Technology Collaboration Programme


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Task 31

Fuels and Energy Carriers for Transport

Objective of Task

The objective is to compare current (2016) and future electric and plug-in hybrid vehicles with vehicles running on the conventional motor fuels gasoline and diesel. The model covers the full life cycle of the vehicles, consisting of the phases production, use and decommissioning (including recycling). The production chain of the fuel or electricity is included as well. The model uses independent, state-of-the-art environmental evaluations (LCA) of vehicles and their use. In the full report, the approach followed is described in detail.

The multitude of model settings enables scenario analysis on a vehicle level and can show the consequences of e.g., a changing electricity mix, or of an increasing average battery size and range of electric vehicles. In the full report, the model is described in detail. The model is prepared for extension into future years, which would enable an investigation of the effect of future developments in manufacturing, use and recycling. Thus far, this has been implemented only for electricity mix compositions.

The present work provides answers to questions such as:

  • How do BEVs, PHEVs and ICEVs (gasoline and diesel) compare on environmental impacts if not only direct emissions are considered but also the indirect emissions from energy production chains and vehicle production and decommissioning?
  • Is the environmental impact comparison between BEV, ICEV and PHEV different for different market segments with corresponding drive patterns?
  • How may future developments influence the comparison between electric vehicles and combustion engine vehicles, in terms of greenhouse gas?
    • Efficiency improvement of combustion engine vehicles
    • Trend towards more sustainable electricity mix
    • Developments in battery capacities and life span
    • Changes in driving behavior: autonomous driving, intelligent traffic systems, platooning
  • What is the influence of the electricity mix on the performance of electric vehicles?
  • What is the impact of PHEVs?
  • What is the variation among passenger car market segments, from compact to luxurious vehicles?
  • What are the impacts of the vehicle production and recycling?
  • What are the impacts of the battery?
    • Battery capacity in kWh (or weight)
    • Battery production (using renewable energy or not)
    • Battery chemistry
    • Battery lifetime (in km’s)
    • Battery recycling

working method

An important aspect in changing to electric mobility (electric drive) is the trade-off in emissions between the use of the vehicle, the production of the energy carrier and the production and recycling of the vehicle. To evaluate the potential contribution to climate change and air pollution, each of these three parts is included in the analysis, see Figure 1.

working method of task 31

The impacts considered are the contribution to climate change, because of the emission of greenhouse gases including CO2, methane and N2O, expressed as CO2-equivalents using GWP-factors.

The model allows the user to define the vehicle configuration to be analysed by setting parameter values in the control panel. The model then calculates for that given configuration the life cycle CO2 impacts.

working method of task 31

Consolidation as Input for the Configuration of the LCA (GHG) Model and Analysis

The collected literature data (see final report for more information) is used as input for the LCA (GHG) model which has been developed to determine the GHG emissions for the vehicle life cycle GHG emissions.

Each study has its own scope and depth. Even LCA studies reported in accordance with the ISO 14040/14044 standards and other guidelines such as the ILCD Handbook can differ significantly amongst each other. Moreover, vehicles discussed in one source may not have the same specified functionality, such as load capacity for trucks, as vehicles in another source.

The aims of the consolidation are:

  1. To create consistent vehicle data sets for well-to-tank, tank-to-wheel and vehicle life cycle data.
  2. To create vehicle cases with comparable functionality/performance among BEVs, PHEVs and ICEVs.
  3. To develop a parametrized model for structuring the comparison of environmental impacts for vehicles in different segments.
  4. To translate data obtained from literature into input data for the model.
  5. To calculate impacts for several scenarios with respect to the input data and specifications of the compared vehicles.

The consolidation has been done by matching literature data. The rules to scale or otherwise interpret the data to perform the matching, are derived from the variety of literature. A model will be built that contains the derived rules, for example the relation between environmental impact and the weight of a vehicle (excluding battery), or the relation between a fuel’s direct emissions and the impact of its production. The relation between vehicle use and fuel consumption will be included as well, based on TNO experience with measurements in this field.

Next, vehicle cases were constructed for both passenger cars that fulfil matching minimum requirements in terms of power to weight ratio and minimum range, as described above.


The objective of Task 31 is to provide stakeholders with credible LCA based information for cars. This information enables users to determine the impacts on greenhouse gas emissions of different vehicle configurations and use profiles and fuels. The objective of the model developed is to investigate the impacts of possible future pathways and thus enable policymakers to make fact-based decisions.

Using an easy-to-use input panel, the user defines the car to be analysed using pre-set choices (for example for the choice of drivetrain or car class) or free value fields (for example for vehicle weight or the battery capacity). The model uses peer reviewed and open LCA data as well as data published in EU Framework publications. In the final report it is explained in detail how the LCA approach has been applied and which sources for the data have been used.

Conclusions from this task include:

  1. For a standard car, the lifetime GHG emissions of a BEV are approximately 50 % lower than those of an average ICEV using the EU electricity mix.
  2. A BEV using renewable energy for recharging has close to 90 % lower life cycle GHG emissions than its ICEV equivalent.
  3. The choice of the lithium-ion battery chemistry used has only a marginal impact on the life cycle GHG emissions of a BEV.
  4. In Urban driving, the life cycle GHG emissions of BEV (standard car) are about 30 % of those of an average ICEV when using the EU-mix electricity. When using renewable energy to charge the vehicle the GHG emissions are 12 times lower than those of the equivalent ICEV. • A light-weight REEV driving 80 % electric has only 10 % higher life cycle GHG emissions than a BEV (standard car). A PHEV driving 30 % electric has GHG emissions which are slightly higher than those of the equivalent ICEV.
  5. For luxury segment cars, a PHEV driving 30 % electric (EU-mix) has about 20 % lower GHG life cycle emissions than the average ICEV in that segment. A luxury BEV has 50 % lower GHG emissions than the ICEV equivalent when using EU mix electricity, 90 % lower when using renewable energy. For a luxury car, the GHG savings of a BEV using renewable energy are 270 grams per kilometre compared to an ICEV.

The T31 model is to analyse and compare published LCA data in an “apple to apple” comparison. Published data from VW Golf, VW Up!, Nissan LEAF and Nissan Pulsar have been compared with the T31 model analysis. From these comparisons, several observations have been made:

  1. Published data are very difficult to compare which each other as different assumptions are made for example for vehicle mileage, electricity GHG footprint, test method or real driving fuel consumption.
  2. Large differences are observed for the GHG emissions related to vehicle manufacturing, unclear whether this is related to inclusions or not of recycling (impacts), differences in assumptions for the manufacturing impacts on the components or the energy footprint. For the VW data, the OEM vehicle emissions are much higher than the T31 model as well as third party Spritmonitor data.
  3. Model T31 can be useful in making data from different sources comparable.
  4. A systematic analyses and comparison of OEM and other third party published data will probably be of high interest to policy makers and other stakeholders as it will provide more transparency on these published data and make them comparable.