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The front camera module is a fundamental component of a modern vehicle’s active safety architecture. The module supports many active safety features. Perception of the road environment, requests for driver notification or alert, and requests for vehicle actuation are among the camera software’s key functions. This paper presents a novel method of testing these functions virtually. First, the front camera module software is compiled and packaged in a Docker container capable of running on a standard Linux computer as a software in the loop (SiL). This container is then integrated with the active safety simulation tool that represents the vehicle plant model and allows modeling of test scenarios. Then the following simulation components form a closed loop: First, the active safety simulation tool generates a video data stream (VDS). Using an internet protocol, the tool sends the VDS to the camera SiL and other vehicle channels.

Cast Al-Si alloys are widely used in automotive industry to produce structural components, such as engine block and cylinder head, because of the increasing demands in reducing mass for improved fuel efficiency. The fatigue performance of the castings is critical in their application. Porosity is highly detrimental to the fatigue behavior of cast Al-Si alloys. Therefore, accurate measurement of pore sizes is important in order to develop the correlations between porosity and fatigue strength. However, quantification of porosity is challenging and shows large variation depending on the measurement methods, particularly for micro-shrinkage porosity due to the torturous and complex morphology. The conventional metallographic image analysis method in the 2D polished surface often underestimates the actual pore size particularly when the porosity morphology is complex.

A Machine Learning (ML) approach is presented to correlate in-cylinder images of early flame kernel development within a spark-ignited (SI) gasoline engine to early-, mid-, and late-stage flame propagation. The objective of this study was to train machine learning models to analyze the relevance of flame surface features on subsequent burn rates. Ultimately, an approach of this nature can be generalized to flame images from a variety of sources. The prediction of combustion phasing was formulated as a regression problem to train predictive models to supplement observations of early flame kernel growth. High-speed images were captured from an optically accessible SI engine for 357 cycles under pre-mixed operation. A subset of these images was used to train three models: a linear regression model, a deep Convolutional Neural Network (CNN) based on the InceptionV3 architecture and a CNN built with assisted learning on the VGG19 architecture.

Sector mesh modeling is the dominant computational approach for combustion system design optimization. The aim of this work is to quantify the errors descending from the sector mesh approach through three geometric modeling approaches to an optical diesel engine. A full engine geometry mesh is created, including valves and intake and exhaust ports and runners, and a full-cycle flow simulation is performed until fired TDC. Next, an axisymmetric sector cylinder mesh is initialized with homogeneous bulk in-cylinder initial conditions initialized from the full-cycle simulation. Finally, a 360-degree azimuthal mesh of the cylinder is initialized with flow and thermodynamics fields at IVC mapped from the full engine geometry using a conservative interpolation approach. A study of the in-cylinder flow features until TDC showed that the geometric features on the cylinder head (valve tilt and protrusion into the combustion chamber, valve recesses) have a large impact on flow complexity.

To achieve high robustness and quality, automotive ECUs must initialize from low-power states as quickly as possible. However, microprocessor and memory advances have failed to keep pace with software image size growth in complex ECUs such as in Infotainment and Telematics. Loading the boot image from non-volatile storage to RAM and initializing the software can take a very long time to show the first screen and result in sluggish performance for a significant time thereafter which both degrade customer perceived quality. Designers of mobile devices such as portable phones, laptops, and tablets address this problem using Suspend mode whereby the main processor and peripheral devices are powered down during periods of inactivity, but memory contents are preserved by a small “self-refresh” current. When the device is turned back “on”, fully initialized memory content allows the system to initialize nearly instantaneously.

Flash-boiling of sprays may occur when a superheated liquid is discharged into an ambient environment with lower pressure than its saturation pressure. Such conditions normally exist in direct-injection spark-ignition engines operating at low in-cylinder pressures and/or high fuel temperatures. The addition of novel high volatile additives/fuels may also promote flash-boiling. Fuel flashing plays a significant role in mixture formation by promoting faster breakup and higher fuel evaporation rates compared to non-flashing conditions. Therefore, fundamental understanding of the characteristics of flashing sprays is necessary for the development of more efficient mixture formation. The present computational work focuses on modelling flash-boiling of n-Pentane and iso-Octane sprays using a Lagrangian particle tracking technique.

This paper addresses the need for fundamental understanding of the mechanisms of fuel spray formation and mixture preparation in direct injection spark ignition (DISI) engines. Fuel injection systems for DISI engines undergo rapid developments in their design and performance, therefore, their spray breakup mechanisms in the physical conditions encountered in DISI engines over a range of operating conditions and injection strategies require continuous attention. In this context, there are sparse data in the literature on spray formation differences between conventionally drilled injectors by spark erosion and latest Laser-drilled injector nozzles. A comparison was first carried out between the holes of spark-eroded and Laser-drilled injectors of same nominal type by analysing their in-nozzle geometry and surface roughness under an electron microscope.

