Search

In this study, the role of turbulence-chemistry interaction in diesel spray auto-ignition, flame stabilization and end of injection phenomena is investigated under engine relevant “Spray A” conditions. A recently developed diesel spray combustion modeling approach, Conditional Source-term Estimation (CSE-FGM), is coupled with Reynolds-averaged Navier-Stokes simulation (RANS) framework to study the details of spray combustion. The detailed chemistry mechanism is included through the Flamelet Generated Manifold (FGM) method. Both unsteady and steady flamelet solutions are included in the manifold to account for the auto-ignition process and the subsequent flame propagation in a diesel spray. Conditionally averaged chemical source terms are closed by the conditional scalars obtained in the CSE routine. Both non-reacting and reacting spray jets are computed over a wide range of Engine Combustion Network (ECN) diesel. “Spray A” conditions. The reacting spray results are compared with simulations using a homogeneous reactor combustion model and a flamelet combustion model with the same chemical mechanism. The present study represents the first application of CSE for a diesel spray. The non-reacting liquid/vapour penetration, the mean and RMS mixture fraction, the reactive region, the flame lift-off and the ignition delay show a good agreement with literature data from an optically accessible combustion vessel over a wide range of tested conditions. The CSE-FGM model also shows a better capability in predicting the end-of-injection events in diesel spray combustion. Overall, the CSE-FGM model is shown to capture the experimental trends well, both quantitatively and qualitatively.

Automated solutions for manufacturing composite products based on prepreg often imply Automatic Fiber Placement or Automatic Tape Laying. These systems are generally associated with huge investments. For certain manufacturing applications it is interesting to investigate alternatives to find simpler and less costly automation. One example of an automated system could be the use of a standard industrial robot to pick single prepreg plies from an automated cutting machine and stack them to form a plane laminate. This paper is based on a case illustrating a product from the aircraft manufacturing industry. The case will demonstrate a pick and place concept on a general level and illustrate challenges that must be solved. The challenge selected to be the main focus for this paper is an automated process for backing paper removal. A literature review of different gripping technologies reveals several interesting technologies, and the most promising are tested for backing paper removal. The tests show that an automated removal process can be designed by using standard vacuum grippers in combination with mechanical clamping grippers. In order to lift the backing paper with a vacuum gripper an initial separation between the backing paper and prepreg is needed. This separation is most easily mechanically induced by bending the material. The proposed solution for automatic backing paper removal can be integrated in a manufacturing cell for manufacturing of the studied product. SAE Technical Paper 2013-01-2289

The Advanced Extra-vehicular Activity (EVA) team of the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC) Crew and Thermal Systems Division (CTSD) participated in the Desert Research and Technology Study (RATS) in September 2003, at Meteor Crater, AZ. The Desert RATS is an integrated remote field site te t with team members from several NASA centers (Johnson Space Center; Glenn and Ames Research Centers) and universities (Bowling Green State University, University of Cincinnati, Massachusetts Institute of Technology) participating. Each week of the two-week field test had a primary focus. The primary test hardware for the first week was the I-Gravity Lunar Rover Training Vehicle, or Grover, which was on loan to NASA from the United States Geological Survey (USGS) Astrogeology Research Program. The 2003 Grover driving test results serve as a rover performance characterization baseline for the Science, Crew, Operation and Utility Testbed (SCOUT) project team, which will be designing and fabricating a next generation roving vehicle prototype in Fiscal Year (FY) 2004. The second week of testing focused on EVA geologic traverses that utilized a geologic sample field analysis science trailer and also focused on human-robotic interaction between the suited subjects and the EVA Robotic Assistant (ERA). This paper will review the Advanced EVA team's role in the context of the overall Desert RATS, as well as the EVA team results and lessons learned. For information regarding other test participants' results, the authors can refer interested parties to the test reports produced by those Desert RATS teams.

International audience; The Phylog project aims at offering a model-based software-aided certification framework for aeronautical systems based on multi/many-core architectures. Certifying such platforms will entail fulfilling the high level objectives of the MCP-CRI / CAST-32A position paper. Among those, two types of analysis are required: interference and safety analyses. Because of the large size of the platforms and their complexity, those analyses can lead to combinatorial explosion and to some misinterpretation. To tackle these issues, we explore a service-based modelling approach that leads to a simplification of the analyses and to the highlighting of salient properties, making the adaptation of the certification argumentation efficient.

Although waste animal fats such as chicken fat are promising alternative energy sources, biodiesels produced from these type of feedstocks hardly satisfies the EN14214 biodiesel standards. In this study, biomixtures were prepared by blending cottonseed biodiesel and chicken rendering fat biodiesel which were produced via transesterification method. Biodiesels were blended with each other at 60/40, 50/50 and 30/70 volume ratios to produce CO60CH40, CO50CH50 and CO30CH70 fuels. First, fuel properties of the neat biodiesels and novel biomixtures were measured and compared to European biodiesel standards and diesel. Then, the engine performance, combustion characteristics and exhaust emissions of these novel biomixture fuels were measured in a three-cylinder indirect injection diesel engine under various engine loads and at constant speed of 1500 rpm. The fuel characterisation showed that CO60CH40 and CO50CH50 biomixtures met the European standards. The Brake Specific Energy Consumption (BSEC) and Brake Thermal Efficiency (BTE) of all biomixtures were comparable with CO100, CH100 and diesel at the full engine load. The combustion results revealed that the maximum in-cylinder pressure and energy release values of the CO50CH50 were 4.2% and 4.4% higher than the diesel at full engine load because of optimised fuel properties of biomixture such as molecular structure, viscosity, cetane number and iodine value. CO50CH50 had 2.9% reduced CO 2 and comparable CO emission compared to diesel, which were also 5.6% and 13% lower than cottonseed biodiesel respectively. However, NO emission of CO50CH50 was found 3.8% and 5.8% higher than diesel and cottonseed biodiesel. A 6.5% reduction on NO emission was observed when CO60CH40 biomixture fuel was used instead of diesel. To conclude, this research showed that blending of cottonseed and chicken fat biodiesels is a promising approach to meet the EN14214 standards, improve in-cylinder pressure, optimise energy release and reduce exhaust emissions. Blending of different biodiesels will be tested as a future work.

Presents results of tests of ultra-low sulfur diesel blended with soy-biodiesel at 5 percent using a Cummins ISB engine with a diesel particulate filter.

Three Intermediate-Scale Aerobic Bioreactors were designed, fabricated, and operated. They utilized mixed microbial communities to bio-degrade plant residues. The continuously stirred tank reactors operated at a working volume of 8 L, and the average oxygen mass transfer coefficient, k(sub L)a, was 0.01 s(exp -1). Mixing time was 35 s. An experiment using inedible wheat residues, a replenishment rate of 0.125/day, and a solids loading rate of 20 gdw/day yielded a 48% reduction in biomass. Bioreactor effluent was successfully used to regenerate a wheat hydroponic nutrient solution. Over 80% of available potassium, calcium, and other minerals were recovered and recycled in the 76-day wheat growth experiment.

