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Authors : Thomas ANTOINE, Christophe THEVENARD, Pierrick BOTTA, Jerome DESTREE, Alain Le Quenven Future noise emission limits for passenger car are going to lower levels by 2024 (Third phase of R51-03, with a limit of 68dBA for the pass by noise) –Social cost of noise for France in 2021, shows clearly that the dominant source of noise pollution is indeed road traffic (81 Bn€ for a total of 146 Bn€) This R51 regulation is meant to lower the noise pollution from road traffic, however when looking closer to the sound source and their contributions, in particular the tire/road noise interaction, the environmental efficiency of this regulation is questionable. Indeed: Tire/Road interaction involves tires characteristics, that are constrained by an array of specification for energy efficiency, safety (wet grip, braking, etc…) and it has been proven that there is a physical limit to what could be expected from the tire as far as tire/road interaction noise is concerned.

Worldwide, there is the demand to reduce harmful emissions from non-road vehicles to fulfill European Stage V+ and VI (2022, 2024) emission legislation. The rules require significant reductions in nitrogen oxides (NOx), methane (CH4) and formaldehyde (CH2O) emissions from non-road vehicles. Compressed natural gas (CNG) engines with appropriate exhaust aftertreatment systems such as three-way catalytic converter (TWC) can meet these regulations. An issue remains for reducing emissions during the engine cold start where the CNG engine and TWC yet do not reach their optimum operating conditions. The resulting complexity of engine and catalyst calibration can be efficiently supported by numerical models. Hence, it is required to develop accurate simulation models which can predict cold start emissions. This work presents a real-time engine model for transient engine-out emission prediction using tabulated chemistry for CNG.

Spray modeling is among the main aspects of mixture formation and combustion in internal combustion engines. It plays a major role in pollutant formation and energy efficiency although adequate modeling is still under development. Strong grid dependence is observed in the droplet-based stochastic spray model commonly used. As an alternative, an interactive model called 'SprayLet' is being developed for spray simulations based on one-dimensional integrated equations for the gas and liquid phases, resulting from cross-sectionally averaging of multi-dimensional transport equations to improve statistical convergence. The formulated one-dimensional cross-section averaged system is solved independently of the CFD program to provide source terms for mass, momentum and heat transfer between the gas and liquid phases. The transport processes take place in a given spray cone where the nozzle exit is automatically resolved.

The world of shipping is at a turning point. Alongside methanol, ammonia and other PtL (Power to Liquid) fuels, liquefied natural gas (LNG) offers one way of achieving climate-friendly ship operation. Although currently still derived from fossil sources, LNG combines the properties of already having a well-established land-based infrastructure, of enabling a 100 % climate-neutral supply via electrolysis and methanization, and of its ability for any high proportion of climate-neutral LNG to be used as a drop-in fuel during the transformation process in the next decades; proven by the first bunkering of the container vessel “ElbBlue” with 20 tons of SNG (Synthetic Natural Gas) in 2021 [1]. Up to now, LNG fueled marine engines have predominantly been operated in fixed operation areas. Therefore, they can bunker stable gas qualities at specific ports and can be optimized for a specific gas quality.

The introduction of a physics-based zero-dimensional stochastic reactor model combined with tabulated chemistry enables the simulation-supported development of future compression-ignited engines. The stochastic reactor model mimics mixture and temperature inhomogeneities induced by turbulence, direct injection and heat transfer. Thus, it is possible to improve the prediction of NOx emissions compared to common mean-value models. To reduce the number of designs to be evaluated during the simulation-based multi-objective optimization, genetic algorithms are proven to be an effective tool. Based on an initial set of designs, the algorithm aims to evolve the designs to find the best parameters for the given constraints and objectives. The extension by response surface models improves the prediction of the best possible Pareto Front, while the time of optimization is kept low.

Bio-alcohol fuel blends will gain in importance for future mobility. The driving force is the necessary reduction of greenhouse gases and harmful exhaust gas components. The new fuels offer advantages in engine combustion and resulting exhaust emissions because of the short-chained molecules and resulting low C/H ratio as well as the higher oxygen content. The aim of the project is a systematic analysis and evaluation of the effects of two bio-alcohol blends on the lubrication oil ageing of a gasoline-driven Euro 6 passenger car engine. For this reason a test engine was operated with three different fuels: a fossil gasoline (E0) without bio-alcohol components, a blend containing 30% vol ethanol (E30) and a blend containing 15% vol methanol (M15). During the engine test, gas of the cylinder charge and blow-by has been sampled and analyzed by ion chromatography regarding short-chained organic and inorganic acids.

