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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.

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.

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.

The use of a hydraulic drive system with accumulator energy storage has the potential of providing large gains in fuel economy of internal combustion engine passenger automobiles. The improvement occurs because of efficient regenerative braking and the practicality of decoupling the engine operation from the driving cycle demands. The concept under study uses an engine-driven pump supplying hydraulic power to individual wheel pump/motors (P/M's) and/or an accumulator. Available P/M's have high efficiencies (e.g., 95%) at the ideal point of operation, but the efficiency falls off considerably at combinations of pressure, speed, and displacement that are significantly away from ideal. In order to maximize the fuel economy of the automobile, it is necessary to provide the proper combination of components, system design, and control policies that operate the wheel P/M's as close as possible to their maximum efficiency under all types of driving and braking conditions.

In-cylinder thermal barrier coatings (TBCs) have the capability to reduce fuel consumption by reducing wall heat transfer and to increase exhaust enthalpy. Low thermal conductivity, low volumetric heat capacity thermal barrier coatings tend to reduce the gas-wall temperature difference, the driving potential for heat transfer from the gas to the combustion chamber surfaces. This paper presents a coupling between an analytical methodology for multi-layer coated wall surface temperature prediction with a fully calibrated production model in a commercial system-level simulation software package (GT-Power). The wall surface temperature at each time step was calculated efficiently by convolving the engine wall response function with the time-varying surface boundary condition, i. e., in-cylinder heat flux and coolant temperature. This tool allows the wall to be treated either as spatially uniform with one set of properties, or with independent head/piston/liner components.

A previously developed CFD-based optimization tool is utilized to find optimal engine operating conditions with respect to fuel consumption and emissions. The optimization algorithm employed is based on the steepest descent method where an adaptive cost function is minimized along each line search using an effective backtracking strategy. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine. The optimization parameters are the start of injection of the two pulses of a split injection system, the duration of each pulse, the exhaust gas recirculation rate, the boost pressure and the compression ratio.

The University of Wisconsin - Madison FutureTruck Team has designed and built a four-wheel drive, charge sustaining, parallel hybrid-electric sport utility vehicle for entry into the FutureTruck 2002 competition. This is a two-year project with tiered goals; the base vehicle for both years is a 2002 Ford Explorer. Wisconsin's FutureTruck, nicknamed the ‘Moolander’, weighs approximately 2050 kg. The vehicle uses a high efficiency, 2.5 liter, turbo-charged, compression ignition common rail, direct-injection engine supplying approximately 100 kW of peak power and a AC induction motor that provides an additional 33 kW of peak power. This hybrid drivetrain is an attractive alternative to the large displacement V6 drivetrain, as it provides comparable performance with similar emissions and drastically reduced fuel consumption.

The University of Wisconsin - Madison FutureTruck Team has designed and built a four-wheel drive, charge sustaining, parallel hybrid-electric sport utility vehicle for entry into the FutureTruck 2001 competition. The base vehicle is a 2000 Chevrolet Suburban. Our FutureTruck is nicknamed the “Moollennium” and weighs approximately 2427 kg. The vehicle uses a high efficiency, 2.5 liter, turbo-charged, compression ignition common rail, direct-injection engine supplying approximately 104 kW of peak power and a three phase AC induction motor that provides an additional 68.5 kW of peak power. This hybrid drivetrain is an attractive alternative to the large displacement V8 drivetrain, as it provides comparable performance with lower emissions and fuel consumption. The PNGV Systems Analysis Toolkit (PSAT) model predicts a Federal Testing Procedure (FTP) urban driving cycle fuel economy of 11.24 km/L (26.43 mpg) with California Ultra Low Emission Vehicle (ULEV) emissions levels.

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).

Students, as members of Team Paradigm, at the University of Wisconsin-Madison have designed a charge regulating, parallel hybrid electric Dodge Intrepid for the 1997 FutureCar Challenge (FCC97). The goals for the Wisconsin “FutureCow” are to achieve an equivalent fuel consumption of 26 km/L (62 mpg) and Tier 2 Federal Emissions levels while maintaining the full passenger/cargo room, appearance, and feel of a stock Intrepid. These goals are realized through drivetrain simulations, a refined vehicle control strategy, decreased engine emissions, and aggressive weight reduction. The vehicle development has been coupled with 8,000 km of reliability and performance testing to ensure Wisconsin will be a strong competitor at the FCC97.

