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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.

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 rising environmental awareness has led to a growing interest in electric and lightweight vehicles. Four-wheeled Ultra-Efficient Lightweight Vehicles (UELVs) have the potential to improve the quality of urban life, reduce environmental impact and make efficient use of land. However, the safety of these vehicles in terms of dynamic behaviour needs to be better understood. This paper aims to provide a quantitative assessment of the handling behaviour of UELVs. An analytical single-track model and a numerical simulation by VI-CarRealTime are analysed to evaluate the dynamic performance of a UELV compared to a city car. This analysis shows that the lightweight vehicle has a higher readiness (i.e. lower reaction time to yaw rate) for step steering and lower steering effort (i.e. higher steady-state value). Experimental analysis through real-time driving sessions on the Dynamic Driving Simulator assesses vehicle responses and subjective perception for different manoeuvres.

Roundabouts are intersections at which automated cars seem currently not performing sufficiently well. Actually, sometimes, they get stuck and the traffic flow is seriously reduced. To overcome this problem a V2N-N2V (vehicle-to-network-network-to-vehicle) communication scheme is proposed. Cars communicate via 5G with an edge computer. A cooperative machine-learning algorithm orchestrates the traffic. Automated cars are instructed to accelerate or decelerate with the triple aim of improving the traffic flow into the roundabout, keeping safety constraints, and providing comfort for passengers on board of automated vehicles. In the roundabout, both automated cars and human-driven cars run. The roundabout scenario has been simulated by SUMO. Additionally, the scenario has been reconstructed into a dynamic driving simulator, with a real human driver in a virtual reality environment. The aim was to check the human perception of traffic flow, driving safety and driving comfort.

ELEVATE (European Low Emission V4 Automotive Two-stroke Engine) was a research project part funded by the European Commission to design and develop a compact and efficient gasoline two-stroke automotive engine. Five partners were involved in the project, IFP (Institut Français Du Pétrole) who were the project leaders, Lotus, Opcon (Autorotor and SEM), Politecnico di Milano and Queen's University Belfast. The general project targets were to achieve Euro 3 emissions compliance without DeNOx catalisation, and a power output of 120 kW at 5000 rev/min with maximum torque of 250 Nm at 2000 rev/min. Specific targets were a 15% reduction in fuel consumption compared to its four-stroke counterpart and a size and weight advantage over the four-stroke diesel with significant reduction in particulate and NOx emissions. This paper describes the design philosophy of the engine as well as the application of the various partner technologies used.

The paper describes the development of a modelling approach to simulate the effect of the new Worldwide harmonized Light duty Test Procedure (WLTP) on the certified CO2 emissions of light duty vehicles. The European fleet has been divided into a number of segments based on specific vehicle characteristics and technologies. Representative vehicles for each segment were selected. A test protocol has been developed in order to generate the necessary data for the validation of the vehicle simulation models. In order to minimize the sources of uncertainty and the effects of flexibilities, a reference “template model” was developed to be used in the study. Subsequently, vehicle models were developed using AVL Cruise simulation software based on the above mentioned template model. The various components and sub-modules of the models, as well as their input parameters, have been defined with the support of the respective OEMs.

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.

The reliable prediction of pollutant emissions generated by IC engine powertrains during the WLTP driving cycle is a key aspect to test and optimize different configurations, in order to respect the stringent emission limits. This work describes the application of an integrated modeling tool in a co-simulation environment, coupling a 1D fluid dynamic code for engine simulation with a specific numerical code for aftertreatment modelling by means of a robust numerical approach, to achieve a complete methodology for detailed simulations of driving cycles. The main goal is to allow an accurate 1D simulation of the unsteady flows along the intake and exhaust systems and to apply advanced thermodynamic combustion models for the calculation of cylinder-out emissions.

In the study presented in this paper, a vehicle driving cycle simulation of the pneumatic hybrid has been conducted. The pneumatic hybrid powertrain has been modeled in GT-Power and validated against experimental data. The GT-Power engine model has been linked with a MATLAB/simulink vehicle model. The engine in question is a single-cylinder Scania D12 diesel engine, which has been converted to work as a pneumatic hybrid. The base engine model, provided by Scania, is made in GT-power and it is based on the same engine configuration as the one used in real engine testing. During pneumatic hybrid operation the engine can be used as a 2-stroke compressor for generation of compressed air during vehicle deceleration and during vehicle acceleration the engine can be operated as a 2-stroke air-motor driven by the previously stored pressurized air.