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The paper reviews the development and optimization of a SI high performance engine, to be used in Formula SAE/Student competitions. The base engine is a single cylinder Yamaha 660cc motorcycle unit, rated at about 48 HP at 6000rpm. Besides the reduction of engine capacity to 600cc and the mounting of the required restrictor, mechanical supercharging has been adopted in order to boost performance. The fluid-dynamic optimization of the engine system has been performed by means of 1D-CFD simulation, coupled to a single-objective genetic algorithm, developed by the authors. The optimization results have been compared to the ones obtained by a well known commercial optimization software, finding a good agreement. Experiments at the brake dynamometer have been carried out, in order to support engine modeling and to demonstrate the reliability of the optimization process.

This paper investigates flow and combustion in a full-cycle simulation of a four-stroke, three-valve HCCI engine by visualizing the flow with pathlines. Pathlines trace massless particles in a transient flow field. In addition to visualization, pathlines are used here to trace the history, or evolution, of flow fields and species. In this study evolution is followed from the intake port through combustion. Pathline analysis follows packets of intake charge in time and space from induction through combustion. The local scalar fields traversed by the individual packets in terms of velocity magnitude, turbulence, species concentration and temperatures are extracted from the simulation results. The results show how the intake event establishes local chemical and thermal environments in-cylinder and how the species respond (chemically react) to the local field.

The purpose of this research is to develop a prediction technique that can be used in the development of port fuel-injection (hereinafter called PFI) gasoline engines, especially for general purpose small utility engines. Utility engines have two contradictory desirable aspects: compactness and high-power at wide open throttle. Therefore, applying the port fuel injector to utility engines presents a unique intractableness that is different from application to automobiles or motorcycles. At the condition of wide open throttle, a large amount of fuel is required to output high power, and injected fuel is deposited as a wall film on the intake port wall. Despite the fuel rich condition, emissions are required to be kept under a certain level. Thus, it is significant to understand the wall film phenomenon and control film thickness in the intake ports.

Many recent studies have shown that the Reactivity Controlled Compression Ignition (RCCI) combustion strategy can achieve high efficiency with low emissions. However, it has also been revealed that RCCI combustion is difficult at high loads due to its premixed nature. To operate at moderate to high loads with gasoline/diesel dual fuel, high amounts of EGR or an ultra low compression ratio have shown to be required. Considering that both of these approaches inherently lower thermodynamic efficiency, in this study natural gas was utilized as a replacement for gasoline as the low-reactivity fuel. Due to the lower reactivity (i.e., higher octane number) of natural gas compared to gasoline, it was hypothesized to be a better fuel for RCCI combustion, in which a large reactivity gradient between the two fuels is beneficial in controlling the maximum pressure rise rate.

In order to investigate the effects of split injection on emission formation and engine performance, experiments were carried out using a heavy duty single cylinder diesel engine. Split injections with varied dwell time and start of injection were investigated and compared with single injection cases. In order to isolate the effect of the selected parameters, other variables were kept constant. In this investigation no EGR was used. The engine was equipped with a common rail injection system with a piezo-electric injector. To interpret the observed phenomena, engine CFD simulations using the KIVA-3V code were also made. The results show that reductions in NOx emissions and brake specific fuel consumption were achieved for short dwell times whereas they both were increased when the dwell time was prolonged. No EGR was used so the soot levels were already very low in the cases of single injections.

Modern high performance engines are usually characterized by high power densities, which lead to high mechanical and thermal loadings acting on engine components. In this scenario, aluminum may not represent the best choice for piston manufacturing and steel may be considered as a valid alternative. In this article, a methodology involving optimization techniques is presented for the design of an internal combustion engine piston. In particular, a design strategy is preliminary investigated aiming at replacing the standard aluminum piston, usually manufactured by forging or casting, with an alternative one made of steel and manufactured via an Additive Manufacturing process. Three different loading conditions are employed for the topology optimizations setup. Optimization results are then interpreted and the various structural features of the steel piston are designed starting from the density distribution contour plots.

