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Tremendous amount of useful information can be extracted from the cylinder pressure signal for engine combustion control. However, the physical cylinder pressure sensors are undesirably expensive and their health need to be monitored for fault diagnostic purpose as well. This paper presents the results of the development of a virtual cylinder pressure sensor (VCPS) with individual variable-oriented independent estimators. Two neural network-based independent cylinder pressure related variable estimators were developed and verified at steady state. The results show that these models can predict the variables correctly compared with the extracted variables from the measured physical cylinder pressure sensor signal. Good generalization capabilities of the developed models are observed in the sense that the models work well not only for the training data set but also for the new inputs that they have never been exposed to before.

A generalized re-normalization group (RNG) turbulence model based on the local "dimensionality" of the flow field is proposed. In this modeling approach the model coefficients C₁, C₂, and C₃ are all constructed as functions of flow strain rate. In order to further validate the proposed turbulence model, the generalized RNG closure model was applied to model the backward facing step flow (a classic test case for turbulence models). The results indicated that the modeling of C₂ in the generalized RNG closure model is reasonable, and furthermore, the predictions of the generalized RNG model were in better agreement with experimental data than the standard RNG turbulence model. As a second step, the performance of the generalized RNG closure was investigated for a complex engine flow.

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.

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 Exhaust Composition Transient Operation LaboratoryTM (ECTO-LabTM) is a burner system developed at Southwest Research Institute (SwRI) for simulation of IC engine exhaust. The current system design requires metering and combustion of nitromethane in conjunction with the primary fuel source as the means of NOX generation. While this method affords highly tunable NOX concentrations even over transient cycles, no method is currently in place for dictating the speciation of nitric oxide (NO) and nitrogen dioxide (NO2) that constitute the NOX mixture. NOX generated through combustion of nitromethane is dominated by NO, and generally results in an NO2:NOX ratio of < 5 %. Generation of any appreciable quantities of NO2 is therefore dependent on an oxidation catalyst to oxidize a fraction of the NO to NO2.

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.

Transmission spin loss has significant influence on the vehicle fuel economy. Transmission output chain may contribute up to 10~15% of the total spin loss. However, the chain spin loss information is not well documented. An experimental study was carried out with several transmission output chains and simulated transmission environment in a testing box. The studies build the bases for the chain spin loss modeling and depicted the influences of the speed, the sprocket sizes, the oil levels, the viscosity, the temperatures and the baffle. The kriging method was employed for the parameter sensitivity study. A closed form of empirical model was developed. Good correlation was achieved.

This paper presents a response to the question: Simulation - mathematical manipulation or useful design tool? A mathematical model of a modulating valve in a transmission control system was developed to predict clutch pressure modulation characteristics. The transmission control system was previously reported in SAE Paper 850783 - “Electronic/Hydraulic Transmission Control System for Off-Highway Vehicles”. The comparison of simulation predictions with test data illustrates the effectiveness of simulation as a design tool. THE EVOLUTION OF COMPUTER hardware and simulation software has resulted in increased interest and usage of simulation for dynamic analysis of hydraulic systems. Most commercially available software is relatively easy to learn to use. The application of such software and the modeling techniques involved require a longer learning curve.

This paper reports on a comprehensive, crank-angle transient, three dimensional, computational fluid dynamics (CFD) model of the complete lubrication system of a multi-cylinder engine using the CFD software Simerics-Sys / PumpLinx. This work represents an advance in system-level modeling of the engine lubrication system over the current state of the art of one-dimensional models. The model was applied to a 16 cylinder, reciprocating internal combustion engine lubrication system. The computational domain includes the positive displacement gear pump, the pressure regulation valve, bearings, piston pins, piston cooling jets, the oil cooler, the oil filter etc… The motion of the regulation valve was predicted by strongly coupling a rigorous force balance on the valve to the flow.

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.

The development of analytic models of diesel engine flow, combustion and subprocesses is described. The models are intended for use as design tools by industry for the prediction of engine performance and emissions to help reduce engine development time and costs. Part of the research program includes performing engine experiments to provide validation data for the models. The experiments are performed on a single-cylinder version of the Caterpillar 3406 engine that is equipped with state-of-the-art high pressure electronic fuel injection and emissions instrumentation. In-cylinder gas velocity and gas temperature measurements have also been made to characterize the flows in the engine.

Verification and validation (V&V) is an enabling methodology for the development of models that can be used to make engineering predictions with high confidence. Model V&V procedures are needed by government and industry to reduce the time, cost and danger associated with component and full-scale testing of products, materials, and weapons. The development of guidelines and procedures for conducting a V&V program are currently being defined by a broad spectrum of researchers. This paper briefly reviews the main concepts involved in V&V and then focuses on the critical role that nondeterministic analysis plays in the V&V process.