The paper presents novel studies on the impact of different ignition control parameters on combustion stability and spark plug wear. First, experimental results from a 32.4-liter biogas fueled large bore single cylinder spark ignition engine are discussed. Two different ignition systems were considered in the experiment: a DC inductive and an AC capacitive. The spark plugs used in the experiment were of dual-iridium standard J-gap design of different electrode gaps. Test results show the importance of different degrees of freedom to control a spark. A robust ignition is found to be achieved by using a very short spark duration, which in turn reduces total energy discharge at the gap. Further observations reveal that once a stable and self-propagating flame kernel is developed, it becomes independent of the spark energy further added to the gap. Finally, results from the spark plug wear tests using a pressurized rig chamber are discussed. It is found that an excessive spark energy discharge at the gap contributes to high erosion of spark plug electrodes, which is not desirable. However, spark energy is not the only factor affecting spark plug erosion. It is also the type of spark discharge (DC/AC) that governs the electrode wear over time. Therefore, the advantage of an AC spark discharge over a DC spark has been well established through the experimental results. The inherent property of an AC spark is found to be significantly slowing down electrode wear over time, hence increasing the service life of a spark plug.

The development of Digital Twin (DT) has become popular. A dominant description of DT is that it is a software representation that mimics a physical object to portray its real-world performance and operating conditions of an asset. It uses near real-time data captured from the asset and enables proactive optimal operation decisions. There are many other definitions of DT, but not many explicit evaluations of DT performance found in literature. The authors have an interest to investigate and evaluate the quality and stability of appropriate DT techniques in real world aircraft Maintenance, Repair, and overhaul (MRO) activities. This paper reviews the origin of DT concept, the evolution and development of recent DT technologies. Examples of DTs in aircraft systems and transferable knowledge in related vehicle industries are collated. The paper contrasts the benefits and bottlenecks of the two categories of DT methods, Data-Driven (DDDT) and Model-Based (MBDT) models. The paper evaluates the applicability of the two models to represent vehicle system management. The authors present their methodological approach on Predictive Maintenance (PM) development basing on reliable DT models for vehicle systems. This paper contributes to design, operation, and support of aircraft/vehicle systems.

Distillation-based waste water pretreatment and recovered water posttreatment methods are proposed for the NASA Space Station. Laboratory investigation results are reported for two nonoxidizing urine pretreatment formulas (hexadecyl trimethyl ammonium bromide and Cu/Cr) which minimize the generation of volatile organics, thereby significantly reducing posttreatment requirements. Three posttreatment methods (multifiltration, reverse osmosis, and UV-assisted ozone oxidation) have been identified which appear promising for the removal of organic contaminants from recovered water.

A commercially available fuel, E85, a blend of ~85% ethanol and ~15% gasoline, can be a viable substitute for fossil fuels in internal combustion engines in order to achieve a reduction of the greenhouse gas (GHG) emissions. Ethanol is traditionally made of biomass, which makes it a part of the food-feed-fuel competition. New processes that reuse waste products from other industries have recently been developed, making ethanol a renewable and sustainable second-generation fuel. So far, work on E85 has focused on spark ignition (SI) concepts due to high octane rating of this fuel. There is very little research on its application in CI engines. Alcohols are known for low soot particle emissions, which gives them an advantage in the NOx–soot trade-off of the compression ignition (CI) concept. Therefore, the main objective of this research is to experimentally characterise the impact of E85 on performance and emissions of a heavy-duty (HD) direct ignition compression ignition (DICI) engine at mid-to-low load, and to identify possible challenges. To do so, a surface response method of the Box-Behnken type is implemented on a measurement campaign on a HD single cylinder CI engine. The effects of common rail pressure (Prail), λ and combustion timing (CA50) as control parameters on experimentally measured values of soot, regulated gaseous emissions (NOx, CO and THC) and gross indicated efficiency (GIE) of the engine are studied. Linear regression (LR) analysis indicates that the outputs of the NOx and soot models are affected by all three control parameters, whereas GIE, THC and CO models in this case exclude λ effects. E85 fuel shows potential to be a good candidate for highly efficient low temperature combustion (LTC) in DICI engines, with reduced NOx and soot levels compared to fossil diesel combustion.

The growing concerns on the emission of particles smaller than 23 nm, which are harmful to human health, lead to the necessity of introducing a regulation for these particles not yet included in the current emission standards. Considering that measurements of concentration of sub-23 nm particles are particularly sensitive to the sampling conditions, it is important to identify an effective assessment procedure. Aim of this paper is the characterization of the effect of the sampling conditions on sub-23 nm particles, emitted by PFI (port fuel injection) and DI (direct injection) spark ignition engines fueled with gasoline, ethanol and a mixture of ethanol and gasoline (E30). The experimental activity was carried out on a 250 cm3 displacement four stroke GDI and PFI single cylinder engines. The tests were conducted at 2000 rpm and 4000 rpm full load, representative of the homologation urban driving cycle. Particle emissions were characterized in terms of mass concentration, by means of a Smokemeter, and of number and size in the range of 5.6-560 nm, through the Engine Exhaust Particle Sizer (EEPS). The sampling was performed by a PMP compliant system, which permits to change the main sampling parameters. Particular attention was focused on the interval of 10-23 nm, to better characterize the effect of the sampling parameters on these particles, with the aim of determining a proper procedure for the measurement. The results show the strong influence of sampling conditions on particle measurements, especially for the sub- 23 nm highlighting the necessity for a definition of an appropriate measurement protocol for this size fraction

In this work, numerical simulations of an automotive-sized scavenged pre-chamber mounted in an optically-accessible rapid compression-expansion machine (RCEM) have been carried out using two different turbulence models: Reynolds-Averaged Navier-Stokes (RANS) and Large-Eddy Simulation (LES). The RANS approach is combined with the G-equation combustion model, whereas the LES approach is coupled with the flamelet generated manifold (FGM) model for partially-premixed combustion. Simulation results are compared with experimental data in terms of OH* chemiluminescence in the main chamber. Both RANS and LES results were found to qualitatively reproduce the main features observed experimentally in terms of spatial flame development. Simulation results are further analysed by means of early flame propagation within the pre-chamber (related to the fuel and turbulence intensity distributions) and the ignition process in the main chamber. During the turbulence jet ignition (TJI) process, the analysis of the LES progress variable variance reveals that during the intensive jet mixing the mixture in the main chamber is predominantly ignited by autoignition followed by a progressive transition to a deflagrative premixed flame propagation mode. For the lean fuel-air mixture considered (λ=2) the mixing of the additional fuel (previously injected into the pre-chamber) within the main chamber was found to play a major role on the ignition process., SAE Technical Papers, 2019-01-0224, ISSN:0148-7191, ISSN:2688-3627

International audience; This paper describes the contribution of the closed-loop control of the motion platform (six degrees of freedom: longitudinal, lateral, and vertical displacements; pitch, roll, yaw) and motion platform’s three-dimensional (3D) displacement scale factor (SF) (0.2 and 1.0) on eye pupil diameter (PD) as an objective measure of driver cognitive load. Longitudinal, lateral, and vertical accelerations as well as longitudinal, lateral, and vertical positions from the center of gravity (CG) of the vehicle were registered through the driving simulation software SCANeRstudio® from OKTAL. Closed-loop control decreases the driver mental load. This type of closed-loop control can be used to decrease the driver mental load.

