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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 use of state of the art simulation tools for effective front-loading of the calibration process is essential to support the additional efforts required by the new Real Driving Emission (RDE) legislation. The process needs a critical model validation where the correlation in dynamic conditions is used as a preliminary insight into the bounds of the representation domain of engine mean values. This paper focuses on the methodologies for correlating dynamic simulations with emissions data measured during dynamic vehicle operation (fundamental engine parameters and gaseous emissions) obtained using dedicated instrumentation on a diesel vehicle, with a particular attention for oxides of nitrogen NOx specie. This correlation is performed using simulated tests run within AVL’s mean value engine and engine aftertreatment (EAS) model MoBEO (Model Based Engine Optimization).

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.

The European Emissions Stage 5b standard for diesel passenger cars regulates particulate matter to 0.0045 g/km and non-volatile part/km greater than 23 nm size to 6.0x10₁₁ as determined by the PMP procedure that uses a heated evaporation tube to remove semi-volatile material. Measurement artifacts associated with the evaporation tube technique prevents reliable extension of the method to a lower size range. Catalytic stripper (CS) technology removes possible sources of these artifacts by effectively removing all hydrocarbons and sulfuric acid in the gas phase in order to avoid any chemical reactions or re-nucleation that may cause measurement complications. The performance of a miniature CS was evaluated and experimental results showed solid particle penetration was 50% at 10.5 nm. The sulfate storage capacity integrated into the CS enabled it to chemically remove sulfuric acid vapor rather than rely on dilution to prevent nucleation.

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.

In this article we present a design of a new miniaturized sensor with the capacity to measure exhaust particle concentrations on board vehicles and engines. The sensor is characterized by ultra-fast response time, high sensitivity, and a wide dynamic range. In addition, the physical dimensions of the sensor enable its placement along the exhaust line. The concentration response and temporal performance of a prototype sensor are discussed and characterized with aerosol laboratory test measurements. The sensor performance was also tested with actual engine exhaust in both chassis and engine dynamometer measurements. These measurements demonstrate that the sensor has the potential to meet and even exceed any requirements around the world in terms of on-board diagnostic (OBD) sensitivity and frequency of monitoring.

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.

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.

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.

Light duty diesel vehicles continue to win recognition and market shares in Europe due to their convincing economy, reliability and driveability features. The diesel boom finds a fresh rationale in the CO2 emission legislation to come, however, the competitiveness of diesel cars may be impaired in future in consequence of the progression of the exhaust emission legislation and its impact on vehicle cost. This paper reviews the technologies currently pursued on the side of the engine and its subsystems, as well as the exhaust gas aftertreatment concepts required to satisfy the European legislation. An integral system approach is suggested, aiming at an optimum match of vehicle design parameters, transmission gear and the engine including aftertreatment elements and control.

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.

The Pegasor Particle Sensor (PPS) has been earlier presented by Ntziachristos et al. (SAE Paper 2011-01-0626) as a novel small and robust instrument that can be directly installed in the exhaust line to measure exhaust particles without any dilution. The instrument is based on the electrical detection of aerosol. It is increasingly being used to measure exhaust particles from engines and vehicles with different exhaust configurations. In this study, a number of tests have been conducted using two sensors in parallel, one directly installed in the tailpipe and one installed in the CVS, side by side to the PM sampling filter. Aim of the study was to make recommendations on the proper use of the sensor and to check how the sensor signal compares to particulate mass, soot concentration, and particle number. A first finding is that external heating has to be provided to the sensor to avoid condensation.

The Pegasor Particle Sensor (PPS) is a small and lightweight sensor that can be used directly in raw exhaust to provide the mass and number concentration of exhaust aerosol. Its operation principle is based on the electrical charging of exhaust aerosol and determination of particle concentration by measuring the charge accumulated on the particles. In this paper we have applied the PPS in a variety of vehicle exhaust configurations to evaluate its performance characteristics. First, the output signal of the instrument was calibrated with diesel exhaust to deliver either the mass or the number concentration of exhaust aerosol. Linear response with the soot mass concentration measured by a Photo Acoustic Soot Sensor and number concentration measured by an Electrical Low Pressure Impactor was established.

Due to the increasing pressure to develop small-size and low-cost after-treatment systems meeting the legislative demands it is desirable to integrate multiple functionalities and exploit any possible synergies. Typical examples include DPFs catalyzed with deNOx catalysts, as well as LNT-SCR combinations using layered coating technology. The present paper deals with the modeling challenges involved for the proper simulation of such advanced concepts. Key role in such advanced simulation attempts has the coupling between diffusion-reaction phenomena, which is captured through intra-layer modeling. All investigations in this paper deal with the application of possible combined LNT-SCR system configurations. The simulation results show that a dual bed LNT- passive SCR configuration offers substantial NOx emissions reductions compared to a single LNT catalyst and effectively controls secondary NH3 emissions produced during LNT regeneration phases.

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.

Non-combustible particles, commonly summarized as ash, influence the lifetime performance of wall flow filters. This study aims to investigate this influence by means of simulation. An existing transient 1D+1D wall flow filter model is extended by dedicated transport balances for soot and ash (1), by a discrete cake model describing changing soot and ash compositions over the cake height (2), by a phenomenological cake filtration model (3), by dedicated cake property models (4) and by a phenomenological model capturing the radial mobility of solids within the cake (5). Results of three different types of simulations are shown. First, the various sub-models are assessed in isolated simulation configurations. The combination of these shall serve as theoretical model validation. Second, isolated loading and passive regeneration simulations are performed.

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.