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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.

The fuel film thickness resulting from diesel fuel spray impingement was measured in a chamber at conditions representative of early injection timings used for low temperature diesel combustion. The adhered fuel volume and the radial distribution of the film thickness are presented. Fuel was injected normal to the impingement surface at ambient temperatures of 353 K, 426 K and 500 K, with densities of 10 kg/m3 and 25 kg/m3. Two injectors, with nozzle diameters of 100 μm and 120 μm, were investigated. The results show that the fuel film volume was strongly affected by the ambient temperature, but was minimally affected by the ambient density. The peak fuel film thickness and the film radius were found to increase with decreased temperature. The fuel film was found to be circular in shape, with an inner region of nearly constant thickness. The major difference observed with temperature was a decrease in the radial extent of the film.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

An investigation of the effect of microflow machining on the spray characteristics of diesel injectors was undertaken. A collection of four VCO injector tips were tested prior to and after an abrasive flow process using a high viscosity media. The injector nozzles were tested on a spray fixture. Rate of injection measurements and high-speed digital images were used for the quantification of the air entrainment rate. Comparisons of the spray characteristics and A/F ratios were made for conditions of before and after the abrasive flow process. Results showed a significant decrease in the injection-to-injection variability and improvement of the spray symmetry. A link between the quantity of air entrained and potential differences in spray plume internal chemical composition and temperature is proposed via equilibrium calculations.

Neural networks are useful tools for optimization studies since they are very fast, so that while capturing the accuracy of multi-dimensional CFD calculations or experimental data, they can be run numerous times as required by many optimization techniques. This paper describes how a set of neural networks trained on a multi-dimensional CFD code to predict pressure, temperature, heat flux, torque and emissions, have been used by a genetic algorithm in combination with a hill-climbing type algorithm to optimize operating parameters of a diesel engine over the entire speed-torque map of the engine. The optimized parameters are mass of fuel injected per cycle, shape of the injection profile for dual split injection, start of injection, EGR level and boost pressure. These have been optimized for minimum emissions. Another set of neural networks have been trained to predict the optimized parameters, based on the speed-torque point of the engine.

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 study investigates using driver prediction to anticipate energy usage over a 160-meter look-ahead distance for a series, plug-in, hybrid-electric vehicle to improve conventional thermostatic powertrain control. Driver prediction algorithms utilize a hidden Markov model to predict route and a regression tree to predict speed over the route. Anticipated energy consumption is calculated by integrating force vectors over the look-ahead distance using the predicted incline slope and vehicle speed. Thermostatic powertrain control is improved by supplementing energy produced by the series generator with regenerative braking during events where anticipated energy consumption is negative, typically associated with declines or decelerations.

An experimental investigation of turbulent flow patterns in a scale model of a high pressure diesel fuel injector nozzle has been conducted. Instantaneous velocity measurements were made in a 50X transparent model of one hole of the injector nozzle using an Aerometrics Phase Doppler Particle Analyzer (PDPA) in the velocity mode. Length to diameter ratio (L/D) values of 1.3, 2.4, 4.9, and 7.7 and inlet radius to diameter ratio (R/D) values of approximately 0 and 0.3 were investigated. Two steady flow average Reynolds numbers (10,500 and 13,300), analogous to fuel injection velocities and sac pressures of approximately 320 and 405 m/s and 67 and 107 MPa (10,000 and 16,000 psi), were investigated. The axial progression of mean and root mean square (rms) axial velocities was obtained for both sharp and rounded inlet conditions and varying L/D. The discharge coefficient was also calculated for each geometry.

An experimental investigation of the spectral characteristics of turbulent flow in a scale model of a high pressure diesel fuel injector nozzle hole has been conducted. Instantaneous velocity measurements were made in a 50X transparent model of one hole of an injector nozzle using an Aerometrics Phase/Doppler Particle Analyzer (PDPA) in the velocity mode. Turbulence spectra were calculated from the velocity data using the Lomb-Scargle method. Injector hole length to diameter ratio (L/D) values of 1.3, 2.4, 4.9, and 7.7 and inlet radius to diameter ratio (R/D) values of approximately 0 and 0.3 were investigated. Results were obtained for a steady flow average Reynolds number of 10,500, which is analogous to a fuel injection velocity of 320 m/s and a sac pressure of approximately 67 MPa (10,000 psi). Turbulence time frequency spectra were obtained for significant locations in each geometry, in order to determine how geometry affects the development of the turbulent spectra.

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.

Automatic manufacturability analysis of injection moldings, sheet metal castings, stampings, forgings, etc., using knowledge-based heuristics depends on shape features, which are abstractions of the three dimensional (3D) geometric model of the parts. Conventional CAD systems do not explicitly contain shape feature information, therefore such information needs to be extracted from them. So far, extraction of shape features has been restricted to models with simple geometric shapes such as planar, cylindrical or conical shapes. Extending shape feature extraction to non-linear geometric models will allow Design For Manufacturability (DFM) analysis of non-linear models. This paper presents an approach to extract features from non-linear geometric models. The approach is based on abstract geometric entities called C-loops. The formation of a C-loop depends on a geometric entity called a silhouette. The C-loops are derived from the silhouette boundaries of an object.