Battery electric vehicles (BEV) share the ability of regenerative braking since they are equipped with two independent types of deceleration devices, namely the electric motor working as a generator and the friction brakes. Correct interaction of these systems in terms of driving safety and energy efficiency is a function of the Brake Blending Control. Individual electric motors for each wheel and a decoupled brake system provides the Brake Blending with a high design flexibility that allows significant advantages regarding energy consumption, brake performance, and driving comfort. This paper is focusing on the fail behaviour and analyses the robustness and redundancy abilities of such systems against various error scenarios. For this purposes, a distributed x-in-the-loop environment, consisting of dedicated simulation and hardware testing components, is introduced. The investigation is carried out based on a high-fidelity real-time simulation model of an electric sport utility vehicle with four in-wheel motors (IWM) and decoupled electro-hydraulic brake system. This model can be used for a detailed analysis of vehicle dynamics in case of brake system fails. The electro-hydraulic decoupled brake system is implemented through a Hardware-in-the-loop test rig, which allows a realistic fault injection. The vehicle stability and controllability is investigated under the circumstances of various brake system failures in the regenerative and friction brake system, respectively. These studies are presented according to standardized test scenarios like Straight line braking (DIN 70028) and Brake-in-turn (ISO 7975). With obtained x-in-the-loop simulation results, the impact of a failure on vehicle dynamics is discussed in the final part of the paper.

Growing concerns about the emissions of internal combustion engines have forced the adoption of aftertreatment devices to reduce the adverse impact of diesel engines on health and environment. Diesel particulate filters are considered as an effective means to reduce the particle emissions and comply with the regulations. Research activity in this field focuses on filter configuration, materials and aging, on understanding the variation of soot layer properties during time, on defining of the optimal strategy of DPF management for on-boardcontrol applications. A model was implemented in order to simulate the filtration and regeneration processes of a wall-flow particulate filter,taking into account the emission characteristic of the engine, whose architecture and operating conditions deeply affect the size distribution of soot particles. The model is based on a lumped parameter approach able to be used for on-board monitoring and control, in order to provide knowledge of DPF status versus time.

This paper describes a multi-degree-of-freedom model of a three-wheeled car, implemented in Matlab®. The purpose was to investigate the dynamics of the car (assumed to be rigid on its suspension) during cornering. While the problems associated with three-wheeled cars are well-known, much of the guidance in the literature and off-the-software assumes a conventional four-wheeled car. Consequently, the authors were approached with a battery-electric concept car which was thought to offer better performance than existing variants, because the use of hub motors lowered the centre of gravity and hence reduced rollover coefficient. However, simulation of the vehicle model in cornering shows that the concept is still prone to instability. Indeed, it suffers greater roll velocities than a comparable three-wheeled car with internal combustion engine, because the ratio of sprung to unsprung mass is significantly altered. This paper therefore recommends a programme of further simulations and model-based design changes to progress the concept to a marketable performance product.

The automotive trends of vehicles with lower aerodynamic drag and more powerful drivetrains have caused increasing concern regarding stability issues at high speeds, since more streamlined bodies show greater sensitivity to crosswinds. This is especially pronounced for high vehicles, such as sports utility vehicles. Besides, the competitiveness in the automotive industry requires faster development times and, thus, a need to evaluate the high speed stability performance in an early design phase, preferable using simulation tools. The usefulness of these simulation tools partly relies on realistic boundary conditions for the wind and quantitative measures for assessing stability without the subjective evaluation of experienced drivers. This study employs an on-road experimental measurements setup to define relevant wind conditions and to find an objective methodology to evaluate high speed stability. The paper focuses on the events in proximity to the drivers’ subjective triggers of instability. Wind direction and magnitude, vehicle motion response, along with the subjective event triggering were measured at different conditions of the natural wind. A statistical approach was utilized to analyze the correlation between the vehicle response and subjective triggers together with the wind conditions. A correlation was established between the subjective triggers and a rapid change in lateral acceleration and yaw velocity response. The paper also proposes a set of four crosswind gust profiles of interest for driving stability, combining results from previous research and the experimental data of the natural wind obtained in this study. These findings can be used as objective measures for virtually assessing stability performance and as realistic boundary conditions for simulating wind gusts.

Connected vehicles (CVs) have situational awareness that can be exploited for control and optimization of the powertrain system. While extensive studies have been carried out for energy efficiency improvement of CVs via eco-driving and planning, the implication of such technologies on the thermal responses of CVs has not been fully investigated. One of the key challenges in leveraging connectivity for optimization-based thermal management of CVs is the relatively slow thermal dynamics, which necessitate the use of a long prediction horizon to achieve the best performance. Long-term prediction of the CV speed, unlike the V2V/V2I-based short-range prediction, is difficult and error-prone. The multiple timescales inherent to power and thermal systems call for a variable timescale optimization framework with access to short- and long-term vehicle speed preview. To this end, a model predictive controller (MPC) with a multi-range speed preview for integrated power and thermal management (iPTM) of connected hybrid electric vehicles (HEVs) is presented in this paper. The MPC is formulated to manage the power-split between the engine and the battery while enforcing the power and thermal (engine coolant and catalytic converter temperatures) constraints. The MPC exploits prediction and optimization over a shorter receding horizon and longer shrinking horizon. Over the longer shrinking horizon, the vehicle speed estimation is based on the data collected from the connected vehicles traveling on the same route as the ego-vehicle. Simulation results of applying the MPC over real-world urban driving cycles in Ann Arbor, MI are presented to demonstrate the effectiveness and fuel-saving potentials of the proposed iPTM strategy under the uncertainty associated with long-term predictions of the CV's speed., 15 pages, 15 figures, 1 table, to appear in 2020 WCX SAE World Congress Experience, SAE Technical Paper 2020-01-0590

