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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. Innovative technology solutions include: • Engine Design: improving the two-stroke, gas direct injection (GDI) engine • Applications of new muffler designs and a catalytic converter • Solving flex-fuel design and engine power problems 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.

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.

Vehicles with power exporting capability are microgrids since they possess electrical power generation, onboard loads, energy storage, and the ability to interconnect. The unique load and silent watch requirements of some military vehicles make them particularly well-suited to augment stationary power grids to increase power resiliency and capability. Connecting multiple vehicles in a peer-to-peer arrangement or to a stationary grid requires scalable power management strategies to accommodate the possibly large numbers of assets. This paper describes a military ground vehicle power management scheme for vehicle-to-grid applications. The particular focus is overall fuel consumption reduction of the mixed asset inventory of military vehicles with diesel generators typically used in small unit outposts.

The paper describes a way to a 1-D central streamline model of a radial turbine flow, suitable for twin-scroll description and based on approximation of real physics of flow mixing and energy transformation. The original 1-D model of a single scroll turbine, described earlier in numerous SAE papers, has been amended by twin-scroll nozzles (both vaneless or with blade cascades) and mixing of individual partitions of flows upstream of additional vaneless nozzle and an impeller. This model is transferable to 1-D unsteady simulations as it is (i.e., using quasi-steady approach) or using 1-D unsteady solvers. It has suitable features even for more detailed description of turbine flows and energy transformation. The first results of pulse influence on turbine maps delivered expected results consisting of complicated interaction between individual losses.

An ordinary, unmodified port fuel injection spark ignition automobile engine with closed-loop air-fuel ratio control and a three-way catalyst was operated on two butanol isomers, n-butanol and iso-butanol, and their blends with gasoline at steady-state operating points covering both common and potentially problematic regimes. The engine control unit was able to maintain the air-fuel ratio while running on both butanol isomers and their blends with gasoline. Only small changes in the heat release rates, small and insignificant decrease in exhaust gas temperatures, and no excessive increase in emissions were observed. Under commanded enrichment operation, the maximum torque, air-fuel ratio and exhaust emissions were comparable among nearly all fuels tested. The exhaust gas temperatures were comparable among fuels, with a moderate increase observed in some regimes during operation with high share of n-butanol in fuel.

Two modern light-duty passenger vehicles were selected for chassis dynamometer testing to evaluate differences in performance end efficiency resulting from CNG and gasoline combustion in a vehicle-based context. The vehicles were chosen to be as similar as possible apart from fuel type, sharing similar test weights and identical driveline configurations. Both vehicles were tested over several chassis dynamometer driving cycles, where it was found that the CNG vehicle exhibited 3-9% lower fuel economy than the gasoline-fueled subject. Performance tests were also conducted, where the CNG vehicle's lower tractive effort capability and longer acceleration times were consistent with the lower rated torque and power of its engine as compared to the gasoline model. The vehicles were also tested using quasi-steady-state chassis dynamometer techniques, wherein a series of engine operating points were studied.

The paper focuses on portable “on-board” instrumentation and methods for evaluation of exhaust emissions from scooters and various small machinery under real-world driving conditions. Two approaches are investigated here. In one, a miniature on-board system mounted on the equipment itself performs online measurements of the concentrations of the pollutants of interest (HC, CO, CO2, NOx, some property of particulate matter), and measurement or computation of the intake air flow. This approach has been used on a 50 cm3 scooter fitted with a 14-kg on-board system and driven on local routes. Measured concentrations of gaseous compounds, particle mass and total particle length were multiplied with the corresponding intake air flow computed from measured engine rpm, intake air manifold pressure and temperature. In the second approach, a full-flow dilution tunnel, gas analyzers and particle measurement or sampling devices are mounted on an accompanying hand cart or vehicle.

High hydrocarbon (HC) emission during a cold start still remains one of the major emission control challenges for spark ignition (SI) engines in spite of about three decades of research in this area. This paper proposes a cold start HC emission control strategy based on a reduced order modeling technique. A novel singular perturbation approximation (SPA) technique, based on the balanced realization principle, is developed for a nonlinear experimentally validated cold start emission model. The SPA reduced model is then utilized in the design of a model-based sliding mode controller (SMC). The controller targets to reduce cumulative tailpipe HC emission using a combination of fuel injection, spark timing, and air throttle / idle speed controls. The results from the designed multi-input multi-output (MIMO) reduced order SMC are compared with those from a full order SMC. The results show the reduced SMC outperforms the full order SMC by reducing both engine-out and tailpipe HC emission.

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.

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.

