Road Transport Fleet Impact Model
overview
main purpose
summary
The DIONE Fleet Impact Model is used to assess the impacts of changes in the European and MS road transport fleet characteristics up to the year 2050. It is a flexible tool which can be employed to analyse scenarios on road vehicle stock development and composition, vehicle activity and driving patterns, and vehicle technology and fuel use trends. The model contains a calibrated baseline which is consistent with the country-specific stock and activity data collected in the project TRACCS, and is taken forward following the trends of a PRIMES baseline scenario. Fuel consumption and emission calculation for combustion engine vehicles is based on COPERT methodology. For alternative fuel vehicles, an energy and emission calculation methodology has been developed which takes account of vehicle characteristics, trip lengths and speed distributions. For both energy consumption and greenhouse gas (GHG) emissions, DIONE can provide real world Tank-to-Wheel (TtW) up to the year 2050 as well as Well-to-Wheel (WtW) results up to 2030.
The DIONE cost curve model is employed for developing cost curves which describe the costs associated with reaching a given CO2 standard, for a given vehicle segment and powertrain. Cost curves are constructed by identifying cost-optimal bundles of technologies for CO2 reduction and then fitting a continuous cost curve.
The DIONE Cross-optimization module identifies cost-optimal strategies to reach given emission targets, building on the cost curves. Cross-optimization outcomes can be used to assess the impact of different policy options on manufacturing costs for different manufacturers and the market as a whole.
The DIONE Total Cost of Ownership Module computes total costs of ownership for different vehicle types and powertrains, summarizing the results from the previous steps and adding fuel/energy costs and maintenance costs. This allows assessing the societal costs associated with a policy option, as well as costs for consumers (new vehicle buyers and second-hand vehicle buyers).
DIONE can be used for ex-ante policy support. All DIONE modules are employed to provide policy support in the context of decarbonisation and electrification of road transport, as well as for assessing possible transitions towards alternative fuels for road transport.
model type
ownership
licence
- Licence type
- Non-Free Software licence
details on model structure and approach
The DIONE model uses a modular structure which allows to add new functionalities as more data becomes available and as policy needs arise. Model development originally started with the DIONE fleet impact model, which is used to calculate road transport fuel and energy consumption and emissions for future fleet development scenarios. The model presently consists of the following modules, which can be used either standalone or in combinations, and cover a broad range of road vehicles (cars, vans, trucks):
- DIONE Fleet Impact Model
- DIONE COPERT module (under development)
- DIONE Cost Curve Module
- DIONE Cross-Optimization Module
- DIONE Fuel and Energy Cost Module
- DIONE TCO and Payback Module
model inputs
Parametrisation: The DIONE fleet impact model contains a calibrated stock baseline which is consistent with the country-specific stock and activity data collected in the project TRACCS, and is taken forward following the trends of PRIMES 2012 baseline scenario with adopted measures.
Fuel consumption and emission calculation for combustion engine vehicles is based on COPERT 4 v.11 road transport emission inventory software. For alternative fuel vehicles, an energy and emission calculation methodology has been developed which takes account of vehicle characteristics, trip lengths and speed distributions.
Inputs:
Main variables that can be defined by the user include:
- vehicle stock,
- new registrations,
- survival rates,
- activity,
- efficiency improvement,
- fuel use of flex-fuel vehicles,
- fuel pathways for well-to-wheel energy consumption and emissions,
- biofuel admixture shares for conventional fuels,
- driving patterns.
Users can define custom scenarios either by adapting baseline values in the DIONE input tables or graphical user interface graphs, or by uploading input files. The user can decide to create a scenario for any predefined entity, i.e., any single EU member state (plus some extra neighbour countries), pre-defined groupings such as EU28, EU15 and EU12, but can also decide to define a custom scenario for any region, city, country or other entity of interest.
The DIONE Cost Curve Module uses data on vehicle efficiency improvement technologies (their efficiencies, costs and compatibilities) as additional inputs, whereas the DIONE Fuel and Energy Cost Module needs to be fed with energy price estimates. For Cross-Optimization and TCO/Payback Calculations, Fleet Composition scenarios can be aligned with DIONE fleet impact model runs or provided from other sources.
model outputs
The output of the DIONE fleet impact model contains fleet development and activity, energy demand, CO2 emissions, other GHGs and all air pollutants included in the COPERT methodology.
For both energy consumption and greenhouse gas (GHG) emissions, DIONE can provide real world tank-to-wheel (TtW) figures up to the year 2050 as well as well-to-wheel (WtW) results up to 2030. For CO2 emissions, NEDC type approval values can be calculated, as well. DIONE also includes a cost module which determines additional costs for achieving given efficiency targets for conventional passenger cars.
DIONE can be used for policy-relevant scenario analysis, including analysis of the following options:
- Fuel efficiency targets
- Technology replacement, Stock composition or new registration technology share targets
- Biofuel Admixture
- Fuel GHG intensities
- Scrappage Schemes
- Vehicle Activity
The further modules provide additional outputs such as
- Cost-optimal segment and powertrain-specific CO2 reductions and related costs
- Fuel and energy costs of vehicle types and fleets
- Total costs of ownership for vehicles within a given scenario,
- Payback times for efficiency technology
model spatial-temporal resolution and extent
| Parameter | Description |
|---|---|
| Spatial Extent/Country Coverage | EU Member states 27 |
| Spatial Resolution | World-regions (supranational)National |
| Temporal Extent | Medium-term (5 to 15 years)Long-term (more than 15 years) 2010-2050 |
| Temporal Resolution | Years |