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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 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.

As the number of different engine and vehicle concepts for powered-two wheelers is very high and will even rise with hybridization, the simulation of emissions and fuel consumption is indispensable for further development towards more environmentally friendly mobility. In this work, an adaptive artificial neural network based predictive model for emission and fuel consumption simulation of motorcycles operated in real world conditions is presented. The model is developed in Matlab and Simulink and is integrated into a longitudinal vehicle dynamic simulation whereby it is possible to simulate various and not yet measured test cycles. Subsequently, it is possible to predict real drive emissions RDE and on-road fuel consumption by a minimum of previous measurement effort.

The release of the “Regulation No. 168/2013” for the approval and market surveillance of two- or three-wheel motorcycles and quadricycles of the European Union started a new challenge for the motorcycle industry. One goal of the European Union is to achieve emission parity between passenger cars (EURO 6) and motorcycles (EURO 5) in 2020. The hybridization of motorcycle powertrains is one way to achieve these strict legislation limits. In the automotive sector, hybridization is well investigated and has already shown improvements of fuel consumption, efficiency and emission behavior. Equally, motorcycle applications have a high potential to improve efficiency and to meet customer needs as fun to drive as well. This paper describes a methodical approach to analyze conventional motorcycles regarding the energy and power demand for different driving cycles and driving conditions. Therefore, a dynamic or forward vehicle simulation within MATLAB Simulink is used.

Due to the diversity of Heavy Duty Vehicles (HDV), the European CO2 and fuel consumption monitoring methodology for HDVs will be based on a combination of component testing and vehicle simulation. In this context, one of the key input parameters that need to be accurately defined for achieving a representative and accurate fuel consumption simulation is the vehicle's aerodynamic drag. A highly repeatable, accurate and sensitive measurement methodology was needed, in order to capture small differences in the aerodynamic characteristics of different vehicle bodies. A measurement methodology is proposed which is based on constant speed measurements on a test track, the use of torque measurement systems and wind speed measurement. In order to support the development and evaluation of the proposed approach, a series of experiments were conducted on 2 different trucks, a Daimler 40 ton truck with a semi-trailer and a DAF 18 ton rigid truck.

Following its commitment to reduce CO2 emissions from road transport in Europe, the European Commission has launched the development of a new methodology for monitoring CO2 emissions from heavy-duty vehicles (HDV). Due to the diversity and particular characteristics of the HDV sector it was decided that the core of the proposed methodology will be based on a combination of component testing and vehicle simulation. A detailed methodology for the measurement of each individual vehicle component of relevance and a corresponding vehicle simulation is being elaborated in close collaboration with the European HDV manufacturers, component suppliers and other stakeholders. Similar approaches have been already adopted in other major HDV markets such as the US, Japan and China. In order to lay the foundations for the future HDV CO2 monitoring and certification software application, a new vehicle simulation software was developed, Vehicle Energy Consumption calculation Tool (henceforward VECTO).

In the future, similar to passenger cars, newly registered European heavy duty vehicles shall be labelled with the fuel consumption in typical driving cycles, determined at standardised conditions. This shall improve the comparability of the vehicles and motivate manufacturers to apply more fuel-saving technology. Therefore, a multi-stage certification procedure has been developed by a consortium of European laboratories under the leadership of the Institute for Internal Combustion Engines and Thermodynamics of TU Graz. It is based on a simulative approach and consists of: On-road measurement of driving resistances; determination of drivetrain losses; power demand of engine auxiliaries and other consumers; generation of an engine fuel consumption map from the engine's type approval tests; development of several driving cycles, typical for different vehicle applications; and a proposal for a calculation method of fuel consumption.

Diesel engines are widespread in both passenger car and heavy duty truck applications. However, despite that the combustion concepts are similar in the two cases, the engine calibration required for compliance with the different emission standards leads to distinct particle emission behavior from the two categories. This paper compares the exhaust particle emissions from heavy duty engines with typical diesel passenger cars of similar emission standard and/or emission control technology. Measurements were conducted with the same sampling system and sampling protocol to avoid interferences induced by the sampling methodology. A range of particle properties were studied, including mass, number of solid and total particles and total particle surface. For comparability, the results are expressed per unit of exhaust volume, per unit of fuel consumed and per unit of distance driven.

In the foreseeable future, legal regulations will require accurate measurement of the number of particles in motor exhaust emissions. Motor exhaust can contain both condensates (sulfates, water, HC) and solid particles. The number of condensates particles may lie as much as two to three orders of magnitude above the number of solid particles. In order to generate meaningful particle number measurements, a way must be found to reliably avoid formation of condensate particles, particularly the so-called nucleation particles (≤50 nm). Here we present a measuring system and characterize the effects of the exhaust gas recirculation rate, the rail pressure and the fuel injection time. Particularly, we show that a full-load preconditioning leads to elimination of condensate particles and to reproducible measurements of solid particle numbers.

This paper presents an overview of the results on heavy duty engines collected in the “PARTICULATES” project, which aimed at the characterization of exhaust particle emissions from road vehicles. The same exhaust gas sampling and measurement system as employed for the measurements on light duty vehicles [1] was used. Measurements were made in three labs to evaluate a wide range of particulate properties with a range of heavy duty engines and fuels. The measured properties included particle number, with focus separately on nucleation mode and solid particles, particle active surface and total mass. The sample consisted of 10 engines, ranging from Euro-I to prototype Euro-V technologies. The same core diesel fuels were used as in the light duty programme, mainly differentiated with respect to their sulphur content. Additional fuels were tested by some partners to extend the knowledge base.