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In an attempt to reach a compromise between the views of environmentalists and snowmobile enthusiasts, the University of Wisconsin-Madison Clean Snowmobile Team set out to design a machine that maintains performance while decreasing air and noise pollution. After careful consideration of all possible design avenues, the decision was made to select a four-stroke power plant. In order to optimize the engine's efficiency, an engine control unit was chosen that was both capable and affordable. Engine modifications were made to allow the snowmobile's stock transmission to be used. Alterations were also made to intake, exhaust, and cooling systems to allow the engine to fit comfortably under the snowmobile's stock hood. Modifications were made to the snowmobile's chassis to accommodate the additional mass associated with the four-stroke engine. The final product is a snowmobile that minimizes environmental impact but still has the appearance and performance necessary to satisfy consumers.

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.

The paper describes a methodology to co-simulate, with high fidelity, simultaneously and in one computational framework, all of the main vehicle subsystems for improved engineering design. The co-simulation based approach integrates in MATLAB/Simulink a physics-based tire model with high fidelity vehicle dynamics model and an accurate powertrain model allowing insights into 1) how the dynamics of a vehicle affect fuel consumption, quality of emission and vehicle control strategies and 2) how the choice of powertrain systems influence the dynamics of the vehicle; for instance how the variations in drive shaft torque affects vehicle handling, the maximum achievable acceleration of the vehicle, etc. The goal of developing this co-simulation framework is to capture the interaction between powertrain and rest of the vehicle in order to better predict, through simulation, the overall dynamics of the vehicle.

We have developed a methodology for predicting combustion and emissions in a Homogeneous Charge Compression Ignition (HCCI) Engine. The methodology judiciously uses a fluid mechanics code followed by a chemical kinetics code to achieve great reduction in the computational requirements; to a level that can be handled with current computers. In previous papers, our sequential, multi-zone methodology has been applied to HCCI combustion of short-chain hydrocarbons (natural gas and propane). Applying the same procedure to long-chain hydrocarbons (iso-octane) results in unacceptably long computational time. In this paper, we show how the computational time can be made acceptable by developing a segregated solver. This reduces the run time of a ten-zone problem by an order of magnitude and thus makes it much more practical to make combustion studies of long-chain hydrocarbons.

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.

An engine cycle simulation code with detailed chemical kinetics has been developed to study Homogeneous Charge Compression Ignition (HCCI) combustion with hydrogen as the fuel. In order to attain adequate combustion duration, resulting from the self-accelerating nature of the chemical reaction, fuel and temperature inhomogeneities have been brought to the calculation by considering the combustion chamber to have various temperature and fuel distributions. Calculations have been done under various conditions including both perfectly homogeneous and inhomogeneous cases, changing the degree of inhomogeneity. The results show that intake gas temperature is more dominant on ignition timing of HCCI than equivalence ratio and that there is a possibility to control HCCI by introducing appropriate temperature inhomogeneity to in-cylinder mixture.

We have developed a methodology for predicting combustion and emissions in a Homogeneous Charge Compression Ignition (HCCI) Engine. This methodology combines a detailed fluid mechanics code with a detailed chemical kinetics code. Instead of directly linking the two codes, which would require an extremely long computational time, the methodology consists of first running the fluid mechanics code to obtain temperature profiles as a function of time. These temperature profiles are then used as input to a multi-zone chemical kinetics code. The advantage of this procedure is that a small number of zones (10) is enough to obtain accurate results. This procedure achieves the benefits of linking the fluid mechanics and the chemical kinetics codes with a great reduction in the computational effort, to a level that can be handled with current computers.

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.

The simulation of combustion chemistry in internal combustion engines is challenging due to the need to include detailed reaction mechanisms to describe the engine physics. Computational times needed for coupling full chemistry to CFD simulations are still too computationally demanding, even when distributed computer systems are exploited. For these reasons the present paper proposes a time scale separation approach for the integration of the chemistry differential equations and applies it in an engine CFD code. The time scale separation is achieved through the estimation of a characteristic time for each of the species and the introduction of a sampling timestep, wherein the chemistry is subcycled during the overall integration. This allows explicit integration of the system to be carried out, and the step size is governed by tolerance requirements.

A new technique which is based on optoacoustic phenomena has been developed for measuring in-cylinder gas temperature and turbulent diffusivity. In the experiments, a high energy Nd:YAG pulsed laser beam was focused to cause local ionization of air at a point in the combustion chamber. This initiates a shock wave and creates a hot spot. The local temperature and turbulent diffusivity are determined by monitoring the shock propagation and the hot spot growth, respectively, with a schlieren photography system. In order to assess the validity and accuracy of the measurements, the technique was also applied to a turbulent jet. The temperature measurements were found to be accurate to within 3%. Results from the turbulent jet measurements also showed that the growth rate of the hot spot diameter can be used to estimate the turbulent diffusivity. In-cylinder gas temperature measurements were made in a motored single cylinder Caterpillar diesel engine, modified for optical access.

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.

Fundamental simulations using DNS type procedures were used to investigate the ignition, combustion characteristics and the lift-off trends of a spatially evolving turbulent liquid fuel jet. In particular, the spatially evolving n-Heptane spray injected in a two-dimensional rectangular domain with an engine like environment was investigated. The computational results were compared to the experimental observations from an optical engine as reported in the literature. It was found that an initial fuel rich combustion downstream of the spray tip is followed by diffusion combustion. Investigations were also made to understand the effects of injection velocity, ambient temperature and the droplet radius on the lift-off length. For each of these parameters three different values in a given range were chosen. For both injection velocity and droplet radius, an increase resulted in a near linear increase in the lift-off length.

