Sampling approaches for road vehicle fuel consumption monitoring

EU Regulations introduced in 2019 for light- and heavy- duty vehicles contain provisions requiring the European Commission to set up a mechanism to monitor the real-world representativeness of the fuel consumption determined during the type-approval tests. This study proposes a sampling based approach to collect these data. Two probability-sampling methods (simple random sampling and stratified sampling) and one non-probability sampling method (quota sampling) are discussed. We use data from three user-based datasets (IFPEN, Travelcard and Spritmonitor) and the 2018 European Environment Agency CO2 monitoring dataset. All three user-based datasets provide fairly good representations of their respective countries’ sub-fleets and to a lesser extent the whole fleet. The standard deviation of the fuel consumption gap was consistently found to be approximately 20%. For a population of 15 million vehicles, using simple random sampling, and the standard deviation of the fuel consumption set at 20%, a sample of fewer than 3000 vehicles is required for estimating the average gap with a confidence level of 99% and sampling error less than 1%. Multivariate stratification with three stratification variables (vehicle manufacturer, fuel type and engine rated power) was the optimal combination, reducing the sample size by around 28% compared to simple random sample. Requiring strata specific estimators resulted to an increase of the sample size, as the number of stratification variables increased. Non-sampling errors, such as inaccuracy of On-Board Fuel and/or energy Consumption Monitor (OBFCM) device measurements, are expected to lead to an increase of the required sample size by at least 20%. Samples using quota sampling were taken and had a sampling error less than 3.5%.JRC.C.4 - Sustainable Transpor

2025 and 2030 CO2 emission targets for Light Duty Vehicles

Road transport is the main contributor to transport emissions of carbon dioxide (CO2) in the European Union (EU), with passenger cars and light commercial vehicles (LCVs) accounting for almost 15% of the total emissions. In order to gradually decarbonise the fleet, the EU has established fleet-wide CO2 targets for annually registered vehicles, assigning manufacturer specific targets based on their average vehicle mass. From 2025, new EU fleet-wide targets will be established applying a percentage reduction to a reference 2021 EU fleet-wide target. This value is calculated from the vehicles’ CO2 emissions for 2020 and the mass and registration figures of 2021. In 2025, the reduction will be 15% for both passenger cars and LCVs, while for 2030 it will increase to 55% and 50%, respectively, following the recent adoption of the more ambitious targets. This report provides the robust method used to calculate the EU fleet-wide targets in 2025 and 2030 and the parameters that will define the manufacturers’ specific target line from 2025 onwards. The EU fleet-wide targets calculated for 2025 are 93.6 g/km for passenger cars and 153.9 g/km for LCVs. For 2030, the EU fleet-wide targets will be reduced to 49.5 g/km for passenger cars and 90.6 g/km for LCVs. The slope of the target line for 2025 will be -0.0144 g/(km∙kg) for passenger cars and 0.0848 g/(km∙kg) for LCVs, while for 2030 the slope will be -0.0076 g/(km∙kg) and 0.0499 g/(km∙kg), respectively. An indicative 2025 average test mass of 1,609.6 kg for cars and 2,163.0 kg for LCVs, was calculated.JRC.C.4 - Sustainable, Smart and Safe Mobilit

Risk assessment for the 2024 In-Service Verification (ISV) of CO2 emissions of Light-Duty Vehicles

