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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 study evaluated the interactions between sheet steel, lubricant and measurement system under typical sheet forming conditions using a fixed draw bead simulator (DBS). Deep drawing quality mild steel substrates with bare (CR), electrogalvanized (EG) and hot dip galvanized (HDG) coatings were tested using a fixed DBS. Various lubricant conditions were targeted to evaluate the coefficient of friction (COF) of the substrate and lubricant combinations, with only rust preventative mill oil (dry-0 g/m2 and 1 g/m2), only forming pre-lube (dry-0 g/m2, 1 g/m2, and >6 g/m2), and a combination of two, where mixed lubrication cases, with incremental amounts of a pre-lube applied (0.5, 1.0, 1.5 and 2.0 g/m2) over an existing base of 1 g/m2 mill oil, were analyzed. The results showed some similarities as well as distinctive differences in the friction behavior between the bare material and the coatings.

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.

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.

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.

The detailed study of part-load conditions is essential to characterize engine-out emissions in key operating conditions. The relevance of part-load operations is further emphasized by the recent regulations such as the new WLTP standard. Combustion development at part-load operations depends on a complex interplay between moderate turbulence levels (low engine speed and tumble ratio), low in-cylinder pressure and temperature, and stoichiometric-to-lean mixture quality (to maximize fuel efficiency). From a modelling standpoint, the reduced turbulence intensity compared to full-load operations complicates the interaction between different sub-models (e.g., reconsideration of the flamelet hypothesis adopted by common combustion models). In this article, the authors focus on chemistry-based simulations for laminar flame speed of gasoline surrogates at conditions typical of part-load operations. The analysis is an extension of a previous study focused on full-load operations.

More than four decades ago, the concept of zero defects was coined by Phillip Crosby. It was only a vision at the time, but the introduction of Artificial Intelligence (AI) in manufacturing has since enabled it to become attainable. Since most mature manufacturing organizations have merged traditional quality philosophies and techniques, their processes generate only a few Defects Per Million of Opportunities (DPMO). Detecting these rare quality events is one of the modern intellectual challenges posed to this industry. Process Monitoring for Quality (PMQ) is an AI and big data-driven quality philosophy aimed at defect detection and empirical knowledge discovery. Detection is formulated as a binary classification problem, where the right Machine Learning (ML), optimization, and statistics techniques are applied to develop an effective predictive system.

GM Powertrain Europe and Istituto Motori CNR have undergone a research project aimed at studying the effects on engine performance, emissions and fuel consumption of alternative diesel fuels, from both first (FAME) and second (GTL) generation. The present paper reports some of the results achieved studying the impact on injection and spray behavior of rapeseed and soybean methyl-esters, as well as of GTL diesel blends. The test were performed on a Bosch second generation common rail solenoid-driven fuel injection system capable of 1600bar maximum injection pressure, fitted on GM 1.9L Euro4 diesel engine for passenger cars. The characterization of the injection process has been carried out in terms both of fuel injection rate, as well as of spatial and temporal fuel distribution in a quiescent non-evaporative optically accessible chamber.

Michigan Technological University has established a broad-based university-wide research initiative, termed Wood-to-Wheels (W2W), to develop and evaluate improved technologies for growing, harvesting, converting, and using woody biomass in renewable transportation fuel applications. The W2W program bridges the entire biomass development-production-consumption life cycle with research in areas including forest resources, bioprocessing, engine/vehicle systems, and sustainable decisions. The W2W chain establishes a closed cycle of carbon between the atmosphere, woody biomass, fuels, and vehicular systems that can reduce the accumulation of CO2 in the atmosphere. This paper will summarize the activities associated with the Wood-to-Wheels initiative and describe challenges and the potential benefits that are achievable.

This report describes a new driving simulator capability at General Motors (GM) Research and Development's (R&D) Vehicle Development Research (VDR) Laboratory and its application in an iterative HMI development process. The paper also provides an overview of three recent simulator usability tests supporting HMI development.

The management of multiple injections in compression ignition (CI) engines is one of the most common ways to increase engine performance by avoiding hardware modifications and after-treatment systems. Great attention is given to the profile of the injection rate since it controls the fuel delivery in the cylinder. The Injection Rate Shaping (IRS) is a technique that aims to manage the quantity of injected fuel during the injection process via a proper definition of the injection timing (injection duration and dwell time). In particular, it consists in closer and centered injection events and in a split main injection with a very small dwell time. From the experimental point of view, the performance of an IRS strategy has been studied in an optical CI engine. In particular, liquid and vapor phases of the injected fuel have been acquired via visible and infrared imaging, respectively. Injection parameters, like penetration and cone angle have been determined and analyzed.

