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The validation of an assembly of component finite element models to high frequencies is a difficult challenge. Basic steps coupled with advanced correlation techniques are required to produce system finite element models that correlate to modal test data. This paper describes those steps as they were applied to a system model of a complex transaxle.

The paper presents the development of a novel approach to the solution of detailed chemistry in internal combustion engine simulations, which relies on the analytical computation of the ordinary differential equations (ODE) system Jacobian matrix in sparse form. Arbitrary reaction behaviors in either Arrhenius, third-body or fall-off formulations can be considered, and thermodynamic gas-phase mixture properties are evaluated according to the well-established 7-coefficient JANAF polynomial form. The current work presents a full validation of the new chemistry solver when coupled to the KIVA-4 code, through modeling of a single cylinder Caterpillar 3401 heavy-duty engine, running in two-stage combustion mode.

To manage the function of a vehicle's engine, transmission, and related subsystems, almost all modern vehicles make use of one or more electronic controllers running embedded software, henceforth referred to as a Powertrain Controller System or PCS. Fully validating this PCS is a necessary step of vehicle development, and the validation process requires extensive amounts of testing. Traditionally, this validation testing is done with open-loop signal generators, powertrain dynamometers, and real vehicles. Such testing methods either cannot simulate complex control system interactions, or are expensive and subject to variability. To address these concerns while decreasing development time and improving vehicle quality, Ford Motor Company is placing increasing focus on validating a PCS through simulation. One such testing method is a Hardware-in-the-Loop (HIL) simulation, which mates the physical elements of a PCS to a real-time computer simulation of a powertrain.

A full calibration exercise of a diesel engine air path can take months to complete (depending on the number of variables). Model-based calibration approach can speed up the calibration process significantly. This paper discusses the overall calibration process of the air-path of the Cat® C7.1 engine using statistical machine learning tool. The standard Cat® C7.1 engine's twin-stage turbocharger was replaced by a VTG (Variable Turbine Geometry) as part of an evaluation of a novel air system. The changes made to the air-path system required a recalculation of the air path's boost set point and desired EGR set point maps. Statistical learning processes provided a firm basis to model and optimize the air path set point maps and allowed a healthy balance to be struck between the resources required for the exercise and the resulting data quality.

Previous research has shown that the homogeneous charge compression ignition (HCCI) combustion concept holds promise for reducing pollutants (i.e. NOx, soot) while maintaining high thermal efficiency. However, it can be difficult to control the operation of the HCCI engines even under steady state running conditions. Power density may also be limited if high inlet air temperatures are used for achieving ignition. A methodology using a small pilot quantity of diesel fuel injected during the compression stroke to improve the power density and operation control is considered in this paper. Multidimensional computations were carried out for an HCCI engine based on a CAT3401 engine. The computations show that the required initial temperature for ignition is reduced by about 70 K for the cases of the diesel pilot charge and a 25∼35% percent increase in power density was found for those cases without adversely impacting the NOx emissions.

Vehicle idle quality has become an increasing quality concern for automobile manufacturers because of its impact on customer satisfaction. There are two factors that critical to vehicle idle quality, the engine excitation force and vehicle sensitivity (transfer function). To better understand the contribution to the idle quality from these two factors and carry out well-planned improvement measures, a quick and easy way to measure vehicle sensitivity at idle conditions is desired. There are several different ways to get vehicle sensitivity at idle conditions. A typical way is to use CAE. One of the biggest advantages using CAE is that it can separate vehicle sensitivities to different forcing inputs. As always, the CAE results need to be validated before being fully utilized. Another way to get vehicle sensitivity is through impact test using impact hammer or shaker. However this method doesn't include the mount preload due to engine firing torque [3, 4, & 5].

This paper reviews the engine modeling program in the Powertrain Control Research Laboratory at the University of Wisconsin-Madison, focuses on simulation results obtained from a complete modular turbocharged diesel engine dynamic model developed in this lab, and suggests ways that dynamic engine system models can be used in the design process. It examines the dynamic responses and interactions between various components in the engine system, looks at how these components affect the overall performance of the system in transient and steady state operation.

The air-hybrid engine absorbs the vehicle kinetic energy during braking, puts it into storage in the form of compressed air, and reuses it to assist in subsequent vehicle acceleration. In contrast to electric hybrid, the air hybrid does not require a second propulsion system. This approach provides a significant improvement in fuel economy without the electric hybrid complexity. The paper explores the fuel economy potential of an air hybrid engine by presenting the modeling results of a 2.5L V6 spark-ignition engine equipped with an electrohydraulic camless valvetrain and used in a 1531 kg passenger car. It describes the engine modifications, thermodynamics of various operating modes and vehicle driving cycle simulation. The air hybrid modeling projected a 64% and 12% of fuel economy improvement over the baseline vehicle in city and highway driving respectively.