This study evaluates iso-butanol as a pathway to introduce higher levels of alternative fuels for recreational marine engine applications compared to ethanol. Butanol, a 4-carbon alcohol, has an energy density closer to gasoline than ethanol. Isobutanol at 16 vol% blend level in gasoline (iB16) exhibits energy content as well as oxygen content identical to E10. Tests with these two blends, as well as indolene as a reference fuel, were conducted on a Mercury 90 HP, 4-stroke outboard engine featuring computer controlled sequential multi-port Electronic Fuel Injection (EFI). The test matrix included full load curves as well as the 5-mode steady-state marine engine test cycle. Analysis of the full load tests suggests that equal full load performance is achieved across the engine speed band regardless of fuel at a 15-20°C increase in exhaust gas temperatures for the alcohol blends compared to indolene.

In spark-ignition engines, fluctuations of the in-cylinder pressure trace and the apparent rate of heat release are usually observed from one cycle to another. These Cycle-to-Cycle Variations (CCV) are affected by the early flame development and the subsequent flame front propagation. The CCV are responsible for engine performance (e.g. fuel consumption) and the knock behavior. The occurrence of the phenomena is unpredictable and the stochastic nature offers challenges in the optimization of engine control strategies. In the present work, CCV are analyzed in terms of their impact on the engine knock behavior and the related efficiency. Target is to estimate the possible fuel consumption savings in steady-state operation and in the drivecycle, when CCV are reduced. Since CCV are immanent on real engines, such a study can only be done by means of simulation.

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.

Battery management system (BMS) plays a key role in the power management of hybrid electric vehicles (HEV). It measures the state of charge (SOC), state of health (SOH) of the battery, protects the battery package and extends cells' life cycles. For HEV applications, lithium-ion battery is usually selected as electric power source due to its high specific energy, high energy density, and long life cycle. However, the non-linear characteristic of a Li-ion battery, complicated electro-chemical model, and environmental factors, raises the difficulties in the real-time estimation of the SOC for a Li-ion battery. To address this challenge, a BMS for HEVs is modeled with MATLAB/Simulink. In addition, a regenerative braking control strategy is proposed to determine the magnitude of the regenerative torque based on the battery SOC.

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.

In certain applications, the use of natural gas can be beneficial when compared to conventional road transportation fuels. Benefits include fuel diversification and CO₂ reduction, allowing future emissions regulations to be met. The use of natural gas in vehicles will also help to prepare the fuel and service infrastructure for future transition to gaseous renewable fuels. The composition of natural gas varies depending on its source, and engine manufacturers must be able to account for these differences. In order to achieve highly fuel flexible engines, the influence of fuel composition on engine properties must first be assessed. This demand is especially important for engines with high power densities. This paper summarizes knowledge acquired from engine dynamometer tests for different compositions of natural gas. Various levels of hydrocarbons and hydrogen in a mixture with methane have been tested at full load and various engine speeds.

This article presents results of the Design Assistance System (DASY) development and examples of its application for engine concept modeling. The software (DASY) for creating and maintaining knowledge database was developed. This software is targeted to simplify and speed up the concept design process. The targets were met by providing the high level of flexibility along with a simple user interface. Two examples that show interaction of DASY with computer-aided design (CAD) software are presented. The DASY creates a template for conserving the knowledge acquired during engine design in the past. It provides hints for the future design tasks by offering a data of similar engines, based on experiments and simulations at different levels of complexity and profoundness.

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).

Homogeneous charge compression ignition (HCCI) has received much attention in recent years due to its ability to reduce both fuel consumption and NO emissions compared to normal spark-ignited (SI) combustion. However, due to the limited operating range of HCCI, production feasible engines will need to employ a combination of combustion strategies, such as stoichiometric SI combustion at high loads and leaner burn spark-assisted compression ignition (SACI) and HCCI at intermediate and low loads. The goal of this study was to extend the high load limit of HCCI into the SACI region while maintaining a stoichiometric equivalence ratio. Experiments were conducted on a single-cylinder research engine with fully flexible valve actuation. In-cylinder pressure rise rates and combustion stability were controlled using cooled external EGR, spark assist, and negative valve overlap. Several engine loads within the SACI regime were investigated.

This paper presents the development of a Stochastic Knock Detection (SKD) method for combustion knock detection in a spark-ignition engine using a model based design approach. The SKD set consists of a Knock Signal Simulator (KSS) as the plant model for the engine and a Knock Detection Module (KDM). The KSS as the plant model for the engine generates cycle-to-cycle accelerometer knock intensities following a stochastic approach with intensities that are generated using a Monte Carlo method from a lognormal distribution whose parameters have been predetermined from engine tests and dependent upon spark-timing, engine speed and load. The lognormal distribution has been shown to be a good approximation to the distribution of measured knock intensities over a range of engine conditions and spark-timings for multiple engines in previous studies.