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Measurements of the soot emissions and engine operating parameters from a diesel engine during transient operation were used to investigate the influence of transient operation on the soot emissions, as well as to validate a realtime mean value soot model (MVSM, [1]) for transient operation. To maximize the temporal resolution of the soot emission and engine parameter measurements (in particular EGR), fast instruments were used and their dynamic responses characterized and corrected. During tip-in transients, an increase in the soot emissions was observed due to a short term oxygen deficit compared to steady-state operation. No significant difference was seen between steady-state and transient operation for acceleration transients. When the MVSM was provided with inputs of sufficient temporal resolution, it was capable of reproducing the qualitative and, in part, quantitative soot emission trends.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An integral part of this System is an Intervention Strategy that uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. Through this strategy, the driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models. This work develops one means to alter the future vehicle states: modulating the driver's brake commands. This control strategy must be considered in relationship to changes in the throttle commands. Three key elements of this strategy are developed in this work.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An Intervention Strategy uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. The driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models which is the focus of this work. This work develops one means to alter the future vehicle states: modulating the driver's throttle commands. First, changes to the longitudinal force are translated to changes in engine torque based on the current operating state (torque and speed) of the engine.

Studying the kinetic and kinematics of the rim-tire combination is very important in full vehicle simulations, as well as for the tire design process. Tire maneuvers are either quasi-static, such as steady-state rolling, or dynamic, such as traction and braking. The rolling of the tire over obstacles and potholes and, more generally, over uneven roads are other examples of tire dynamic maneuvers. In the latter case, tire dynamic models are used for durability assessment of the vehicle chassis, and should be studied using high fidelity simulation models. In this study, a three-dimensional finite element model (FEM) has been developed using the commercial software package ABAQUS. The purpose of this study is to investigate the tire dynamic behavior in multiple case studies in which the transient characteristics are highly involved.

Magnetic Resonance Velocimetry (MRV) measurements are performed in 1:1 scale models of a single-cylinder optical engine to investigate the differences in the inlet flow due to geometrical changes of the cylinder head. The models are steady flow water-analogue of the optical IC engine with a fixed valve lift of 9.21 mm to simulate the induction flow at 270° bTDC. The applicability of MRV to engine flows despite the differences in experimental operating parameters between the steady flow model and the optical IC engine are demonstrated and well addressed in this manuscript and in a previous work [1]. To provide trust into the MRV measurements, the data is validated with phase-averaged particle image velocimetry (PIV) measurements performed within the optical engine. The main geometrical changes between the cylinder heads include a variation of intake valve diameter and slight modifications to the exit of the intake port.

Modeling the tire forces and moments (F&M) generation, during combined slip maneuvers, which involves cornering and braking/driving at the same time, is essential for the predictive vehicle performance analysis. In this study, a new semi-empirical method is introduced to estimate the tire combined slip F&M characteristics based on flat belt testing machine measurement data. This model is intended to be used in the virtual tire design optimization process. Therefore, it should include high accuracy, ease of parameterization, and fast computational time. Regression is used to convert measured F&M into pure slip multi-dimensional interpolant functions modified by weighting functions. Accurate combined slip F&M predictions are created by modifying pure slip F&M with empirically determined shape functions. Transient effects are reproduced using standard relaxation length equations. The model calculates F&M at the center of the contact patch.

This study investigates n-dodecane split injections of “Spray A” from the Engine Combustion Network (ECN) using two different turbulence treatments (RANS and LES) in conjunction with a Conditional Moment Closure combustion model (CMC). The two modeling approaches are first assessed in terms of vapor spray penetration evolutions of non-reacting split injections showing a clearly superior performance of the LES compared to RANS: while the former successfully reproduces the experimental results for both first and second injection events, the slipstream effect in the wake of the first injection jet is not accurately captured by RANS leading to an over-predicted spray tip penetration of the second pulse. In a second step, two reactive operating conditions with the same ambient density were investigated, namely one at a diesel-like condition (900K, 60bar) and one at a lower temperature (750K, 50bar).

