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Transient engine operations are modeled and simulated with a 1-D code (GT Power) using heat release and emission data computed by a 3-D CFD code (Kiva3). During each iteration step of a transient engine simulation, the 1-D code utilizes the 3-D data to interpolate the values for heat release and emissions. The 3-D CFD computations were performed for the compression and combustion stroke of strategically chosen engine operating points considering engine speed, torque and excess air. The 3-D inlet conditions were obtained from the 1-D code, which utilized 3-D heat release data from the previous 1-D unsteady computations. In most cases, only two different sets of 3-D input data are needed to interpolate the transient phase between two engine operating points. This keeps the computation time at a reasonable level. The results are demonstrated on the load response of a generator which is driven by a medium-speed diesel engine.

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.

In a recent study, quantitative measurements were presented of in-cylinder spatial distributions of mixture equivalence ratio in a single-cylinder light-duty optical diesel engine, operated with a non-reactive mixture at conditions similar to an early injection low-temperature combustion mode. In the experiments a planar laser-induced fluorescence (PLIF) methodology was used to obtain local mixture equivalence ratio values based on a diesel fuel surrogate (75% n-heptane, 25% iso-octane), with a small fraction of toluene as fluorescing tracer (0.5% by mass). Significant changes in the mixture's structure and composition at the walls were observed due to increased charge motion at high swirl and injection pressure levels. This suggested a non-negligible impact on wall heat transfer and, ultimately, on efficiency and engine-out emissions.

One of the major challenges in multiobjective, multidisciplinary design optimization (MDO) is the long computational time required in evaluating the new designs' performances. To shorten the cycle time of product design, a data mining-based strategy is developed to improve the efficiency of heuristic optimization algorithms. Based on the historical information of the optimization process, clustering and classification techniques are employed to identify and eliminate the low quality and repetitive designs before operating the time-consuming design evaluations. The proposed method improves design performances within the same computation budget. Two case studies, one mathematical benchmark problem and one vehicle side impact design problem, are conducted as demonstration.

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.

Analytical models (math or computer simulation models) are typically built on the basis of many assumptions and simplifications and hence model prediction could be inaccurate in intended applications. Model validation is thus critical to quantify and improve the degree of accuracy of these models. So far, little work considers model validation for various design configurations so that model prediction is accurate in the intended design space. Furthermore, there is a lack of effective approaches that can be used to quantify model accuracy considering different number of experimental data. To overcome these limitations, objective of this paper is to develop a model validation approach for various design configurations with a reference metric for model accuracy check considering different number of experimental data.

Particle swarm optimization (PSO) is a relatively new stochastic optimization algorithm and has gained much attention in recent years because of its fast convergence speed and strong optimization ability. However, PSO suffers from premature convergence problem for quick losing of diversity. That is to say, if no particle discovers a new superiority position than its previous best location, PSO algorithm will fall into stagnation and output local optimum result. In order to improve the diversity of basic PSO, design of experiment technique is used to initialize the particle swarm in consideration of its space-filling property which guarantees covering the design space comprehensively. And the optimization procedure of PSO is divided into two stages, optimization stage and improving stage. In the optimization stage, the basic PSO initialized by Optimal Latin hypercube technique is conducted.

A dynamic powertrain system model of the High Mobility Multi-Wheeled Vehicle (HMMWV) was created in the Powertrain Control Research Laboratory (PCRL) at the University of Wisconsin-Madison. Simulink graphical programming software was used to create the model. This dynamic model includes a Torsen differential model and a Hyrda-matic 4L80-E automatic transmission model as well as several other powertrain component models developed in the PCRL. Several component inertias and shaft stiffnesses are included in the dynamic model. The concepts of modularity, flexibility, and user-friendliness were emphasized during model development so that the system model would be a useful design tool. Simulation results from the model are shown.

Pending reductions in light duty vehicle PM emissions standards from 10 to 3 mg/mi and below will push the limits of the gravimetric measurement method. At these levels the PM mass collected approaches the mass of non-particle gaseous species that adsorb onto the filter from exhaust and ambient air. This introduces an intrinsic lower limit to filter based measurement that is independent of improvements achieved in weighing metrology. The statistical variability of back-up filter measurements at these levels makes them an ineffective means for correcting the adsorption artifact. The proposed subtraction of a facility based estimate of the artifact will partially alleviate the mass bias from adsorption, but its impact on weighing variability remains a problem that can reach a significant fraction of the upcoming 3 and future 1 mg/mi standards. This paper proposes an improved PM mass method that combines the gravimetric filter approach with real time aerosol measurement.

