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Journal Article

An Experimental Methodology for Measuring of Aerodynamic Resistances of Heavy Duty Vehicles in the Framework of European CO2 Emissions Monitoring Scheme

2014-04-01
2014-01-0595
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.
Technical Paper

An Analysis of Modern Vehicle Road Loads for Fleetwide Energy Consumption Modelling

2021-09-05
2021-24-0080
Passenger and light-duty vehicles have a high, and steadily increasing, greenhouse gas emissions footprint. Industry and regulators put effort into new, efficient propulsion configurations to reduce carbon dioxide (CO2) emissions from the transport sector. Energy savings are highly impacted not only by the driving style and needs of the driver, but also by the energy mix used during a trip, making the vehicle efficiency benchmarking increasingly complex. A potential way to curb the vehicle energy demand is by minimising the losses due to factors opposing the forward movement, such as vehicle inertia, tyre deformation, drivetrain, and vehicle air-drag. These losses are included in the vehicle road loads. In the present study, we derive representative road load values by employing open access vehicle information and combining physical and statistical methods. These values are then compared to the ones declared by the manufacturer, which are derived by physical coast down tests.
Technical Paper

A Simplified CO2 and Fuel Consumption Model for Buses Derived from VECTO Simulations

2021-09-05
2021-24-0075
New heavy-duty vehicles are simulated with the Vehicle Energy Consumption Calculation Tool (VECTO) to certify their fuel consumption and CO2 emissions in the European Union. The vehicle manufacturer runs the simulation tool and requires the vehicle components' characteristics to simulate the vehicle over standardized mission profiles. The detailed component characteristics required to run the tool are not always publicly available. In this work, a simplified model was developed to predict the fuel consumption and CO2 emissions of heavy buses over the VECTO mission profiles. It requires only the basic vehicle properties as input, such as the air drag, tire rolling resistance, mass, drivetrain efficiency and auxiliary power use. The model was derived from detailed VECTO simulations of numerous variants of a diesel high floor bus, a diesel low floor bus and a CNG low floor bus.
Technical Paper

Calculating Heavy-Duty Truck Energy and Fuel Consumption Using Correlation Formulas Derived From VECTO Simulations

2019-04-02
2019-01-1278
The Vehicle Energy Consumption calculation Tool (VECTO) is used in Europe for calculating standardised energy consumption and CO2 emissions from Heavy-Duty Trucks (HDTs) for certification purposes. The tool requires detailed vehicle technical specifications and a series of component efficiency maps, which are difficult to retrieve for those that are outside of the manufacturing industry. In the context of quantifying HDT CO2 emissions, the Joint Research Centre (JRC) of the European Commission received VECTO simulation data of the 2016 vehicle fleet from the vehicle manufacturers. In previous work, this simulation data has been normalised to compensate for differences and issues in the quality of the input data used to run the simulations. This work, which is a continuation of the previous exercise, focuses on the deeper meaning of the data received to understand the factors contributing to energy and fuel consumption.
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