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15-02-2024 | Engine and Emissions, Fuels and Lubricants

Study on CO2 Emission Assessment of Heavy-Duty and Ultra-Heavy-Duty Vehicles Using Machine Learning

Authors: Seokho Moon, Jinhee Lee, Hyung Jun Kim, Jung Hwan Kim, Suhan Park

Published in: International Journal of Automotive Technology | Issue 3/2024

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Abstract

EU is actively moving towards the implementation of Euro-7 regulations, thus placing a strong emphasis on real-road emissions. Euro-7 introduced OBM (on-board monitoring), which is an enhancement of regulations that closely replicates real-world road conditions. Furthermore, there is a need to devise an effective application strategy for utilizing the driving monitoring data prior to the enforcement of OBM. This study addresses these challenges by conducting RDE (real-driving emission) tests on both 3.5-ton and 25-ton commercial vehicles to gather CO2 emissions and engine control unit data accessible through an OBD (on-board diagnostics) port. To process the RDE data, an appropriate machine learning model, XGBoost, was selected and trained. The outcome of our CO2 emission prediction for the two vehicles demonstrated that employing monitoring data yielded reliable estimates of actual road CO2 emissions. Finally, a comparative analysis was conducted between the proposed monitoring approach and the fuel-based CO2 monitoring method using the emission factor from EMEP/EEA air pollutant emission inventory guidebook 2019 utilizing fuel consumption data achieved through the OBFCM (on-board fuel and energy consumption monitoring) rule. Our method, which is based on predictive CO2 emissions monitoring, exhibited significantly greater accuracy. This outcome underscores the necessity to adopt the proposed approach.

