engine case are described in detail.

A numerical study of air-fuel mixing in a direct-injection spark-ignition engine was carried out. In this paper, the numerical models are described and grid generation methods to represent a realistic port-valve-chamber geometry is discussed. To model a vaporizing hollow-cone spray resulting from an automotive pressure-swirl injector, a newly developed sheet spray atomization model was used to compute the processes of disintegration of the liquid sheet and breakup of the subsequent drops. Computations were performed of a particular 4-valve pent-roof engine configuration in which the intake process and an early fuel injection scheme were considered. After an analysis of the intake-generated flow structures in this engine configuration, the spray behavior and the spatial and temporal evolution of fuel liquid and vapor phases are characterized.

A non-intrusive sensing technique to determine start of combustion for mixing-controlled compression-ignition engines was developed based on an accelerometer mounted to the engine block of a 4-cylinder automotive turbo-diesel engine. The sensing approach is based on a physics-based conceptual model for the signal generation process that relates engine block acceleration to the time derivative of heat release rate. The frequency content of the acceleration and pressure signals was analyzed using the magnitude-squared coherence, and a suitable filtering technique for the acceleration signal was selected based on the result. A method to determine start of combustion (SOC) from the acceleration measurements is presented and validated.

This paper investigates flow and combustion in a full-cycle simulation of a four-stroke, three-valve HCCI engine by visualizing the flow with pathlines. Pathlines trace massless particles in a transient flow field. In addition to visualization, pathlines are used here to trace the history, or evolution, of flow fields and species. In this study evolution is followed from the intake port through combustion. Pathline analysis follows packets of intake charge in time and space from induction through combustion. The local scalar fields traversed by the individual packets in terms of velocity magnitude, turbulence, species concentration and temperatures are extracted from the simulation results. The results show how the intake event establishes local chemical and thermal environments in-cylinder and how the species respond (chemically react) to the local field.

The demand for highly flexible manipulation of plant growth generations, modification of specific plant processes, and genetically engineered crop varieties in a controlled environment has led to the development of a Commercial Plant Biotechnology Facility (CPBF). The CPBF is a quad-middeck locker playload to be mounted in the EXPRESS Rack that will be installed in the International Space Station (ISS). The CPBF integrates proven ASTROCULTURE” technologies, state-of-the-art control software, and fault tolerance and recovery technologies together to increase overall system efficiency, reliability, robustness, flexibility, and user friendliness. The CPBF provides a large plant growing volume for the support of commercial plant biotechnology studies and/or applications for long time plant research in a reduced gravity environment.

Five potato (Solanum tuberosum L.) leaf cuttings were flown on STS-73 in late October, 1995 as part of the 16-day USML-2 mission. Pre-flight studies were conducted to study tuber growth, determine carbohydrate concentrations and examine the developing starch grains within the tuber. In these tests, tubers attained a fresh weight of 1.4 g tuber-1 after 13 days. Tuber fresh mass was significantly correlated to tuber diameter. Greater than 60% of the tuber dry mass was starch and the starch grains varied in size from 2 to 40 mm in the long axis. For the flight experiment, cuttings were obtained from seven-week-old Norland potato plants, kept at 5°C for 12 hours then planted into arcillite in the ASTROCULTURE™ flight hardware. The flight package was loaded on-board the orbiter 22 hours prior to launch.