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In spark-ignition engines, fluctuations of the in-cylinder pressure trace and the apparent rate of heat release are usually observed from one cycle to another. These Cycle-to-Cycle Variations (CCV) are affected by the early flame development and the subsequent flame front propagation. The CCV are responsible for engine performance (e.g. fuel consumption) and the knock behavior. The occurrence of the phenomena is unpredictable and the stochastic nature offers challenges in the optimization of engine control strategies. In the present work, CCV are analyzed in terms of their impact on the engine knock behavior and the related efficiency. Target is to estimate the possible fuel consumption savings in steady-state operation and in the drivecycle, when CCV are reduced. Since CCV are immanent on real engines, such a study can only be done by means of simulation.

The Vehicle Energy Consumption calculation Tool (VECTO) is used for the official calculation and reporting of CO2 emissions of HDVs in Europe. It uses certified input data in the form of energy or torque loss maps of driveline components and engine fuel consumption maps. Such data are proprietary and are not disclosed. Any further analysis of the fleet performance and CO2 emissions evolution using VECTO would require generic inputs or reconstructing realistic component input data. The current study attempts to address this issue by developing a process that would create VECTO input files based as much as possible on publicly available data. The core of the process is a series of models that calculate the vehicle component efficiency maps and produce the necessary VECTO input data. The process was applied to generate vehicle input files for rigid trucks and tractor-trailers of HDV Classes 4, 5, 9 and 10.

Beside hard facts as performance, emissions and fuel consumption especially the brand specific attributes such as styling and sound are very emotional, unique selling prepositions. To develop these emotional characters, within the given boundary conditions of the future pass-by regulation, it is necessary to define them at the very beginning of the project and to follow a consequent development process. The following paper shows examples of motorcycle NVH development work on noise cleaning and sound engineering using a hybrid development process combining front loading, simulation and testing. One of the discussed solutions is the investigation of a piston pin offset in combination with a crankshaft offset for the reduction of friction. The optimization of piston slap noise as a result of the piston secondary motion was performed by simulation. As another example a simulation based development was performed for the exhaust system layout.

The European Union road transport CO2 emissions regulation foresees mandatory targets for passenger vehicles. However, several studies have shown that there is a divergence between official and real-world values that could range up to 40% compared to the NEDC reference value. The introduction of the Worldwide Harmonized Test Protocol (WLTP) limited this divergence, but it is uncertain whether it can adequately address the problem, particularly considering future evolutions of vehicle technology. In order to address this issue, the recent EU CO2-standards regulation introduces the monitoring of on-road fuel consumption and subsequently CO2 emissions by utilizing On-Board Fuel Consumption Meters (OBFCM). In the near future, all vehicles should provide instantaneous and lifetime-cumulative fuel consumption signals at the diagnostics port. Currently, the fuel consumption signal is not always available.

With the adoption of the Worldwide harmonized Light Vehicles Test Procedure (WLTP) and the Real Driving Emissions (RDE) regulations for testing and monitoring the vehicle pollutant emissions, as well as CO2 and fuel consumption, the gap between real world and type approval performances is expected to decrease to a large extent. With respect to CO2, however, WLTP is not expected to fully eliminate the reported 40% discrepancy between real world and type approval values. This is mainly attributed to the fact that laboratory tests take place under average controlled conditions that do not fully replicate the environmental and traffic conditions experienced over daily driving across Europe. In addition, any uncertainties of a pre-defined test protocol and the vehicle operation can be optimized to lower the CO2 emissions of the type approval test. Such issues can be minimized in principle with the adoption of a real-world test for fuel consumption.

The electrification of the powertrain is a prerequisite to meet future fuel consumption limits, while the internal combustion engine (ICE) will remain a key element of most production volume relevant powertrain concepts. High volume applications will be covered by electrified powertrains. The range will include parallel hybrids, 48V- or High voltage Mild- or Full hybrids, up to Serial hybrids. In the first configurations the ICE is the main propulsion, requiring the whole engine speed and load range including the transient operation. At serial hybrid applications the vehicle is generally electrically driven, the ICE provides power to drive the generator, either exclusively or supporting a battery charging concept. As the ICE is not mechanically coupled to the drive train, a reduction of the operating range and thus a partial simplification of the ICE is achievable.

The accurate prediction of pollutant emissions generated by IC engines is a key aspect to guarantee the respect of the emission regulation legislation. This paper describes the approach followed by the authors to achieve a strict numerical coupling of two different 1D modeling tools in a co-simulation environment, aiming at a reliable calculation of engine-out and tailpipe emissions. The main idea is to allow an accurate 1D simulation of the unsteady flows and wave motion inside the intake and exhaust systems, without resorting to an over-simplified geometrical discretization, and to rely on advanced thermodynamic combustion models and kinetic sub-models for the calculation of cylinder-out emissions. A specific fluid dynamic approach is then used to track the chemical composition along the exhaust duct-system, in order to evaluate the conversion efficiency of after-treatment devices, such as TWC, GPF, DPF, DOC, SCR and so on.