An electronically controlled Caterpillar single-cylinder oil test engine (SCOTE) was used to study diesel combustion. The SCOTE retains the port, combustion chamber, and injection geometry of the production six cylinder, 373 kW (500 hp) 3406E heavy-duty truck engine. The engine was equipped with an electronic unit injector and an electronically controlled common rail injector that is capable of multiple injections. An emissions investigation was carried out using a six-mode cycle simulation of the EPA Federal Transient Test Procedure. The results show that the SCOTE meets current EPA mandated emissions levels, despite the higher internal friction imposed by the single-cylinder configuration. NOx versus particulate trade-off curves were generated over a range of injection timings for each mode and results of heat release calculations were examined, giving insight into combustion phenomena in current “state of the art” heavy-duty diesel engines.

China has become the world’s largest vehicle market in terms of sales volume. Automobiles sales keep growing in recent years despite the declining economic growth rate. Due to the increasing attention given to the environmental impact, more stringent emission regulations are being drafted to control traditional internal combustion engine emissions. In order to reduce vehicle emissions, environmentally-friendly new-energy vehicles, such as electric vehicles and plug-in hybrid vehicles, are being promoted by government policies. The Chinese government plans to boost sales of new-energy cars to account for about five percent of China’s total vehicle sales. It is well known that more electric and electronic components will be integrated into a vehicle platform during vehicle electrification.

For competition in the 1998 FutureCar Challenge (FCC98), the University of Wisconsin - Madison FutureCar Team has designed and built a lightweight, charge sustaining, parallel hybrid electric vehicle by modifying a 1994 Mercury Sable Aluminum Intensive Vehicle (AIV), nicknamed the Aluminum Cow. The Wisconsin team is striving for a combined, FTP cycle gasoline-equivalent fuel economy of 21.3 km/L (50 mpg) and Ultra Low Emissions Vehicle (ULEV) federal emissions levels while maintaining the full passenger/cargo room, appearance, and feel of a full-size car. To reach these goals, Wisconsin has concentrated on reducing the overall vehicle weight. In addition to customizing the drivetrain, the team has developed a vehicle control strategy that both aims to achieve these goals and also allows for the completion of a reliable hybrid in a short period of time.

Simulation is a useful tool which can significantly reduce resources invested during product development. Vehicle manufacturers are using simulations to aid in the evaluation of designs and components, including powertrain systems and controllers. These simulations can be made more useful by addressing issues such as flexibility, modularity, and causality. These issues and other aspects involved in the development and use of powertrain system simulations are discussed in this paper, and a case study of a powertrain system model developed in the PCRL using methodologies based on considerations of such issues is presented.

An integrated numerical model has been developed for diesel engine computations based on the KIVA-II code. The model incorporates a modified RNG k-ε, turbulence model, a ‘wave’ breakup spray model, the Shell ignition model, the laminar-and-turbulent characteristic-time combustion model, a crevice flow model, a spray/wall impingement model that includes rebounding and breaking-up drops, and other improved submodels in the KIVA code. The model was validated and applied to model successfully different types of diesel engines under various operating conditions. These engines include a Caterpillar engine with different injection pressures at different injection timings, a small Tacom engine at different loads, and a Cummins engine modified by Sandia for optical experiments. Good levels of agreement in cylinder pressures and heat release rate data were obtained using the same computer model for all engine cases.

Over twenty prototype hybrid buses and other commercial vehicles are currently being completed and deployed. These vehicles are primarily “series” hybrid vehicles which use electric motors for primary traction while internal combustion engines, or high-speed turbine engines connected to generators, supply some portion of the electric propulsion and battery recharge energy. Hybrid-electric vehicles have an electric energy storage system on board that influences the operation of the heat engine. The storage system design and level affect the vehicle emissions, electricity consumption, and fuel economy. Existing heavy-duty emissions test procedures require that the engine be tested over a transient cycle before it can be used in vehicles (over 26,000 lbs GVW). This paper describes current test procedures for assessing engine and vehicle emissions, and proposes techniques for evaluating engines used with hybrid-electric vehicle propulsion systems.

Boundary element analysis (BEA) is an effective computer simulation program for certain applications in design engineering. The BEA technique has been used extensively at Caterpillar for structural analysis of engine and vehicle components. The time savings and modeling ease of BEA are illustrated with specific examples of engine component models. These examples represent a variety of modeling techniques, and include comparisons with measured test data.

A new generation of vehicle dynamics and powertrain control technologies are being developed to leverage information streams enabled via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity [1, 2, 3, 4, 5]. While algorithms that use these connected information streams to enable improvements in energy efficiency are being studied in detail, methodologies to quantify and analyze these improvements on a vehicle have not yet been explored fully. A procedure to test and accurately measure energy-consumption benefits of a connected and automated vehicle (CAV) is presented. The first part of the test methodology enables testing in a controlled environment. A traffic simulator is built to model traffic flow in Fort Worth, Texas with sufficient accuracy. The benefits of a traffic simulator are two-fold: (1) generation of repeatable traffic scenarios and (2) evaluation of the robustness of control algorithms by introducing disturbances.