Article 13 of Regulation (EU) 2019/631 requires the type-approval authorities to verify the CO2 emission and fuel consumption values of light-duty vehicles in-service. Commission Delegated Regulation (EU) 2023/2867 sets out the guiding principles and criteria for defining the procedures for that verification, while Commission Implementing Regulation (EU) 2023/2866 determines the actual verification procedures. Article 3(4) of that Implementing Regulation requires the Commission to set out a methodology for assessing the risk that in-service verification (ISV) families may include vehicles with a deviation in the CO2 emission values and to publish each year a report describing that methodology and listing those families with the highest risk of including such vehicles. JRC has been tasked to perform the risk assessment on behalf of the Commission. When assessing the risk, at least the elements mentioned in Article 3(3) of the Implementing Regulation need to be taken into account, when available. The type-approval authorities must use the Commission’s risk assessment as a basis for selecting the families for their in-service verification. This is the first annual report describing the methodology for the assessment, and the main findings. The risk assessment methodology described is based on a Composite Risk Index (CRI), which combines the probability and severity of a specific occurrence. Probability levels are determined based on the total number of new vehicles from the in-service verification family that have been placed on the Union market. For the severity determination, the data collected pursuant to Article 14 of Implementing Regulation (EU) 2021/392 and through the Commission’s market surveillance test campaigns have been utilized. The real-world data, as referred to in Article 3(3)(e) of Implementing Regulation (EU) 2023/2866, has not yet been used for this risk assessment due to the limited number of such data submitted so far. This report also identifies the ISV families with the highest risk of including vehicles with a deviation in CO2 emissions values. These families are labelled as ISV families with the first testing priority in 2024. Based on the risk assessment, a total of 131 interpolation families, representing 106 ISV families, have been identified as having such high risk. Additionally, a significant number of interpolation families were reported as part of the annual CO2 monitoring for light-duty vehicles, but could not be found amongst those reported to the Commission under Article 14 of Implementing Regulation (EU) 2021/392. Therefore, a number (66) of those missing interpolation families with the highest vehicle registration numbers in the last three years has been selected as high risk, and labelled as ISV families with the first testing priority for the 2024 in-service verification. To further support the vehicle selection for the 2024 in-service verification, this report also presents a random selection of additional IP families both registered and not registered in Database of In-service verification of CO2 Emissions (DICE). Finally, all remaining families that are not registered in DICE are also presented.JRC.C.4 - Sustainable, Smart and Safe Mobilit

Risk assessment for the 2025 In-Service Verification (ISV) of CO2 emissions of Light-Duty Vehicles

Article 13 of Regulation (EU) 2019/631 requires the type-approval authorities to verify the CO2 emission and fuel consumption values of light-duty vehicles in-service. Commission Delegated Regulation (EU) 2023/2867 sets out the guiding principles and criteria for defining the procedures for that verification, while Commission Implementing Regulation (EU) 2023/2866 determines the actual verification procedures. Article 3(4) of that Implementing Regulation requires the Commission to set out a methodology for assessing the risk that in-service verification (ISV) families may include vehicles with a deviation in the CO2 emission values and to publish each year a report describing that methodology and listing those families with the highest risk of including such vehicles. JRC has been tasked to perform the risk assessment on behalf of the Commission. This is the second annual report describing the methodology for the assessment, and the main findings. The risk assessment methodology described was built upon the approach established in last year’s report, using the concept of the Composite Risk Index (CRI). The CRI combines the probability and severity of a specific occurrence. Probability levels are determined based on the total number of new vehicles from the in-service verification family that have been placed on the Union market. For the severity determination, the data collected pursuant to Article 14 of Implementing Regulation (EU) 2021/392 and the real-world data, as referred to in Article 3(3)(e) of Implementing Regulation (EU) 2023/2866 have been used. In addition, tests performed through the Commission’s market surveillance test campaigns and from the in-service conformity tests pursuant to Regulation (EU) 2017/1151 have been part of this year’s risk assessment. This report identifies the ISV families with the highest risk of including vehicles with a deviation in CO2 emissions values. Based on the risk assessment and random selection, 333 unique interpolation families, representing 250 unique ISV families, have been identified as having such high risk. Additionally, some interpolation families were reported as part of the annual CO2 monitoring for light-duty vehicles, but could not be found amongst those reported to the Commission under Article 14 of Implementing Regulation (EU) 2021/392. As a result, a number (24) of those missing interpolation families with the highest vehicle registration numbers in the last three years and manufacturers with the highest percentage of missing families, has been selected and included in the list of high risk families for the 2025 in-service verification. In addition, and to fill the gap between the 2025 ISV testing needs and to cover all manufacturers, the final list of families includes also 13 interpolation families selected based on medium risk or the highest registration volumes. In total, the ISV 2025 testing plan comprises 370 unique interpolation families. To further support the vehicle selection for the 2025 in-service verification, this report also links potential risks associated with ISV families flagged as high risk to chassis-dynamometer testing, road load tests, or the implementation of artificial strategies. Consequently, each of the listed ISV families was marked for specific types of tests based on the outcomes of this risk assessment.JRC.C.4 - Sustainable, Smart and Safe Mobilit

