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This collection is a resource for studying the history of the evolving technologies that have contributed to snowmobiles becoming cleaner and quieter machines. Papers address design for a snowmobile using the EPA test procedure and standard for off-road vehicles, along with more stringent U.S. National Park Best Available Technology (BAT) standards that are likened to those of the California Air Resourced Board (CARB). Innovative technology solutions include: • Standard application for diesel engine designs • Applications to address and test both engine and track noise • Benefits of the Miller cycle and turbocharging The SAE International Clean Snowmobile Challenge (CSC) program is an engineering design competition. The program provides undergraduate and graduate students the opportunity to enhance their engineering design and project management skills by reengineering a snowmobile to reduce emissions and noise.

This collection is a resource for studying the history of the evolving technologies that have contributed to snowmobiles becoming cleaner and quieter machines. Papers address design for a snowmobile using E10 gasoline (10% ethanol mixed with pump gasoline). Performance technologies that are presented include: • Engine Design: application of the four-stroke engine • Applications to address both engine and track noise • Exhaust After-treatment to reduce emissions The SAE International Clean Snowmobile Challenge (CSC) program is an engineering design competition. The program provides undergraduate and graduate students the opportunity to enhance their engineering design and project management skills by reengineering a snowmobile to reduce emissions and noise. The competition includes internal combustion engine categories that address both gasoline and diesel, as well as the zero emissions category in which range and draw bar performance are measured.

Spray structure has a significant effect on emissions and performance of an internal combustion engine. The main objective of this study is to investigate spray structures based on four different multiple jet impingement injectors. These four different multiple jet-to-jet impingement injectors include 1). 4-hole injector (Case 1), which has symmetric inwardly opening nozzles; 2). 5-1-hole (Case 2); 3). 6-2-hole (Case 3); and 4). 7-3-hole (Case 4) which corresponding to 1, 2, 3 numbers of adjacent holes blocked in a 5-hole, 6-hole, and 7-hole symmetrical drill pattern, respectively. All these configurations are basically 4-holes but with different post collision spray structure. Computational Fluid Dynamics (CFD) work of these sprays has been performed using an Eulerian-Lagrangian modelling approach.

Exergy or availability is the potential of a system to do work. In this paper, an innovative exergy-based control approach is presented for Internal Combustion Engines (ICEs). An exergy model is developed for a Homogeneous Charge Compression Ignition (HCCI) engine. The exergy model is based on quantification of the Second Law of Thermodynamic (SLT) and irreversibilities which are not identified in commonly used First Law of Thermodynamics (FLT) analysis. An experimental data set for 175 different ICE operating conditions is used to construct the SLT efficiency maps. Depending on the application, two different SLT efficiency maps are generated including the applications in which work is the desired output, and the applications where Combined Power and Exhaust Exergy (CPEX) is the desired output. The sources of irreversibility and exergy loss are identified for a single cylinder Ricardo HCCI engine.

A wide variety of spray models and their associated sub-models exist to assist with numerical spray development studies in the many applicable areas viz., turbines, internal combustion engines etc. The accuracy of a simulation when compared to the experiments varies, as these models chosen are varied. Also, the computational grid plays a crucial role in model correctness; a grid-converged CFD study is more valuable and assists in proper validation at later stages. Of primary relevance to this paper are the combustion models for a grid-converged Lagrangian spray modeling scenario. CONVERGE CFD code is used for simulation of split injection diesel (n-heptane) sprays and a structured methodology, using RNG k-ε turbulence model, is followed to obtain a grid-converged solution for the key Computational Fluid Dynamics (CFD) parameters viz., grid size, injected parcels and spray break-up time constant.

Vehicle operation during cold-start powertrain conditions can have a significant impact on drivability, fuel economy and tailpipe emissions in modern passenger vehicles. As efforts continue to maximize fuel economy in passenger vehicles, considerable engineering resources are being spent in order to reduce the consumption penalties incurred shortly after engine start and during powertrain warmup while maintaining suitably low levels of tailpipe emissions. Engine downsizing, advanced transmissions and hybrid-electric architecture can each have an appreciable effect on cold-start strategy and its impact on fuel economy. This work seeks to explore the cold-start strategy of several passenger vehicles with different powertrain architectures and to understand the resulting fuel economy impact relative to warm powertrain operation. To this end, four vehicles were chosen with different powertrain architectures.

