Assessment of the Heavy-Duty Natural Gas technology

Heavy Duty Vehicles (HDV) powered by Compressed Natural Gas (CNG) are seen as a possible option for curbing CO2 emissions, fuel consumption and operating costs of goods transport. CNG engines have been employed in public use HDVs as an alternative to diesel engines due to their environmental benefits, and particularly due to lower particulate matter (PM) and nitrogen oxides (NOx) emissions. In the framework of the current project, an advanced newly designed CNG prototype engine developed as part of the 7th Framework Programme research project “CO2 Reduction for long distance transport” (CO2RE), is benchmarked against its parent Euro V compliant CNG engine (reference) in order to quantify the improvement in terms of real-world emissions. Results indicated a significant reduction in CO2 emissions with the prototype CNG engine both at low and high loads, which varied between 5.0-8.4%. The highest CO2 reduction was observed during on-road testing, with the corresponding reduction at low loads being more pronounced compared to high loads. Furthermore, reductions of NOx and CO emissions were observed under all testing conditions. On the other hand, hydrocarbon and methane emissions were increased with the introduction of the Prototype engine.JRC.F.8-Sustainable Transpor

Assessment of the monitoring methodology for CO₂ emissions from heavy duty vehicles: Pilot phase test-campaign report and analysis of the ex-post verification options

Following a request from DG-Clima and DG-GROW, JRC launched a test-campaign in order to investigate the validity, accuracy and plausibility of the methodology proposed for the verification of the certified CO2 emissions from Heavy Duty Vehicles (aka ex-post verification methodology). In addition scope of the test campaign was to demonstrate the representativeness of the CO2 emissions calculations made by the official simulator (VECTO) by comparing against the actual performance of vehicles. Experiments were conducted on four Euro VI trucks, both on the chassis dyno and on the road with the aim of understanding the advantages and disadvantages of different approaches proposed. Two main verification approaches were investigated, steady state measurements in chassis-dyno / controlled conditions, and measurements under transient conditions on chassis-dyno and actual on-road operating conditions. The official simulation software (VECTO) was used for simulating the operation of vehicles under the different test conditions. The key conclusion of the test campaign is that an ex-post verification method which is based on transient, on-road tests is possible for trucks and comes with the advantage that it could potentially cover also other vehicle types which are difficult to be validated under steady state conditions in a laboratory or on a test track under controlled conditions. However, there is a clear need to work on the details of the test protocol to be finally implemented, define boundary conditions for transient tests on road, and establish the necessary acceptance and rejection margins for any such validation. Finally, additional testing is necessary in order to calculate accurately any systematic deviation between the officially reported, simulated, CO2 values and those actually occurring in reality. VECTO results should be periodically controlled and assessed in order to make sure that its CO2 estimates remain representative and minimize the possibility that discrepancies will occur in the future between the officially reported and actually experienced fuel consumption.JRC.C.4-Sustainable Transpor

Development and review of Euro 5 passenger car emission factors based on experimental results over various driving cycles

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Characterization of drivers heterogeneity and its integration within traffic simulation

Drivers heterogeneity and the broad range of vehicle characteristics are considered primarily responsible for the stochasticity observed in road traffic dynamics. Assessing the differences in driving style and incorporating individual driving behaviour in microsimulation has attracted significant attention lately. The first topic is studied extensively in the literature. The second one, on the contrary, remains an open issue. The present study proposes a methodology to characterise driving style in the free-flow regime and to incorporate drivers heterogeneity within a microsimulation framework. The methodology uses explicit and simplified modelling of the vehicle powertrain to separate the drivers behavior from the vehicle characteristics. Results show that inter and intra-driver heterogeneity can be captured by log-normal distributions of well-designed metric.Drivers are classified into three different groups (dynamic, ordinary and timid drivers)

fUel-SAVing trip plannEr (U-SAVE): a product of the JRC PoC Instrument: Final report

