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Equivalent Consumption Minimization Strategy for the Control of Real Driving NOx Emissions of a Diesel Hybrid Electric Vehicle

Author

Listed:
  • Tobias Nüesch

    (Institute for Dynamic Systems and Control, ETH Zurich, Sonneggstrasse 3, Zurich 8092, Switzerland)

  • Alberto Cerofolini

    (Department of Industrial Engineering, University of Bologna, Viale Risorgimento 2, Bologna 40136, Italy)

  • Giorgio Mancini

    (Department of Industrial Engineering, University of Bologna, Viale Risorgimento 2, Bologna 40136, Italy)

  • Nicolò Cavina

    (Department of Industrial Engineering, University of Bologna, Viale Risorgimento 2, Bologna 40136, Italy)

  • Christopher Onder

    (Institute for Dynamic Systems and Control, ETH Zurich, Sonneggstrasse 3, Zurich 8092, Switzerland)

  • Lino Guzzella

    (Institute for Dynamic Systems and Control, ETH Zurich, Sonneggstrasse 3, Zurich 8092, Switzerland)

Abstract

Motivated by the fact that the real driving NOx emissions (RDE) of conventional diesel vehicles can exceed the legislation norms by far, a concept for the control of RDE with a diesel parallel hybrid electric vehicle (HEV) is proposed. By extending the well-known equivalent consumption minimization strategy (ECMS), the power split degree of freedom is used to control the NOx emissions and the battery state of charge (SOC) simultaneously. Through an appropriate formulation of the problem, the feedback control is shown to be separable into two dependent PI controllers. By hardware-in-the-loop (HIL) experiments, as well as by simulations, the proposed method is shown to minimize the fuel consumption while tracking a given reference trajectory for both the NOx emissions and the battery SOC.

Suggested Citation

  • Tobias Nüesch & Alberto Cerofolini & Giorgio Mancini & Nicolò Cavina & Christopher Onder & Lino Guzzella, 2014. "Equivalent Consumption Minimization Strategy for the Control of Real Driving NOx Emissions of a Diesel Hybrid Electric Vehicle," Energies, MDPI, vol. 7(5), pages 1-31, May.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:5:p:3148-3178:d:35981
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    References listed on IDEAS

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    1. Jeongbin Lee & Jaeshin Yi & Chee Burm Shin & Seung Ho Yu & Won Il Cho, 2013. "Modeling the Effects of the Cathode Composition of a Lithium Iron Phosphate Battery on the Discharge Behavior," Energies, MDPI, vol. 6(11), pages 1-12, October.
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    3. Stephan Zentner & Jonas Asprion & Christopher Onder & Lino Guzzella, 2014. "An Equivalent Emission Minimization Strategy for Causal Optimal Control of Diesel Engines," Energies, MDPI, vol. 7(3), pages 1-21, February.
    4. Tobias Ott & Christopher Onder & Lino Guzzella, 2013. "Hybrid-Electric Vehicle with Natural Gas-Diesel Engine," Energies, MDPI, vol. 6(7), pages 1-22, July.
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    Cited by:

