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Noise concerns regarding snowmobiles have increased in the recent past. Current standards, such as SAE J192 are used as guidelines for government agencies and manufacturers to regulate noise emissions for all manufactured snowmobiles. Unfortunately, the test standards available today produce results with variability that is much higher than desired. The most significant contributor to the variation in noise measurements is the test surface. The test surfaces can either be snow or grass and affects the measurement in two very distinct ways: sound propagation from the source to the receiver and the operational behavior of the snowmobile. Data is presented for a known sound pressure speaker source and different snowmobiles on various test days and test surfaces. Relationships are shown between the behavior of the sound propagation and track interaction to the ground with the pass-by noise measurements.

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

In the present paper, two different methodologies are adopted and critically integrated to analyze the knock behavior of a last generation small size spark ignition (SI) turbocharged VVA engine. Particularly, two full load operating points are selected, exhibiting relevant differences in terms of knock proximity. On one side, a knock investigation is carried out by means of an Auto-Regressive technique (AR model) to process experimental in-cylinder pressure signals. This mathematical procedure is used to estimate the statistical distribution of knocking cycles and provide a validation of the following 1D-3D knock investigations. On the other side, an integrated numerical approach is set up, based on the synergic use of 1D and 3D simulation tools. The 1D engine model is developed within the commercial software GT-Power™. It is used to provide time-varying boundary conditions (BCs) for the 3D code, Star-CD™.

Computer programs and models are playing an increasing role in simulating vehicle crashworthiness, dynamic, and fuel efficiency. To maximize the effectiveness of these models, the validity and predictive capabilities of these models need to be assessed quantitatively. For a successful implementation of Computer Aided Engineering (CAE) models as an integrated part of the current vehicle development process, it is necessary to develop objective validation metric that has the desirable metric properties to quantify the discrepancy between multiple tests and simulation results. However, most of the outputs of dynamic systems are multiple functional responses, such as time history series. This calls for the development of an objective metric that can evaluate the differences of the multiple time histories as well as the key features under uncertainty.

Simulation based design optimization has become the common practice in automotive product development. Increasing computer models are developed to simulate various dynamic systems. Before applying these models for product development, model validation needs to be conducted to assess their validity. In model validation, for the purpose of obtaining results successfully, it is vital to select or develop appropriate metrics for specific applications. For dynamic systems, one of the key obstacles of model validation is that most of the responses are functional, such as time history curves. This calls for the development of a metric that can evaluate the differences in terms of phase shift, magnitude and shape, which requires information from both time and frequency domain. And by representing time histories in frequency domain, more intuitive information can be obtained, such as magnitude-frequency and phase-frequency characteristics.

Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

The study of spray-wall interaction is of great importance to understand the dynamics that occur during fuel impingement onto the chamber wall or piston surfaces in internal combustion engines. It is found that the maximum spreading length of an impinged droplet can provide a quantitative estimation of heat transfer and energy transformation for spray-wall interaction. Furthermore, it influences the air-fuel mixing and hydrocarbon and particle emissions at combusting conditions. In this paper, an analytical model of a single diesel droplet impinging on the wall with different inclined angles (α) is developed in terms of βm (dimensionless maximum spreading length, the ratio of maximum spreading length to initial droplet diameter) to understand the detailed impinging dynamic process.

A growing number of electric vehicles (EV) and hybrid electric vehicles (HEV) in the present market depicts the rapid growing demand for energy storage systems. The battery’s main peculiarities must be the power density and reliability over time. The temperature strongly affects battery performance for low and high intensity. In particular, the management of the heat generated by the battery itself is one of the main aspects to handle to preserve the performance over time. The objective of this paper is to compare the surface temperature of the lithium-ion polymer battery at different discharging rates by infrared thermography. Thermal imaging is performed to detect the battery surface temperature distribution, focusing on its variation over time and the local inhomogeneity. Temperature measurements are then used to estimate the contributions of the different heat transfer mechanisms for the dissipation of the heat generated by the battery.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional fuel to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

In recent years, the increase of gasoline fuel injection pressure is a way to improve thermal efficiency and lower engine-out emissions in GDI homogenous combustion concept. The challenge of controlling particulate formation as well in mass and number concentrations imposed by emissions regulations can be pursued improving the mixture preparation process and avoiding mixture inhomogeneity with ultra-high injection pressure values up to 100 MPa. The increase of the fuel injection pressure in GDI homogeneous systems meets the demand for increased injector static flow, while simultaneously improves the spray atomization and mixing characteristics with consequent better combustion performance. Few studies quantify the effects of high injection pressure on transient gasoline spray evolution. The aim of this work was to simulate with OpenFOAM the spray morphology of a commercial gasoline injected in a constant volume vessel by a prototypal GDI injector.

The electrochemical performance of a lithium-ion battery is strongly affected by the temperature. During charge and discharge cycles, batteries are subjected to an increment of temperature that can accelerate aging and loss of efficiency if critical values are reached. Knowing the thermal parameters that affect the heat exchange between the battery surface and the surrounding environment (air, cooling fins, plates, etc…) is fundamental to their thermal management. In this work, thermal imaging is applied to a laminated lithium-polymers battery as a non-invasive temperature-indication method. Measurements are taken during the discharge phase and the following cooling down until the battery reaches the ambient temperature. The 2d images are used to analyze the homogeneity of the temperature distribution on the battery surface. Then, experimental results are coupled with mathematical correlations.

