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An Equivalent Emission Minimization Strategy for Causal Optimal Control of Diesel Engines

Author

Listed:
  • Stephan Zentner

    (Institute for Dynamic Systems and Control, Department of Mechanical and Process Engineering, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland)

  • Jonas Asprion

    (Institute for Dynamic Systems and Control, Department of Mechanical and Process Engineering, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland)

  • Christopher Onder

    (Institute for Dynamic Systems and Control, Department of Mechanical and Process Engineering, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland)

  • Lino Guzzella

    (Institute for Dynamic Systems and Control, Department of Mechanical and Process Engineering, ETH Zurich, Sonneggstrasse 3, 8092 Zurich, Switzerland)

Abstract

One of the main challenges during the development of operating strategies for modern diesel engines is the reduction of the CO 2 emissions, while complying with ever more stringent limits for the pollutant emissions. The inherent trade-off between the emissions of CO 2 and pollutants renders a simultaneous reduction difficult. Therefore, an optimal operating strategy is sought that yields minimal CO 2 emissions, while holding the cumulative pollutant emissions at the allowed level. Such an operating strategy can be obtained offline by solving a constrained optimal control problem. However, the final-value constraint on the cumulated pollutant emissions prevents this approach from being adopted for causal control. This paper proposes a framework for causal optimal control of diesel engines. The optimization problem can be solved online when the constrained minimization of the CO2 emissions is reformulated as an unconstrained minimization of the CO 2 emissions and the weighted pollutant emissions (i.e., equivalent emissions). However, the weighting factors are not known a priori. A method for the online calculation of these weighting factors is proposed. It is based on the Hamilton–Jacobi–Bellman (HJB) equation and a physically motivated approximation of the optimal cost-to-go. A case study shows that the causal control strategy defined by the online calculation of the equivalence factor and the minimization of the equivalent emissions is only slightly inferior to the non-causal offline optimization, while being applicable to online control.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:7:y:2014:i:3:p:1230-1250:d:33474
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    Citations

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    Cited by:

    1. Johannes Ritzmann & Christian Peterhans & Oscar Chinellato & Manuel Gehlen & Christopher Onder, 2022. "Model Predictive Supervisory Control for Integrated Emission Management of Diesel Engines," Energies, MDPI, vol. 15(8), pages 1-22, April.
    2. Johannes Ritzmann & Oscar Chinellato & Richard Hutter & Christopher Onder, 2021. "Optimal Integrated Emission Management through Variable Engine Calibration," Energies, MDPI, vol. 14(22), pages 1-23, November.
    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. 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.

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