Many of today's advanced simulation tools are suitable for modeling specific systems, but they provide rather limited support for automated model building and management. The diverse tools available for modeling different components of a vehicle make it all the more challenging to comprehend their integration and interactions and analyze the complete system. In addition, the complexities and sizes of the models require a better use of computing resources, such as multicore or remote processing, to greatly reduce the simulation time. In this paper we describe how modern software techniques can support modeling and design activities, with the objective to create system models quickly by assembling them in a “plug-and-play” architecture. System models can be integrated, co-simulated, and reused regardless of the environment in which they are developed, and their simulation results can be consolidated for analysis into a single tool.

Global Sensitivity Analysis (GSA) is conducted for a diesel engine simulation to understand the sensitivities of various modeling constants and boundary conditions in a global manner with regards to multi-target functions such as liquid length, ignition delays, combustion phasing, and emissions. The traditional local sensitivity analysis approach, which involves sequential perturbation of model constants, does not provide a complete picture since all the parameters can be uncertain. However, this approach has been studied extensively and is advantageous from a computational point of view. The GSA simultaneously incorporates the uncertainty information for all the relevant boundary conditions, modeling constants, and other simulation parameters. A global analysis is particularly useful to address the important parameters in a model where the response of the targets to the values of the variables is highly non-linear.

The ability to operate a spark-ignition (SI) engine near the knock limit provides a net reduction of engine fuel consumption. This work presents a real-time knock control system based on stochastic knock detection (SKD) algorithm. The real-time stochastic knock control (SKC) system is developed in MATLAB Simulink, and the SKC software is integrated with the production engine control strategy through ATI's No-Hooks. The SKC system collects the stochastic knock information and estimates the knock level based on the distribution of knock intensities fitting to a log-normal (LN) distribution. A desired knock level reference table is created under various engine speeds and loads, which allows the SKC to adapt to changing engine operating conditions. In SKC system, knock factor (KF) is an indicator of the knock intensity level. The KF is estimated by a weighted discrete FIR filter in real-time.

Energy management is one of the key challenges for the development of Hybrid Electric Vehicle (HEV) due to its complex powertrain structure. Hardware-In-the-Loop (HIL) simulation provides an open software architecture which enables rapid prototyping HEV energy management system. This paper presents the investigation of the energy management system for a single shaft parallel hybrid electric vehicle using dSPACE eDrive HIL system. The parallel hybrid electric vehicle, energy management system, and low-level Electronic Control Unit (ECU) were modeled using dSPACE Automotive Simulation Models and dSPACE blocksets. Vehicle energy management is achieved by a vehicle-level controller called hybrid ECU, which controls vehicle operation mode and torque distribution among Internal Combustion Engine (ICE) and electric motor. The individual powertrain components such as ICE, electric motor, and transmission are controlled by low-level ECUs.

Diesel combustion and emissions formation is spray and mixing controlled and understanding spray parameters is key to determining the impact of fuel injector operation and nozzle design on combustion and emissions. In this study, both spray visualization and computational fluid dynamics (CFD) modeling were undertaken to investigate key mechanisms for liquid length fluctuations. For the experimental portion of this study a common rail piezoelectric injector was tested in an optically accessible constant volume combustion vessel. Liquid penetration of the spray was determined via processing of images acquired from Mie back scattering under vaporizing conditions by injecting into a charge gas at elevated temperature with a 0% oxygen environment. Tests were undertaken at a gas density of 34.8 kg/m₃, 2000 bar injection pressure, and at ambient temperatures of 900, 1100, and 1300 K.

Numerical modeling of aftertreatment systems has been proven to reduce development time as well as to facilitate understanding of the internal physical and chemical processes occurring during different operating conditions. Such a numerical model for a catalyzed diesel particulate filter (CPF) was developed in this research work which has been improved from an existing numerical model briefly described in reference. The focus of this CPF model was to predict the effect of the catalyst on the gaseous species concentrations and to develop particulate matter (PM) filtration and oxidation models for the PM cake layer and substrate wall so as to develop an overall model that accurately predicts the pressure drop and PM oxidized during passive oxidation and active regeneration. Descriptions of the governing equations and corresponding numerical methods used with relevant boundary conditions are presented.

A numerical simulation of autoignition of gasoline-ethanol/air mixtures has been performed using the closed homogeneous reactor model in CHEMKIN® to compute the dependence of autoignition time with ethanol concentration, pressure, temperature, dilution, and equivalence ratio. A semi-detailed validated chemical kinetic model with 142 species and 672 reactions for a gasoline surrogate fuel with ethanol has been used. The pure components in the surrogate fuel consisted of n-heptane, isooctane and toluene. The ethanol volume fraction is varied between 0 to 85%, initial pressure is varied between 20 to 60 bar, initial temperature is varied between 800 to 1200K, and the dilution is varied between 0 to 32% at equivalence ratios of 0.5, 1.0 and 1.5 to represent the in-cylinder conditions of a spark-ignition engine. The ignition time is taken to be the point where the rate of change of temperature with respect to time is the largest (temperature inflection point criteria).