This paper presents a multidimensional approach to the hydraulic components design by means of an open-source fluid dynamics code. A preliminary study of a basic geometry was carried out by simulating the efflux of an incompressible fluid through circular pipes. Both laminar and turbulent conditions were analyzed and the influence of the grid resolution and modeling settings were investigated. A qualitative description of the internal flow-field distribution, and a quantitative comparison of pressure and velocity profiles along the pipe axis were used to asses the multidimensional open-source code capabilities. Moreover the results were compared with the experimental measurements available in literature and with the theoretical trends which can be found in well-known literature fundamentals (Hagen-Poiseuille theory and Nikuradse interpolation). Further comparison was performed by using a commercial CFD code.

The University of Wisconsin-Madison Snowmobile Team designed and constructed a hybrid-electric snowmobile for the 2005 Society of Automotive Engineers' Clean Snowmobile Challenge. Built on a 2003 cross-country touring chassis, this machine features a 784 cc fuel-injected four-stroke engine in parallel with a 48 V electric golf cart motor. The 12 kg electric motor increases powertrain torque up to 25% during acceleration and recharges the snowmobile's battery pack during steady-state operation. Air pollution from the gasoline engine is reduced to levels far below current best available technology in the snowmobile industry. The four-stroke engine's closed-loop EFI system maintains stoichiometric combustion while dual three-way catalysts reduce NOx, HC and CO emissions by up to 94% from stock. In addition to the use of three way catalysts, the fuel injection strategy has been modified to further reduce engine emissions from the levels measured in the CSC 2004 competition.

A previously developed CFD-based optimization tool is utilized to find optimal engine operating conditions with respect to fuel consumption and emissions. The optimization algorithm employed is based on the steepest descent method where an adaptive cost function is minimized along each line search using an effective backtracking strategy. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine. The optimization parameters are the start of injection of the two pulses of a split injection system, the duration of each pulse, the exhaust gas recirculation rate, the boost pressure and the compression ratio.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

The fuel film thickness resulting from diesel fuel spray impingement was measured in a chamber at conditions representative of early injection timings used for low temperature diesel combustion. The adhered fuel volume and the radial distribution of the film thickness are presented. Fuel was injected normal to the impingement surface at ambient temperatures of 353 K, 426 K and 500 K, with densities of 10 kg/m3 and 25 kg/m3. Two injectors, with nozzle diameters of 100 μm and 120 μm, were investigated. The results show that the fuel film volume was strongly affected by the ambient temperature, but was minimally affected by the ambient density. The peak fuel film thickness and the film radius were found to increase with decreased temperature. The fuel film was found to be circular in shape, with an inner region of nearly constant thickness. The major difference observed with temperature was a decrease in the radial extent of the film.

The lift-off length plays a significant role in spray combustion as it influences the air entrainment upstream of the lift-off location and hence the soot formation. Accurate prediction of lift-off length thus becomes a prerequisite for accurate soot prediction in lifted flames. In the present study, KIVA-3v coupled with CHEMKIN, as developed at the Engine Research Center (ERC), is used as the CFD model. Experimental data from the Sandia National Labs. is used for validating the model predictions of n-heptane lift-off lengths and soot formation details in a constant volume combustion chamber. It is seen that the model predictions, in terms of lift-off length and soot mass, agree well with the experimental results for low ambient density (14.8 kg/m3) cases with different EGR rates (21% O2 - 8% O2). However, for high density cases (30 kg/m3) with different EGR rates (15% O2 - 8% O2) disagreements were found.

Multi-zone CFD simulations with detailed kinetics were used to model iso-octane HCCI experiments performed on a single-cylinder research engine. The modeling goals were to validate the method (multi-zone combustion modeling) and the reaction mechanism (LLNL 857 species iso-octane) by comparing model results to detailed exhaust speciation data, which was obtained with gas chromatography. The model is compared to experiments run at 1200 RPM and 1.35 bar boost pressure over an equivalence ratio range from 0.08 to 0.28. Fuel was introduced far upstream to ensure fuel and air homogeneity prior to entering the 13.8:1 compression ratio, shallow-bowl combustion chamber of this 4-stroke engine. The CFD grid incorporated a very detailed representation of the crevices, including the top-land ring crevice and head-gasket crevice. The ring crevice is resolved all the way into the ring pocket volume. The detailed grid was required to capture regions where emission species are formed and retained.

