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The hydrogen internal combustion engine is a promising alternative to fossil fuel-based engines, which, in a short time, can reduce the carbon footprint of the ground transport sector. However, the high heat release rates associated with hydrogen combustion results in higher NOx emissions. The NOx production can be mitigated by diluting the in-cylinder mixture with air, Exhaust Gas Recirculation (EGR) or water injected in the intake manifold. This study aims at assessing these dilution options on the emissions, efficiency, combustion performance and boosting effort. These dilution modes are, at first, compared on a single cylinder engine (SCE) with direct injection of hydrogen in steady state conditions. Air and EGR dilutions are then evaluated on a corresponding 4-cylinder engine by 0D simulation on a complete map under NOx emission constraint.

With the increase of heavy-duty transportation, more fuel efficient technologies and services have become of great importance due to their environmental and economical impacts for the fleet managers. In this paper, we first develop a new analytical model of the heavy-truck for its dynamics and its fuel consumption, and valid the model with experimental measurements. Then, we propose a bi-level optimization approach to reduce the fuel consumption, thus the CO2 emissions, while ensuring several safety constraints in real-time. Numerical results show that important reduction of the fuel consumption can be achieved, while satisfying imposed safety constraints.

The role of numerical simulations in the development of innovative and sustainable powertrains is constantly growing thanks to their capabilities to significantly reduce the calibration efforts and to point out potential synergies among different technologies. In such a framework, this paper describes the development of a fully physical 1D-CFD engine model to support the calibration of the highly efficient spark ignition engine of the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) EU H2020 project. The availability of a reliable simulation platform is essential to effectively exploit the combination of the several features introduced to achieve the project target of 47% peak gross indicated efficiency, such as SwumbleTM in-cylinder charge motion, Miller cycle combined with high Compression Ratio (CR), lean mixture exploiting cooled low pressure Exhaust Gas Recirculation (EGR) and electrified turbocharging.

The recent particle number limits for a spark ignition engine combined with the real driving emissions (RDE) compliance have motivated the need for a better understanding of the effect of the gasoline fuel composition on the particle emissions. More particularly, the fundamental role of high boiling point components and heavy aromatics on particle emissions was highlighted in several literature works. In addition, works driven by the European Renewable Energy Directive are underway in order to explore the feasibility of an increased amount of sustainable Biofuels in Gasoline. Already widely distributed, ethanol is a clear candidate to such an increase. In this context, the present work aims to understand the effect of ethanol addition and aromatics composition on particulate emissions. Vehicle tests were performed over the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) using a Euro 6c model without a Gasoline Particulate Filter (GPF) and a Euro 6d-Temp one equipped with a GPF.

A practical Gasoline Compression Ignition (GCI) concept is presented that works on standard European 95 RON E10 gasoline over the whole speed/load range. A spark is employed to assist the gasoline autoignition at low loads; this avoids the requirement of a complex cam profile to control the local mixture temperature for reliable autoignition. The combustion phasing is controlled by the injection pattern and timing, and a sufficient degree of stratification is needed to control the maximum rate of pressure rise and prevent knock. With active control of the swirl level, the combustion system is found to be relatively robust against variability in charge motion, and subtle differences in fuel reactivity. Results show that the new concept can achieve very low fuel consumption over a significant portion of the speed/load map, equivalent to diesel efficiency. The efficiency is worse than an equivalent diesel engine only at low load where the combustion assistance operates.

The reduction of particulate emissions is one of the most important challenges facing the development of future gasoline engines. Several studies have demonstrated the impact of fuel chemical composition on the emissions of particulate matter, more particularly, the detrimental effect of high boiling point components such as heavy aromatics. Fuel contamination is likely to become a critical issue as new regulations such as Real Driving Emissions RDE involves the use of market fuel. The objective of this study is to investigate several experimental approaches to detect the presence of Diesel contamination in Gasoline which is likely to alter pollutant emissions. To achieve this, a fuel matrix composed of 12 fuels was built presenting diesel fuel in varying concentrations from 0.1 to 2% v/v. The fuel matrix was characterized using several original techniques developed in this study.

Oxygenated fuels are studied in spark combustion engines because of their potentially positive impact on greenhouse emissions, and as part of alternative renewable fuels. Furthermore, engine test results position them as a promising lever to reduce engine-out emissions, and most notably, particles. This study focuses on oxygenated fuel Butanol, which is a potential output of recent developments on Algae and Cyanobacteria harvest process. Its blending into gasoline and application into spark ignition engines is investigated. Blending levels of n-Butanol and iso-Butanol have been proposed based on standard gasoline’s octane number, RON, at two ethanol concentration levels, 10 and 25%. Fuel blend impact on combustion, and on regulated and non-regulated emissions is analysed. Fuel knock resistance properties, RON and MON, determine the knocking tendencies for ethanol and butanol at 2000 rpm. However, test results highlight different knocking sensibility behaviour at higher engine speed.