Available tools for trip planning mostly rely on travel time and travel distance. Fuel costs, when taken into account, are based on simplified fuel consumption models and are usually independent from vehicle type and technology. Building on the work carried out by the Sustainable Transport Unit of the Joint Research Centre, European Commission, in developing (a.) CO2MPAS, the official tool supporting the WLTP/NEDC Correlation Exercise and allowing the back-translation of a WLTP test to the equivalent NEDC CO2 emission value during the type approval, and (b.) Green Driving, an interactive web-based tool allowing the estimation of fuel costs and CO2 emissions of individual car journeys on the basis of variables such as car segment, engine power, fuel type and driving style, the present project aimed at developing and proving the concept of a routing machine to be used when fuel consumption minimization is considered. Throughout the project a stand-alone off-board trip planner has been developed, the U-SAVE Desktop Version, while a smartphone application, the U-SAVE Navigation Application, is currently under the last development phase, and shall be used once completed as a low cost in-board navigation system. The tool has been extensively validated internally demonstrating both its capability to accurately estimate fuel and energy consumption via alternative trip options, and its capacity to provide a more efficient route when different from the shortest and/or fastest options. An open-access version of the tool is expected to become a reference instrument for private citizens who are concerned about their fuel consumption and a more efficient use of their vehicles, while a premium API-based commercial version of the tool can operate as a viable and scalable business model targeting, among others, established navigation software providers who want to extend their offering by providing an alternative route option to their clients, mainly private companies managing fleets of light-duty vehicles, for whom saving fuel from the daily vehicle operations is of crucial financial importance.JRC.C.4-Sustainable Transpor

The energy impact of adaptive cruise control in real-world highway multiple-car-following scenarios

Abstract Background Surging acceptance of adaptive cruise control (ACC) across the globe is further escalating concerns over its energy impact. Two questions have directed much of this project: how to distinguish ACC driving behaviour from that of the human driver and how to identify the ACC energy impact. As opposed to simulations or test-track experiments as described in previous studies, this work is unique because it was performed in real-world car-following scenarios with a variety of vehicle specifications, propulsion systems, drivers, and road and traffic conditions. Methods Tractive energy consumption serves as the energy impact indicator, ruling out the effect of the propulsion system. To further isolate the driving behaviour as the only possible contributor to tractive energy differences, two techniques are offered to normalize heterogeneous vehicle specifications and road and traffic conditions. Finally, ACC driving behaviour is compared with that of the human driver from transient and statistical perspectives. Its impact on tractive energy consumption is then evaluated from individual and platoon perspectives. Results Our data suggest that unlike human drivers, ACC followers lead to string instability. Their inability to absorb the speed overshoots may partly be explained by their high responsiveness from a control theory perspective. Statistical results might imply the followers in the automated or mixed traffic flow generally perform worse in reproducing the driving style of the preceding vehicle. On the individual level, ACC followers have tractive energy consumption 2.7–20.5% higher than those of human counterparts. On the platoon level, the tractive energy values of ACC followers tend to consecutively increase (11.2–17.3%). Conclusions In general, therefore, ACC impacts negatively on tractive energy efficiency. This research provides a feasible path for evaluating the energy impact of ACC in real-world applications. Moreover, the findings have significant implications for ACC safety design when handling the stability-responsiveness trade-off. </jats:sec

Fuel consumption and CO2 emissions of passenger cars over the New Worldwide Harmonized Test Protocol

AbstractIn 2014 the United Nations Economic Commission for Europe (UNECE) adopted the global technical regulation No. 15 concerning the Worldwide harmonized Light duty Test Procedure (WLTP). Having significantly contributed to its development, the European Commission is now aiming at introducing the new test procedure in the European type-approval legislation for light duty vehicles in order to replace the New European Driving Cycle (NEDC) as the certification test.The current paper aims to assess the effect of WLTP introduction on the reported CO2 emissions from passenger cars presently measured under the New European Driving Cycle and the corresponding test protocol. The most important differences between the two testing procedures, apart from the kinematic characteristics of the respective driving cycles, is the determination of the vehicle inertia and driving resistance, the gear shifting sequence, the soak and test temperature and the post-test charge balance correction applied to WLTP. In order to quantify and analyze the effect of these differences in the end value of CO2 emissions, WLTP and NEDC CO2 emission measurements were performed on 20 vehicles, covering almost the whole European market. WLTP CO2 values range from 125.5 to 217.9g/km, NEDC values range from 105.4 to 213.2g/km and the ΔCO2 between WLTP and NEDC ranges from 4.7 to 29.2g/km for the given vehicle sample. The average cold start effect over WLTP was found 6.1g/km, while for NEDC it was found 12.3g/km. For a small gasoline and a medium sized diesel passenger car, the different inertia mass and driving resistance is responsible 63% and 81% of the observed ΔCO2 between these two driving cycles respectively, whereas the other parameters (driving profile, gear shifting, test temperature) account for the remaining 37% and 19%

Analysing the potential of a simulation-based method for the assessment of CO2 savings from eco-innovative technologies in light-duty vehicles