During gasoline direct injection (GDI) in spark ignition engines, droplets may hit piston or liner surfaces and be rebounded or deposit in the liquid phase as wallfilm. This may determine slower secondary atomization and local enrichments of the mixture, hence be the reason of increased unburned hydrocarbons and particulate matter emissions at the exhaust. Complex phenomena indeed characterize the in-cylinder turbulent multi-phase system, where heat transfer involves the gaseous mixture (made of air and gasoline vapor), the liquid phase (droplets not yet evaporated and wallfilm) and the solid walls. A reliable 3D CFD modelling of the in-cylinder processes, therefore, necessarily requires also the correct simulation of the cooling effect due to the subtraction of the latent heat of vaporization of gasoline needed for secondary evaporation in the zone where droplets hit the wall. The related conductive heat transfer within the solid is to be taken into account.

The paper describes the challenges and results achieved in developing a new high-speed Diesel combustion system capable of exceeding the imaginative threshold of 100 kW/l. High-performance, state-of-art prototype components from automotive diesel technology were provided in order to set-up a single-cylinder research engine demonstrator. Key design parameters were identified in terms boost, engine speed, fuel injection pressure and injector nozzle flow rates. In this regard, an advanced piezo injection system capable of 3000 bar of maximum injection pressure was selected, coupled to a robust base engine featuring ω-shaped combustion bowl and low swirl intake ports. The matching among the above-described elements has been thoroughly examined and experimentally parameterized.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

In order to extend the operability limit of the gasoline compression ignition (GCI) engine, as an avenue for low temperature combustion (LTC) regime, the effects of parametric variations of engine operating conditions on the performance of six-stroke GCI (6S-GCI) engine cycle are numerically investigated, using an in-house 3D CFD code coupled with high-fidelity physical sub-models along with the Chemkin library. The combustion and emissions were calculated using a skeletal chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Authors’ previous study highlighted the effects of the variation of injection timing and split ratio on the overall performance of 6S-GCI engine and the unique mixing-controlled burning mode of the charge mixtures during the two additional strokes. As a continuing effort, the present study details the parametric studies of initial gas temperature, boost pressure, fuel injection pressure, compression ratio, and EGR ratio.

Gas engines (fuelled with CNG, LNG or Biogas) for generation of power and heat are, to this date, taking up larger shares of the market with respect to diesel engines. In order to meet the limit imposed by the TA-Luft regulations on stationary engines, lean combustion represents a viable solution for achieving lower emissions as well as efficiency levels comparable with diesel engines. Leaner mixtures however affect the combustion stability as the flame propagation velocity and consequently heat release rate are slowed down. As a strategy to deliver higher ignition energy, an active pre-chamber may be used. This work focuses on assessing the performance of a pre-chamber combustion configuration in a stationary heavy-duty engine for power generation, operating at different loads, air-to-fuel ratios and spark timings.

Isooctane sprays from a multi-hole GDI injector were investigated in a constant volume chamber by means of high speed imaging techniques. The tests were performed under inert conditions (nitrogen), at temperatures and densities ranging between representative operating conditions of late injection, flash boiling and early injection in a GDI engine. The global parameters of the sprays were obtained by processing Schlieren, Shadowgraph, DBI and Mie-scattering images through an in-house image processing method. Thus, the boundaries of the spray vapor phase can be easily detected with great accuracy, regardless of whether Schlieren or the less sensitive shadowgraph imaging is used. Furthermore, the boundaries of the liquid phase were also obtained from shadowgraph images and compared with those obtained through DBI and scattering. The results show that the signature of the liquid phase in a shadowgraph image can be distinguished from that of the vaporized fuel.

In the last years, increasing concerns about environmental pollution and fossil sources depletion led transport sectors research and development towards the study of new technologies capable to reduce vehicles emissions and fuel consumption. Direct-injection systems (DI) for internal combustion engines propose as an effective way to achieve these goals. This technology has already been adopted in Gasoline Direct Injection (GDI) engines and, lately, a great interest is growing for its use in natural gas fueling, so increasing efficiency with respect to port-fuel injection ones. Alone or in combination with other fuels, compressed natural gas (CNG) represents an attractive way to reduce exhaust emission (high H/C ratio), can be produced in renewable ways, and is more widespread and cheaper than gasoline or diesel fuels. Gas direct-injection process involves the occurrence of under-expanded jets in the combustion chamber.

Today, Direct-Injection systems are widely used on Spark-Ignition engines in combination with turbo-charging to reduce the fuel-consumption and the knock risks. In particular, the spread of Gasoline Direct Injection (GDI) systems is mainly related to the use of new generations of multi-hole, high-pressure injectors whose characteristics are quite different with respect to the hollow-cone, low-pressure injectors adopted in the last decade. This paper presents the results of an experimental campaign conducted on the spray produced by a GDI six-holes injector into a constant volume vessel with optical access. The vessel was filled with air at atmospheric pressure. Different operating conditions were considered for an injection pressure ranging from 3 to 20 MPa. For each operating condition, spray images were acquired by a CCD camera and then post processed to evaluate the spray penetration and cone angles.