Water injection is a promising technology to improve the fuel efficiency of turbocharged gasoline engines due to the possibility to suppress engine knock. Additionally, this technology is believed to enable the efficient operation of the three-way catalyst also at high-load conditions, through limiting the exhaust temperature. In this numerical study, we investigate the effect of water on the chemical and thermodynamic processes using 3D computational fluid dynamics (CFD) Reynolds-averaged Navier–Stokes (RANS) with detailed chemistry. In the first step, the influence of different amounts of water vapor on ignition delay time, laminar flame speed, and heat capacity is investigated. In the second step, the impact of water vaporization is analyzed for port and direct injection. For this purpose, the water mass flow and the injection pressure are varied.

The present paper is concerned with part of the work performed by Renault, IFPEN and Politecnico di Torino within a research project founded by the European Commission. The project has been focused on the development of a dedicated CNG engine featuring a 25% decrease in fuel consumption with respect to an equivalent Diesel engine with the same performance targets. To that end, different technologies were implemented and optimized in the engine, namely, direct injection, variable valve timing, LP EGR with advanced turbocharging, and diluted combustion. With specific reference to diluted combustion, it is rather well established for gasoline engines whereas it still poses several critical issues for CNG ones, mainly due to the lower exhaust temperatures. Moreover, dilution is accompanied by a decrease in the laminar burning speed of the unburned mixture and this generally leads to a detriment in combustion efficiency and stability.

Engine knock is an important phenomenon that needs consideration in the development of gasoline fueled engines. In our days, this development is supported by the use of numerical simulation tools to further understand and subsequently predict in-cylinder processes. In this work, a model tool chain based on detailed chemical and physical models is proposed to predict the auto-ignition behavior of fuels with different octane ratings and to evaluate the transition from harmless auto-ignitive deflagration to knocking combustion. In our method, the auto-ignition and emissions are calculated based on a new reaction scheme for mixtures of iso-octane, n-heptane, toluene and ethanol (Ethanol consisting Toluene Reference Fuel, ETRF). The reaction scheme is validated for a wide range of mixtures and every desired mixture of the four fuel components can be applied in the engine simulation.

The current trend of downsizing used in gasoline engines, while reducing fuel consumption and CO2 emissions, imposes severe thermal loads inside the combustion chamber. These critical thermodynamic conditions lead to the possible auto-ignition (AI) of fresh gases hot-spots around Top-Dead-Center (TDC). At this very moment where the surface to volume ratio is high, wall heat transfer influences the temperature field inside the combustion chamber. The use of a realistic wall temperature distribution becomes important in the case of a downsized engine where fresh gases hot spots found near high temperature walls can initiate auto-ignition. This paper presents a comprehensive numerical methodology for an accurately prediction of thermodynamic conditions inside the combustion chamber based on Conjugate Heat Transfer (CHT).

Engine downsizing is potentially one of the most effective strategies being explored to improve fuel economy. A main problem of downsizing using a turbocharger is the small range of stable functioning of the turbocharger centrifugal compressor at high boost pressures, and hence the measurement of the performance maps of both compressor and turbine. Automotive manufacturers use mainly numerical simulations for internal combustion engines simulations, hence the need of an accurate extrapolation model to get a complete turbine performance map. These complete maps are then used for internal combustion engines calibration. Automotive manufacturers use commercial softwares to extrapolate the turbine narrow performance maps, both mass flow characteristics and the efficiency curve.

Methanol is today considered a viable green fuel for combustion engines because of its low soot emissions and the possibility of it being produced in a CO2-neutral manner. Methanol as a fuel for combustion engines have attracted interest throughout history and much research was conducted during the oil crisis in the seventies. In the beginning of the eighties the oil prices began to decrease and interest in methanol declined. This paper presents the emission potential of methanol. T-Φ maps were constructed using a 0-D reactor with constant pressure, temperature and equivalence ratio to show the emission characteristics of methanol. These maps were compared with equivalent maps for diesel fuel. The maps were then complemented with engine simulations using a stochastic reactor model (SRM), which predicts end-gas emissions. The SRM was validated using experimental results from a truck engine running in Partially Premixed Combustion (PPC) mode at medium loads.

The objective of this paper is to present the results of the GT Power calibration with engine test results of the air loop system technology down selection described in the SAE Paper No. 2012-01-0831. Two specific boosting systems were identified as the preferred path forward: (1) Super-turbo with two speed Roots type supercharger, (2) Super-turbo with centrifugal mechanical compressor and CVT transmission both downstream a Fixed Geometry Turbine. The initial performance validation of the boosting hardware in the gas stand and the calibration of the GT Power model developed is described. The calibration leverages data coming from the tests on a 2 cylinder 2-stroke 0.73L diesel engine. The initial flow bench results suggested the need for a revision of the turbo matching due to the big gap in performance between predicted maps and real data. This activity was performed using Honeywell turbocharger solutions spacing from fixed geometry waste gate to variable nozzle turbo (VNT).