[EN] Mandatory targets are set in Europe for Carbon Dioxide (CO2) emissions of light-duty vehicles. EU law recognises the potential of certain innovative technologies to contribute to reducing CO2 emissions. Vehicle systems and innovations are becoming increasingly complex, and the accurate quantification of their benefits increasingly difficult. The study investigates the potential of the CO2MPAS simulator to serve this purpose. Two innovative technologies were studied, Light-emitting diode (LED) lighting systems, efficient alternators (EA), and their combination. The model was validated on detailed test results from eight vehicles. A total of 452 passenger cars, for which test data were available, were subsequently simulated using CO2MPAS simulator. The mean simulated CO2 savings was 0.91gCO2/km (LED lights), 0.98 gCO2/km (EA), and 1.78 gCO2/km (combined). Results show that simulated CO2 savings were comparable to those calculated using the existing standardised method. For gasoline and diesel vehicles respectively, the difference in CO2 savings between simulated and existing method was 2.8% and 0.14% in the LED lights case, and 0.6% and 0.67% in the alternator case. In the combined case, the difference was calculated to be 1.7% and 0.34%. Similar approaches could be used in the future for accurately capturing the benefits of more complex technologies.Authors would like to thank Mr Filip Francois, Ms Susanna Lindvall, and Mr Sotirios Kakarantzas of DG Climate Action for their valuable comments. A special thanks goes to Dr Vincenzo Arcidiacono who guided in the targeted sample CO2MPAS simulations which gave the starting point for this work, and to Dr Giuseppe Di Pierro who provided insight and expertise that greatly improved this work.Gil-Sayas, S.; Komnos, D.; Lodi, C.; Currò, D.; Serra, S.; Broatch, A.; Fontaras, G. (2022). Analysing the potential of a simulation-based method for the assessment of CO2 savings from eco-innovative technologies in light-duty vehicles. Energy. 245:1-14. https://doi.org/10.1016/j.energy.2022.12323811424

Impact of WLTP introduction on CO2 emissions from M1 and N1 vehicles: Evidence from type-approval and 2018 EEA data

The analysis of official type-approval documents covering the period September 2017 - August 2018 and which were uploaded in the ETAES platform has given a first insight of the impact of the introduction of the WLTP procedure on declared and measured CO2 emissions. The first topic analysed was the ratio between declared WLTP and NEDC emissions. On average, this ratio is higher for diesel ICE vehicles compared to gasoline ICE vehicles. The mean ratio for diesel VH was 1.26 for M1 category and 1.28 for N1 and for VL 1.18 for M1 and 1.22 for N1 category. The 2018 EEA data showed an average ratio of 1.25 for M1 and 1.27 for N1 category. For gasoline ICE vehicles the mean ratio for VH is 1.16 for M1 1.19 for N1 category and for VL 1.13 for M1 and 1.14 for N1 category. The 2018 EEA data show an average ratio of 1.19 for M1 1.16 for N1 category. The highest average ratio for diesel and gasoline VH was calculated for OEM_3 group and for VL for OEM_15 (diesel) and OEM_3 (gasoline) groups. The 2018 EEA registrations data show the highest average ratio coming from OEM_3 (diesel) and OEM_11 (gasoline) groups. For NOVC-HEVs and OVC-HEVs the data sets analysis were much smaller and any conclusions drawn should be treated with caution. The mean WLTP/NEDC ratio for NOVC-HEVs was 1.22 (VH) and 1.18 (VL), which is higher than that of gasoline ICE vehicles. For all OVC-HEVs analysed (weighted-combined CO2 emissions) the ratio for VH is 1.13, but with a range from 0.34 to 1.44 and for VL the average was 1.03 (range: 0.31-1.32). In the 2018 EEA data NOVC-HEVs and OVC-HEVs could not be distinguished. Analysis of Emission type-approval documents (ETA) revealed that for the majority of IP families analysed (70% for VH and 73% for VL) the declared WLTP values were less than 5% higher than the WLTP measured values. In 26% of cases for VH and 23% for VL the over-declaration was between 5% and 10%. In only 4% of cases for VH and 4% for VL OEM’s over-declaration was above 10% (but always below 20%). In total, 18% (266) of IP families are type-approved with only vehicle high (VH), which leads to higher CO2 emissions compared to the interpolation approach. Some OEMs are only type-approving VH (OEM_13, OEM_16, OEM_17, OEM_18, OEM_19, OEM_21, OEM_22, OEM_23, OEM_24, OEM_25, OEM_27, OEM_28), but except OEM_13, the other OEM groups have very low registrations. OEM groups with high registrations (more than half million) and high % of IP families with only VH are: OEM_7 (24%), OEM_5 (22%), OEM_2 (20%), OEM_9 (7%), and OEM_3 (6%). OEM_12 and OEM_10 are another OEMs with high % of IP families with only VH (91% and 73%, respectively) and registrations higher than 200,000. Various inconsistencies and issues have been identified in the data collected. Such inconsistencies should be addressed to ensure correct implementation of the legislation and a level playing field.JRC.C.4-Sustainable Transpor