Powered two-wheeler (PTW) riders and passengers are among the group of vulnerable road users (VRU). This group uses the road transportation system together with other better-protected users such as passenger cars and truck drivers. The main vulnerability of PTW rider lies in their unequal position during the crash, due to the inability of application of the crashworthiness concept during the PTW vehicle design. This inequality could be somehow mitigated by the design of personal protective equipment (PPE). Mostly the design of the PPE’s is led by the standards which often are obsolete and takes into account only simple drop-tests (ECE 22.05). Those tests did not take into account complicated kinematics of the motorcycle accidents and biomechanics of the human body (the assessment is based only on the linear acceleration of the headform center of gravity). The authors propose a virtual approach for the PTW rider injury risk assessment, which coupled with the pre-impact conditions, could be used for the new PPE protection standards preparation. In this paper, authors want to present a numerical study on the most common PTW impact scenarios, which are described in ISO 13232. The simulations of the accidents were conducted in the VPS numerical environment (PAM-Crash explicit solver). Accidents participants, namely opposite vehicle (OV) modeled by finite element method (FEM) approach, powered two-wheeler (PTW) modeled by multibody system (MBS) approach, PTW driver represented by hybrid FE-MBS human body model Virthuman and a helmet (modeled by FE approach) were coupled to represent the 7 most common accident scenarios. The helmet is the only PPE enforced by the law, but not in all territories (Afghanistan, Dominica, Guyana, Mexico, Libya, Senegal, USA). Due to the complexity of the OV FE model, there was a necessity of model simplification and revalidation, which also was done in this work. The results of the simulations were examined with special emphasis on realistic representation of real accident kinematics. In each configuration, an injury risk assessment was done on the PTW rider model. The assessment was done based on injury criterion used by the NCAP, UNE 135900 and the LNL criterion. The paper shows that the virtual approach using the Virthuman human body model could be used for the simulation of PTW accidents. The results of this paper could be used for future PPE design.

Conference paper presented at WCX SAE World Congress Experience, 18-20 April, 2023, Detroit, MI, USA. This study aims to improve the dual fuel combustion for low/zero carbon fuels. Seven cases were tested in a single cylinder optical engine and their ignition and combustion characteristics are compared. The baseline case is the conventional diesel combustion. Four cases are diesel-gas (compressed natural gas) dual-fuel combustion operations, and two cases are diesel-hythane combustion. The diesel fuel injection process was visualized by a high-speed copper vapour laser. The combustion processes were recorded with a high-speed camera at 10000 Hz with an engine speed of 1200 rpm. The high-speed recordings for each case included 22 engine cycles and were postprocessed to create one spatial overlapped average combustion image. The average combustion cycle images were then further thresholded and these images were then used in a new method to analyze the cycle-to-cycle variation in a dimensionless, for all cases comparable value. Furthermore, the ignition delay and heat release profile of each case are analyzed. The results showed the lowest deviation from the complete overlap for the pure Diesel case and the Hythane Cases since the flames are more concentrated in these. From these studies, it can be concluded that the cyclic variation for the pure diesel combustion is mostly caused by the different swirl speeds in the piston bowl. The diesel-gas dual-fuel combustion with earlier pilot injections have lower cyclic variation due to a wider spread of the combustible mixture. The usage of hythane as main fuel instead of methane results in a about 10% faster combustion and more concentrated flames areas. European Union Horizon 2020 Research and Innovation programme. Grant Agreement No. 861002.

Autonomous truck and trailer configurations face challenges when operating in reverse due to the lack of sensing on the trailer. It is anticipated that sensor packages will be installed on existing trailers to extend autonomous operations while operating in reverse in uncontrolled environments, like a customer's loading dock. Power Line Communication (PLC) between the trailer and the tractor cannot support high bandwidth and low latency communication. This paper explores the impact of using Ethernet or a wireless medium for commercial trailer-tractor communication on the lifecycle and operation of trailer electronic control units (ECUs) from a Systems Engineering perspective to address system requirements, integration, and security. Additionally, content-based and host-based networking approaches for in-vehicle communication, such as Named Data Networking (NDN) and IP-based networking are compared. Implementation, testing and evaluation of prototype trailer ECU communication with the tractor ECUs over Ethernet is shown by transmitting different data types simultaneously. The implementation is tested with two networking approaches, Named Data Networking, and Data Distribution Service (DDS) and the test indicated that NDN over TCP is an efficient approach that is capable of meeting automotive communication requirements. Using Ethernet or a wireless harness and NDN for commercial trailer Anti-Lock Braking System (ABS) ECU provides adequate resources for the operation of autonomous trucks and the expansion of its capabilities, and at the same time significantly reduces the complexities compared to when new features are added to legacy communication systems. Using a wireless medium for tractor-trailer communication will bring new cybersecurity challenges and requirements which requires new development and lifecycle considerations.

This paper proposes the use of an on-demand, ride hailed and ride-Shared Autonomous Vehicle (SAV) service as a feasible solution to serve the mobility needs of a small city where fixed route, circulator type public transportation may be too expensive to operate. The presented work builds upon our earlier work that modeled the city of Marysville, Ohio as an example of such a city, with realistic traffic behavior, and trip requests. A simple SAV dispatcher is implemented to model the behavior of the proposed on-demand mobility service. The goal of the service is to optimally distribute SAVs along the network to allocate passengers and shared rides. The pickup and drop-off locations are strategically placed along the network to provide mobility from affordable housing, which are also transit deserts, to locations corresponding to jobs and other opportunities. The study is carried out by varying the behaviors of the SAV driving system from cautious to aggressive along with the size of the SAV fleet and analyzing their corresponding performance. It is found that the size of the network and behavior of AV driving system behavior results in an optimal number of SAVs after which increasing the number of SAVs does not improve overall mobility. For the Marysville network, which is a 9 mile by 8 mile network, this happens at the mark of a fleet of 8 deployed SAVs. The results show that the introduction of the proposed SAV service with a simple optimal shared scheme can provide access to services and jobs to hundreds of people in a small sized city.

International audience; Recent internal combustion (IC) engine developments focus on gasoline fuel. This requires a better understanding of fuel reactivity at different thermodynamic conditions. Gasoline fuel reactivity control by additives is an efficient method to get better IC engine performances. 2-Ethylhexyl nitrate (EHN) promoting effect (0.1-1% mol.) on combustion has been investigated experimentally and numerically. Rapid compression machine (RCM) experiments were carried out at equivalence ratio 0.5 at 10 bar, from 675 to 995 K. The targeted surrogate fuel is a mixture of toluene and n-heptane in order to capture the additive effect on both cool flame and main ignition. A kinetic model was developed from literature data assembly and validated upon a large set of variations including species profiles and ignition delays of pure compounds as well as mixtures. At the experimental conditions, it was found that the EHN reduces the ignition delay time (IDT) of the surrogate fuel in the whole temperature range. EHN effectiveness tends to be minimum around 705 K and increases with temperature. The results also indicate that EHN effect increases nonlinearly with EHN doping levels. Numerical analyses revealed that the EHN effect is linked to NO2-NO loops, which enhances fuel reactivity. The methodology proposed here enable to simulate the EHN effect with simple compounds rather than the full EHN chemistry set. This strategy could simplify the consideration of additive effect when computational fluid dynamics (CFD) simulations are performed on engine. Finally, the study also highlights the EHN effectiveness on several thermodynamic conditions as well as equivalence ratios. The objective is to assess its performance upon large operating conditions which appears to be of interest with novel combustion systems targeting low temperature as well as lean combustion.