One of the latest advancements in injector technology is laser drilling of the nozzle holes. In this context, the spray formation and atomisation characteristics of gasoline, ethanol and 1-butanol were investigated for a 7-hole spark eroded (SE) injector and its ‘direct replacement’ Laser-drilled (LD) injector using optical techniques. In the first step of the optical investigation, high-speed spray imaging was performed in a quiescent injection chamber with global illumination using diffused Laser light. The images were statistically analyzed to obtain spray penetration, spray tip velocity and spray ‘cone’ angles. Furthermore, droplet sizing was undertaken using Phase Doppler Anemometry (PDA). A single spray plume was isolated for this analysis and measurements were obtained across the plume at a fixed distance from the nozzle exit.

This paper presents a study of the combustion mechanism of hydrous and anhydrous ethanol in comparison to iso-octane and gasoline fuels in a single-cylinder spark-ignition research engine operated at 1000 rpm with 0.5 bar intake plenum pressure. The engine was equipped with optical access and tests were conducted with both Port Fuel Injection (PFI) and Direct Injection (DI) mixture preparation methods; all tests were conducted at stoichiometric conditions. The results showed that all alcohol fuels, both hydrous and anhydrous, burned faster than iso-octane and gasoline for both PFI and DI operation. The rate of combustion and peak cylinder pressure decreased with water content in ethanol for both modes of mixture preparation. Flame growth data were obtained by high-speed chemiluminescence imaging. These showed similar trends to the mass fraction burned curves obtained by in-cylinder heat release analysis for PFI operation; however, the trend with DI was not as consistent as with PFI.

The Reverse Braking Assist (RBA) feature is designed to automatically activate full braking in a backing vehicle. When this feature activates, a backing vehicle is suddenly stopped or may slide to a stop. During this process, an understanding of the driver's behavior may be useful in the design of an appropriate human-machine-interface (HMI) for the RBA. Several experimental studies were done to examine driver behavior in response to an unexpected and automatic braking event while backing [1]. Two of these studies are reported in this paper. A 7-passenger Crossover Utility Vehicle was fitted with a rear-view camera, a center-stack mounted LCD screen, and ancillary recording devices. In the first study, an object was suddenly placed in the path of a backing vehicle. The backing vehicle came to a sudden and complete stop. The visual image of the backing path on the LCD prominently showed that an obstacle was present in the backing path of the vehicle.

High-resolution planar laser-induced fluorescence (PLIF) measurements were performed on the scalar field in an optical engine. The measurements were of sufficient resolution to fully resolve all of the length scales of the flow field through the full cycle. The scalar dissipation spectrum was calculated, and by fitting the results to a model turbulent spectrum the Batchelor scale of the turbulent flow was estimated. The scalar inhomogeneity was introduced by a low-momentum gas jet injection. A consistent trend was observed in all data; the Batchelor scale showed a minimum value at top dead center (TDC) and was nearly symmetric about TDC. Increasing the engine speed resulted in a decrease of the Batchelor scale, and the presence of a shroud on the intake valve, which increased the turbulence intensity, also reduced the Batchelor scale. The effect of the shrouded valve was less significant compared to the effect of engine speed.

The fuel economy and emissions performance of a Diesel engine is strongly influenced by the fuel injection process. This paper presents early results of an experimental investigation into diesel spray development carried out in a novel in-house developed optical pressure chamber capable of operating at pressure up to 50 bar and temperatures up to 900 K. The spatial evolution of a diesel spray tends to experience many transitory macroscopic phenomena that directly influence the mixing process. These phenomena are not considered highly reproducible and are extremely short lived, hence recording and understanding these transient effects is difficult. In this study, high-speed backlight-illuminated imaging has been employed in order to capture the transient dynamics of a short signal duration diesel spray injected into incremental back pressures and temperatures reaching a maximum of 10 bar and 473 K respectively.

Effects of fuel cell material properties on water management were numerically investigated using Volume of Fluid (VOF) method in the FLUENT. The results show that the channel surface wettability is an important design variable for both serpentine and interdigitated flow channel configurations. In a serpentine air flow channel, hydrophilic surfaces could benefit the reactant transport to reaction sites by facilitating water transport along channel edges or on channel surfaces; however, the hydrophilic surfaces would also introduce significantly pressure drop as a penalty. For interdigitated air flow channel design, it is observable that liquid water exists only in the outlet channel; it is also observable that water distribution inside GDL is uneven due to the pressure distribution caused by interdigitated structure. An in-situ water measurement method, neutron imaging technique, was used to investigate the water behavior in a PEM fuel cell.