Bluetooth Low Energy (BLE) is an energy-efficient radio communication technology that is rapidly gaining popularity for various Internet of Things (IoT) applications. While BLE was not designed specifically with vehicular communications in mind, its simple and quick connection establishment mechanisms make BLE a potential inter-vehicle communication technology, either replacing or complementing other vehicle-to-vehicle (V2V) technologies (such as the yet to be deployed DSRC). In this paper we propose a framework for V2V communication using BLE and evaluate its performance under various configurations. BLE uses two major methods for data transmission: (1) undirected advertisements and scanning (unconnected mode) and (2) using the central and peripheral modes of the Generic Attribute Profile (GATT) connection (connected mode).

Reactivity-controlled compression ignition (RCCI) has been shown to be capable of providing improved engine efficiencies coupled with the benefit of low emissions via in-cylinder fuel blending. Much of the previous body of work has studied the benefits of RCCI operation using high injection pressures (e.g., 500 bar or greater) with common rail injection (CRI) hardware. However, low-pressure fueling technology is capable of providing significant cost savings. Due to the broad market adoption of gasoline direct injection (GDI) fueling systems, a market-type prototype GDI injector was selected for this study. Single-cylinder light-duty engine experiments were undertaken to examine the performance and emissions characteristics of the RCCI combustion strategy with low-pressure GDI technology and compared against high injection pressure RCCI operation. Gasoline and diesel were used as the low-reactivity and high-reactivity fuels, respectively.

Accurate prediction of engine combustion characteristics, especially burn rates, can eliminate a number of hardware iterations, thus resulting in a significant reduction in design and developmental time and cost. An analytical methodology has been developed which allows the determination of part-load MBT spark timing to within 2 crank-angle degrees. The design methodology employs the in-house-developed steady-state quasi-dimensional engine simulation model (GESIM), coupled with full-field measurement of the in-cylinder fluid motion at bottom dead center (BDC) in the computer-controlled water analog system (AquaDyne). The in-cylinder flow-field measurements are obtained using 3-D Particle Tracking Velocimetry (3-D PTV), also developed in-house. In this methodology, the in-cylinder flow measurement data are used to calibrate both the tumble and swirl models in GESIM.

Previously fuel consumption on a drive cycle has been shown to be proportional to traction work, with an offset for powertrain losses. This model had different transfer functions for different drive cycles, performance levels, and applied powertrain technologies. Following Soltic it is shown that if fuel usage and traction work are both expressed in terms of cycle average power, a wide range of drive cycles collapse to a single transfer function, where cycle average traction power captures the drive cycle and the vehicle size. If this transfer function is then normalized by weight, i.e. by working in cycle average power/weight (P/W), a linear model is obtained where the offset is mainly a function of rated performance and applied technology. A final normalization by rated power/weight as the primary performance metric further collapses the data to express the cycle average fuel power/rated power ratio as a function of cycle average traction power/rated power ratio.

The previously developed power-based fuel consumption theory for Internal Combustion Engine Vehicles (ICEV) is extended to Battery Electric Vehicles (BEV). The main difference between the BEV model structure and the ICEV is the bi-directional character of traction motors and batteries. A traction motor model was developed as a bi-linear function of positive and negative traction power. Another difference is that the accessories and cabin heating are powered directly from the battery, and not from the powertrain. The resulting unified model for ICEV and BEV energy consumption has linear terms proportional to positive and negative traction power, accessory power, and overhead, in varying proportions. Compared to the ICEV, the BEV powertrain has a high marginal efficiency and low overhead. As a result, BEV energy consumption data under a wide range of driving conditions are mainly proportional to net traction power, with only a small offset.

Variable Cam Timing (VCT) has been proven to be a very effective method in PFI (Port Fuel Injection) engines for improved fuel economy and combustion stability, and reduced emissions. In DISI (Direct Injection Spark Ignition) engines, VCT is applied in both stratified-charge and homogeneous charge operating modes. In stratified-charge mode, VCT is used to reduce NOx emission and improve combustion stability. In homogeneous charge mode, the function of VCT is similar to that in PFI engines. In DISI engine, however, the VCT also affects the available fuel-air mixing time. This paper focuses on VCT effects on the induction process and the fuel-air mixing homogeneity in a DISI engine. The detailed induction process with large exhaust-intake valve overlap has been investigated with CFD modeling. Seven characteristic sub-processes during the induction have been identified. The associated mechanism for each sub-process is also investigated.

