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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.

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.

The battery of a vehicle with an electrified powertrain (Hybrid Electric Vehicle or Battery Electric Vehicle), is required to operate with highly dynamic power outputs, both for charging and discharging operation. Consequently, the battery current varies within an extensive range during operation and the battery temperature also changes. In some cases, the relationship between the current flow and the change in the electrical energy stored seems to be affected by inefficiencies, in literature described as current losses, and nonlinearities, typically associated with the complex chemical and physical processes taking place in the battery. When calculating the vehicle electrical energy consumption over a trip, the change in the electrical energy stored at vehicle-level has to be taken into account. This quantity, what we could call the vehicle electricity balance, is typically obtained through a time-based integration of the battery current of all the vehicle batteries during operation.

Waste heat recovery based on an Organic Rankine Cycle is a technology proposed for the reduction of the fuel consumption of heavy-duty vehicles. This technology is currently not simulated by VECTO, the tool used in Europe to certify the fuel consumption and CO2 emissions of new heavy-duty vehicles. In this work, a class 5 lorry equipped with a prototype Organic Rankine Cycle system is tested on the chassis dyno during steady state and transient driving cycles, with the waste heat recovery enabled and disabled. The waste heat recovery system enabled a brake specific fuel consumption reduction of 3.1% over the World Harmonized Vehicle Cycle, 2.5% during the official EU Regional Delivery Cycle, and up to 6.5% at certain engine operating points during the fuel consumption mapping cycle. A model of the vehicle was created in VECTO based on the experimental data. The fuel consumption map of the engine with and without the Organic Rankine Cycle was derived from the steady-state experiments.

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.

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.

Heavy-duty vehicles (HDVs) account for some 5% of the EU’s total greenhouse gas emissions. They present a variety of possible configurations that are deployed depending on the intended use. This variety makes the quantification of their CO2 emissions and fuel consumption difficult. For this reason, the European Commission has adopted a simulation-based approach for the certification of CO2 emissions and fuel consumption of HDVs in Europe; the VECTO simulation software has been developed as the official tool for the purpose. The current study investigates the impact of various technologies on the CO2 emissions of European trucks through vehicle simulations performed in VECTO. The chosen vehicles represent average 2015 vehicles and comprised of two rigid trucks (Class 2 and 4) and a tractor-trailer (Class 5), which were simulated under their reference configurations and official driving cycles.

Plug-in Hybrid Electric Vehicles (PHEVs) are one of the main technology options for reducing vehicle CO2 emissions and helping vehicle manufacturers (OEMs) to meet the CO2 targets set by different Governments from all around the world. In Europe OEMs have introduced a number of PHEV models to meet their CO2 target of 95 g/km for passenger cars set for the year 2021. Fuel consumption (FC) and CO2 emissions from PHEVs, however, strongly depend on the way they are used and on the frequency with which their battery is charged by the user. Studies have indeed revealed that in real life, with poor charging behavior from users, PHEV FC is equivalent to that of conventional vehicles, and in some cases higher, due to the increased mass and the need to keep the battery at a certain charging level.

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).

Governments worldwide are taking actions aiming to achieve a sustainable transportation system that can comprise of minimal pollutant and GHG emissions. Particular attention is given to the real-world emissions, i.e. to the emissions achieved in the real driving conditions, outside of a controlled testing environment. In this framework, interest in vehicle fleet electrification is rapidly growing, as it is seen as a way to simultaneously reduce pollutant and GHG emissions, while on the other hand OEMs are facing a significant increase in the number of tests which are needed to calibrate this new generation of electrified powertrains over a variety of different driving scenarios.

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 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.

European Union's (EU) Climate Law sets a legally binding target of net-zero greenhouse gas emissions by 2050. EU identified hydrogen technologies as a priority introducing hydrogen-powered propulsion systems into the market. Even though the new registrations of fuel cell (FC) passenger cars increased by 41% in 2020 in Europe, the research community faces a lack of public and independent available data regarding the performance and energy efficiency of state-of-the-art FC electric vehicles. This study introduces a tailored methodology to characterise the different powertrain components and analyse the energy flow for a Fuel Cell Electric Vehicle (FCEV) already available on the market. Experimental data are gathered over different driving conditions, including standard driving cycles such as WLTP and US06 tests performed in a laboratory.

In European Union (EU), new heavy-duty vehicles are simulated with the Vehicle Energy Consumption calculation TOol (VECTO) to certify their fuel consumption and CO2 emissions. VECTO will also be used to certify vehicles with hybrid-electric powertrains in all topological configurations from P0 to P4 parallel systems and series hybrids. A development version of VECTO able to simulate these configurations is already available and was used for this study. The study team collected measurement data from a specific P2 hybrid lorry, instrumented with wheel torque sensors, current and voltage sensors, fuel flow sensor and a PEMS device. The vehicle was tested on the chassis dyno and on the road, and a representative model was created in VECTO. The regional delivery certification cycle was simulated in VECTO in charge sustaining and full electric mode.

Battery Electric Vehicle (BEV) sales have been spiking up due to a series of factors: zero tailpipe emissions, wider model availability, increased customer acceptance, reduced purchase price, improved performance and range. The latter is a crucial factor the consumers consider when purchasing a BEV, and it largely depends on how the vehicle operates (e.g. average speed), traffic, ambient conditions, and battery size. When driven on the roads, the actual range of BEVs can be significantly smaller than the certified value obtained from laboratory testing at standard conditions. To understand the factors influencing vehicle range in real-world operation, the study team performed on-road tests on three production passenger vehicles currently available in the European market. The measured quantities, including vehicle signals from OBD/UDS, were used to quantify the vehicle energy consumption.

In 2023, the European Union set more ambitious targets for reducing greenhouse gas emissions from passenger cars: the new fleet-wide average targets became 93.6 g/km for 2025, 49.5 g/km in 2030, going to 0 in 2035. One year away from the 2025 target, this study evaluates what contribution to CO2 reduction was achieved from new conventional vehicles and how to interpret forecasts for future efficiency gains. The European Commission’s vehicle efficiency cost-curves suggest that optimal technology adoption can guarantee up to 50% CO2 reduction by 2025 for conventional vehicles. Official registration data between 2013 and 2022, however, reveal only an average 14% increase in fuel efficiency in standard combustion vehicles, although reaching almost 23% for standard hybrids. The smallest gap between certified emissions and best-case scenarios is of 14 g/km, suggesting that some manufacturers’ declared values are approaching the optimum.