In the past decade, various Plug-in Hybrid Electric Vehicles have been demonstrated which offer the potential of a significant reduction in fuel consumption and emission. However, this capability strongly depends on the sizing of the components, driver's usage profile and the quality of the energy management. These challenges require new optimization procedures for a systematical exploration of the design space with the objective of an optimal powertrain configuration. A novel optimization strategy based on a multi-objective problem formulation is proposed. The optimization procedure consists of a multi-objective genetic algorithm for determining the best design parameters with respect to fuel consumption and driving performance. The approach is combined with an analytical optimal control problem to find the optimal continuous and discrete control trajectories for the energy management.

The target of substantial CO₂ reductions in the spirit of the Kyoto Protocol as well as higher engine efficiency requirements has increased research efforts into hybridization of passenger cars. In the frame of this hybridization, there is a real need to develop small Internal Combustion Engines (ICE) with high power density. The two-stroke cycle can be a solution to reach these goals, allowing reductions of engine displacement, size and weight while maintaining good NVH, power and consumption levels. Reducing the number of cylinders, could also help reduce engine cost. Taking advantage of a strong interaction between the design office, 0D system simulations and 3D CFD computations, a specific methodology was set up in order to define a first optimized version of a two-stroke uniflow diesel engine. The main geometrical specifications (displacement, architecture) were chosen at the beginning of the study based on a bibliographic pre-study and the power target in terms.

In this paper optimal control problems for hybrid powertrain vehicles with different drive-modes are considered and solved using numerical techniques. This leads to the formulation of hybrid optimal control problems. The aim is to find optimal controls and optimal switchings between the drive-modes to minimize a cost function resembling fuel consumption. The problem is nonlinear and subject to constraints concerning both controls and state. The techniques include indirect methods as well as direct optimization methods. Efficiency and accuracy are evaluated for all methods using simulation studies. An experimental test on a near mass-production vehicle confirms the usability of the direct optimization approach.

The quality of the powertrain design has a significant impact on the fuel consumption and emissions of hybrid vehicles. Lack of experience with these relatively new technologies, the enormous variety of hybrid powertrain configurations, and the multitude of components make this area an ideal application for computer-based modeling and optimizations. Global optimization techniques have the advantage to explore systematically the design space to find the optimal configuration space. In this paper, a systematic procedure for an optimal design of hybrid powertrain configurations using an evolutionary algorithm is proposed. It will be shown that the design steps for parallel and power-split configurations are quite similar. This results in a computing approach with high synergy effects and the ability to exchange components seamless to compare different ‘virtual’ configurations.

This paper reports on a turbulent flame propagation model combined with a zero-dimensional two-zone stochastic reactor model (SRM) for efficient predictive SI in-cylinder combustion calculations. The SRM is a probability density function based model utilizing detailed chemistry, which allows for accurate knock prediction. The new model makes it possible to - in addition - study the effects of fuel chemistry on flame propagation, yielding a predictive tool for efficient SI in-cylinder calculations with all benefits of detailed kinetics. The turbulent flame propagation model is based on a recent analytically derived formula by Kolla et al. It was simplified to better suit SI engine modelling, while retaining the features allowing for general application. Parameters which could be assumed constant for a large spectrum of situations were replaced with a small number of user parameters, for which assumed default values were found to provide a good fit to a range of cases.

An innovative alternative to overcome the load limits of the early injection highly premixed combustion concept consists of taking advantage of the intrinsic characteristics of two-stroke engines, since they can attain the full load torque of a four-stroke engine as the addition of two medium load cycles, where the implementation of this combustion concept could be promising. In this frame, the main objective of this investigation focuses on evaluating the potential of the early injection HPC concept using a conventional diesel fuel combined with a two-stroke poppet valves engine architecture for pollutant control, while keeping a competitive engine efficiency. On a first stage, the HPC concept was implemented at low engine load, where the concept is expected to provide the best results, by advancing the start of injection towards the compression stroke and it was confirmed how it is possible to reduce NOX and soot emissions, but increasing HC and CO emissions.

This paper introduces a research work on the air loop system for a downsized two-stroke two-cylinder diesel engine conducted in framework of the European project dealing with the POWERtrain for Future Light-duty vehicles - POWERFUL. The main objective was to determine requirements on the air management including the engine intake and exhaust system, boosting devices and the EGR system and to select the best possible technical solution. With respect to the power target of 45 kW and scavenging demands of the two-cylinder two-stroke engine with a displacement of 0.73 l, a two-stage boosting architecture was required. Further, to allow engine scavenging at any operation, supercharger had to be integrated in the air loop. Various air loop system layouts and concepts were assessed based on the 1-D steady state simulation at full and part load with respect to the fuel consumption.