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EGR coolers are effective to reduce NOx emissions from diesel engines due to lower intake charge temperature. EGR cooler fouling reduces heat transfer capacity of the cooler significantly and increases pressure drop across the cooler. Engine coolant provided at 40–90 C is used to cool EGR coolers. The presence of a cold surface in the cooler causes particulate soot deposition and hydrocarbon condensation. The experimental data also indicates that the fouling is mainly caused by soot and hydrocarbons. In this study, a 1-D model is extended to simulate particulate soot and hydrocarbon deposition on a concentric tube EGR cooler with a constant wall temperature. The soot deposition caused by thermophoresis phenomena is taken into account the model. Condensation of a wide range of hydrocarbon molecules are also modeled but the results show condensation of only heavy molecules at coolant temperature.

This study uses full drive cycle simulation to compare the fuel consumption of a vehicle with a turbocharged (TC) engine to the same vehicle with an alternative boosting technology, namely, a hybrid supercharger, in which a planetary gear mechanism governs the power split to the supercharger between the crankshaft and a 48 V 5 kW electric motor. Conventional mechanically driven superchargers or electric superchargers have been proposed to improve the dynamic response of boosted engines, but their projected fuel efficiency benefit depends heavily on the engine transient response and driver/cycle aggressiveness. The fuel consumption benefits depend on the closed-loop engine responsiveness, the control tuning, and the torque reserve needed for each technology. To perform drive cycle analyses, a control strategy is designed that minimizes the boost reserve and employs high rates of combustion dilution via exhaust gas recirculation (EGR).

This paper presents a framework for modeling a modern diesel engine and its aftertreatment system which are intended to be used for real-time implementation as a virtual engine and in a model-based control architecture to predict critical variables such as fuel consumption and tailpipe emissions. The models are specifically able to capture the impact of critical control variables such as the Exhaust Gas Recirculation (EGR) valve position and fuel injection timing, as well as operating conditions of speed and torque, on the engine airpath variables and emissions during transient driving conditions. To enable real-time computation of the models, a minimal realization of the nonlinear airpath model is presented and it is coupled with a cycle averaged NOx emissions predictor to estimate feed gas NOx emissions. Then, the feedgas enthalpy is used to calculate the thermal behavior of the aftertreatment system required for prediction of tailpipe emissions.

The effects of combining premixed, low temperature combustion (LTC) with biodiesel are relatively unknown to this point. This mode allows simultaneously low soot and NOx emissions by using high rates of EGR and increasing ignition delay. This paper compares engine performance and emissions of neat, soy-based methyl ester biodiesel (B100), B20, B50, pure ultra low sulfur diesel (ULSD) and a Swedish, low aromatic diesel in a multi-cylinder diesel engine operating in a late-injection premixed LTC mode. Using heat release analysis, the progression of LTC combustion was explored by comparing fuel mass fraction burned. B100 had a comparatively long ignition delay compared with Swedish diesel when measured by start of ignition (SOI) to 10% fuel mass fraction burned (CA10). Differences were not as apparent when measured by SOI to start of combustion (SOC) even though their cetane numbers are comparable.

A method for detection of ethanol content in fuel for an engine equipped with direct injection (DI) is presented. The methodology is based on in-cylinder pressure measurements during the compression stroke and exploits the different charge cooling properties of ethanol and gasoline. The concept was validated using dynamometer data of a 2.0L DI turbocharged engine with variable valve timing (VVT). An algorithm was developed to process the experimental data and generate a residue from the complex cycle-to-cycle in-cylinder pressure evolution which captures the charge cooling effect. The experimental results show that there is a monotonic correlation between the residues and the fuel ethanol percentage in the majority of the cases. However, the correlation varies for different engine operating parameters; such as, speed, load, valve timing, fuel rail pressure, intake and exhaust temperature and pressure.

Premixed low temperature combustion (LTC) in diesel engines simultaneously reduces soot and NOx at the expense of increased hydrocarbon (HC) and CO emissions. The use of biodiesel in the LTC regime has been shown to produce lower HC emissions than petroleum diesel; however, unburned methyl esters from biodiesel are more susceptible to particulate matter (PM) formation following atmospheric dilution due to their low volatility. In this study, the efficacy of a production-type diesel oxidation catalyst (DOC) for the conversion of light hydrocarbons species and heavier, semi-volatile species like those in unburned fuel is examined. Experimental data were taken from a high speed direct-injection diesel engine operating in a mid-load, late injection partially premixed LTC mode on ultra-low sulfur diesel (ULSD) and neat soy-based biodiesel (B100). Gaseous emissions were recorded using a conventional suite of analyzers and individual light HCs were measured using an FT-IR analyzer.

