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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.

Hydrogen engines are currently considered as a viable solution to preserve the internal combustion engine as a power unit for vehicle propulsion. In particular, lean-burn gasoline Spark-Ignition (SI) engines have been a major subject of investigations due to the reduced emission levels and high thermodynamic efficiency. This strategy is suitable for the purpose of passenger car applications and cannot be tailored in the field of high performance engine, where the air mass delivered would require oversized turbocharging systems or more complex charging solutions. For this reason, the range of stoichiometric feeding condition is explored in the high performance engine, leading to the consequent issue of abatement of pollutant emissions. In this work a 1D model will be applied to the modeling of a V8 engine fueled with DI of hydrogen. The engine has been derived by a gasoline configuration and adapted to hydrogen in such a way to keep the same performance.

In this work a detailed model to simulate the transient behavior of catalytic converters is presented. The model is able to predict the unsteady and reacting flows in the exhaust ducts, by solving the system of conservation equations of mass, momentum, energy and transport of reacting chemical species. The en-gine and the intake system have not been included in the simulation, imposing the measured values of mass flow, gas temperature and chemical composition as a boundary condition at the inlet of the exhaust system. A detailed analysis of the diffusion stage triggering is proposed along with simplifications of the physics, finalized to the reduction of the calculation time. Submodels for water condensation and its following evaporation on the monolith surface have been taken into account as well as oxygen storage promoted by ceria oxides.

In this work an integration between a 1D code (Gasdyn) with a CFD code (OpenFOAM®) has been applied to improve the performance of a Moto3 engine. The four-stroke, single cylinder S.I. engine was modeled, in order to predict the wave motion in the intake and exhaust systems and to study how it affects the cylinder gas exchange process. The engine considered was characterized by having an air induction system with integrated filter cartridge, air-box and intake runner, including two fuel injectors, resulting in a complex air-path from the intake mouth to the intake valves, which presents critical aspects when a 1D modeling is addressed. The exhaust and intake systems have been optimized form the point of view of the wave action. However, due to the high revolution speed reached by this type of engine, the interaction between the gas stream and the fuel spray becomes a key aspect to be addressed in order to achieve the best performance at the desired operating condition.

Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

Beside the automotive industry, where 2-cylinder inline engines are catching attention again, twin-cylinder configurations are quite usual in the small engine world. From stationary engines and range-extender use to small motorcycles up to big cruisers and K-Cars this engine architecture is used in many types of applications. Because of very good overall packaging, performance characteristics and not least the possibility of parts-commonality with 4-cylinder engines nearly every motorcycle manufacturer provides an inline twin in its model range. Especially for motorcycle applications where generally the engine is a rigid member of the frame and vibrations can be transferred directly to the rider an appropriate balancing system is required.

The continuous pursuit of higher combustion efficiencies, as well as the possible usage of synthetic fuels with different properties than fossil-ones, require reliable and low-cost numerical approaches to support and speed-up engines industrial design. In this context, SI engines operated with homogeneous ultra-lean mixtures both characterized by a classical ignition configuration or equipped with an active prechamber represent the most promising solutions. In this work, for the classical ignition arrangement, a 3DCFD strategy to model the impact of the ignition system type on the CCV is developed using the RANS approach for turbulence modelling. The spark-discharge is modelled through a set of Lagrangian particles, whose velocity is modified with a zero-divergence perturbation at each discharge event, then evolved according to the Simplified Langevin Model (SLM) to simulate stochastic interactions with the surrounding gas flow.

The demand of game-changing technologies to improve efficiency and abate emissions of heavy-duty trucks and off-road vehicles promoted the development of novel engine concepts. The Recuperated Split-Cycle (R-SC) engine allows to recover the exhaust gases energy into the air intake by separating the compression and combustion stages into two different but connected cylinders: the compressor and expander, respectively. The result is a potential increase of the engine thermal efficiency. Accordingly, the 3D-computational fluid dynamics (CFD) modelling of the gas exchange process and the combustion evolution inside the expander becomes essential to control and optimize the R-SC engine concept. This work aims to address the most challenging numerical aspects encountered in a 3D numerical simulation of an R-SC engine.

Nowadays quasi-3D approaches are included in many commercial and research 1D numerical codes, in order to increase their simulation accuracy in presence of complex shape 3D volumes, e.g. plenums and silencers. In particular, these are regarded as valuable approaches for application during the design phase of an engine, for their capability of predicting non-planar waves motion and, on the other hand, for their low requirements in terms of computational runtime. However, the generation of a high-quality quasi-3D computational grid is not always straightforward, especially in case of complex elements, and can be a time-consuming operation, making the quasi-3D tool a less attractive option. In this work, a quasi-3D module has been implemented on the basis of the open-source CFD code OpenFOAM and coupled with the 1D code GASDYN.

A 2-D computational model was developed to describe the flow and filtration processes, in a honeycomb structured ceramic diesel particulate trap. This model describes the steady state trap loading, as well as the transient behavior of the flow and filtration processes. The theoretical model includes the effect of a copper fuel additive on trap loading and transient operation. The convective terms were based on a 2-D analytical flow field solution derived from the conservation of mass and momentum equations. The filtration theory incorporated in the time dependent numerical code included the diffusion, inertia, and direct interception mechanisms. Based on a measured upstream particle size distribution, using the filtration theory, the downstream particle size distribution was calculated. The theoretical filtration efficiency, based on particle size distribution, agreed very well (within 1%) with experimental data for a number of different cases.

