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Powertrain and vehicle technology is rapidly changing to meet the ever increasing demands of customers and government regulations. In some cases technologies that are designed to improve one attribute may impact others or interact with other design decisions in unexpected ways. Understanding the interactions and optimizing the transient performance at the vehicle level may require controls and calibration that is not available until late in the vehicle development process, after hardware changes are no longer possible. As a result, an efficient, up front, CAE process for assessing the interaction of various design choices on transient vehicle behavior is desirable. Building, calibrating and validating a vehicle system model with full controls and a mature calibration is very time consuming and often requires significant experimental data that is not available until it is too late to make hardware changes.

For diesel engines to meet current and future emissions levels, the amount of EGR required to reach these levels has increased dramatically. This increased EGR has posed big challenges for conventional turbocharger technology to meet the higher emissions requirements while maintaining or improving other vehicle attributes, to the extent that some OEMs resort to multiple turbocharger configurations. These configurations can include parallel, series sequential, or parallel - series turbocharger systems, which would inevitably run into other issues, such as cost, packaging, and thermal loss, etc. This study, as part of a U.S. Department of Energy (USDoE) sponsored research program, is focused on the experimental evaluation of the emission and performance of a modern diesel engine with an advanced single stage turbocharger.

Optimization of the engine cold start is critical for gasoline direct injection (GDI) engines to meet increasingly stringent emission regulations, since the emissions during the first 20 seconds of the cold start constitute more than 80% of the hydrocarbon (HC) emissions for the entire EPA FTP75 drive cycle. However, Direct Injection Spark Ignition (DISI) engine cold start optimization is very challenging due to the rapidly changing engine speed, cold thermal environment and low cranking fuel pressure. One approach to reduce HC emissions for DISI engines is to adopt retarded spark so that engines generate high heat fluxes for faster catalyst light-off during the cold idle. This approach typically degrades the engine combustion stability and presents additional challenges to the engine cold start. This paper describes a CFD modeling based approach to address these challenges for the Ford 3.5L V6 EcoBoost engine cold start.

Advancing intake valve timing shortly after engine crank and run-up can potentially reduce vehicle cold start hydrocarbon (HC) emissions in port fuel injected (PFI) engines equipped with intake variable cam timing (iVCT). Due to the cold metal temperatures, there can be significant accumulation of liquid fuel in the intake system and in the cylinder. This accumulation of liquid fuel provides potential sources for unburned hydrocarbons (HCs). Since the entire vehicle exhaust system is cold, the catalyst will not mitigate the release of unburned HCs. By advancing the intake valve timing and increasing valve overlap, liquid fuel vaporization in the intake system is enhanced thereby increasing the amount of burnable fuel in the cylinder. This increase in burnable HCs must be countered by a reduction in injector-delivered fuel via a compensator that reacts to cam movement.

As regulations become more stringent, transient fuel control becomes extremely important for meeting emissions requirements in a cost-effective manner. Significant modeling work has been performed for a variety of conventional gasolines in port fuel injected (PFI) engines. This paper describes an extension of previous modeling work for alternative fuels. The paper first details the application of a distillation model to create the multi-component fuel models used in the simulations. The fuel models are then used in the transient Four Puddle Model to simulate the coupled liquid fuel and thermal/thermodynamic processes in the engine. Simulation results from the model are compared with dynamometer data over a transient, warm-up test.

Ethanol is one of many alternative transportation fuels that can be burned in internal combustion engines in the same ways as gasoline and diesel. Compared to hydrogen and electric energy, ethanol is very similar to gasoline in many aspects and can be delivered to end-users by the same infrastructures. It can be produced from biomass and is considered renewable. It is expected that the improvement in fuels over the next 20 years will be by blending biomass-based fuels with fossil fuels using existing technologies in present-day automobiles with only minor modifications, even though the overall costs of using biomass-based fuels are still considerably higher than conventional fuels. Ethanol may represent a significant alternative fuel source, especially during the transition from fossil-based fuels to more exotic power sources. Mapping engines for flexible fuel vehicles (FFV), however, would be very costly and time consuming, even with the help of model-based engine mapping (MBM).

A model has been developed to predict quantitatively the results of the ASTM D86 fuel distillation procedure. The model uses material and energy balances to treat the procedure as a two stage unsteady-state distillation coupled with an air-filled continuous stirred-tank reactor (CSTR). Heat is removed from the second stage to simulate convection losses from the experimental apparatus. The model requires as inputs the fuel composition and the physical properties of all components (vapor phase heat capacity, vapor pressure, critical properties, density, molecular weight, solubility parameter). Correlations were used to approximate other needed properties. Liquid-phase activity coefficients were calculated with the UNIFAC model. Heat losses were modeled with a correlation from the literature. The model was validated by comparing predictions to experimental measurements on a seven-component model fuel. Agreement was extremely good across the entire range of volume fractions distilled.