In the present work, a scalable simulation methodology is presented that enables the assessment of the impact of SI-engine cycle-to-cycle combustion variations on fuel consumption and hence CO2 emissions on three different levels of modeling depth: in-cylinder, steady-state engine and transient engine and vehicle simulation. On the detailed engine combustion chamber level, a 3D-CFD approach is used to study the impact of the turbulent in-cylinder flow on the cycle-resolved flame propagation characteristics. On engine level, cycle-to-cycle combustion variations are assessed regarding their impact on indicated mean effective pressure, aiming at estimating the possible fuel consumption savings when cyclic variations are minimized. Finally, on the vehicle system level, a combined real-time engine approach with crank-angle resolved cylinder is used to assess the potential fuel consumption savings for different vehicle drivecycle conditions.

In order to meet current and future emission and CO2 targets, an efficient vehicle thermal management system is one of the key factors in conventional as well as in electrified powertrains. Global vehicle simulation is already a well-established tool to support the vehicle development process. In contrast to conventional vehicles, electrified powertrains offer an additional challenge to the thermal conditioning: the durability of E-components is not only influenced by temperature peaks but also by the duration and amplitude of temperature swings as well as temperature gradients within the components during their lifetime. Keeping all components always at the preferred lowest temperature level to avoid ageing under any conditions (driving, parking, etc.) will result in very high energy consumption which is in contradiction to the efficiency targets.

The fuel supply chain faces challenges associated with microbial contamination symptoms. Microbial growth is an issue usually known to be associated with middle distillate fuels and biodiesel, however, incidents where microbial populations have been isolated from unleaded gasoline storage tanks have also been recently reported. Alcohols are employed as gasoline components and the use of these oxygenates is rising, especially ethanol, which can be a renewable alternative to gasoline, as well. Despite their alleged disinfectant properties, a number of field observations suggests that biodeterioration could be a potential issue in fuel systems handling ethanol-blended gasoline. For this reason, in this study, the effect of alcohols on microbial proliferation in unleaded gasoline fuel was assessed. Ethanol (EtOH), iso-propyl alcohol (IPA) and tert-butyl-alcohol (TBA) were evaluated as examples of alcohols utilized in gasoline as oxygenates.

Upcoming, increasingly stringent greenhouse gas (GHG) as well as emission limits demand for powertrain electrification throughout all vehicle applications. Increasing complexity of electrified powertrain architectures require an overall system approach combining modular component technology with integration and industrialization requirements when heading for further significant efficiency optimization. At the same time focus on reduced development time, product cost and minimized additional investment demand reuse of current production, machining, and assembly facilities as far as possible. Up to date additive manufacturing (AM) is an established prototype component, as well as tooling technology in the powertrain development process, accelerating procurement time and cost, as well as allowing to validate a significantly increased number of variants. The production applications of optimized, dedicated AM-based component design however are still limited.

The rate in the electrification of vehicles has risen in recent years. With intensified development more and more attention is paid to the noise and vibration in such vehicles especially from the EDU (Electric Drive Unit). In this paper the main NVH simulation process of a high-speed E-axle up to 30,000 rpm for premium class vehicle application is presented. The high speed, high-power density and lightweight design introduces new challenges. Benchmarking of different EDUs and vehicles leads to targets which can be used at the early stage of development as subsystem targets. This paper shows the CAE methodology which can be used to verify the design and guarantee the target achievement. Using CAE both source and structure can be optimized to improve the NVH behavior.

A vital element of any vehicle-certification test is the use of representative values for the vehicle resistance forces. In most certification procedures, including the WLTP recently adopted by the EU, the latter is achieved mainly through coast down tests. Subsequently, the resistance values measured are used for setting up the chassis-dyno resistances applied during the laboratory measurements. These reference values are obtained under controlled conditions, while a series of corrections are applied to make the test procedure more repeatable and reproducible. In real driving, the actual vehicle road loads are influenced by a series of factors leading to a divergence between the certified fuel consumption values, and the real-world ones. An approach of calculating representative road loads during on-road tests can help to obtain a more unobstructed view of vehicle efficiency and, when needed, confirm the officially declared road loads.