A 2-D CFD model was developed to describe the heat transfer, and reaction kinetics in a honeycomb structured ceramic diesel particulate trap. This model describes the steady state as well as the transient behavior of the flow and heat transfer during the trap regeneration processes. The trap temperature profile was determined by numerically solving the 2-D unsteady energy equation including the convective, heat conduction and viscous dissipation terms. The convective terms were based on a 2-D analytical flow field solution derived from the conservation of mass and momentum equations (Opris, 1997). The reaction kinetics were described using a discretized first order Arrhenius function. The 2-D term describing the reaction kinetics and particulate matter conservation of mass was added to the energy equation as a source term in order to represent the particulate matter oxidation. The filtration model describes the particulate matter accumulation in the trap.

The paper investigates the interaction between soil and tractor tires through a 2D numerical model. The tire is schematized as a rigid ring presenting a series of rigid tread bars on the external circumference. The outer profile of the tire is divided into a series of elements, each one able to exchange a normal and a tangential contact force with the ground. A 2D soil model was developed to compute the forces at the ground-tire interface: the normal force is determined on the basis of the compression of the soil generated by the sinking of the tire. The soil is modeled through a layer of springs characterized by two different stiffness for the loading (lower stiffness) and unloading (higher stiffness) condition. This scheme allows to introduce a memory effect on the soil which results stiffer and keeps a residual sinking after the passage of the tire. The normal contact force determines the maximum value of tangential force provided before the soil fails.

The acoustics of automotive intake and exhaust systems is typically modeled using linear acoustics or gas-dynamics simulation. These approaches are preferred during basic sound design in the early development stages due to their computational efficiency compared to complex 3D CFD and FEM solutions. The linear acoustic method reduces the component being modelled to an equivalent acoustic two-port transfer matrix which describes the acoustic characteristic of the muffler. Recently this method was used to create more detailed and more accurate models based on a network of 3D cells. As the typical automotive muffler includes perforated elements and sound absorptive material, this paper demonstrates the extension of the 3D linear acoustic network description of a muffler to include the aforementioned elements. The proposed method was then validated against experimental results from muffler systems with perforated elements and sound absorptive material.

Active prechamber combustion systems for SI engines represent a feasible and effective solution in reducing fuel consumption and pollutant emissions for both marine and ground heavy-duty engines. However, reliable and low-cost numerical approaches need to be developed to support and speed-up their industrial design considering their geometry complexity and the involved multiple flow length scales. This work presents a CFD methodology based on the RANS approach for the simulation of active prechamber spark-ignition engines. To reduce the computational time, the gas exchange process is computed only in the prechamber region to correctly describe the flow and mixture distributions, while the whole cylinder geometry is considered only for the power-cycle (compression, combustion and expansion). Outside the prechamber the in-cylinder flow field at IVC is estimated from the measured swirl ratio.

A further development of the ETAB atomization and drop breakup model for high pressure-driven liquid fuel jets, has been developed, tuned and validated. As in the ETAB model, this breakup model reflects a cascade of drop breakups, where the breakup criterion is determined by the Taylor drop oscillator and each breakup event resembles experimentally observed breakup mechanisms. A fragmented liquid core due to inner-nozzle disturbances is achieved by injecting large droplets subject to this breakup cascade. These large droplets are equipped with appropriate initial deformation velocities in order to obtain experimentally observed breakup lengths. In contrast to the ETAB model which consideres only the bag breakup or the stripping breakup mechanism, the new model has been extended to include the catastrophic breakup regime. In addition, a continuity condition on the breakup parameters has lead to the reduction of one model constant.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

High fidelity engine simulation requires realistic fuel models. Although typical automotive fuels consist of more than few hundreds of hydrocarbon species, researches show that the physical and chemical properties of the real fuels could be represented by appropriate surrogate fuel models. It is desirable to represent the fuel using the same set of physical and chemical surrogate components. However, when the reaction mechanisms for a certain physical surrogate component is not available, the chemistry of the unmatched physical component is described using that of a similar chemical surrogate component at the expense of accuracy. In order to reduce the prediction error while maintaining the computational efficiency, a method of on-the-fly reactivity adjustment (ReAd) of chemical reaction mechanism along with fuel re-distribution based on reactivity is presented and tested in this study.

Power split in Fuel Cell Hybrid Electric Vehicles (FCHEVs) has been controlled using different strategies ranging from rule-based to optimal control. Dynamic Programming (DP) and Model Predictive Control (MPC) are two common optimal control strategies used in optimization of the power split in FCHEVs with a trade-off between global optimality of the solution and online implementation of the controller. In this paper, both control strategies are developed and tested on a FC/battery vehicle model, and the results are compared in terms of total energy consumption. In addition, the effects of the MPC prediction horizon length on the controller performance are studied. Results show that by using the DP strategy, up to 12% less total energy consumption is achieved compared to MPC for a charge sustaining mode in the Urban Dynamometer Driving Schedule (UDDS) drive cycle.

Damping measurements on vehicle subsystems are rarely straightforward due to the complexity of the dynamic interaction of system joints, trim, and geometry. Various experimental techniques can be used for damping estimation, such as frequency domain modal analysis curve-fitting methods, time domain decay-rate methods, and other methods based on energy and wave propagation. Each method has its own set of advantages and drawbacks. This paper describes an analytical and an experimental comparison between two, widely used loss factor estimation techniques frequently used in Statistical Energy Analysis (SEA). The single subsystem Power Injection Method (PIM) and the Impulse Response Decay Method (IRDM) were compared using analytical models of a variety of simulated simple spring-mass-damper systems. Frequency averaged loss factor values were estimated from both methods for comparison.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.