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.

Although turbocharging can extend the high load limit of low temperature combustion (LTC) strategies such as reactivity controlled compression ignition (RCCI), the low exhaust enthalpy prevalent in these strategies necessitates the use of high exhaust pressures for improving turbocharger efficiency, causing high pumping losses and poor fuel economy. To mitigate these pumping losses, the divided exhaust period (DEP) concept is proposed. In this concept, the exhaust gas is directed to two separate manifolds: the blowdown manifold which is connected to the turbocharger and the scavenging manifold that bypasses the turbocharger. By separately actuating the exhaust valves using variable valve actuation, the exhaust flow is split between two manifolds, thereby reducing the overall engine backpressure and lowering pumping losses. In this paper, results from zero-dimensional and one-dimensional simulations of a multicylinder RCCI light-duty engine equipped with DEP are presented.

An engine emissions and performance study was conducted in conjunction with a series of experiments using a constant volume cold spray chamber. The purpose of the study was to explore the effects of number of holes and hole size on the emissions and performance of a direct injection heavy duty diesel engine. The spray experiments provide insight into the spray parameters and their role in the engine's combustion processes. The fuel system used for both the engine and spray chamber experiments was an electronically controlled, common rail injector. The injector nozzle hole size and number combinations used in the experiments included 225X8 (225 gm diameter holes with 8 holes in the nozzle), 260X6, 260X8, and 30OX6. The engine tests were conducted on an instrumented single cylinder version of the Caterpillar 3400 series heavy duty diesel engine. Data were taken with the engine running at 1600 RPM, 75% load.

A study of the combined use of split injections, EGR, and flexible boosting was conducted. Statistical optimization of the engine operating parameters was accomplished using a new response surface method. The objective of the study was to demonstrate the emissions and fuel consumption capabilities of a state-of-the-art heavy -duty diesel engine when using split injections, EGR, and flexible boosting over a wide range of engine operating conditions. Previous studies have indicated that multiple injections with EGR can provide substantial simultaneous reductions in emissions of particulate and NOx from heavy-duty diesel engines, but careful optimization of the operating parameters is necessary in order to receive the full benefit of these combustion control techniques. Similarly, boost has been shown to be an important parameter to optimize. During the experiments, an instrumented single-cylinder heavy -duty diesel engine was used.

In this paper results are given from single-cylinder, steady-state engine tests using the Texaco Diesel Additive (TDA) as an in-fuel emission reducing agent. The data include NOx, total unburned hydrocarbons, indicated specific fuel consumption, and heat release analysis for one engine speed (1500 RPM) with two different loads (Φ ≈ 0.3, IMEP = 0.654 MPa and Φ ≈ 0.5, IMEP = 1.006 MPa) using the baseline fuel and fuels with one percent and five percent additive by weight. The emissions were measured in the exhaust stream of a modified TACOM-LABECO single cylinder engine. This engine is a 114 mm x 114 mm (4.5″ x 4.5″) open chamber low swirl design with a 110.5 MPa (16,000 psi) peak pressure Bosch injector. The injector has 8 holes, each of 0.2 mm diameter. The intake air was slightly boosted (approximately 171 kPa (25 psia)) and slightly heated (333 K (140 °F)). In previous research on this engine the emissions, including soot, were well documented.

Brake systems in current production automobiles are the result of a long evolutionary process beginning with the first practical hydraulic brake patent in 1917. While the basic hydraulic design has many advantages, recent modifications to this system for anti-lock braking and traction control considerably increase the cost of manufacture. As a result, many manufacturers are investigating the possibility of developing alternate braking system structures that cost less and can easily interface with vehicle electronics. Evaluating these systems for fault tolerance and failure effects is crucial to provide a safe and reliable vehicle braking system. This paper demonstrates the use of the Fault Tree Analysis method for carrying out such an evaluation. An example system is presented to illustrate the application of this method to automobile brake design.

Forage harvesting, processing and handling equipment research is currently underway which will improve commodity quality, produce “value -added” products from forages, reduce energy and labor requirements of the equipment and improve forage marketability. Technologies are described which could increase forage quality and value by removing it from the field sooner after it is mowed to minimize the risk of weather damage. Mechanisms and management strategies for reducing the labor and energy required for field processing and for improving the marketability of forages are also described.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

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.