In this work the performance and noxious emissions of a prototype Spark Ignition (SI) engine, working in ultra-lean conditions, are investigated. It is a four-cylinder engine, having a very high compression ratio, and an active pre-chamber. The required amount of air is provided by a low-pressure variable geometry turbocharger, coupled to a high-pressure E-compressor. The engine is equipped with a variable valve timing device on the intake camshaft. The goal of this activity is to support the development and the calibration of the described engine, and to exploit the full potential of the ultra-lean concept. To this aim, a combustion model for a pre-chamber engine, set up and validated in a previous paper for a similar single-cylinder unit, is utilized. It is coupled to additional in-house developed sub-models, employed for the prediction of the in-cylinder turbulence, heat transfer, knock and pollutant emissions. Such a complex architecture, schematized in a commercial 1D modeling framework, presents several control parameters which have to be properly selected to maximize the engine efficiency and minimize the noxious emissions over its whole operating domain. A Rule-Based (RB) calibration strategy is hence implemented in the 1D model to identify the optimal values of each control variable. The reliability of the RB calibration is also demonstrated through the comparison with the outcomes of a general-purpose optimizer, over a load sweep at a constant speed. The 1D model and the RB methodology are then applied for the performance prediction over the whole engine operating domain. The predicted performances show the possibility to achieve a wide zone of very high efficiency, with limited penalizations only at very low loads. Main advantages of the lean-combustion concept are highlighted, concerning a higher specific heat ratio, reduced heat losses, improved knock mitigation, and abatement of pollutant emissions, especially regarding CO and NOx. The presented methodology demonstrates to be a valuable tool to support the development and calibration of the considered high-efficiency engine architecture.

This paper evaluates a thermodynamic ice crystal icing model that has been previously presented to describe the possible mechanisms of icing within the core of a turbofan jet engine. The model functions between two distinct ice accretions based on a surface energy balance: freeze-dominated icing and melt-dominated icing. Freeze-dominated icing occurs when liquid water (from melted ice crystals) freezes and accretes on a surface along with the existing ice of the impinging water and ice mass. This freeze-dominated icing is characterized as having strong adhesion to the surface. The amount of ice accretion is partially dictated by a freeze fraction, which is the fraction of impinging liquid water that freezes. Melt-dominated icing occurs as unmelted ice on a surface accumulates. This melt-dominated icing is characterized by weakly bonded surface adhesion. The amount of ice accumulation is partially dictated by a melt fraction, which is the fraction of impinging ice crystals that melts. Experimentally observed ice growth rates suggest that only a small fraction of the impinging ice remains on the surface, implying a mass loss mechanism such as splash, runback, bounce, or erosion. The fraction of mass loss must be determined in conjunction with the fraction of freezing liquid water or fraction of melting ice on an icing surface for a given ice growth rate. This mass loss parameter, however, along with the freeze fraction and melt fraction, are the only experimental parameters that are currently not measured directly. Using icing growth rates from ice crystal icing experiments, a methodology that has been previously proposed is used to determine these unknown parameters. This work takes ice accretion data from tests conducted by the National Aeronautics and Space Administration (NASA) at the Glenn Research Center in 2018 that examined the fundamental physics of ice crystal icing. This paper continues evaluation of the thermodynamic model from a previous effort, with additions to the model that account for sub-freezing temperatures that have been observed at the leading edge of the airfoil during icing. The predicted temperatures were generally in good agreement with measured temperatures. Other key findings include the total wet-bulb temperature being a good first order indicator of whether icing is freeze-dominated (sub-freezing values) or melt-dominated (above freezing). Maximum sticking efficiency values, the fraction of impinging mass that adheres to a surface, was calculated to be about 0.2, and retained this maximum value for a range of melt ratios (0.3 to 0.65 and possibly higher), which is defined as the ratio of liquid water content to total water content. Higher air velocities reduced the maximum sticking efficiency and shifted the icing regime to higher melt ratio values. Finally, the leading edge ice accretion angle was found to be related to ice growth (lower growth rates for smaller angles) and melt ratio (smaller melt ratios resulted in smaller angles, likely due to erosion effects).

This paper describes an ice-crystal icing experiment conducted at the NASA Propulsion System Laboratory during June 2018. This test produced ice shape data on an airfoil for different test conditions similar to those inside the compressor region of a turbo-fan jet engine. Mixed-phase icing conditions were generated by partially freezing out a water spray using the relative humidity of flow as the primary parameter to control freeze-out. The paper presents the ice shape data and associated conditions which include pressure, velocity, temperature, humidity, total water content, melt ratio, and particle size distribution. The test featured a new instrument traversing system which allowed surveys of the flow and cloud. The purpose of this work was to provide experimental ice shape data and associated conditions to help develop and validate ice-crystal icing accretion models. The results support previous experimental observations of a minimum melt-ratio threshold for accretion to occur as well as the existence of a plateau region where the icing severity is high for a range of melt ratios. However, a maximum limit for melt ratio, which is suggested in the ice crystal icing literature, was not observed perhaps complicated by the potential for some supercooling of the water at these conditions.

This paper reports on temperature and humidity measurements from a series of ice-crystal icing tunnel experiments conducted in June 2018 at the Propulsion Systems Laboratory at the NASA Glenn Research Center. The tests were fundamental in nature and were aimed at investigating the icing processes on a two-dimensional NACA0012 airfoil subjected to artificially generated icing clouds. Prior to the tests on the airfoil, a suite of instruments, including total temperature and humidity probes, were used to characterize the thermodynamic flow and icing cloud conditions of the facility. Two different total temperature probes were used in these tests which included a custom designed rearward facing probe and a commercial self-heating total temperature probe. The rearward facing probe, the main total temperature probe, was designed to reduce and mitigate the contaminating effects of icing and ingestion of ice crystals and water droplets at the probe's inlet. The probe also serves as an air-sample inlet for a light absorption based humidity measurement. The paper includes a section which discusses total temperature and humidity measurement considerations, and another section which provides an analysis of the main probe's performance characteristics. A computational fluid dynamic model of the flow around the probe was also conducted to gain insight into the trajectory of the flow entering the probe inlet. The experiments included a series of tests in which the relative humidity of the facility flow was swept through with increasingly larger values. The data showed that the rearward facing probe can reasonably capture the flow's total temperature and humidity under mild to moderate icing conditions but produces anomalous results under more intense icing conditions. The experimental data was also compared to an in-house developed thermodynamic model which takes into account the interaction of the main flow with the icing cloud. Comparison to the thermodynamic model showed that the rearward facing probe measured the predicted trends.