Studies of transient diesel spray characteristics at high injection pressures were conducted in a constant volume chamber by utilizing a high speed photography and light extinction optical diagnostic technique. Two different types of nozzle hole entrances were investigated: a sharp-edged and a round-edged nozzle. The experimental results show that for the same injection delivery, the sharp-edged inlet injector needed a higher injection pressure to overcome the higher friction loss, but it produced longer spray tip penetration length, larger spray angle, smaller droplet sizes, and also lower particulate emission from a parallel engine test. For the round-edged and smooth edged tips at the same injection pressure, the sharp-edged inlet tip took a longer injection duration to deliver a fixed mass of fuel and produced larger overall average Sauter Mean Diameter (SMD) droplets.

An emissions and performance study was performed to show the effects of injection pressure, nozzle hole inlet condition (sharp and rounded edge) and nozzle included spray angle on particulate, NOx, and BSFC. The tests were conducted on a fully instrumented single-cylinder version of the Caterpillar 3406 heavy duty engine at 75% and 25% load at 1600 RPM. The fuel system consisted of an electronically controlled, hydraulically actuated, unit injector capable of injection pressures up to 160 MPa. Particulate versus NOx trade-off curves were generated for each case by varying the injection timing. The 75% load results showed the expected decrease in particulate and flattening of the trade-off curve with increased injection pressure. However, in going from 90 to 160 MPa, the timing had to be retarded to maintain the same NOx level, and this resulted in a 1 to 2% increase in BSFC. The rounded edged nozzles were found to have an increased discharge coefficient.

A study was performed to correlate the Sauter Mean Diameter (SMD), NOx and particulate emissions of a direct injection diesel engine with various injection pressures and different nozzle geometry. The spray experiments and engine emission tests were conducted in parallel using the same fuel injection system and same operating conditions. With high speed photography and digital image analysis, a light extinction technique was used to obtain the spray characteristics which included spray tip penetration length, spray angle, and overall average SMD for the entire spray. The NOx and particulate emissions were acquired by running the tests on a fully instrumented Caterpillar 3406 heavy duty engine. Experimental results showed that for higher injection pressures, a smaller SMD was observed, i.e. a finer spray was obtained. For this case, a higher NOx and lower particulate resulted.

A study of fuel spray characteristics for diesel fuel from a multi-hole nozzle injector was performed yielding tip penetration length and spray cone angle for each of the spray plumes from a six hole injector. The main feature of the system used was that analysis of all the fuel plumes could occur at one time, as all the plumes were imaged on the same piece of film. Spray behavior was examined for two injection pressures (72 MPa and 122 MPa) and for ambient temperatures up to 523 K (250°C). The results in this paper show how the spray plumes behave as they leave each of the six holes of the injector. The characteristics of each hole differs during injection. The variations of spray cone angle and tip penetration length between holes are small, but significant. These variations in tip penetration and cone angle changed as the temperature of the chamber changed, but the overall characteristics of the spray plumes changed only slightly for the temperatures used in this paper.

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.

The objective of this study was to investigate the effects of fuel viscosity and the effects of nozzle inlet configuration on the characteristics of high injection pressure sprays. Three different viscosity fuels were used to reveal the effects of viscosity on the spray characteristics. The effects of nozzle inlet configuration on spray characteristics were studied using two mini-sac six-hole nozzles with different inlet configurations. A common rail injection system was used to introduce the spray at 90 MPa injection pressure into a constant volume chamber pressurized with argon gas. The information on high pressure transient sprays was captured by a high speed movie camera synchronized with a pulsed copper vapor laser. The images were analyzed to obtain the spray characteristics which include spray tip penetration, spray cone angle at two different regions, and overall spray Sauter Mean Diameter (SMD).

The flow through diesel fuel injector nozzles is important because of the effects on the spray and the atomization process. Modeling this nozzle flow is complicated by the presence of cavitation inside the nozzles. This investigation uses a two-dimensional, two-phase, transient model of cavitating nozzle flow to observe the individual effects of several nozzle parameters. The injection pressure is varied, as well as several geometric parameters. Results are presented for a range of rounded inlets, from r/D of 1/40 to 1/4. Similarly, results for a range of L/D from 2 to 8 are presented. Finally, the angle of the corner is varied from 50° to 150°. An axisymmetric injector tip is also simulated in order to observe the effects of upstream geometry on the nozzle flow. The injector tip calculations show that the upstream geometry has a small influence on the nozzle flow. The results demonstrate the model's ability to predict cavitating nozzle flow in several different geometries.

Traffic state identification is a key problem in intelligent transportation system. As a new technology, connected and automated vehicle can play a role of identifying traffic state with the installation of onboard sensors. However, research of lane level traffic state identification is relatively lacked. Identifying lane level traffic state is helpful to lane selection in the process of driving and trajectory planning. In addition, traffic state identification precision with low penetration of connected and automated vehicles is relatively low. To fill this gap, this paper proposes a novel method of identifying traffic state in the presence of connected and automated vehicles with low penetration rate. Assuming connected and automated vehicles can obtain information of surrounding vehicles’, we use the perceptible information to estimate imperceptible information, then traffic state of road section can be inferred.