An experimental study is performed for homogeneous charge compression ignition (HCCI) combustion focusing on late phasing conditions with high cyclic variability (CV) approaching misfire. High CV limits the feasible operating range and the objective is to understand and quantify the dominating effects of the CV in order to enable controls for widening the operating range of HCCI. A combustion analysis method is developed for explaining the dynamic coupling in sequences of combustion cycles where important variables are residual gas temperature, combustion efficiency, heat release during re-compression, and unburned fuel mass. The results show that the unburned fuel mass carries over to the re-compression and to the next cycle creating a coupling between cycles, in addition to the well known temperature coupling, that is essential for understanding and predicting the HCCI behavior at lean conditions with high CV.

A quasi-dimensional computer simulation of the turbocharged spark-ignition engine has been developed in order to study system performance as various design parameters and operating conditions are varied. The simulation is of the “filling and emptying” type. Quasi-steady flow models of the compressor, intercooler, manifolds, turbine, wastegate, and ducting are coupled with a multi-cylinder engine model where each cylinder undergoes the same thermodynamic cycle. A turbulent entrainment model of the combustion process is used, thus allowing for studies of the effects of various combustion chamber shapes and turbulence parameters on cylinder pressure, temperature, NOx emissions and overall engine performance. Valve open areas are determined either based on user supplied valve lift data or using polydyne-generated cam profiles which allow for variable valve timing studies.

Direct injection of natural gas under high pressure conditions has emerged as a promising option for improving engine fuel economy and emissions. However, since the gaseous injection technology is new, limited experience exists as to the optimum configuration of the injection system and associated combustion chamber design. The present study uses KIVA-3 based, multidimensional modeling to improve the understanding and assist the optimization of the gaseous injection process. Compared to standard k-ε models, a Renormalization Group Theory (RNG) based k-ε model [1] has been found to be in better agreement with experiments in predicting gaseous penetration histories for both free and confined jet configurations. Hence, this validated RNG model is adopted here to perform computations in realistic engine geometries.

A detailed chemical kinetic mechanism, consisting of 22 species and 104 elementary reactions, has been used in conjunction with the multi-dimensional reactive flow code KIVA-3 to study autoignition of natural gas injected under compression ignition conditions. Calculations for three different blends of natural gas are performed on a three-dimensional computational grid by modeling both the injection and ignition processes. Ignition delay predictions at pressures and temperatures typical of top-dead-center conditions in compression ignition engines compare well with the measurements of Naber et al. [1] in a combustion bomb. Two different criteria, based on pressure rise and mass of fuel burned, are used to detect the onset of ignition. Parametric studies are conducted to show the effect of additives like ethane and hydrogen peroxide in increasing the fuel consumption rate.

A personal computer-based vehicle powertrain simulation (VPS) is developed to predict fuel economy and performance. This paper summarizes the governing equations used in the model. Then the different simulation techniques are described with emphasis on the more complicated time-dependent simulation. The simulation is validated against constant speed and variable cycle test track data obtained for a 5 ton army truck. Then the simulation is used to compare the performance of the 5 ton truck when powered by a cooled and natually aspirated engine, a cooled and turbocharged engine, and an uncooled and turbocharged engine. Studies of the effect of payload, tire efficiency, and drag coefficient on vehicle performance are also conducted, as well as a performance comparison between manual and automatic transmissions. It is concluded that the VPS code can provide good predictions of vehicle fuel economy, and thus is a useful tool in designing and evaluating vehicle powertrains.

This paper analyzes and compares reactor and engine behavior of a diesel oxidation catalyst (DOC) in the presence of conventional diesel exhaust and low temperature premixed compression ignition (PCI) diesel exhaust. Surrogate exhaust mixtures of n-undecane (C11H24), ethene (C2H4), CO, O2, H2O, NO and N2 are defined for conventional and PCI combustion and used in the gas flow reactor tests. Both engine and reactor tests use a DOC containing platinum, palladium and a hydrocarbon storage component (zeolite). On both the engine and reactor, the composition of PCI exhaust increases light-off temperature relative to conventional combustion. However, while nominal conditions are similar, the catalyst behaves differently on the two experimental setups. The engine DOC shows higher initial apparent HC conversion efficiencies because the engine exhaust contains a higher fraction of trappable (i.e., high boiling point) HC.

Flexible fuel vehicles (FFVs) are able to operate on a blend of ethanol and gasoline in any volumetric concentration of up to 85% ethanol (93% in Brazil). The estimation of ethanol content is crucial for optimized and robust performance in such vehicles. Even if an ethanol sensor is utilized, an estimation scheme independent of the ethanol sensor measurement retains advantages in enhancing the reliability of ethanol estimation and allowing on-board diagnostics. It is well-known that an exhaust gas oxygen (EGO) sensor could be utilized to estimate the ethanol content, which exploits the difference in stoichiometric air-to-fuel ratio (SAFR) between ethanol (9.0) and gasoline (14.6). The SAFR-based ethanol estimation has been shown to be prone to large errors with mass air flow sensor bias and/or fuel injector shift.

