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Stoichiometric natural gas (CNG) engines are an attractive solution for heavy-duty vehicles considering their inherent advantage in emitting lower CO2 emissions compared to their Diesel counterparts. Additionally, their aftertreatment system can be simpler and less costly as NOx reduction is handled simultaneously with CO/HC oxidation by a Three-Way Catalyst (TWC). The conversion of methane over a TWC shows a complex behavior, significantly different than non-methane hydrocarbons in stoichiometric gasoline engines. Its performance is maximized in a narrow A/F window and is strongly affected by the lean/rich cycling frequency. Experimental and simulation results indicate that lean-mode efficiency is governed by the palladium’s oxidation state while rich conversion is governed by the gradual formation of carbonaceous compounds which temporarily deactivate the active materials.

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.

The proposed Euro 7 emission standard foresees that the emission behaviour of Euro 7 vehicles is monitored via an on-board monitoring (OBM) system. In Euro 7 vehicles, OBM systems will monitor the emissions of nitrogen oxides (NOX), ammonia (NH3) and particulate matter (PM) for every trip through a combination of measured and modelled data. Sensors employed to support on-board diagnostics (OBD) in current vehicles may be used to support OBM. According to the Euro 7 OBM concept presented in this paper, OBM will serve a dual purpose: the first is to warn the user of a vehicle about the need to perform repairs on the engine or the pollution control systems when these are needed. If these repairs are not performed in a timely manner, the OBM system will be able to ultimately prevent engine restart, akin to the existing low-reagent driver warning system in some compression ignition vehicles. The second purpose of OBM is to monitor the compliance of vehicle types with the emission limits.

The current European fleet of vehicles is ageing and lifetime mileages are rising proportionally. Consequently, a substantial fraction of the vehicle fleet is currently operating at mileages well beyond current durability legislation (≤ 160,000 km). Emissions inventories and models show substantial increases in emissions with increasing mileage, but knowledge of the effect of emissions control system deterioration at very high mileages is sparse. Emissions testing has been conducted on matched pairs (or more) of diesel and gasoline (and CNG) vehicles, of low and high mileage, supplementing the results with in-house data, in order to explore high mileage emission deterioration factors (DF). The study isolated, as far as possible, the effect of emissions deterioration with mileage, by using nominally identical vehicle models and controlling other variables.

The implementation of emission standards has brought significant reductions in vehicle emissions in the EU, but road transport is still a major source of air pollution. Future emission standards will aim at making road vehicles as clean as possible under a wide range of driving conditions and throughout their complete lifetime. The current paper presents the methodology followed by the Consortium for ultra LOw Vehicle Emissions (CLOVE) to support the preparation of the Euro 7 proposal. As a first step, the emission performance of the latest-technology vehicles under various driving conditions was evaluated. Towards this direction, an emissions database was developed, containing data from a wide range of tests, both within and beyond the current RDE boundaries.

The shift toward electrification and limitations in battery electric vehicle technology have led to high demand for hybrid vehicles (HEVs) that utilize a battery and an internal combustion engine (ICE) for propulsion. Although HEVs enable lower fuel consumption and emissions compared to conventional vehicles, they still require combustion of fuels for ICE operation. Thus, emissions from hybrid vehicles are still a major concern. Engine starts are a major source of emissions during any driving event, especially before the three-way catalyst (TWC) reaches its light-off temperature. Since the engine is subjected to multiple starts during most driving events, it is important to mitigate and better understand the impact of these emissions. In this study, experiments were conducted to analyze engine starts in a hybrid powertrain on different experimental setup.

Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

The latest generation of internal combustion engines may emit significant levels of sub-23 nm particles. The main objective of the Horizon 2020 “DownToTen” project was to develop a robust methodology and provide policy recommendations towards the particle number (PN) emissions measurements in the sub-23 nm region. In order to achieve this target, a new portable exhaust particle sampling system (PEPS) was developed, being capable of measuring exhaust particles down to at least 10 nm under real-world conditions. The main design target was to build a system that is compatible with current PMP requirements and is characterized by minimized losses in the sub-23 nm region, high robustness against artefacts and high flexibility in terms of different PN modes investigation, i.e. non-volatile, volatile and secondary particles.

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.

Meeting the particle number (PN) emissions limits in vehicle test sequences needs specific attention on each power variation event occurring in the internal combustion engine (ICE). ICE power variations arise from engine start onwards along the entire test drive. In hybrid systems, there is one further source for transient ICE response: each power shift between E-motor and ICE introduces gas flow variations with subsequent temperature response in the ICE and in the engine aftertreatment system (EAS). This bears consequences for engine out emissions as well as for the EAS efficiency and even for the durability of a catalytic converter. As system calibration engineers must decide on numerous actuator parameters, their decisions, finally, are crucial for meeting legislative limits under the boundary conditions given by the hybrid vehicle’s drive environment.