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.

Engine-out CO emission and fuel conversion efficiency were measured in a highly-dilute, low-temperature diesel combustion regime over a swirl ratio range of 1.44-7.12 and a wide range of injection timing. At fixed injection timing, an optimal swirl ratio for minimum CO emission and fuel consumption was found. At fixed swirl ratio, CO emission and fuel consumption generally decreased as injection timing was advanced. Moreover, a sudden decrease in CO emission was observed at early injection timings. Multi-dimensional numerical simulations, pressure-based measurements of ignition delay and apparent heat release, estimates of peak flame temperature, imaging of natural combustion luminosity and spray/wall interactions, and Laser Doppler Velocimeter (LDV) measurements of in-cylinder turbulence levels are employed to clarify the sources of the observed behavior.

Phosphorus contamination from engine oil additives has been associated with reduced performance of vehicle-aged exhaust gas catalysts. Identifying phosphorus species on aged catalysts is important for understanding the reasons for catalytic performance degradation. However, phosphorus is present only in small quantities, which makes its detection with bulk analytical techniques difficult. Raman microscopy probes small regions (a few microns in diameter) of a sample, and can detect both crystalline and amorphous materials. It is thus ideal for characterizing phosphates that may have limited distribution in a catalyst. However, suitable Raman spectra for mixed-metal phosphates that might be expected to be present in contaminated catalysts are not generally available.

A co-operative program initiated by the Automotive Aluminum Alliance and supported by USAMP continues to pursue the goal of establishing an in-laboratory cosmetic corrosion test for finished aluminum auto body panels that provides a good correlation with in-service performance. The program is organized as a task group within the SAE Automotive Corrosion and Protection (ACAP) Committee. Initially a large reservoir of test materials was established to provide a well-defined and consistent specimen supply for comparing test results. A series of laboratory procedures have been conducted on triplicate samples at separate labs in order to evaluate the reproducibility of the various lab tests. Exposures at OEM test tracks have also been conducted and results of the proving ground tests have been compared to the results in the laboratory tests. Outdoor tests and on-vehicle tests are also in progress. An optical imaging technique is being utilized for evaluation of the corrosion.

An investigation of the effect of microflow machining on the spray characteristics of diesel injectors was undertaken. A collection of four VCO injector tips were tested prior to and after an abrasive flow process using a high viscosity media. The injector nozzles were tested on a spray fixture. Rate of injection measurements and high-speed digital images were used for the quantification of the air entrainment rate. Comparisons of the spray characteristics and A/F ratios were made for conditions of before and after the abrasive flow process. Results showed a significant decrease in the injection-to-injection variability and improvement of the spray symmetry. A link between the quantity of air entrained and potential differences in spray plume internal chemical composition and temperature is proposed via equilibrium calculations.

This paper proposes a novel algorithm. This algorithm is called Self-Organizing Fuzzy Neural Network (SOFNN). SOFNN revolutionizes how researchers apply control theories, image/signal processing on control systems and other applications. In general, SOFNN is an identification technique that automatically initiates, builds and fine-tunes the required network parameters. SOFNN evaluates required structures without predefined parameters or expressions regarding systems. SOFNN sets out to learn and configure a system's characteristics. Self-constructing and self-tuning features enable SOFNN to handle complex, non-linear, and time-varying systems with higher accuracy, making systems identification easier. SOFNN constructs and fine-tunes the system parameter through two phases. The two phases are the construction and the parameter-tuning phase. The two phases run concurrently allowing SOFNN to identify systems on-line.

This paper presents the results of an experimental study into the liquid sheet break-up mechanisms of high-pressure swirl atomizers of the type commonly used in direct-injection spark-ignition (DISI) engines. Sheet disintegration was investigated at two fuel pressures: 5 and 10 MPa, and three ambient back pressures: 50, 100 (atmospheric) and 200 kPa for a pre-production DISI injector. Microscopic images of the near-nozzle spray region were obtained with a high-speed rotating drum camera and copper vapour laser. For the range of conditions considered, the results show the initial break-up to occur in ‘perforated-sheet’ mode. A novel ‘void fraction’ analysis technique was applied to multiple images from the steady-state period of a single injection event in order to characterise and quantify details of the sheet break-up process. The sheet break-up lengths obtained by the authors were compared with the break-up lengths predicted by three commonly employed models from the literature.