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This study explores the feasibility of using a sustainable lignin-based fuel, consisting of 44 % lignin, 50 % ethanol, and 6 % water, in conventional compression ignition (CI) marine engines. Through experimental evaluations on a modified small-bore CI engine, we identified the primary challenges associated with lignin-based fuel, including engine startup and shutdown issues due to solvent evaporation and lignin solidification inside the fuel system, and deposit formation on cylinder walls leading to piston ring seizure. To address these issues, we developed a fuel switching system transitioning from lignin-based fuel to cleaning fuel with 85 vol% of acetone, 10 vol% of water and 5 vol% of ignition improving additive, effectively preventing system clogs.

With the current trend of including the evaluation of the risk of brain injuries in vehicle crashes due to rotational kinematics of the head, two injury criteria have been introduced since 2013 – BrIC and DAMAGE. BrIC was developed by NHTSA in 2013 and was suggested for inclusion in the US NCAP for frontal and side crashes. DAMAGE has been developed by UVa under the sponsorship of JAMA and JARI and has been accepted tentatively by the EuroNCAP. Although BrIC in US crash testing is known and reported, DAMAGE in tests of the US fleet is relatively unknown. The current paper will report on DAMAGE in NCAP-like tests and potential future frontal crash tests involving substantial rotation about the three axes of occupant heads. Distribution of DAMAGE of three-point belted occupants without airbags will also be discussed. Prediction of brain injury risks from the tests have been compared to the risks in the real world.

Electrification is the well-accepted solution to address carbon emissions and modernize vehicle controls. Batteries play a critical in the journey of electrification and modernization with battery voltage prediction as the foundation for safe and efficient operation. Due to its strong dependency on prior information, battery voltage was estimated with recurrent neural network methods in the recent literatures exploring a variety of deep learning techniques to estimate battery behaviors. In these studies, standard recurrent neural networks, gated recurrent units, and long-short term memory are popular neural network architectures under review. However, in most cases, each neural network architecture is individually assessed and therefore the knowledge about comparative study among three neural network architecture is limited. In addition, many literatures only studied either the dynamic voltage response or the voltage relaxation.

The liquefied natural gas (LNG)-fueled ships were provisioned to meet the strict emission legislation in the marine application since 2000. However, the scientific approach of burning the low-emission natural gas in lean combustion uncovered that the engine suffers from high methane slip emission. Serious questions are raised about the quantity of methane slip during marine conditions when the load varies in multiple frequencies and amplitudes. Previous studies by these authors explained how methane slip increases during load oscillation. This paper examined several practical methods to reach stable combustion in transient conditions to reduce the methane slip. Employing Proportional-Integral-Derivative (PID) controllers in a closed loop, implementing open-loop lookup tables, model predictive controller (MPC), and an innovated solenoid method are performed in a high-fidelity medium-speed natural gas spark-ignition (SI) engine model.

A computational fluid dynamics study of the scavenging process in a large two-stroke marine engine is presented in this work. Scavenging which is one of the key processes in the two-stroke marine engines, has a direct effect on fuel economy and emissions. This process is responsible for fresh air delivery, removing the combustion products from the cylinder, cooling the combustion chamber surfaces and providing a swirling flow for better air-fuel mixing. Therefore, having a better understanding of this process and the associated flow pattern is crucial. This is not achievable solely by experimental tests for large engines during engine operation due to the difficulties of measuring the flow field inside the cylinder. In this study, the axial and tangential velocities are compared and validated with the experimental results obtained from Particle Image Velocimetry (PIV) tests [1].

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.

Future legislation scenarios as well as stringent CO2 targets, in particular under real driving conditions, will require the introduction of new and additional powertrain technologies. Beside the increasing electrification of the powertrain, it will be essential to utilize the full potential of the Internal Combustion Engine (ICE). There is clearly a competition of new and different ICE-Technologies [1] including VCR. VCR systems are expected to be introduced to a considerable number of next generation turbocharged Spark Ignited (SI) engines in certain vehicle classes. The implementation of Miller or Atkinson cycles is an essential criterion for increased geometric Compression Ratio (CR). The DUAL MODE Variable Compression System (VCS)TM enables a 2-stage variation of the connecting rod length and thus of the compression ratio (CR).

The Composite Lightweight Automotive Suspension System is a composite rear suspension knuckle/tieblade consisting of UD prepreg (epoxy resin), SMC (vinylester resin) carbon fibre and a steel insert to reduce the weight of the component by 35% and reduce Co2. The compression moulding manufacturing process and CAE optimisation are unique and ground-breaking for this product and are designed to allow high volume manufacture of approx. 30,000 vehicles per year. The manufacturing techniques employed allow for multi-material construction within a five minute cycle time to make the process viable for volume manufacture. The complexities of the design lie in the areas of manufacturing, CAE prediction and highly specialised design methods. It is a well-known fact that the performance of a composite part is primarily determined by the way it is manufactured.

In this study, we present an intelligent and wireless subsystem for powering and communicating with three sets of seat belt buckle sensors that are each installed on removable and interchangeable automobile seating. As automobile intelligence systems advance, a logical step is for the driver’s dashboard to display seat belt buckle indicators for rear seating in addition to the front seating. The problem encountered is that removable and interchangeable automobile seating outfitted with wired power and data links are inherently less reliable than rigidly fixed seating, as there is a risk of damage to the detachable power and data connectors throughout end-user seating removal/re-installation cycles.