DiMethyl Ether (DME) has been known to be an outstanding fuel for combustion in diesel cycle engines for nearly twenty years. DME has a vapour pressure of approximately 0.5MPa at ambient temperature (293K), thus it requires pressurized fuel systems to keep it in liquid state which are similar to those for Liquefied Petroleum Gas (mixtures of propane and butane). The high vapour pressure of DME permits the possibility to optimize the fuel injection characteristic of direct injection diesel engines in order to achieve a fast evaporation and mixing with the charged gas in the combustion chamber, even at moderate fuel injection pressures. To understand the interrelation between the fuel flow inside the nozzle spray holes tests were carried out using 2D optically accessed nozzles coupled with modelling approaches for the fuel flow, cavitation, evaporation and the gas dynamics of 2-phase (liquid and gas) flows.

This study investigates the impact of mid-high biodiesel blends on the criteria and PAH emissions from a modern pick-up diesel vehicle. The vehicle was a Euro 4 (category N1, subclass III) compliant common-rail light-duty goods pick-up truck fitted with a diesel oxidation catalyst. Emission and fuel consumption measurements were performed on a chassis dynamometer equipped with CVS, following the European regulations. All measurements were conducted over the certification New European Driving Cycle (NEDC) and the real traffic-based Artemis driving cycles. Aiming to evaluate the fuel impact on emissions, a soy-based biodiesel, a palm-based biodiesel, and an oxidized biodiesel obtained from used frying oils were blended with a typical automotive ultra-low-sulfur diesel at proportions of 30, 50 and 80% by volume. The experimental results revealed that CO₂ emissions and fuel consumption exhibited an increase with biodiesel over all driving conditions.

For nearly twenty years, DiMethyl Ether has been known to be an outstanding fuel for combustion in diesel cycle engines. Not only does it have a high Cetane number, it burns absolutely soot free and produces lower NOx exhaust emissions than the equivalent diesel. However, the physical properties of DME such as its low viscosity, lubricity and bulk modulus have negative effects for the fuel injection system, which have both limited the achievable injection pressures to about 500 bar and DME's introduction into the market. To overcome some of these effects, a common rail fuel injection system was adapted to operate with DME and produce injection pressures of up to 1000 bar. To understand the effect of the high injection pressure, tests were carried out using 2D optically accessed nozzles. This allowed the impact of the high vapour pressure of DME on the onset of cavitation in the nozzle hole to be assessed and improve the flow characteristics.

The paper describes a zero-dimensional crank angle resolved combustion model which was developed for the analysis and prediction of combustion in compression ignition (CI) engines. The model relies on the multi zone combustion model (MZCM) approach of Hiroyasu. The main sub-models were taken from literature and extended with additional features described in this paper. A special procedure described in a previous paper is used to identify the mechanisms of the combustion process on the basis of the measured cylinder pressure trace. Based on the identified mechanisms the present work concentrates on the analysis of the causal effects that predominantly control the combustion process and the formation of NOx and Soot. The focus lies on the changes of the thermodynamic states and the composition of the reaction zones caused by different emission control strategies.

This paper describes some of the recent work carried out in our laboratory regarding the effects of novel oxygen and nitrogen containing compounds on the antiknock quality of unleaded gasoline and their effects on some other gasoline properties. In particular, the research included Research Octane Number (RON) measurements and the evaluation of the effects of the most effective antiknock compounds on Dry Vapour Pressure Equivalent (DVPE), distillation temperatures, aromatic content, olefins, and oxygen content. Emphasis was given in studying chemical structures that can be derived from renewable raw materials. The compounds tested included substituted phenols, furan derivatives, aliphatic amines, various amide structures and Mannich base phenols. Methyl t-butyl ether (MTBE), the most widespread oxygenate currently used in gasoline, was used as a yardstick for assessing the quality of the compounds tested.

The internal combustion engine contains several actuators to control engine performance and emissions. These are controlled within the engine ECU and follow a specific operating strategy to achieve objectives such as NOx reduction and fuel economy. However, these two goals are conflicting and a compromise is required. The operating state depends on system constraints such as engine speed, load, temperature levels, and aftertreatment system efficiency. This results in constantly changing target values to stay within the defined limits, especially the legal emission limits. The conventional approach is to use multiple operating modes. Each mode represents a specific compromise and is activated accordingly. Multiple modes are required to meet emissions regulations under all required conditions, which increases the calibration effort. This new control approach uses an artificial neural network to replace the conventional multiple mode approach.

In Plug in hybrid electric vehicles (PHEVs), the management of the main drivetrain components and the shift between pure electric and hybrid propulsion is decided by the on-board energy management system (EMS). The EMS decisions have a direct impact on CO2 emissions and need to be optimized to achieve as low emissions as possible. This paper presents optimization methods for EMS algorithms of a parallel P2 PHEV. Two different supervisory control algorithms are examined, employing simulations on a validated PHEV platform. An Equivalent Consumption Minimization Strategy (ECMS) algorithm is implemented and compared to a rule-based one, the latter derived by back-engineering of available experimental data. The different EMS algorithms are analyzed and compared on an equal basis in terms of distance, demanded energy and state of charge levels over different driving cycles.