In order to assist in fast design cycle of Diesel engines selective catalytic reduction (SCR) exhaust systems, significant endeavor is currently being made to improve numerical simulation accuracy of urea thermo-hydrolysis. In this article, the achievements of a recently developed urea semi-detailed decomposition chemical scheme are assessed using three available databases from the literature. First, evaporation and thermo-hydrolysis of urea-water solution (UWS) single-droplets hanged on a thin thermocouple ring (127 μm) as well as on a thick quartz (275 μm), have been simulated at ambient temperature conditions ranging from 473K to 773K. It has been shown that the numerical results, in terms of evaporation rate and urea gasification, as well as droplet temperature history are very close to the experiments if the heat flux coming from the droplet support is properly accounted for.

The increasing use of downsized turbocharged gasoline engines for passengers cars and the new European homologation cycles (WLTC and RDE) both impose an optimization of the whole engine map. More weight is given to mid and high loads, thus enhancing knock and overfueling limitations. At low and moderate engine speeds, knock mitigation is one of the main issues, generally addressed by retarding spark advance thereby penalizing the combustion efficiency. At high engine speeds, knock still occurs but is less problematic. However, in order to comply with thermo-mechanical properties of the turbine, excess fuel is injected to limit the exhaust gas temperature while maximizing engine power, even with cooled exhaust manifolds. This also implies a decrease of the combustion efficiency and an increase in pollutant emissions. Water injection is one way to overcome both limitations.

The performance of environment perceiving sensors such as e.g. lidar, radar, camera and ultrasonic sensors is safety critical for automated driving vehicles. Therefore, one has to assess the sensors’ performance to assure the automated driving system’s safety. The performance of these sensors is however to some degree sensitive towards adverse weather conditions. A challenge is to quantify the effect of adverse weather conditions on the sensor’s performance early in the development of an automated driving system. This challenge is addressed in this work for lidar sensors. The lidar equation was previously employed in this context to derive estimates of a lidar’s maximum range in different weather conditions. In this work, we present a stochastic simulation framework based on a probabilistic extension of the lidar equation, to quantify the effect of adverse rainfall conditions on a lidar’s raw detection performance.

Minimizing the lap time for a given race track is the main target in racecar development. In order to achieve the highest possible performance of the vehicle configuration the mutual interaction at the level of assemblies and components requires a balance between the advantages and disadvantages for each design decision. Especially the major shift in the focus of racecar powerunit development to high efficiency powertrains is driving a development of lean boosted and rightsized engines. In terms of dynamic engine behavior the time delay from requested to provided torque could influence the lap time performance. Therefore, solely maximizing the full load behavior objective is insufficient to achieve minimal lap time. By means of continuous predictive virtual methods throughout the whole development process, the influence on lap time by dynamic power lags, e.g. caused by the boost system, can be recognized efficiently even in the early concept phase.

Meeting Euro 6d NOx emission regulations lower than 80 mg/km for light duty diesel (60 mg/km gasoline) vehicles remains a challenge, especially during cold-start tests at which the selective catalyst reduction (SCR) system does not work because of low exhaust gas temperatures (light-off temperature around 200 °C). While several exhaust aftertreatment system (EATS) designs are suggested in literature, solutions with gaseous ammonia injections seem to be an efficient and cost-effective way to enhance the NOx abatement at low temperature. Compared to standard SCR systems using urea water solution (UWS) injection, gaseous NH3 systems allow an earlier injection, prevent deposit formation and increase the NH3 content density. However non-uniform ammonia mixture distribution upstream of the SCR catalyst remains an issue. These exhaust gas/ NH3 inhomogeneities lead to a non-optimal NOx reduction performance, resulting in higher than expected NOx emissions and/or ammonia slip.

The main purpose of this paper will be to investigate if a small snowmobile gasoline Direct Injected (DI) two-stroke engine has the potential to be adapted for two other types of applications: as a range extender (REX) for electric vehicles and for a motorcycle application. For the REX application, the main requested specifications (NVH, lightweight, compactness, minimum production cost and easy maintenance), correspond well to the main features of DI 2-stroke engines. The potential of a modified production engine operating in part load ultra-low NOx Controlled Auto Ignition (CAI) to meet the Euro 6 emissions standards on the NEDC cycle has already been demonstrated in a previous paper. In the first part of this new paper, we will investigate which solutions can be used to maintain this potential with even stricter legislations based on Euro 6d, WLTP cycle and Real Driving Emissions (RDE).