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Literature
go back to reference AECC. (2023). Newsletter international regulatory developments. AECC. (2023). Newsletter international regulatory developments.
go back to reference Aeriseurope. (2021). Euro 7 Impact Assessment: The outlook for air quality compliance in the EU and the role of the road transport sector. Aeriseurope. (2021). Euro 7 Impact Assessment: The outlook for air quality compliance in the EU and the role of the road transport sector.
go back to reference Automobile Production Statistics (KOREA). (2022). KOSIS. Automobile Production Statistics (KOREA). (2022). KOSIS.
go back to reference Cha, J. P., Park, J. H., Lee, H. W. & Chon, M. S. (2021). KSAE, 22(3): 569–577. Cha, J. P., Park, J. H., Lee, H. W. & Chon, M. S. (2021). KSAE, 22(3): 569–577.
go back to reference Chen, T, & Guestrin, C. (2016). XGBoost: a scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, San Francisco California USA, pp. 785–794. Chen, T, & Guestrin, C. (2016). XGBoost: a scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, San Francisco California USA, pp. 785–794.
go back to reference Chung, J. W., Lee, B. H., Lee, S. W., Choi, S. H., & Kim, D. J. (2022a). A study on the real road driving DB-based trip CO2 emission prediction calculation method that can reflect the vehicle type and driving environment conditions of the ICEV. KSAE, 30(9), 693–702.CrossRef Chung, J. W., Lee, B. H., Lee, S. W., Choi, S. H., & Kim, D. J. (2022a). A study on the real road driving DB-based trip CO2 emission prediction calculation method that can reflect the vehicle type and driving environment conditions of the ICEV. KSAE, 30(9), 693–702.CrossRef
go back to reference Chung, J. W., Lee, B. H., Lee, S. W., Choi, S. H., & Kim, D. J. (2022b). Development of prediction model for CO2 and NOx emissions for diesel engine vehicles by considering real road driving environment. International Journal of Automotive Technology, 23(2), 541–554.CrossRef Chung, J. W., Lee, B. H., Lee, S. W., Choi, S. H., & Kim, D. J. (2022b). Development of prediction model for CO2 and NOx emissions for diesel engine vehicles by considering real road driving environment. International Journal of Automotive Technology, 23(2), 541–554.CrossRef
go back to reference Commission Regulation (EU) No 582/2011 of 25 May 2011 implementing and amending Regulation (EC) No 595/2009 of the European Parliament and of the Council with respect to emissions from heavy duty vehicles (Euro VI) and amending Annexes I and III to Directive 2007/46/EC of the European Parliament and of the CouncilText with EEA relevance. Commission Regulation (EU) No 582/2011 of 25 May 2011 implementing and amending Regulation (EC) No 595/2009 of the European Parliament and of the Council with respect to emissions from heavy duty vehicles (Euro VI) and amending Annexes I and III to Directive 2007/46/EC of the European Parliament and of the CouncilText with EEA relevance.
go back to reference Commission regulation (EU) 2018/ 1832—of 5 November 2018—amending Directive 2007/46/EC of the European Parliament and of the Council, Commission Regulation (EC) No 692/2008 and Commission Regulation (EU) 2017/1151 for the purpose of improving the emission type approval tests and procedures for light passenger and commercial vehicles, including those for in-service conformity and real-driving emissions and introducing devices for monitoring the consumption of fuel and electric energy. Commission regulation (EU) 2018/ 1832—of 5 November 2018—amending Directive 2007/46/EC of the European Parliament and of the Council, Commission Regulation (EC) No 692/2008 and Commission Regulation (EU) 2017/1151 for the purpose of improving the emission type approval tests and procedures for light passenger and commercial vehicles, including those for in-service conformity and real-driving emissions and introducing devices for monitoring the consumption of fuel and electric energy.
go back to reference Commission Regulation (EU) 2018/ 932—of 29 June 2018—amending Regulation (EU) No 582/2011 as regards the provisions on testing by means of portable emission measurement systems (PEMS) and the requirements for universal fuel range type-approval. Commission Regulation (EU) 2018/ 932—of 29 June 2018—amending Regulation (EU) No 582/2011 as regards the provisions on testing by means of portable emission measurement systems (PEMS) and the requirements for universal fuel range type-approval.
go back to reference Danquah, B., Riedmaier, S., & Lienkamp, M. (2022). Potential of statistical model verification, validation and uncertainty quantification in automotive vehicle dynamics simulations: A review. Vehicle System Dynamics, 60(4), 1292–1321.CrossRef Danquah, B., Riedmaier, S., & Lienkamp, M. (2022). Potential of statistical model verification, validation and uncertainty quantification in automotive vehicle dynamics simulations: A review. Vehicle System Dynamics, 60(4), 1292–1321.CrossRef
go back to reference Demuynck, J., & Bosteels, D. (2023). Zero-impact emissions from a gasoline car with advanced emission controls and e-fuels. Springer.CrossRef Demuynck, J., & Bosteels, D. (2023). Zero-impact emissions from a gasoline car with advanced emission controls and e-fuels. Springer.CrossRef
go back to reference EMEP/EEA air pollutant emission inventory guidebook. (2019). EMEP/EEA air pollutant emission inventory guidebook. (2019).
go back to reference EPA. (2021). Overview of EPA’s motor vehicle emission simulator (MOVES3). EPA. (2021). Overview of EPA’s motor vehicle emission simulator (MOVES3).
go back to reference European Commission. (2018). The European Commission’s science and knowledge service VECTO—Overview. European Commission. (2018). The European Commission’s science and knowledge service VECTO—Overview.