Developing an optimal sampling design to monitor the vehicle fuel consumption gap

Monitoring the fuel consumption gap between official and real-world measurements is of great interest to policy makers and researchers. This study explores how sampling methods (simple random, stratified and quota sampling) can be used to supplement and validate the monitoring. Three user-datasets were utilised to simulate the fuel consumption gap of the 11.6-15.5 million vehicles registered annually in the European Union (2018-2020). Results suggest that a simple random sample of 16240 vehicles is sufficient to estimate accurately the fleets’ average fuel consumption gap. Stratified sampling can reduce the sample size to less than 4500 vehicles. To estimate accurately the fuel consumption gap of each manufacturer, the sample size increases to approximately 17200 vehicles. The increase in sales of plug-in hybrid vehicles in 2020 led to an increase of the average fuel consumption gap by 8% and its standard deviation (variability) by 20%. This higher variability resulted in a more than double sample size, compared to previous years. It was also found that the introduction of the Worldwide Harmonized Light-duty vehicle Test Procedure (WLTP) reduced the average gap by 20-24%. This study highlights the viability of a sampling scheme to estimate the fuel consumption gap by monitoring less than 0.04% of the fleet. The study also draws attention to the need for further analysis and understanding of the real-world use and fuel consumption of plug-in hybrid vehicles.JRC.C.4 - Sustainable Transpor

Evolution of European light-duty vehicle CO2 emissions based on recent certification datasets

A new vehicle testing procedure (WLTP - Worldwide Light duty vehicle Test Procedure) was introduced in the European Union (EU) in 2017. In order to examine its actual impact on CO2 emissions for different vehicle technologies and categories, this study analysed data from vehicles certified and registered in the EU in 2019 and 2020. It was found that in average, for all vehicles sold in 2020, the increase in CO2 emissions due to the intoduction of the WLTP was 21% for passenger cars and 27% for vans. Also that diesel vehicles are impacted more than gasoline ones and that the impact on conventional hybrid vehicles is 27% and plug-in hybrid vehicles between 0% (in 2020) and 11% (in 2019). Models employed revealed that the increase in CO2 is mainly due to the higher test masses and more realistic road load coefficients of WLTP that result in higher cycle energy demands. Moreover, results confirmed that the impact of the WLTP’s introduction is in line, both in terms of absolute increase and variability, with model-based predictions performed before fleet-wide data were made available.JRC.C.4 - Sustainable Transpor

How accurately can we measure vehicle fuel consumption in real world operation?

European regulations for both light-duty (LDV) and heavy-duty vehicles (HDVs) require from 2021 the monitoring of in-use fuel consumption using on-board monitoring (OBFCM) devices. For LDVs, the accuracy to measure fuel consumed is set by regulation to ±5%, while for HDVs no requirements exist so far. In this study, OBFCM data from 15 LDVs and 12 HDVs are measured in lab and on-road. Results indicate that the FC measured by the OBFCM, for the majority of the vehicles, satisfies the accuracy requirements of ±5% over complete WLTP tests or complete on-road trips. Also, for most of the vehicles the OBD distance can be measured with an accuracy of ±1.5% on-road when Global Positioning System (GPS) distance is used as a reference. The results of this study could be used to further support the standardization of OBFCM accuracy in vehicles, and the setup of the EU real-world CO2 emissions monitoring approach.JRC.C.4 - Sustainable Transpor