One-dimensional simulation methods for unsteady (transient) engine operations have been developed and published in previous studies. These 1-D methods utilize heat release and emissions results obtained from 3-D CFD simulations which are stored in a data library. The goal of this study is to improve the 1-D methodology by optimizing the control strategies. Also, additional independent parameters are introduced to extend the 3-D data library, while, as in the previous studies, the number of interpolation points for each parameter remains small. The data points for the 3-D simulations are selected in the vicinity of the expected trajectories obtained from the independent parameter changes, as predicted by the transient 1-D simulations. By this approach, the number of time-consuming 3-D simulations is limited to a reasonable amount.

Lookup tables and functions are widely used in real-time embedded automotive applications to conserve scarce processor resources. To minimize the resource utilization, these lookup tables (LUTs) commonly use custom data structures. The lookup function code is optimized to process these custom data structures. The legacy routines for these lookup functions are very efficient and have been in production for many years. These lookup functions and the corresponding data structures are typically used for calibration tables. The third-party calibration tools are specifically tailored to support these custom data structures. These tools assist the calibrators in optimizing the control algorithm performance for the targeted environment for production. Application software typically contains a mix of both automatically generated software and manually developed code. Some of the same calibration tables may be used in both auto generated and hand-code [ 1 ] [ 2 ].

Environmental awareness and fuel economy legislation has resulted in greater emphasis on developing more fuel efficient vehicles. As such, achieving fuel economy improvements has become a top priority in the automotive field. Companies are constantly investigating and developing new advanced technologies, such as hybrid electric vehicles, plug-in hybrid electric vehicles, improved turbo-charged gasoline direct injection engines, new efficient powershift transmissions, and lighter weight vehicles. In addition, significant research and development is being performed on energy management control systems that can improve fuel economy of vehicles. Another area of research for improving fuel economy and environmental awareness is based on improving the customer's driving behavior and style without significantly impacting the driver's expectations and requirements.

Diesel particulate trap regeneration is a complex process involving the interaction of phenomena at several scales. A hierarchy of models for the relevant physicochemical processes at the different scales of the problem (porous wall, filter channel, entire trap) is employed to obtain a rigorous description of the process in a multidimensional context. The final model structure is validated against experiments, resulting in a powerful tool for the computer-aided study of the regeneration behavior. In the present work we employ this tool to address the effect of various spatial non-uniformities on the regeneration characteristics of diesel particulate traps. Non-uniformities may include radial variations of flow, temperature and particulate concentration at the filter inlet, as well as variations of particulate loading. In addition, we study the influence of the distribution of catalytic activity along the filter wall.

Wall-flow Diesel particulate filters operating at low filtration velocities usually exhibit a linear dependence between the filter pressure drop and the flow rate, conveniently described by a generalized Darcy's law. It is advantageous to minimize filter pressure drop by sizing filters to operate within this linear range. However in practice, since there often exist serious constraints on the available vehicle underfloor space, a vehicle manufacturer is forced to choose an “undersized” filter resulting in high filtration velocities through the filter walls. Since secondary inertial contributions to the pressure drop become significant, Darcy's law can no longer accurately describe the filter pressure drop. In this paper, a systematic investigation of these secondary inertial flow effects is presented.

This paper details the computer algorithm which was developed to determine the A/C refrigeration circuit balance point under the system transient operating conditions. The A/C circuit model consisting of major component submodels, such as the evaporator, compressor, condenser, orifice, air handling system, and connecting hoses, are included in the study. Pressure drop and thermal capacity for the evaporator, condenser, and connecting ducts/hoses are also considered in the simulation. The results obtained from the simulation model are in good agreement with the experimental data. Users can take advantage of this CAE tool to optimize the A/C system design and to minimize the development process with time-saving and cost-effective perspectives.

A Computer-Aided Engineering (CAE) model for automobile climate control system is presented to provide engineers with an cost effective analysis tool for designing, developing, and optimizing the vehicle interior climate. It is the objective of this paper to develop a mathematical model which predicts the lumped temperature and lumped humidity variations inside the passenger compartment under design and operating conditions. The transient nature of the passenger cabin temperature, average interior mass temperature, and humidity are modeled using three coupled non-linear ordinary differential equations based on mass and energy balances. These equations are then solved by a fourth-order Runge-Kutta method with adaptive step size control.