Recent work has demonstrated the potential of gasoline-like fuels to reduce NOx and particulate emissions when used in compression ignition engines. In this context, low research octane number (RON) gasoline, a refinery stream derived from the atmospheric crude oil distillation process, has been identified as a highly valuable fuel. In addition, thanks to its higher H/C ratio and energy content compared to diesel, CO2 benefits are also expected when used in such engines. In previous studies, different cetane number (CN) fuels have been evaluated and a CN 35 fuel has been selected. The assessment and the choice of the required engine hardware adapted to this fuel, such as the compression ratio, bowl pattern and nozzle design have been performed on a single cylinder compression-ignition engine.

Driven by the growing internet and remote connectivity of automobiles, combined with the emerging trend to automated driving, the importance of security for automotive systems is massively increasing. Although cyber security is a common part of daily routines in the traditional IT domain, necessary security mechanisms are not yet widely applied in the vehicles. At first glance, this may not appear to be a problem as there are lots of solutions from other domains, which potentially could be re-used. But substantial differences compared to an automotive environment have to be taken into account, drastically reducing the possibilities for simple reuse. Our contribution is to address automotive electronics engineers who are confronted with security requirements. Therefore, it will firstly provide some basic knowledge about IT security and subsequently present a selection of automotive specific security use cases.

Reduction of CO2 emissions is becoming one of the great challenges for future gasoline engines. Downsizing is one of the most promising strategies to achieve this reduction, though it facilitates occurrence of knocking. Therefore, downsizing has to be associated with knock limiting technologies. The aim of the current research program is to adapt the fuel Research-Octane-Number (RON) injected in the combustion chamber to prevent knock occurrence and keep combustion phasing at optimum. This is achieved by a dual fuel injection strategy, involving a low-RON naphtha-based fuel (Naphtha, RON 71) and a high-RON octane booster (Ethanol, RON107). The ratio of fuel quantity on each injector is adapted to fit the RON requirement as a function of engine operating conditions. Hence, it becomes crucial to understand and predict the mixture preparation, to quantify its spatial and cycle-to-cycle variations and to apprehend the consequences on combustion behavior - knock especially.

Longitudinal models are used to evaluate different vehicle-engine concepts with respect to driving behavior and emissions. The engine is generally map-based. An explicit calculation of both fluid dynamics inside the engine air path and cylinder combustion is not considered due to long computing times. Particularly for dynamic certification cycles (WLTC, US06 etc.), dynamic engine effects severely influence the quality of results. Hence, an evaluation of transient engine behavior with map-based engine models is restricted to a certain extent. The coupling of detailed 1D-engine models is an alternative, which rapidly increases the model computation time to approximately 300 times higher than that of real time. In many technical areas, the Fourier transformation (FT) method is applied, which makes it possible to represent superimposed oscillations by their sinusoidal harmonic oscillations of different orders.

The Engine Combustion Network (ECN) has become a leading group concerning the experimental and computational analysis of engine combustion phenomena. In order to establish a coherent database for model validation, all the institutions participating in the experimental effort carry out tests at well-defined boundary conditions and using wellcharacterized hardware. In this framework, the reference Spray A injectors have produced different results even when tested in the same facility, highlighting that the nozzle employed and its fouling are important parameters to be accounted for. On the other hand, the number of the available Spray A injectors became an issue, due to the increasing number of research centers and simultaneous experiments taking place in the ECN community. The present work has a double aim: on the one hand, to seek for an appropriate methodology to “validate” new injectors for ECN experiments and to provide new hardware for the ECN community.

The 3-Zones Extended Coherent Flame Model (ECFM3Z) and the Tabulated Kinetics for Ignition (TKI) auto-ignition model are widely used for RANS simulations of reactive flows in Diesel engines. ECFM3Z accounts for the turbulent mixing between one zone that contains compressed air and EGR and another zone that contains evaporated fuel. These zones mix to form a reactive zone where combustion occurs. In this mixing zone TKI is applied to predict the auto-ignition event, including the ignition delay time and the heat release rate. Because it is tabulated, TKI can model complex fuels over a wide range of engine thermodynamic conditions. However, the ECFM3Z/TKI combustion modeling approach requires an efficient predictive spray injection calculation. In a Diesel direct injection engine, the turbulent mixing and spray atomization are mainly driven by the liquid/gas coupling phenomenon that occurs at moving liquid/gas interfaces.

Recent work has demonstrated the potential of gasoline-like fuels to reduce NOx and particulate emissions when used in Diesel engines. In this context, straight-run naphtha, a refinery stream directly derived from the atmospheric crude oil distillation process, has been identified as a highly valuable fuel. The current study is one step further toward naphtha-based fuel to power compression ignition engines. The potential of a cetane number 25 fuel (CN25), resulting from a blend of hydro-treated straight-run naphtha CN35 with unleaded non-oxygenated gasoline RON91 was assessed. For this purpose, investigations were conducted on multiple fronts, including experimental activities on an injection test bed, in an optically accessible vessel and in a single cylinder engine. CFD simulations were also developed to provide relevant explanations.