The present work investigates a number of recalibration possibilities of a common rail turbocharged diesel engine, aiming at the improvement of its emissions performance and fuel consumption (FC), with Hydrotreated Vegetable Oil (HVO). Initially, steady-state experimental data with nominal engine settings revealed HVO benefits as a drop-in fuel. Under these conditions, pure HVO results in lower engine-out PM emissions, lower CO2 emissions, and lower mass-based FC, while the respective NOx emissions present a mixed trend. In mid loads and speeds NOx emissions of HVO are lower while at higher loads and speeds are slightly higher compared to conventional diesel. At a second step, a combustion model was developed, in order to investigate the possible re-adjustments of IT (Injection Timing) and EGR (Exhaust Gas Recirculation) settings in order to exploit HVO’s properties for further reduction of emissions and FC.

Most stringent emission legislations have been implemented in all major markets to improve air quality across the past years. This effects the product cost of the vehicles which is considered being critical and needs to be minimized. India suffers from bad air quality and countermeasures have been defined. One being the implementation of similar emission standards than EU VI. By doing so, India takes a large step going from the currently effective BS IV directly to BS VI. Emission reduction is currently mainly handled by the usage of EGR, thus no engine aftertreatment system has been applied. BS VI will require an aftertreatment (EAS) concept with several catalysts and corresponding control system. India is a very cost sensitive market and a carry over of solutions from the EU needs to be evaluated carefully and new approaches need to be found.

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).

Certain diesel fuel specification properties are considered to be environmental parameters according to the European Fuels Quality Directive (FQD, 2009/EC/30) and previous regulations. These limits included in the EN 590 specification were derived from the European Programme on Emissions, Fuels and Engine Technologies (EPEFE) which was carried out in the 1990’s on diesel vehicles meeting Euro 2 emissions standards. These limits could potentially constrain FAME blending levels higher than 7% v/v. In addition, no significant work has been conducted since to investigate whether relaxing these limits would give rise to performance or emissions debits or fuel consumption benefits in more modern vehicles. The objective of this test programme was to evaluate the impact of specific diesel properties on emissions and fuel consumption in Euro 4, Euro 5 and Euro 6 light-duty diesel vehicle technologies.

The present work introduces an extended particulate filter model focusing on capabilities to cover catalytic and surface storage reactions and to serve as a virtual multi-functional reactor/separator. The model can be classified as a transient, non-isothermal 1D+1D two-channel model. The applied modeling framework offers the required modeling depth to investigate arbitrary catalytic reaction schemes and it follows the computational requirement of running in real-time. The trade-off between model complexity and computational speed is scalable. The model is validated with the help of an analytically solved reference and the model parametrization is demonstrated by simulating experimentally given temperatures of a heat-up measurement. The detailed 1D+1D model is demonstrated in a concept study comparing the impact of different spatial washcoat distributions.

The present work introduces an innovative mechanistically based 0D spray model which is coupled to a combustion model on the basis of an advanced mixture controlled combustion approach. The model calculates the rate of heat release based on the injection rate profile and the in-cylinder state. The air/fuel distribution in the spray is predicted based on momentum conservation by applying first principles. On the basis of the 2-zone cylinder framework, NOx emissions are calculated by the Zeldovich mechanism. The combustion and emission models are calibrated and validated with a series of dedicated test bed data specifically revealing its capability of describing the impact of variations of EGR, injection timing, and injection pressure. A model based optimization is carried out, aiming at an optimum trade-off between fuel consumption and engine-out emissions. The findings serve to estimate an economic optimum point in the NOx/BSFC trade-off.

The continuously decreasing emission limits lead to a growing importance of exhaust aftertreatment in Diesel engines. Hence, methods for achieving a rapid catalyst light-off after engine cold start and for maintaining the catalyst temperature during low load operation will become more and more necessary. The present work evaluates several valve timing strategies concerning their ability for doing so. For this purpose, simulations as well as experimental investigations were conducted. A special focus of simulation was on pointing out the relevance of exhaust temperature, mass flow and enthalpy for these thermomanagement tasks. An increase of exhaust temperature is beneficial for both catalyst heat-up and maintaining catalyst temperature. In case of the exhaust mass flow, high values are advantageous only in case of a catalyst heat-up process, while maintaining catalyst temperature is supported by a low mass flow.

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.

A key element to achieving vehicle emission certification for most light-duty vehicles using spark-ignition engine technology is prompt catalyst warming. Emission mitigation largely does not occur while the catalyst is below its “light-off temperature”, which takes a certain time to achieve when the engine starts from a cold condition. If the catalyst takes too long to light-off, the vehicle could fail its emission certification; it is necessary to minimize the catalyst warm up period to mitigate emissions as quickly as possible. One technique used to minimize catalyst warm up is to calibrate the engine in such a way that it delivers high temperature exhaust. At idle or low speed/low-load conditions, this can be done by retarding spark timing with a corresponding increase in fuel flow rate and / or leaning the mixture. Both approaches, however, encounter limits as combustion stability degrades and / or nitrogen oxide emissions rise excessively.

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.