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    3. Antonio Rossetti & Nicola Andretta & Alarico Macor, 2022. "On the Use of the Disability-Adjusted Life Year (DALY) Estimator as a Metric to Optimally Manage ICE Emissions," Energies, MDPI, vol. 15(12), pages 1-14, June.
    4. Fengqi Zhang & Lihua Wang & Serdar Coskun & Hui Pang & Yahui Cui & Junqiang Xi, 2020. "Energy Management Strategies for Hybrid Electric Vehicles: Review, Classification, Comparison, and Outlook," Energies, MDPI, vol. 13(13), pages 1-35, June.
    5. Duhr, Pol & Christodoulou, Grigorios & Balerna, Camillo & Salazar, Mauro & Cerofolini, Alberto & Onder, Christopher H., 2021. "Time-optimal gearshift and energy management strategies for a hybrid electric race car," Applied Energy, Elsevier, vol. 282(PA).
    6. Yuping Zeng & Yang Cai & Guiyue Kou & Wei Gao & Datong Qin, 2018. "Energy Management for Plug-In Hybrid Electric Vehicle Based on Adaptive Simplified-ECMS," Sustainability, MDPI, vol. 10(6), pages 1-24, June.
    7. Gang Yao & Changbo Du & Quanbo Ge & Haoyu Jiang & Yide Wang & Mourad Ait-Ahmed & Luc Moreau, 2019. "Traffic-Condition-Prediction-Based HMA-FIS Energy-Management Strategy for Fuel-Cell Electric Vehicles," Energies, MDPI, vol. 12(23), pages 1-21, November.
    8. Teng Liu & Yuan Zou & Dexing Liu & Fengchun Sun, 2015. "Reinforcement Learning–Based Energy Management Strategy for a Hybrid Electric Tracked Vehicle," Energies, MDPI, vol. 8(7), pages 1-18, July.
    9. Balerna, Camillo & Lanzetti, Nicolas & Salazar, Mauro & Cerofolini, Alberto & Onder, Christopher, 2020. "Optimal low-level control strategies for a high-performance hybrid electric power unit," Applied Energy, Elsevier, vol. 276(C).
    10. Di Guo & Changqing Du & Fuwu Yan, 2016. "Drivability-Related Discrete-Time Model Predictive Control of Mode Transition in Pre-Transmission Parallel Hybrid Powertrains," Energies, MDPI, vol. 9(9), pages 1-31, September.
    11. Hung, Yi-Hsuan & Tung, Yu-Ming & Chang, Chun-Hsin, 2016. "Optimal control of integrated energy management/mode switch timing in a three-power-source hybrid powertrain," Applied Energy, Elsevier, vol. 173(C), pages 184-196.
    12. Saiteja, Pemmareddy & Ashok, B., 2022. "Critical review on structural architecture, energy control strategies and development process towards optimal energy management in hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    13. Fengqi Zhang & Haiou Liu & Yuhui Hu & Junqiang Xi, 2016. "A Supervisory Control Algorithm of Hybrid Electric Vehicle Based on Adaptive Equivalent Consumption Minimization Strategy with Fuzzy PI," Energies, MDPI, vol. 9(11), pages 1-26, November.
    14. García, Antonio & Carlucci, Paolo & Monsalve-Serrano, Javier & Valletta, Andrea & Martínez-Boggio, Santiago, 2020. "Energy management strategies comparison for a parallel full hybrid electric vehicle using Reactivity Controlled Compression Ignition combustion," Applied Energy, Elsevier, vol. 272(C).
    15. Giorgio Previati & Giampiero Mastinu & Massimiliano Gobbi, 2022. "Thermal Management of Electrified Vehicles—A Review," Energies, MDPI, vol. 15(4), pages 1-29, February.
    16. Caiyang Wei & Theo Hofman & Esin Ilhan Caarls & Rokus van Iperen, 2020. "A Review of the Integrated Design and Control of Electrified Vehicles," Energies, MDPI, vol. 13(20), pages 1, October.
    17. Xiong, Rui & Cao, Jiayi & Yu, Quanqing, 2018. "Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle," Applied Energy, Elsevier, vol. 211(C), pages 538-548.
    18. Camillo Balerna & Marc-Philippe Neumann & Nicolò Robuschi & Pol Duhr & Alberto Cerofolini & Vittorio Ravaglioli & Christopher Onder, 2020. "Time-Optimal Low-Level Control and Gearshift Strategies for the Formula 1 Hybrid Electric Powertrain," Energies, MDPI, vol. 14(1), pages 1-30, December.
    19. Zeyu Chen & Jiahuan Lu & Bo Liu & Nan Zhou & Shijie Li, 2020. "Optimal Energy Management of Plug-In Hybrid Electric Vehicles Concerning the Entire Lifespan of Lithium-Ion Batteries," Energies, MDPI, vol. 13(10), pages 1-15, May.
    20. Johannes Schalk & Harald Aschemann, 2016. "A Causal and Real-Time Capable Power Management Algorithm for Off-Highway Hybrid Propulsion Systems," Energies, MDPI, vol. 10(1), pages 1-17, December.
    21. Chen, Z. & Liu, Y. & Ye, M. & Zhang, Y. & Chen, Z. & Li, G., 2021. "A survey on key techniques and development perspectives of equivalent consumption minimisation strategy for hybrid electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    22. Chen, Zheng & Xia, Bing & You, Chenwen & Mi, Chunting Chris, 2015. "A novel energy management method for series plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 145(C), pages 172-179.

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