Automotive technology is rapidly changing with electrification of vehicles, driver assistance systems, advanced safety systems etc. This advancement in technology is making the task of validation and verification of embedded software complex and challenging. In addition to the component testing, integration testing imposes even tougher requirements for software testing. To meet these challenges dSPACE is continuously evolving the Hardware-In-the-Loop (HIL) technology to provide a systematic way to manage this task. The paper presents developments in the HIL hardware technology with latest quad-core processors, FPGA based I/O technology and communication bus systems such as Flexray. Also presented are developments of the software components such as advanced user interfaces, GPS information integration, real-time testing and simulation models. This paper provides a real-world example of implication of integration testing on HIL environment for Chassis Controls.

The interest of the vehicle producers in fulfillment emission legislations without adopting after treatment systems is driving to the use of non-conventional energy sources for modern engines. A previous test campaign dealing with the use of blends of diesel and propane in a CI engine has pointed out the potential of this non-conventional fuel for diesel engines. The soft adaptation of the common rail injection system and the potential benefits, in terms of engine performances and pollutant emissions, encourage the use of propane-diesel blends if an optimization of the injection strategies is performed. In this work, the performances of a propane-diesel mixture in a research diesel engine have been investigated. The injection strategies of Euro 5 calibration have been used as reference for the development of optimized strategies. The aim of the optimization process was to ensure the same engine power output and reduce the pollutant emissions.

This paper aims to provide the experimental and numerical investigation of a single fuel droplet impingement on the different wall conditions to understand the detailed impinging dynamic process. The experimental work was carried out at the room temperature and pressure except for the variation of the impinged wall temperature. A high-speed camera was employed to capture the silhouette of the droplet impinging on wall process against a collimated light. Water, diesel, n-dodecane, and n-heptane were considered as four different droplets and injected from a precision syringe pump with the volume flow rate of 0.2 mL/min at various impact Weber numbers. The impingement outcomes after droplet impacting on the wall include stick, spread, rebound and splash, which depend on the controlling parameters of Weber number, Reynolds number, liquid and surface properties, etc.

This paper is based on a Research Project of the Department of Mechanical Engineering (DiME) in collaboration with Aprilia, the Italian motorbike manufacturer. In an attempt to simulate the functioning of the cooling plant of the Aprilia RSV-4 motorbike a numerical model was constructed using mono-dimensional and three-dimensional simulation codes. Our ultimate aim was to create a simulation model which could be of assistance to engine designers to improve cooling plant performance, thereby reducing research and development costs. The model allows to simulate the running conditions of the whole cooling circuit upon variations in environmental and running conditions. In particular, the centrifugal pump of the cooling plant was simulated by a 3D commercial software, while the whole circuit was built by a 1D commercial code which allows simulation of all the thermal exchanges and pressure drops in the cooling circuit.

The piezoelectric cylinder pressure transducer is one of the most critical tools for internal combustion (IC) engine research and development. However, not all cylinder pressure transducers perform equally in every application, and the fidelity of transducers can vary across different models and manufacturers. Even slightly dissimilar models from the same manufacturer can have significantly different performance in areas such as sensitivity and resistance to intra-cycle thermal shock. These performance differences can lead to errors and inconsistencies in the calculation of combustion metrics like mean effective pressure (MEP), the polytropic compression and expansion exponents (PolyC and PolyE), and mass fraction burn (MFB) calculations. The variations can lead to suboptimal hardware and calibration choices during the engine development phase.

The H-point is a critical part of vehicle design as it is the basis for many engineering dimensions within the vehicle interior. A complete design process includes comparisons of the design to competitive benchmark vehicles. However, the competitive design considerations needed to determine the common standard H-point reference are often unknown. The SAE Human Accommodation and Design Devices (HADD) technical committee recently published a new standard benchmark SgRP procedure [2]. This new standard practice needed to be tested with respect to the accuracy and repeatability for determining the unknown h-point design parameters within industry benchmarking tolerances. In 2019, the SAE HADD committee conducted a study to evaluate the reproducibility of the new procedure. This paper presents detailed results of that study and discusses opportunities for applying the new benchmark practice.

The paper reviews the role of drawbeads in sheet metal stamping. The design of drawbeads is discussed in depth, with treatment of different bead cross sections, bead end shapes, and bead materials. International standards and practices are included. This is followed by the historical development of the modeling of the drawbead restraining force, starting with basic equilibrium approaches, and leading to the use of the finite element method which permits the study of drawbead effects on sheet metal flow in three dimensions. Finally, the potential of active drawbeads is described based upon ongoing research which is directed toward closed-loop computer control of the stamping process through adjustment of the drawbead penetration.

This paper presents the experimental results obtained on Fuel Cell System designed and realized in Istituto Motori and based on 16 kW PEM (Proton Exchange Membrane) stack. This activity is part of the HBUS Project, whose goal is the realization of a midi-bus for public transportation in urban areas based on fuel cell technology. This Project involves several private and public partners, comprising Istituto Motori as research institution, I2T3 (Industrial Innovation Through Technological Transfer) agency for technological innovation and project management, together with public transportation companies and vehicle component makers.