A procedure has been developed to build system level predictive models that incorporate physical laws as well as information derived from experimental data. In particular a soot model was developed, trained and tested using experimental data. It was seen that the model could fit available experimental data given sufficient training time. Future accuracy on data points not encountered during training was estimated and seen to be good. The approach relies on the physical phenomena predicted by an existing system level phenomenological soot model coupled with ‘weights’ which use experimental data to adjust the predicted physical sub-model parameters to fit the data. This approach has developed from attempts at incorporating physical phenomena into neural networks for predicting emissions. Model training uses neural network training concepts.

The largest contribution to engine rubbing friction is made by the piston and piston rings running in the cylinder liner. The magnitude and characteristics of the friction behaviour and the influence on these of factors such as surface roughness, piston design and lubricant properties are of keen interest. Investigating presents experimental challenges, including potential problems of uncontrolled build-to-build variability when component changes are made. These are addressed in the design of a new motored piston and floating liner rig. The design constrains transverse movement of a single liner using cantilevered mounts at the top and bottom. The mounts and two high stiffness strain gauged load cells constrain vertical movement. The outputs of the load cells are processed to extract the force contribution associated with friction. The liner, piston and crankshaft parts were taken from a EuroV-compliant, HPCR diesel engine with a swept capacity of 550cc per cylinder.

A droplet vaporization model has been developed for use in high pressure spray modeling. The model is a modification of the common Spalding vaporization model that accounts for the effects of high pressure on phase equilibrium, transport properties, and surface tension. The new model allows for a nonuniform temperature within the liquid by using a simple 2-zone model for the droplet. The effects of the different modifications are tested both for the case of a single vaporizing droplet in a quiescent environment as well as for a high pressure spray using the KIVA II code. Comparisons with vaporizing spray experiments show somewhat improved spray penetration predictions. Also, the effect of the vaporization model on diesel combustion predictions was studied by applying the models to simulate the combustion process in a heavy duty diesel engine. In this case the standard and High Pressure vaporization models were found to give similar heat release and emissions results.

Design optimization methods are commonly used for weight reduction subjecting to multiple constraints in automotive industry. One of the major challenges remained is to deal with a large number of design variables for large-scale design optimization problems effectively. In this paper, a new approach based on fuzzy rough set is proposed to address this issue. The concept of rough set theory is to deal with redundant information and seek for a reduced design variable set. The proposed method first exploits fuzzy rough set to screen out the insignificant or redundant design variables with regard to the output functions, then uses the reduced design variable set for design optimization. A vehicle body structure is used to demonstrate the effectiveness of the proposed method and compare with a traditional weighted sensitivity based main effect approach.

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.

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.

A fundamentally based quasi-dimensional NOx emission model for spark ignition direct injection (SIDI) gasoline engines was developed. The NOx model consists of a chemical mechanism and three sub-models. The classical extended Zeldovich mechanism and N₂O pathway for NOx formation mechanism were employed as the chemical mechanism in the model. A characteristic time model for the radical species H, O and OH was incorporated to account for non-equilibrium of radical species during combustion. A model of homogeneity which correlates fundamental dimensionless numbers and mixing time was developed to model the air-fuel mixing and inhomogeneity of the charge. Since temperature has a dominant effect on NOx emission, a flame temperature correlation was developed to model the flame temperature during the combustion for NOx calculation. Measured NOx emission data from a single-cylinder SIDI research engine at different operating conditions was used to validate the NOx model.

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.

This Paper introduces a modular, flexible and user-friendly dynamic powertrain model of the US Army's High Mobility Multi-Wheeled Vehicle (HMMWV). It includes the DDC 6.5L diesel engine, Hydra-matic 4L80-E automatic transmission, Torsen differentials, transfer case, and flexible drive and axle shafts. This model is used in a case study on transmission optimization design to demonstrate an application of the model. This study shows how combined optimization of the transmission hardware (clutch capacity) and control strategy (shift time) can be explored, and how the models can help the designer understand dynamic interactions as well as provide useful design guidance early in the system design phase.

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).