Variable Compression Systems (VCS) for Internal Combustion Engines (ICE) will become increasingly more important in the future to meet stringent global fuel economy and CO2 standards. A Dual Mode VCS is in development at AVL and the basic functionality and potential were described in a technical paper which was presented at the SAE WCX 2017 [1]. The system is based on a hydraulically switched and locked conrod with telescopic shank. The AVL Dual Mode VCS was designed and virtually optimized with CAE simulation methods for the boundary conditions of a typical 2.0 L Inline (I) 4 Turbocharged Gasoline Direct Injection (TGDI) engine representing state-of-the-art gasoline engine technology for the next years to come.

Of late there has been a resurgence in studies investigating parameters that quantify combustion knock in both standardized platforms and modern spark-ignition engines. However, it is still unclear how metrics such as knock (octane) rating, knock onset, and knock intensity are related and how fuels behave according to these metrics across a range of conditions. As part of an ongoing study, the air supply system of a standard Cooperative Fuel Research (CFR) F1/F2 engine was modified to allow mild levels of intake air boosting while staying true to its intended purpose of being the standard device for American Society for Testing and Materials (ASTM)-specified knock rating or octane number tests. For instance, the carburation system and intake air heating manifold are not altered, but the engine was equipped with cylinder pressure transducers to enable both logging of the standard knockmeter readout and state-of-the-art indicated data.

With the implementation of EURO VI and similar emission legislation, the industry assumed the pace and stringency of new legislation would be reduced in the future. The latest announcements of proposed and implemented legislation steps show that future legislation will be even more stringent. The currently leading announced legislation, which concerns a large number of global manufacturers, is the legislation from the United States (US) Environmental Protection Agency (EPA) and the California Air Resources Board (CARB). Both announced new legislation for CO2, Greenhouse Gas (GHG) Phase II. CARB is also planning additional Ultra Low NOx regulations. Both regulations are significant and will require a number of technologies to be used in order to achieve the challenging limits. AVL published some engine related measures to address these legislation steps.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

This work investigates the effects of cavitation on spray characteristics by comparing measurements of liquid and vapor penetration as well as ignition delay and lift-off length. A smoothed-inlet, converging nozzle (nominal KS1.5) was compared to a sharp-edged nozzle (nominal K0) in a constant-volume combustion vessel under thermodynamic conditions consistent with modern compression ignition engines. Within the near-nozzle region, the K0 nozzle displayed larger radial dispersion of the liquid as compared to the KS1.5 nozzle, and shorter axial liquid penetration. Moving downstream, the KS1.5 jet growth rate increased, eventually reaching a growth rate similar to the K0 nozzle while maintaining a smaller radial width. The increasing spreading angle in the far field creates a virtual origin, or mixing offset, several millimeters downstream for the KS1.5 nozzle.

The automotive electronic architectures have moved from federated architectures, where one function is implemented in one ECU (Electronic Control Unit), to distributed architectures, where several functions may share resources on an ECU. In addition, multicore ECUs are being adopted because of better performance, cost, size, fault-tolerance and power consumption. In this paper we present an approach for the automatic software functionality assignment to multicore distributed architectures. We consider that the systems use the AUTomotive Open System ARchitecture (AUTOSAR). The functionality is modeled as a set of software components composed of subtasks, called runnables, in AUTOSAR terminology.

In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).

This paper presents the application of a proposed fuzzy inference system as part of a stability control design scheme implemented with active steering actuator sets. The fuzzy inference system is used to detect the level of overseer/understeer at the high level and a speed-adaptive activation module determines whether an active front steering, active rear steering, or active 4 wheel steering is suited to improve vehicle handling stability. The resulting model-free system is capable of minimizing the amount of model calibration during the vehicle stability control development process as well as improving vehicle performance and stability over a wide range of vehicle and road conditions. A simulation study will be presented that evaluates the proposed scheme and compares the effectiveness of active front steer (AFS) and active rear steer (ARS) in enhancing the vehicle performance. Both time and frequency domain results are presented.

Modern diesel systems have come to rely on fuel systems with the capacity for high injection pressures. The benefits of such high pressures include improved tolerance for EGR, reduced emissions and improved performance. Current production fuel systems have typical capacities to 2500 bar, when a decade ago 1800 bar was a typical limit. Following the trend, this paper investigates the effect of rail pressures up to 3000 bar on a 1.5L single cylinder research engine. The injector nozzles tested include two variations in flow rate, the number of holes, and spray cone angle. In addition to fuel rail pressure, the effects of intake swirl, excess-air ratio, EGR, and injection timing are evaluated at speed and load points representative of A100, B100, and C100 test conditions of the U.S. EPA on-highway 13 Mode test cycle.

This work concerns the modelling of soot formation process in diesel spray combustion under engine-like conditions. The key aim is to investigate the soot formation characteristics at different ambient temperatures. Prior to simulating the diesel combustion, numerical models including a revised multi-step soot model is validated by comparing to the experimental data of n-dodecane fuel in which the associated chemistry is better understood. In the diesel spray simulations, a single component n-heptane mechanism and the multi-component Diesel Oil Surrogate (DOS) model are adopted. A newly developed C16-based model which comprises skeletal mechanisms of n-hexadecane, heptamethylnonane, cyclohexane and toluene is also implemented. Comparisons of the results show that the simulated liftoff lengths are reasonably well-matched to the experimental measurement, where the relative differences are retained to below 18%.

A new turbocharged 60° 2.7L 4V-V6 gasoline engine has been developed by Ford Motor Company for both pickup trucks and car applications. This engine was code named “Nano” due to its compact size; it features a 4-valves DOHC valvetrain, a CGI cylinder block, an Aluminum ladder, an integrated exhaust manifold and twin turbochargers. The goal of this engine is to deliver 120HP/L, ULEV70 emission, fuel efficiency improvements and leadership level NVH. This paper describes the upfront design and optimization process used for the NVH development of this engine. It showcases the use of analytical tools used to define the critical design features and discusses the NVH performance relative to competitive benchmarks.