Three-dimensional reactive computational fluid dynamics (CFD) plays a crucial role in IC engine development tasks complementing experimental efforts by providing improved understanding of the combustion process. A widely adopted combustion model in the engine community for (partially) premixed combustion is the G-Equation where the flame front is represented by an iso-level of an arbitrary scalar G. A convective-reactive equation for this iso-surface is solved, for which the turbulent flame speed ST must be provided. In this study, the commonly used and well-established Damköhler approach is compared to a novel correlation, derived from an algebraic closure for the scalar dissipation of reaction progress as proposed by Kolla et al. [1].

An existing three-stage ignition delay model which has seen successful application to Primary Reference Fuels (PRFs) has been extended to six surrogate fuels which constitute potential candidates for future Homogeneous Charge Compression Ignition (HCCI) engines. The fuels include petroleum-derived and oxygenated components and can be divided into low, intermediate and high cetane number groups. A new methodology to obtain the model parameters is presented which relies jointly on simulation and experimental data: in a first step, constant volume adiabatic reactor simulations using chemical kinetic mechanisms are performed to generate ignition delays for a very wide range of conditions, namely variations in equivalence ratio, Exhaust Gas Recirculation (EGR), pressure and temperature.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

The interaction of turbulent premixed methane combustion with the surrounding flow field can be studied using optically accessible test rigs such as a rapid compression expansion machine (RCEM). The high flexibility offered by such a test rig allows its operation at various thermochemical conditions at ignition. However, limitations inherent to such test rigs due to the absence of an intake stroke do not allow turbulence production as found in IC-engines. Hence, means to introduce turbulence need to be implemented and the relevant turbulence quantities have to be identified in order to enable comparability with engine relevant conditions. A dedicated high-pressure direct injection of air at the beginning of the compression phase is considered as a measure to generate adjustable turbulence intensities at spark timing and during the early flame propagation.

Large-bore natural gas engines may use pre-chamber ignition. Despite extensive research in engine environments, the exact nature of the jet, as it exits the pre-chamber orifice, is not thoroughly understood and this leads to uncertainty in the design of such systems. In this work, a specially-designed rig comprising a quartz pre-chamber fit with an orifice and a turbulent flowing mixture outside the pre-chamber was used to study the pre-chamber flame, the jet, and the subsequent premixed flame initiation mechanism by OH* and CH* chemiluminescence. Ethylene and methane were used. The experimental results are supplemented by LES and 0D modelling, providing insights into the mass flow rate evolution at the orifice and into the nature of the fluid there. Both LES and experiment suggest that for large orifice diameters, the flow that exits the orifice is composed of a column of hot products surrounded by an annulus of unburnt pre-chamber fluid.

Cycle-to-cycle variations in internal combustion engines are known to lead to limitations in engine load and efficiency, as well as increases in emissions. Recent research has led to the identification of the source of cyclic variations of pressure, soot and NO emissions in direct injection common rail diesel engines, when employing a single block injection and operating under long ignition delay conditions. The variations in peak pressure arise from changes in the diffusion combustion rate, caused by randomly occurring in-cylinder pressure fluctuations. These fluctuations result from the excitation of the first radial mode of vibration of the cylinder gases which arises from the rapid premixed combustion after the long ignition delay period. Cycles with high-intensity fluctuations present faster diffusion combustion, resulting in higher cycle peak pressure, as well as higher measured exhaust NO concentrations.

Particle image velocimetry measurements of the in-cylinder flow in an optically accessible single-cylinder research engine were taken to better understand the effects of intake pressure variations on the flow field. At a speed of 1500 rpm, the engine was run at six different intake pressure loads from 0.4 to 0.95 bar under motored operation. The average velocity fields show that the tumble center position is located closer to the piston and velocity magnitudes decrease with increasing pressure load. A closer investigation of the intake flow near the valves reveals sharp temporal gradients and differences in maximum and minimum velocity with varying intake pressure load which are attributed to intake pressure oscillations. Despite measures to eliminate acoustic oscillations in the intake system, high-frequency pressure oscillations are shown to be caused by the backflow of air from the exhaust to the intake pipe when the valves open, exciting acoustic modes in the fluid volume.

