Search Results

The focus of this paper is to discuss the modeling and control of intake plenum pressure on the Powertrain Control Research Laboratory's (PCRL) Single-Cylinder Engine (SCE) transient test system using a patented device known as the Intake Air Simulator (IAS), which dynamically controls the intake plenum pressure, and, subsequently, the instantaneous airflow into the cylinder. The IAS exists as just one of many devices that the PCRL uses to control the dynamic boundary conditions of its SCE transient test system to make it “think” and operate as though it were part of a Multi-Cylinder Engine (MCE) test system. The model described in this paper will be used to design a second generation of this device that utilizes both continuously and discretely actuating valves working in parallel.

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.

Powertrain simulation is becoming an increasingly valuable tool to evaluate new technologies proposed for future military vehicles. The powertrain of the M1A1 Abrams tank is currently being modeled in the Powertrain Control Research Laboratory (PCRL) at the University of Wisconsin-Madison. This powertrain model is to be integrated with other component models in an effort to produce a high fidelity simulation of the entire vehicle.

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.

Micro-machined planar orifice nozzles have been developed and used with commercially produced diesel injection systems. Such a system may have the capability to improve the spray characteristics in DI diesel engines. The availability of a MEMS (Micro-Electro-Mechanical-Systems) processing sequence supported the construction of micro-planar orifice nozzles, and micro-systems technology was also employed in our macro-instrumentation. To demonstrate this process, fourteen MEMS nozzles were fabricated with deep X-ray lithography and electroplating technology. The circular orifice diameters were varied from 40 to 260 microns and the number of orifices varied from one to 169. Three plates with non-circular orifices were also fabricated to examine the effect of orifice shape on spray characteristics. These nozzles were then attached to commercial injectors and the associated injection systems were used for the spray experiments.

This paper presents advanced and cost-reducing technologies of a motor drive system with reduced permanent magnets but without a position sensor. The key enabler is the integration of novel designs of flux-intensifying interior permanent magnet synchronous machines (FI-IPMSMs) and position self-sensing control technologies. In this paper, we focus on two advantages of FI-IPMSM over conventional flux-weakening interior permanent magnet synchronous machines (FW-IPMSMs). The first benefit is that thinner magnets are possible and there is less concern for demagnetization because of its significantly smaller flux-weakening current. This paper presents two design examples of FI-IPMSMs, one of which has not only smaller magnets but also similar power conversion capability. The second advantage is reduced saturation and cross-saturation effect, which leads to improved position self-sensing capability.

The effect of wall temperature on single surface flame quenching and flame structure of an atmospheric premixed methane-air flame was studied. The luminous region of a laminar flame was located at an angle of 45 degrees to a temperature- controlled surface. C2 laser-induced fluorescence was used as an indicator of flame position while Raman spectroscopy was used to determine gas temperature profiles near the surface. These measurements were conducted for wall positions (vertical distance from the surface) ranging from 50 mm to 1.0 mm and wall temperatures ranging from 150 °C to 600 °C. C2 laser-induced fluorescence measurements indicated flame position is affected by the presence of a surface and the surface temperature. Larger C2 fluorescence intensity values were observed for higher wall temperatures at all distances from the surface.

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.

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.

We have developed and used micro-machined injector nozzles with commercially produced diesel injection systems that have the capability to improve the spray characteristics in DI diesel engines. The availability of a MEMS (Micro-Electro-Mechanical-Systems) processing sequence supported the construction of micro-diesel injector nozzles, and micro-systems technology was also employed in our macro-instrumentation. Fourteen different circular plates (nickel-iron alloy) were fabricated with deep X-ray lithography and electroplating technology. Five plates that have a single orifice were fabricated to investigate the effect of orifice diameter on spray characteristics; i.e., 40 to 260 microns. The spacing between multiple orifices was also varied; e.g., two plates that each had 41 orifices and 169 orifices, respectively, with a diameter of 40 microns. Finally, three plates with non-circular orifices were also made to examine the effect of orifice shape on spray characteristics.