Nikiforos Zacharof

This study investigates the CO2 reduction potential of powertrain hybridisation on heavy-duty lorries and city buses. The analysis considers modern parallel and serial hybrid architectures, assessing their efficiency and limits in CO2 emission reduction through vehicle simulation in VECTO, which is the official tool of the European Commission for calculating heavy-duty vehicle fuel and energy consumption. The results reveal distinct trends for each vehicle type and architecture. In lorries, more significant improvements are observed in urban delivery profiles, reaching up to ~16%, indicating the benefits of hybridisation in transient conditions with energy recuperation opportunities. City buses, particularly those with serial architectures, exhibit significant emission reductions that reach 36%, making them suitable for urban environments. The optimisation of electric motor size and performance plays a crucial role in achieving emission reductions, while battery capacity must be carefully considered to avoid adverse effects. For lorries in urban delivery use, further improvements of 17.5% can be achieved by utilising a 160 kW engine motor and 30 kWh battery. Buses are already quite well optimised, with serial architecture presenting the highest benefits with a 120 kW electric motor and a battery of 11 kWh. Future research should focus on supercapacitors and gearboxes to improve efficiency at higher vehicle speeds and assess hybridisation potential in interurban coach travel. The heavy-duty vehicle sector can make significant strides towards low-carbon transport by maximising hybrid powertrain efficiency and emission reductions.

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. Subsequently, evaluating the accuracy of the process, the simulation results were compared with reference VECTO results supplied by various vehicle manufacturers. The results showed that the difference between simulated and reference CO₂ emissions was on average -0.6% in the Long Haul cycle and 1% in the Regional Delivery. Such a process could be a powerful tool for calculating HDV CO₂ emissions for development and analysis purposes, e.g. for new vehicle prototypes or multistage vehicles, and for creating VECTO equivalent models that can be used to assess alternative operating conditions and mission profiles of existing vehicle models. The methodology was applied for creating input of various components in the US tool for HDV certification, GEM, for generic sample-vehicle models available.

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. Fuel efficiency distributions and energy breakdown figures were derived from the data and are presented in this work. Correlation formulas were produced to calculate the energy loss contributions of individual components and resistances (air drag, rolling resistance, axle losses, gearbox losses, etc.) over the Regional Delivery and Long Haul cycles, given a limited number of input parameters such as vehicle characteristics and average component efficiencies. Default values and meaningful ranges of variation of these parameters obtained from the data of the fleet are also reported in this work. The importance of air drag and rolling resistance losses are highlighted since these losses account for about 70% of the energy consumed downstream the engine. Finally, based on the correlation formulas to calculate the individual energy losses, a method is presented that calculates the final energy consumption and CO₂ emissions for all the regulated HDTs classes and that does not rely on the use of VECTO.

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. The effects of aerodynamics, auxiliary systems, curb-weight, tyre rolling resistance, engine internal losses, and engine and gearbox efficiency were investigated. Factors exhibited a varying reduction potential that depended on the vehicle category and the driving cycle. Results indicate where focus should be given for improving the energy performance of trucks in view of the Commission’s future efforts to propose CO2 reduction targets for HDVs.