The thorough understanding of the effects due to the fuel direct injection process in modern gasoline direct injection engines has become a mandatory task to meet the most demanding regulations in terms of pollutant emissions. Within this context, computational fluid dynamics proves to be a powerful tool to investigate how the in-cylinder spray evolution influences the mixture distribution, the soot formation and the wall impingement. In this work, the authors proposed a comprehensive methodology to simulate the air-fuel mixture formation into a gasoline direct injection engine under multiple operating conditions. At first, a suitable set of spray sub-models, implemented into an open-source code, was tested on the Engine Combustion Network Spray G injector operating into a static vessel chamber. Such configuration was chosen as it represents a typical gasoline multi-hole injector, extensively used in modern gasoline direct injection engines.

The selection and configuration of sensors can strongly influence the closed-loop dynamics of a system. Therefore a methodology for finding the best sensor placement is a valuable tool. This paper deals with this problem by formulating an optimization problem and applies the new method on an SI engine. The best sensor configuration is one that minimizes the overall system costs, yet still meets the system constraints. Before solving the optimization problem, the system is modeled, different sensor configurations are defined, the appropriate controller and the feedback term are developed, and the locations and size of the various errors present in the model are determined. Then, the objective function and the system constraints are defined and the optimization problem is solved considering the worst-case combination of modeling errors, which is computed using genetic algorithms. The objective function is defined as the sum of the sensor costs and of a penalty term.

Models for off-road vehicles, such as farm equipment and military vehicles, require an off-road tire model in order to properly understand their dynamic behavior on off-road driving surfaces. Extensive literature can be found for on-road tire modeling, but not much can be found for off-road tire modeling. This paper presents an off-road tire model that was developed for use in vehicle handling studies. An on-road, dry asphalt tire model was first developed by performing rolling road force and moment testing. Off-road testing was then performed on dirt and gravel driving surfaces to develop scaling factors that explain how the lateral force behavior of the tire will scale from an on-road to an off-road situation. The tire models were used in vehicle simulation software to simulate vehicle behavior on various driving surfaces. The simulated vehicle response was compared to actual maximum speed before sliding vs. turning radius data for the studied vehicle to assess the tire model.

Numerical simulations of diesel sprays in a constant-volume vessel have been performed with the conditional moment closure (CMC) combustion model for a broad range of conditions. On the oxidizer side these include variations in ambient temperature (800-1100 K), oxygen volume fraction (15-21%) and density (7.3-58.5 kg/m₃) and on the fuel side variation in injector orifice diameter (50-363 μm) and fuel pressure (600-1900 bar); in total 22 conditions. Results are compared to experimental data by means of ignition delay and flame lift-off length (LOL). Good agreement for both quantities is reported for the vast majority of conditions without any changes to model constants: the variations relating to the air side are quantitatively accurately predicted; for the fuel side (viz. orifice diameter and injection pressure) the trends are qualitatively well reproduced.

One seminal question that faces a vehicle's driver (either human or computer) is predicting the capability of the vehicle as it encounters upcoming terrain. A Location-Aware Adaptive Vehicle Dynamics (LAAVD) System is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. In contrast to current active safety systems, this system is predictive rather than reactive. This work provides the conceptual groundwork for the proposed system. The LAAVD System employs a predictor-corrector method in which the driver's input commands (throttle, brake, steering) and upcoming driving environment (terrain, traffic, weather) are predicted. An Intervention Strategy uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. The driver's throttle and brake control are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority.

Modern Diesel engines have become ever more complex systems with many degrees of freedom. Simultaneously, with increasing computational power, simulations of engines have become more popular, and can be used to find the optimum set up of engine operation parameters which result in the desired point in the emission-efficiency trade off. With increasing number of engine operation parameter combinations, the number of calculations increase exponentially. Therefore, adequate models for combustion and emissions with limited calculation costs are required. For obvious reasons, the accuracy of the ignition timing is a key point for the following combustion and emission model quality. Furthermore, the combination of mixing and chemical processes during the ignition delay is very challenging to model in a fast way for a wide range of operation conditions.