A major challenge in automotive NVH engineering is to approach complex structure-borne sound and vibration problems with sufficient accuracy but reasonable experimental effort. Typical issues encountered are poor correlation between objective component performance criteria tested for during bench validation and corresponding subjective targets evaluated during system validation in the actual vehicle. Additional challenges arise from the need to impose assumptions on sophisticated physical vibration problems to reduce the complexity to a level feasible for conventional experimental test methods. This paper addresses all mentioned issues by elaborating on a system NVH engineering approach employing Virtual Acoustic Prototyping (VAP) (related to what is now often called component Transfer Path Analysis) to synthesize time domain sound and vibration responses of vibrating machinery operated in a virtual vehicle environment. One crucial step of VAP is to characterize the strength of vibrating machinery by independent quantities at the significant coupling degrees of freedom (DoF). This study puts special focus on the measurement of free velocity, suitable for machinery operated when resiliently mounted as per ISO 9611, and the in-situ measurement of blocked forces, applicable for sources connected to any type of receiving structure during operation, as per ISO/DIS 20270. In order to reduce complexity of the underlying measurements this paper investigates the possibility of using collocated sensor arrays and methods to validate assumptions imposed to abstract away from rotational coupling DoF. An electric power steering (EPS) system inducing vibrations into a sub-frame-type structure is considered as a representative automotive source-receiver installation to investigate the feasibility of free velocity and in-situ blocked force approach with respect to independent source characterization for component Transfer Path Analysis (TPA) and VAP. The obtained Virtual Acoustic Prototype is expanded using an algorithm to synthesize realistic time domain data, enabling NVH engineers to conduct reliable objective and subjective design evaluations.

This paper presents a methodology used to configure an electric drive system for a Formula Student car and the detailed design of a transmission for in-hub motor placement. Various options for the size, number and placement of electric motors were considered and a systematic process was undertaken to determine the optimum configuration and type of motor required. The final configuration selected had four 38 kW in-hub motors connected through a 14.8:1 reduction transmission to 10” wheels. Preliminary design of the transmission design indicated that the overall gear ratio would be best achieved with a two-stage reduction, and in this work an offset primary spur stage coupled to a planetary second stage was chosen. Detailed design and validation of the transmission was conducted in Ricardo SABR and GEAR, using a duty cycle derived from an existing internal combustion Formula Student car. The analysis was conducted in line with ISO 6336 and permitted the examination of the stresses in gear teeth and the prediction of gear and bearing life. A detailed design was proposed with due regard to ease of manufacture and assembly, and a full-scale prototype was manufactured to facilitate physical validation of the design. The design analysis showed all gears and bearings had a suitable predicted lifetime with a minimum factor of safety of 1.8 on gear wear.

Internal combustion (IC) engine exhaust system can influence the engine's performance in a significant way. This paper shows that a variable exhaust manifold runner length can improve the engine performance in terms of its output torque by over 10% especially at lower engine speed. Similarly, other exhaust systems such as valve timing and valve lift can improve the performance of the engine in different magnitudes. But when smaller improvements are clubbed together, a significant improvement can be achieved. This paper researches first the exhaust runner length on the engine's performance. Then, the exhaust valve timing is adjusted to further improve the engine torque produced for the exhaust runner lengths analyzed. Study of a combined effect showed that the runner length requirement shifts slightly as the valve timing is changed. Due to practical limitations foreseen in having longer runner lengths and limitations in the rate of runner length variation, certain areas have to undergo through a region where the torque values are as low as they can be. Though this happens in every single exhaust system out in the market today, valve lift is be used to compensate this loss. In this research the engine torque loss at these points can be regained by 50% by taking the benefit of a variable exhaust valve timing and valve lift system. The combined effect of changing runner length, valve timing and valve lift yields improvements in torques of 2-3% and 7-10% at higher and lower engine speeds, respectively Refereed/Peer-reviewed

© 2019 SAE International. All Rights Reserved. Electric vehicles are considered as one of the most popular way to decrease the consumption of petroleum resources and reduce environmental pollutions. Motor control system is one of the most important part of electric vehicles. It includes power supply module, IGBT driver, digital signal processing (DSP) controller, protection adjustment module, and resolver to digital convertor. To implement the control strategies on motor control system, a lot of practical aspects need to be taken into accounts. It includes setup of the initial excitation current, consistency of current between motor and program code, over-modulation, field weakening control, current protection, and so on. In this paper, an induction motor control system for electric vehicles is developed based on DSP. The control strategy is based on the field-oriented control (FOC) and space vector pulse width modulation (SVPWM). Speed calculation, over-modulation, field weakening control, PI controller, and fault diagnosis are also applied in this DSP algorithm. As an industry product running on a real electric bus with a 100kW induction motor, communication with vehicle control unit (VCU) by CAN bus, control system safety and PC software designed for lab experiments are also discussed. This paper focused on how to develop the advanced motor control system for electric vehicles for industrial application. The steady-state and transient performances of this motor control system are analyzed by both test-bench experiments and road experiments. Its performance is satisfactory when applied to the real electric vehicle.

This paper introduces a data driven model for predicting airport arrival capacity with a look-ahead time 2-8 hour forecast. The model is suitable for air traffic flow management by explicitly investigating the impact of convective weather on airport arrival meter fix throughput. Estimation of the arrival airport capacity under arrival meter fix flow constraints due to severe weather is an important part of Air Traffic Management (ATM). Airport arrival capacity can be reduced if one or more airport arrival meter fixes are partially or completely blocked by convective weather. When the predicted airport arrival demands exceed the predicted available airport's arrival capacity for a sustained period, Ground Delay Program (GDP) operations will be triggered by ATM system. Serious imbalances between demand and capacity occur most frequently when the airport capacity is severely degraded due to either bad airport terminal surface weather or inclement convective weather around airport arrival fixes. A model that predicts the weather-impacted airport arrival meter fix throughput may help ATM personnel to plan GDP operations more efficiently. This paper identifies the characteristics of air traffic flow across arrival meter fixes at Newark Liberty International Airport (EWR). The proposed approach, based on machine-learning methods, is developed to predict the weather impacted EWR arrival Meter Fix (MF) throughput. Sector forecast coverage is used to envision the weather impact on airport arrival MF flow, and the validation is accomplished by using Convective Weather Avoidance Model (CWAM) 0.5 to 2-hour and Collaborative Convective Forecast Product (CCFP) 4 to 8-hour look-ahead forecast data for the period of April-September in 2014. Furthermore, the regression tree ensemble learning of random forests approach for translating a sector forecast coverage model to an EWR arrival meter fix throughput model is examined. The results suggest that ATM decision makers in charge of MF flow control and GDP planning may benefit from adopting the airport arrival meter capacity prediction models to estimate the inclement weather impacts.

© 2019 SAE International. All Rights Reserved. Evolvable Assembly Systems is a five year UK research council funded project into flexible and reconfigurable manufacturing systems. The principal goal of the research programme has been to define and validate the vision and support architecture, theoretical models, methods and algorithms for Evolvable Assembly Systems as a new platform for open, adaptable, context-aware and cost effective production. The project is now coming to a close; the concepts developed during the project have been implemented on a variety of demonstrators across a number of manufacturing domains including automotive and aerospace assembly. This paper will show the progression of demonstrators and applications as they increase in complexity, specifically focussing on the Future Automated Aerospace Assembly Phase 1 technology demonstrator (FA3D). The FA3D Phase 1 demonstrated automated assembly of aerospace products using precision robotic processes in conjunction with low-cost reconfigurable fixturing supported by large volume metrology. This was underpinned by novel agent-based control for transformable batch-size-of-one production. The paper will conclude by introducing Phase 2 of the Future Automated Aerospace Assembly Demonstrator - currently in development - that will translate the Evolvable Assembly Systems research to a higher technology readiness level and address the challenges of scalable and transformable manufacturing systems.