Fundamental understanding of the sources of fuel-derived Unburned Hydrocarbon (UHC) emissions in heavy duty diesel engines is a key piece of knowledge that impacts engine combustion system development. Current emissions regulations for hydrocarbons can be difficult to meet in-cylinder and thus after treatment technologies such as oxidation catalysts are typically used, which can be costly. In this work, Computational Fluid Dynamics (CFD) simulations are combined with engine experiments in an effort to build an understanding of hydrocarbon sources. In the experiments, the combustion system design was varied through injector style, injector rate shape, combustion chamber geometry, and calibration, to study the impact on UHC emissions from mixing-controlled diesel combustion.

Advanced features in automotive systems often necessitate the management of complex interactions between subsystems. Existing control strategies are designed for certain levels of robustness, however their performance can unexpectedly deteriorate in the presence of significant uncertainties, resulting in undesirable system behaviors. This limitation is further amplified in systems with complex nonlinear dynamics. Hydro-mechanical clutch actuators are among those systems whose behaviors are highly sensitive to variations in subsystem characteristics and operating environments. In a P2 hybrid propulsion system, a wet clutch is utilized for cranking the engine during an EV-HEV mode switching event. It is critical that the hydro-mechanical clutch actuator is stroked as quickly and as consistently as possible despite the existence of uncertainties. Thus, the quantification of uncertainties on clutch actuator behaviors is important for enabling smooth EV-HEV transitions.

The sources of unburned hydrocarbon (UHC) emissions in direct injection stratified charge engines are presented. Whereas crevices in the combustion chamber are the primary sources of UHC emissions in homogeneous charge engines, lean quenching and liquid film layers dominate UHC emissions in stratified charge operation. Emissions data from a single cylinder engine, operating in stratified charge mode at a low speed / light load condition is summarized. This operating point is interesting in that liquid film formation, as evidenced by smoke emissions, is minimal, thus highlighting the lean quenching process. The effects of operating parameters on UHC emissions are demonstrated via sweeps of spark advance, injection timing, manifold pressure, and swirl level. The effects of EGR dilution are also discussed. Spark advance is shown to be the most significant factor in UHC emissions. A semi-empirical model for UHC emissions is presented based on the analysis of existing engine data.

Wet clutch packs are widely used in today’s automatic transmission systems for gear-ratio shifting. The frictional interfaces between the clutch plates are continuously lubricated with transmission fluid for both thermal and friction management. The open clutch packs shear transmission fluid across the rotating plates, contributing to measurable energy losses. A typical multi-speed transmission includes as many as 5 clutch packs. Of those, two to three clutches are open at any time during a typical drive cycle, presenting an opportunity for fuel economy gain. However, reducing open clutch drag is very challenging, while meeting cooling requirements and shift quality targets. In practice, clutch design adjustment is performed through trial-and-error evaluation of hardware on a test bench. The use of analytical methodologies is limited for optimizing clutch design features due to the complexity of fluid-structure interactions under rotating conditions.

Two-Color imaging optics were developed and used to observe soot emission processes in a modern heavy-duty diesel engine. The engine was equipped with a common rail, electronically-controlled, high-pressure fuel injection system that is capable of up to four injection pulses per engine cycle. The engine was instrumented with an endoscope system for optical access for the combustion visualization. Multidimensional combustion and soot modeling results were used for comparisons to enhance the understanding and interpretation of the experimental data. Good agreement between computed and measured cylinder pressures, heat release and soot and NOx emissions was achieved. In addition, good qualitative agreement was found between in-cylinder soot concentration (KL) and temperature fields obtained from the endoscope images and those obtained from the multidimensional modeling.

An experimental study of luminous combustion in a modern diesel engine was performed to investigate the effect of injection parameters on NOX and soot formation via flame temperature and soot KL factor measurements. The two-color technique was applied to 2-D soot luminosity images and area-averaged soot radiation signals to obtain spatially and temporally resolved flame temperature and soot KL factor. The imaging system used for this study was based on a wide-angle endoscope that was mounted in the cylinder head and allowed different views of the combustion chamber. The experiments were carried out on a single-cylinder 2.4 liter D.I. diesel engine equipped with an electronically controlled common-rail injection system. Operating conditions were 1600 rpm and 75% load. The two-color results confirm that retarding the injection timing causes lower flame temperatures and NOX emissions but increased soot formation, independent of injection strategy.