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Real transportation fuels, such as gasoline and diesel, are mixtures of thousands of different hydrocarbons. For multidimensional engine applications, numerical simulations of combustion of real fuels with all of the hydrocarbon species included exceeds present computational capabilities. Consequently, surrogate fuel models are normally utilized. A good surrogate fuel model should approximate the essential physical and chemical properties of the real fuel. In this work, we present a novel methodology for the formulation of surrogate fuel models based on local optimization and sensitivity analysis technologies. Within the proposed approach, several important fuel properties are considered. Under the physical properties, we focus on volatility, density, lower heating value (LHV), and viscosity, while the chemical properties relate to the chemical composition, hydrogen to carbon (H/C) ratio, and ignition behavior. An error tolerance is assigned to each property for convergence checking.

Recent increases in emissions regulations within the snowmobile industry have led to significant advancements in fuel, exhaust, and control systems on snowmobiles. However, particulate matter is currently an unregulated exhaust component of snowmobile engines. The measurement of dry soot as well as particulate matter from snowmobiles is the focus of this paper. Two industry-representative snowmobiles were chosen for this research which included a 2006 Yamaha Nytro carbureted four-stroke and a 2009 Ski-Doo MX-Z direct-injected two-stroke. Measurements for each snowmobile included gaseous emissions (CO₂, CO, NOx, O₂, and THC), particulate matter collected on quartz filters, and dry soot measured using an AVL Micro Soot Sensor. Each snowmobile was tested over the industry-standard five-mode emissions certification test cycle to determine the emissions, dry soot, and particulate matter levels from idle to wide open throttle (full-load).

The catalyzed particulate filter (CPF), used in conjunction with a diesel oxidation catalyst (DOC) is an important aftertreatment device used to meet Environmental Protection Agency (EPA) heavy-duty diesel emission standards for particulate matter (PM). Numerical modeling of these exhaust after-treatment devices decreases the time and cost of development involved. Modeling CPF active regeneration gives insight into the PM oxidation kinetics, which helps in reducing the regeneration fuel penalty. As seen from experimental data, active regeneration of the CPF results in a significant temperature increase into the CPF (up to 8°C/sec) which affects the oxidation rate of particulate matter (PM). PM oxidation during active regeneration was determined to be a function of filter PM loading, inlet temperature and inlet hydrocarbon concentration.

Particular matter (PM) has been greatly concerned over the recent decades due to the constantly increasing restriction on its effect on environmental aspect. Oxygenated fuel such as dimethyl ether (DME) has been known to have beneficial impact on diesel engine emissions in terms of zero soot formation. In current study, under several ambient conditions including surrounding gas temperature and oxygen percentages, soot and emission formation of DME spray is investigated to provide a comparison with other diesel surrogate (n-heptane) and JP-8 surrogate fuels. One important work is to develop a number of chemical kinetic mechanisms with soot chemistry including the growth of polycyclic aromatic hydrocarbon (PAH) and nitro oxides (NOx) formation. Using the developing detailed mechanisms, several numerical approaches were introduced to provide an integrated picture of emission formations.

An intermittent sampling valve was used to investigate local fuel H/C ratio and species concentrations in an operating DI diesel engine. Additionally, predictions of carbon and hydrogen originating from particulates and nonmethane hydrocarbons (carbon and hydrogen remainders) were made by calculation. Sample H/C ratio was used to assess local fuel phase as gaseous or liquid. Evidence of intermediate species quenching in the lean region between spray plumes was found under low swirl. Reduction in the rate of penetration under high swirl may account for the observed loss in efficiency under this condition.

Diesel Oxidation Catalysts (DOC) are used on heavy duty diesel engine applications and experience large internal temperature variations from 150 to 600°C. The DOC oxidizes the CO and HC in the exhaust to CO2 and H2O and oxidizes NO to NO2. The oxidation reactions are functions of its internal temperatures. Hence, accurate estimation of internal temperatures is important both for onboard diagnostic and aftertreatment closed loop control strategies. This paper focuses on the development of a reduced order model and an Extended Kalman Filter (EKF) state estimator for a DOC. The reduced order model simulation results are compared to experimental data. This is important since the reduced order model is used in the EKF estimator to predict the CO, NO, NO2 and HC concentrations in the DOC and at the outlet. The estimator was exercised using transient drive cycle engine data. The closed loop EKF improves the temperature estimate inside the DOC compared to the open loop estimator.