In recent years, the More-Electric Aircraft (MEA) concept has undergone significant development and refinement, striving towards the attainment of reductions in noise and CO2 emissions, increased power transmission efficiency and improved reliability under a range of flight scenarios. The More-Electric Engine (MEE) is increasingly being seen as a key complementary system to the MEA. With this concept, conventional engine auxiliary systems (i.e. fuel pumps, oil pumps, actuators) will be replaced by electrically-driven equivalents, providing even greater scope for the combined aircraft and engine electrical power system optimisation and management. This concept, coupled with extraction of electrical power from multiple engine spools also has the potential to deliver significant fuel burn savings. To date, single or dual channel electrical power generation and distribution systems have been used in engines and aircrafts. However, with the increasing electrification of flight-critical engine auxiliaries along with the requirement for greater load transfer flexibility, a three-channel architecture should be considered. This paper investigates potential concepts for a three-channel power system architecture in an MEE system. The paper considers issues such as architecture layout and key technologies that may be considered for MEE architecture. Using an extensive database of public domain MEA/MEE power system component failure rates, a detailed fault tree analysis is then presented. This provides a quantitative comparison of dual channel and three-channel architecture candidates under the pertinent failure modes as well as showing the impact of common architecture features on system reliability and robustness. Finally, the paper concludes with a discussion of the ring busbar topology operation and power electronics technology requirements that could successfully implement a flexible and robust three-channel architecture for MEE systems.

A detailed understanding of Gasoline Direct Injection (GDI) techniques applied to spark-ignition (SI) engines is necessary as they allow for many technical advantages such as increased power output, higher fuel efficiency and better cold start performances. Within this context, the extensive validation of multi-dimensional models against experimental data is a fundamental task in order to achieve an accurate reproduction of the physical phenomena characterizing the injected fuel spray. In this work, simulations of different Engine Combustion Network (ECN) Spray G conditions were performed with the Lib-ICE code, which is based on the open source OpenFOAMtechnology, by using a RANS Eulerian-Lagrangian approach to model the ambient gas-fuel spray interaction. Foremost, the main scope of the activity was to identify the most accurate numerical set-up in terms of atomization ad secondary break-up models, thanks to a validation of the computed results against experimental data available for the ECN Spray G baseline condition. Specifically, attention was focused on spray penetration along with an analysis of spray morphology and effects of plume-to-plume interaction. Afterwards, the reference set-up was tested and validated under different operating conditions, characterized by detailed experimental measurements specifically provided for this work. In particular, Mie scattering and Schlieren techniques allowed the quasi-simultaneous acquisition of both vapor and liquid penetrations, while a customized image-processing procedure, developed in Matlab environment, was used for the outline of the spray contours of both fuel phases to measure the parameters characterizing the jet development. A robust reference numerical set-up was identified, capable to reproduce with good accuracy the injection process of a multi-hole GDI spray under the wide range of tested operating conditions

[EN] To face the current challenges of the automotive industry, there is a need for computational models capable to simulate the engine behavior under low-temperature and low-pressure conditions. Internal combustion engines are complex and have interconnected systems where many processes take place and influence each other. Thus, a global approach to engine simulation is suitable to study the entire engine performance. The circuits that distribute the hydraulic fluids -liquid fuels, coolants and lubricants- are critical subsystems of the engine. This work presents a 0D model which was developed and set up to make possible the simulation of hydraulic circuits in a global engine model. The model is capable of simulating flow and pressure distributions as well as heat transfer processes in a circuit. After its development, the thermo-hydraulic model was implemented in a physical based engine model called Virtual Engine Model (VEMOD), which takes into account all the relevant relations among subsystems. In the present paper, the thermo-hydraulic model is described and then it is used to simulate oil and coolant circuits of a diesel engine. The objective of the work is to validate the model under steady-state and transient operation, with focus on the thermal evolution of oil and coolant. For validation under steady-state conditions, 22 operating points were measured and simulated, some of them in cold environment. In general, good agreement was obtained between simulation and experiments. Next, the WLTP driving cycle was simulated starting from warmed-up conditions and from ambient temperature. Results were compared with the experiment, showing that modeled trends were close to those experimentally measured. Thermal evolutions of oil and coolant were predicted with mean errors between 0.7 °C and 2.1 °C. In particular, the warm-up phase was satisfactorily modeled., This research has been partially funded by the European Union’s Horizon 2020 Framework Programme for research, technological development and demonstration under grant agreement 723976 (“DiePeR”) and by the Spanish government under the grant agreement TRA2017-89894-R. Josep SalvadorIborra was supported by Universitat Politècnica de València through the contract FPI-S2-2016-1357 of the program PAID01-16. The authors wish to thank Renault SAS, especially P. Mallet and E. Gaïffas, for supporting this research. Jaime Monfort San Segundo is acknowledged for his helpful collaboration in the code implementation

A path tracking control system is chosen as the proof-of-concept demonstration application in this paper. A disturbance observer (DOB) is embedded within the steering to path error automated driving loop to handle uncertain parameters such as vehicle mass, vehicle velocities and road friction coefficient and to reject yaw moment disturbances. The compensation of vehicle model with the embedded disturbance observer forces it to behave like its nominal model within the bandwidth of the disturbance observer. A parameter space approach based steering controller is then used to optimize performance. The proposed method demonstrates good disturbance rejection and achieves stability robustness. The variable time delay from the steer-by-wire system in an actual vehicle can also lead to stability issues since it adds large negative phase angle to the plant frequency response and tends to destabilize it. A communication disturbance observer (CDOB) based time delay compensation approach that does not require exact knowledge of this time delay is embedded into the steering actuation loop to handle this problem. Stability analysis of both DOB and CDOB compensation system are presented in this paper. Extensive model-in-the-loop simulations were performed to test the designed disturbance observer and CDOB systems and show reduced path following errors in the presence of uncertainty, disturbances and time delay. A validated model of our 2017 Ford Fusion Hybrid research autonomous vehicle is used in the simulation analyses. Simulation results verify the performance enhancement of the vehicle path following control with proposed DOB and CDOB structure. A HiL simulator that uses a validated CarSim model with sensors and traffic will be used later to verify the real time capability of our approach., arXiv admin note: text overlap with arXiv:2306.01899

The data set contains the simulation files related to the research paper “Numerical Study of the Impinging Jets Formed by an Injector with Different Nozzle Diameters”, https://doi.org/10.4271/2022-01-1080.