This paper reports the development of a model of diesel combustion and NO emissions, based on a modified eddy dissipation concept (EDC), and its implementation into the KIVA-3V multidimensional simulation. The EDC model allows for more realistic representation of the thin sub-grid scale reaction zone as well as the small-scale molecular mixing processes. Realistic chemical kinetic mechanisms for n-heptane combustion and NOx formation processes are fully incorporated. A model based on the normalized fuel mass fraction is implemented to transition between ignition and combustion. The modeling approach has been validated by comparison with experimental data for a range of operating conditions. Predicted cylinder pressure and heat release rates agree well with measurements. The predictions for NO concentration show a consistent trend with experiments. Overall, the results demonstrate the improved capability of the model for predictions of the combustion process.

Variable geometry turbines (VGT) are of particular interest to advanced diesel powertrains for future conventional trucks, since they can dramatically improve system transient response to sudden changes in speed and load, characteristic of automotive applications. VGT systems are also viewed as the key enabler for the application of the EGR system for reduction of heavy-duty diesel emissions. This paper applies an artificial neural network methodology to VGT modeling in order to enable representation of the VGT characteristics for any blade (nozzle) position. Following validation of the ANN model of the baseline, fixed geometry turbine, the VGT model is integrated with the diesel engine system. The latter is linked to the driveline and the vehicle dynamics module to form a complete, high-fidelity vehicle simulation.

The need for a rigorous systems engineering approach to automotive powertrains has been addressed in this work from the perspective of the diesel engine. A high-fidelity engine simulation has been integrated with a total vehicle model for the purpose of reverse engineering the optimal powerplant for a given vehicle mission. Engine parameters have been coordinated between the simulations to develop a framework for total vehicle design. The design strategies discussed in this paper allow engine researchers to set targets for individual system components and to analyze the tradeoffs associated with different vehicle mission objectives. A detailed case study employing these techniques is presented for a conventional vehicle where the most fuel-efficient engine is found that simultaneously conforms to the desired performance criteria.

A quasi-dimensional, multi-zone, direct injection (DI) diesel combustion model has been developed and implemented in a full cycle simulation of a turbocharged engine. The combustion model accounts for transient fuel spray evolution, fuel-air mixing, ignition, combustion and NO and soot pollutant formation. In the model, the fuel spray is divided into a number of zones, which are treated as open systems. While mass and energy equations are solved for each zone, a simplified momentum conservation equation is used to calculate the amount of air entrained into each zone. Details of the DI spray, combustion model and its implementation into the cycle simulation of Assanis and Heywood [1] are described in this paper. The model is validated with experimental data obtained in a constant volume chamber and engines. First, predictions of spray penetration and spray angle are validated against measurements in a pressurized constant volume chamber.

A hybrid electric vehicle simulation tool (HE-VESIM) has been developed at the Automotive Research Center of the University of Michigan to study the fuel economy potential of hybrid military/civilian trucks. In this paper, the fundamental architecture of the feed-forward parallel hybrid-electric vehicle system is described, together with dynamic equations and basic features of sub-system modules. Two vehicle-level power management control algorithms are assessed, a rule-based algorithm, which mainly explores engine efficiency in an intuitive manner, and a dynamic-programming optimization algorithm. Simulation results over the urban driving cycle demonstrate the potential of the selected hybrid system to significantly improve vehicle fuel economy, the improvement being greater when the dynamic-programming power management algorithm is applied.

This paper investigates the effects of manufacturing variations in fuel injectors on the engine performance with emphasis on emissions. The variations are taken into consideration within a Reliability-Based Design Optimization (RBDO) framework. A reduced version of Multi-Zone Diesel engine Simulation (MZDS), MZDS-lite, is used to enable the optimization study. The numerical noise of MZDS-lite prohibits the use of gradient-based optimization methods. Therefore, surrogate models are developed to filter out the noise and to reduce computational cost. Three multi-objective optimization problems are formulated, solved and compared: deterministic optimization using MZDS-lite, deterministic optimization using surrogate models and RBDO using surrogate models. The obtained results confirm that manufacturing variation effects must be taken into account in the early product development stages.

This paper investigates the opportunities for improving truck fuel economy through the use of a Fuel Cell Auxiliary Power Unit (FC APU) for silent watch, as well as for powering electrified engine accessories during driving. The particular vehicle selected as the platform for this study is a prototype of the Family of Medium Tactical Vehicles (FMTV) capable of carrying a 5 ton payload. Peak stand-by power requirements for on-board power are determined from the projected future digitized battlefield vehicle requirements. Strategic selection of electrified engine accessories enables engine shutdowns when the vehicle is stopped, thus providing additional fuel savings. Proton Exchange Membrane (PEM) fuel cell is integrated with a partial oxidation reformer in order to allow the use of the same fuel (JP8) as for the propulsion diesel engine.