Two distinct atomization strategies are contrasted through the measurement of time and spatially dependent mass flux. The two systems investigated include a pressure atomizer (6.9 MPa opening pressure) and an air-assist atomizer. Both systems have potential for use in direct injection spark ignition engines. The mass flux data presented were obtained using a spray patternator that was developed to allow phased sampling of the spray. The temporal mass related history of the spray was reconstructed as volume versus time plots and interpolated mass flux contour plots. Results indicate substantial differences in the distribution of both mass and mass flux in space and time for the two injection systems. For example, the pressure atomizer at high mass delivery rates produced a spray that collapsed into a dispersed cylindrical shape while at low rates, generated a hollow cone structure.

Two soot-containing turbulent non-premixed flames burning gaseous acetylene in atmospheric-pressure air were investigated by conducting non-intrusive optical experiments at various flame locations. The differences in burner exit Reynolds numbers of these flames were large enough to examine the influence of flow dynamics on soot formation and evolution processes in heavily-sooting flames. By accounting for the fractal nature of aggregated primary particles (spherules), the proper interpretation of the laser scattering and extinction measurements yielded all the soot parameters of principal interest. With the separation of spherule and aggregate sizes, the axial zones of the prevailing turbulent soot mechanisms were accurately identified. With the high propensity of acetylene fuel to soot, relatively fast particle nucleation process led to high concentrations immediately above the burner exit.

This paper presents the results of an experimental program in which a Texaco L-163S engine was fueled with methanol and operated in its traditional stratified charge mode and then modified to run as a homogeneous charge spark ignited engine. The primary data taken were the aldehyde and unburned fuel emissions (UBF). These data were taken using a continuous time-averaging sampling probe at the exhaust tank and at the exhaust port and with a rotary time-resolving sampling valve located at the exhaust port. The data are for two loads, 138.1 kPa (20 psi) and 207.1 kPa (30 psi) BMEP and three speeds, 1000, 1400 and 1800 rpm. The data indicate that for both the stratified charge and the homogeneous charge modes of operation formaldehyde was the only aldehyde detected in the exhaust and it primarily originated in the cylinder.

The ASTROCULTURE™ (ASC) middeck flight experiment series was developed to test and integrate subsystems required to grow plants in reduced gravity, with the goal of developing a plant growth unit suitable for conducting quality biological research in microgravity. Flights on the Space Shuttle have demonstrated control of water movement through a particulate rooting material, growth chamber temperature and humidity control, LED lighting systems and control, recycling of recovered condensate, ethylene scrubbing, and carbon dioxide control. A complete plant growth unit was tested on STS-63 in February 1995, the first ASC flight in which plant biology experiments were conducted in microgravity. The methods and objectives used for control of environmental conditions in the ASC unit are described in this paper.

A hydrostatic dynamometer capable of accurately controlling the speed and torque of an engine has been designed and constructed. The thrust of this work is not only to build a better dynamometer, it is the first step in creating a system for laboratory simulation of the actual load environment of engines and powertrains. This paper presents the design, construction, and evaluation of a hydrostatic dynamometer. The evaluation includes speed and torque limits, and bandwidth of the dynamometer. Also, the dynamometer is compared with those in common use, and the feasibility of accurately reproducing the engine or powertrain load environments are assessed. This is the first phase of a development program; future research is discussed.

The University of Wisconsin - Madison Hybrid Vehicle Team has designed, fabricated, tested and optimized a four-wheel drive, charge sustaining, split-parallel hybrid-electric crossover vehicle for entry into the 2006 Challenge X competition. This multi-year project is based on a 2005 Chevrolet Equinox platform. Trade-offs in fuel economy, greenhouse gas impact (GHGI), acceleration, component packaging and consumer acceptability were weighed to establish Wisconsin's Vehicle Technical Specifications (VTS). Wisconsin's Equinox, nicknamed the Moovada, utilizes a General Motors (GM) 110 kW 1.9 L CIDI engine coupled to GM's 6-speed F40 transmission. The rear axle is powered by a 65 kW Ballard induction motor/gearbox powered from a 44-module (317 volts nominal) Johnson Controls Inc., nickel-metal hydride hybrid battery pack. It includes a newly developed proprietary battery management algorithm which broadcasts the battery's state of charge onto the CAN network.

The University of Wisconsin - Madison hybrid vehicle team has designed and constructed a four-wheel drive, charge sustaining, parallel hybrid-electric sport utility vehicle for entry into the FutureTruck 2003 competition. This is a multi-year project utilizing a 2002 4.0 liter Ford Explorer as the base vehicle. Wisconsin's FutureTruck, nicknamed the ‘Moolander’, weighs 2000 kg and includes a prototype aluminum frame. The Moolander uses a high efficiency, 1.8 liter, common rail, turbo-charged, compression ignition direct injection (CIDI) engine supplying 85 kW of peak power and an AC induction motor that provides an additional 60 kW of peak power. The 145 kW hybrid drivetrain will out-accelerate the stock V6 powertrain while producing similar emissions and drastically reducing fuel consumption. The PNGV Systems Analysis Toolkit (PSAT) model predicts a Federal Testing Procedure (FTP) combined driving cycle fuel economy of 16.05 km/L (37.8 mpg).

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.