Small diesel engines are a common primer for micro and mini-grid systems, which can supply affordable electricity to rural and remote areas, especially in developing countries. These diesel generators have no exhaust after-treatment system thus exhaust emissions are high. This paper investigates the potential of introducing simulated synthetic gas (syngas) to diesel in a small diesel engine to explore the opportunities of widening fuel choices and reducing emissions using a 5.7kW single cylinder direct injection diesel generator engine. Three different simulated syngas blends (with varying hydrogen content) were prepared to represent the typical syngas compositions produced from downdraft gasification and were injected into the air inlet. In-cylinder pressure, ignition delay, premixed combustion, combustion stability, specific energy consumption (SEC), and gaseous and particle emissions were measured at various power settings and mixing ratios. Particle size distributions (PSD) were measured by DMS500, and gaseous emissions were measured by the HORIBA MEXA7100 series. The correlations between combustion and emission performance and mixing ratios and substitution ratios were investigated. Dual fuel operation led to a decrease in diesel consumption, thermal efficiency, NOx, and NO emissions and an increase in THC and CO emissions. For all dual fuel tests, a reduction in the total particle number concentration (TPNC) was noted while the particle size distribution curves remained unchanged relative to diesel baseline data at all engine loads except for 30%. At 30% engine load, the change in the particle size distribution curves was dependent on the syngas blend used. The syngas with the highest hydrogen content showed superior combustion performance relative to the other syngas blends evaluated due to shorter ignition delay times and higher maximum in-cylinder pressure values, thus producing lower THC and CO emissions, but higher NOx emissions.

ispartof: SAE Technical Papers status: Published online

International audience; Recent work in the area of safety analysis has shown that system Fault Trees and Failure Modes and Effects Analyses (FMEAs) can be automatically derived from a topological model of the system that has been annotated with local, component-level, specifications of failure. In this paper, the concept of a component failure specification is extended to enable description and reuse of generalized patterns of failure behaviour that are commonly exhibited by components. A language for the description of such patterns is specified, useful patterns are presented and the use of such patterns is demonstrated on an example of a Time-Triggered system. The paper tentatively concludes that careful reuse of failure patterns in conjunction with automated fault tree and FMEA synthesis algorithms can help to rationalize, and simplify, complex safety assessments.

Safety assurance is a central concern for the development and societal acceptance of automated driving (AD) systems. Perception is a key aspect of AD that relies heavily on Machine Learning (ML). Despite the known challenges with the safety assurance of ML-based components, proposals have recently emerged for unit-level safety cases addressing these components. Unfortunately, AD safety cases express safety requirements at the system level and these efforts are missing the critical linking argument needed to integrate safety requirements at the system level with component performance requirements at the unit level. In this paper, we propose the Integration Safety Case for Perception (ISCaP), a generic template for such a linking safety argument specifically tailored for perception components. The template takes a deductive and formal approach to define strong traceability between levels. We demonstrate the applicability of ISCaP with a detailed case study and discuss its use as a tool to support incremental development of perception components.

Large-eddy simulation (LES) is an important tool to understand and analyze sprays, such as those found in engines. Subfilter models are crucial for the accuracy of spray-LES, thereby signifying the importance of their development for predictive spray-LES. Recently, new subfilter models based on physics-informed generative adversarial networks (GANs) were developed, known as physics-informed enhanced super-resolution GANs (PIESRGANs). These models were successfully applied to the Spray A case defined by the Engine Combustion Network (ECN). This work presents technical details of this novel method, which are relevant for the modeling of spray combustion, and applies PIESRGANs to the ECN Spray C case. The results are validated against experimental data, and computational challenges and advantages are particularly emphasized compared to classical simulation approaches.

The major contribution of this paper is to propose a low-cost accurate distance estimation approach. It can potentially be used in driver modelling, accident avoidance and autonomous driving. Based on MATLAB and Python, sensory data from a Continental radar and a monocular dashcam were fused using a Kalman filter. Both sensors were mounted on a Volkswagen Sharan, performing repeated driving on a same route. The established system consists of three components, radar data processing, camera data processing and data fusion using Kalman filter. For radar data processing, raw radar measurements were directly collected from a data logger and analyzed using a Python program. Valid data were extracted and time stamped for further use. Meanwhile, a Nextbase monocular dashcam was used to record corresponding traffic scenarios. In order to measure headway distance from these videos, object depicting the leading vehicle was first located in each frame. Afterwards, the corresponding vanishing point was also detected and used to automatically compute the camera posture, which is to minimize the interference caused by camera vibration. The headway distance can hence be obtained by assuming the leading and host vehicles were in the same ground plane. After both sensory data were obtained, they were synthesized and fused using Kalman filter, to generate a better estimation of headway distance. The performances of both sensors were assessed individually and the correlation between their measurements was evaluated by replotting radar measurements on the video stream. The results of individual sensors and Kalman filter were compared to investigate the optimization performance of the data fusion approach.This is a general guidance of headway distance estimation with a low cost radar and a monocular camera. With described general procedures, this paper can allow researchers to easily fuse radar and camera measurements to obtain optimized headway distance estimation. This paper can facilitate the development of a more realistic robotic driver that can mimic human driver behaviors.

This paper is a preliminary step in the direction of the definition of a radically new wing concept that has been conceived to maximize the lift even at low speeds. It is expected to equip new aerial vehicle concepts that aim to compete against helicopters and tilt rotors. They aim achieving very good performance at very low speed (5 to 30 m/s) by mean of an innovative concept of morphing ducted-fan propelled wing that has been designed to maximize the lift force. This paper presents an effective bibliographic analysis of the problem that is a preliminary necessary step in the direction of the preliminary design of the wing. A preliminary CFD evaluation allows demonstrating that the claimed results are in line with the initial expectations. According to\ud the CFD, results it has been produced a preliminary energetic evaluation of the vehicle in a flying car configuration by EMIPS method. Even if the results are still preliminary, they allow evidencing a good energy efficiency of the vehicle against helicopters.

© 2017 SAE International. The goal of grid friendly charging is to avoid putting additional load on the electricity grid when it is heavily loaded already, and to reduce the cost of charging to the consumer. In a smart metering system, Day Ahead tariff (DA) prices are announced in advance for the next day. This information can be used for a simple optimization control, to select to charge at cheapest times. However, the balance of supply and demand is not fully known in advance and the Real-Time Prices (RTP) are therefore likely to be different at times. There is always a risk of a sudden price change, hence adding a stochastic element to the optimization in turn requiring dynamic control to achieve optimal time selection. A stochastic dynamic program (SDP) controller which takes this problem into account has been made and proven by simulation in a previous paper. Since there are differences between the DA and the RTP tariff, this paper proposes a (1) predictor to create an unbiased estimate of the RTP tariff based on available data. It uses a regression on historical data to find the best prediction of the expected price. Finally, a (2) case study based on data from the Illinois Electricity Grid prices is presented to validate the SDP controller over several years of data. The stochastic optimization uses the RTP prices effectively, getting very close to the globally optimal charging price. However, the predictor achieves only a slight reduction in prediction uncertainty with this data sate, and it has a negligible effect on cost. This means that DA prices can be used as a fair prediction of RTP charging cost here. The SDPM successfully reacts in the case study and leads to savings on charging costs over the years presented.