go back to reference European Commission. Joint Research Centre. (2019). Joint Research Centre 2018 light-duty vehicles emissions testing: Contribution to the EU market surveillance: Testing protocols and vehicle emissions performance. Publications Office. European Commission. Joint Research Centre. (2019). Joint Research Centre 2018 light-duty vehicles emissions testing: Contribution to the EU market surveillance: Testing protocols and vehicle emissions performance. Publications Office.
go back to reference Global technical regulation No. 5. Technical requirement for on-board diagnostic (OBD) systems for road vehicles. ECE/TRANS/180/Add.5. 2007. Global technical regulation No. 5. Technical requirement for on-board diagnostic (OBD) systems for road vehicles. ECE/TRANS/180/Add.5. 2007.
go back to reference Islam, E., et al. (2021). A detailed vehicle modeling & simulation study quantifying energy consumption and cost reduction of advanced vehicle technologies through 2050. Islam, E., et al. (2021). A detailed vehicle modeling & simulation study quantifying energy consumption and cost reduction of advanced vehicle technologies through 2050.
go back to reference Kutluay, E., & Winner, H. (2014). Validation of vehicle dynamics simulation models—a review. Vehicle System Dynamics, 52(2), 186–200.CrossRef Kutluay, E., & Winner, H. (2014). Validation of vehicle dynamics simulation models—a review. Vehicle System Dynamics, 52(2), 186–200.CrossRef
go back to reference Proposal for a regulation of the European parliament and of the council—on type-approval of motor vehicles and engines and of systems, components and separate technical units intended for such vehicles, with respect to their emissions and battery durability (Euro 7) and repealing Regulations (EC) No 715/2007 and (EC) No 595/2009; 2022. Proposal for a regulation of the European parliament and of the council—on type-approval of motor vehicles and engines and of systems, components and separate technical units intended for such vehicles, with respect to their emissions and battery durability (Euro 7) and repealing Regulations (EC) No 715/2007 and (EC) No 595/2009; 2022.
go back to reference Singh, M., & Dubey, R. (2023). Deep learning model based CO2 emissions prediction using vehicle telematics sensors data. IEEE Transactions on Intelligent Vehicles., 8(1), 768–777.CrossRef Singh, M., & Dubey, R. (2023). Deep learning model based CO2 emissions prediction using vehicle telematics sensors data. IEEE Transactions on Intelligent Vehicles., 8(1), 768–777.CrossRef
go back to reference Song, J. G., & Cha, J. P. (2022). Development of prediction methodology for CO2 emissions and fuel economy of light duty vehicle. Energy, 244, 123166.CrossRef Song, J. G., & Cha, J. P. (2022). Development of prediction methodology for CO2 emissions and fuel economy of light duty vehicle. Energy, 244, 123166.CrossRef
go back to reference The California Low-Emission Vehicle Regulations. (2022). The California Low-Emission Vehicle Regulations. (2022).
go back to reference Tier 3 Motor Vehicle Emission and Fuel Standards (Final Rule). (2014). Tier 3 Motor Vehicle Emission and Fuel Standards (Final Rule). (2014).
go back to reference Transport & Environment. (2021). Euro 7: Europe’s chance to have clean air. Transport & Environment. (2021). Euro 7: Europe’s chance to have clean air.
go back to reference Wen, H. T., Lu, J. H., & Jhang, D. S. (2021). Features importance analysis of diesel vehicles’ NOx and CO2 emission predictions in real road driving based on gradient boosting regression model. IJERPH, 18(24), 13044.CrossRef Wen, H. T., Lu, J. H., & Jhang, D. S. (2021). Features importance analysis of diesel vehicles’ NOx and CO2 emission predictions in real road driving based on gradient boosting regression model. IJERPH, 18(24), 13044.CrossRef
go back to reference Williams, M., & Minjares, R. (2016). A technical summary of Euro 6/VI vehicle emission standards. Williams, M., & Minjares, R. (2016). A technical summary of Euro 6/VI vehicle emission standards.
go back to reference Xie, H., Zhang, Y. J., He, Y., Kun, Y., Boqiang, F., Yu, D. Q., & Lei, B. (2021). Parallel attention-based LSTM for building a prediction model of vehicle emissions using PEMS and OBD. Measurement, 185, 110074.CrossRef Xie, H., Zhang, Y. J., He, Y., Kun, Y., Boqiang, F., Yu, D. Q., & Lei, B. (2021). Parallel attention-based LSTM for building a prediction model of vehicle emissions using PEMS and OBD. Measurement, 185, 110074.CrossRef
go back to reference Yang, S., Lu, Y., & Li, S. (2013). An overview on vehicle dynamics. International Journal Dynamics and Control, 1(4), 385–395.CrossRef Yang, S., Lu, Y., & Li, S. (2013). An overview on vehicle dynamics. International Journal Dynamics and Control, 1(4), 385–395.CrossRef
go back to reference Zien, N., Kramer, S., & Sonnenburg, G. R., et al. (2009). The feature importance ranking measure. Lecture Notes in Computer ScienceIn W. Buntine (Ed.), Machine learning and knowledge discovery in databases (pp. 694–709). Springer.CrossRef Zien, N., Kramer, S., & Sonnenburg, G. R., et al. (2009). The feature importance ranking measure. Lecture Notes in Computer ScienceIn W. Buntine (Ed.), Machine learning and knowledge discovery in databases (pp. 694–709). Springer.CrossRef
Metadata
Title
Study on CO2 Emission Assessment of Heavy-Duty and Ultra-Heavy-Duty Vehicles Using Machine Learning
Authors
Seokho Moon
Jinhee Lee
Hyung Jun Kim
Jung Hwan Kim
Suhan Park
Publication date
15-02-2024
Publisher
The Korean Society of Automotive Engineers
Published in
International Journal of Automotive Technology / Issue 3/2024
Print ISSN: 1229-9138
Electronic ISSN: 1976-3832
DOI
https://doi.org/10.1007/s12239-024-00051-5

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