Transient engine operations are modeled and simulated with a 1-D code (GT Power) using heat release and emission data computed by a 3-D CFD code (Kiva3). During each iteration step of a transient engine simulation, the 1-D code utilizes the 3-D data to interpolate the values for heat release and emissions. The 3-D CFD computations were performed for the compression and combustion stroke of strategically chosen engine operating points considering engine speed, torque and excess air. The 3-D inlet conditions were obtained from the 1-D code, which utilized 3-D heat release data from the previous 1-D unsteady computations. In most cases, only two different sets of 3-D input data are needed to interpolate the transient phase between two engine operating points. This keeps the computation time at a reasonable level. The results are demonstrated on the load response of a generator which is driven by a medium-speed diesel engine.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

A 2200 cc engine head for marine applications has been analysed and optimized by means of decoupled CFD and FEM simulations in order to assess the fatigue strength of the component. The fluid distribution within the cooling jacket was extensively analysed and improved in previous works, in order to enhance the performance of the coolant galleries. A simplified methodology was then proposed in order to estimate the thermo-mechanical behaviour of the head under actual engine operation [1, 2]. As a consequence of the many complex phenomena involved, an improved approach is presented in this paper, capable of a better characterization of the fatigue strength of the engine head under both high-cycle and low-cycle fatigue loadings. The improved methodology is once again based on a decoupled CFD and FEM analysis, with relevant improvements added to both simulation realms.

Predictive models of soot formation during Diesel combustion are of great practical interest, particularly in light of newly proposed strict regulations on particulate emissions. A modified version of the phenomenological model of soot formation developed previously has been implemented in KIVA-II CFD code. The model includes major generic processes involved in soot formation during combustion, i.e., formation of soot precursors, formation of surface growth species, soot particle nucleation, coagulation, surface growth and oxidation. The formulation of the model within the KIVA-II is fully coupled with the mass and energy balances in the system. The model performance has been tested by comparison with the results of optical in-cylinder soot measurements in a single cylinder Cummins NH Diesel engine. The predicted soot volume fraction, number density and particle size agree reasonably well with the experimental data.

In the current investigation, the authors identified conditions under which increased in-cylinder turbulence can be used to improve diesel emissions. Two separate regimes of engine operation were identified; one in which combustion was constrained by mixing and one in which it was not. These regimes were dubbed under-mixed and over-mixed, respectively. It was found that increasing mixing in the former regime had a profound effect on soot emission. Fuel injection characteristics were found to be extremely important in determining the point at which mixing became inadequate. In addition, the ratio of the fuel injection momentum flux relative to that of the gas injection was found to be important in determining how increasing mixing would effect soot emissions.

One dimensional CFD codes are standard tools for engine development, in particular for the optimization of intake and exhaust systems. However, the accurate prediction of both engine brake performance and acoustic outputs is not that trivial. A quite critical issue is the modeling of complex engine components, such as air cleaners, plenums, exhaust junctions, silencers, etc. A trade-off is required in order to balance the accuracy of the acoustic analysis and the computational cost, particularly when DOE techniques have to be applied. In this paper a methodology for an integrated acoustic and performance analysis of a high performance SI engine is described. An engine simulation model has been built by using a commercial software, and it has been validated against experiments, finding a good agreement. It is remarked that the measurements of both acoustic and engine performance parameters are taken by using standard facilities and equipment, no anechoic test bench is required.

Neural networks are useful tools for optimization studies since they are very fast, so that while capturing the accuracy of multi-dimensional CFD calculations or experimental data, they can be run numerous times as required by many optimization techniques. This paper describes how a set of neural networks trained on a multi-dimensional CFD code to predict pressure, temperature, heat flux, torque and emissions, have been used by a genetic algorithm in combination with a hill-climbing type algorithm to optimize operating parameters of a diesel engine over the entire speed-torque map of the engine. The optimized parameters are mass of fuel injected per cycle, shape of the injection profile for dual split injection, start of injection, EGR level and boost pressure. These have been optimized for minimum emissions. Another set of neural networks have been trained to predict the optimized parameters, based on the speed-torque point of the engine.