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Dynamic Feedforward Control of a Diesel Engine Based on Optimal Transient Compensation Maps

Author

Listed:
  • Giorgio Mancini

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

  • Jonas Asprion

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

  • 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, 8092 Zurich, Switzerland)

  • Lino Guzzella

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

Abstract

To satisfy the increasingly stringent emission regulations and a demand for an ever lower fuel consumption, diesel engines have become complex systems with many interacting actuators. As a consequence, these requirements are pushing control and calibration to their limits. The calibration procedure nowadays is still based mainly on engineering experience, which results in a highly iterative process to derive a complete engine calibration. Moreover, automatic tools are available only for stationary operation, to obtain control maps that are optimal with respect to some predefined objective function. Therefore, the exploitation of any leftover potential during transient operation is crucial. This paper proposes an approach to derive a transient feedforward (FF) control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. A partially physics-based model is thereby used to replace the engine. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient. These maps complement the static control maps by accounting for the dynamic behavior of the engine. The procedure is implemented on a real engine and experimental results are presented along with the development of the methodology.

Suggested Citation

  • Giorgio Mancini & Jonas Asprion & Nicolò Cavina & Christopher Onder & Lino Guzzella, 2014. "Dynamic Feedforward Control of a Diesel Engine Based on Optimal Transient Compensation Maps," Energies, MDPI, vol. 7(8), pages 1-25, August.
  • Handle: RePEc:gam:jeners:v:7:y:2014:i:8:p:5400-5424:d:39458
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    Citations

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    Cited by:

    1. Landry Frank Ineza Havugimana & Bolan Liu & Fanshuo Liu & Junwei Zhang & Ben Li & Peng Wan, 2023. "Review of Artificial Intelligent Algorithms for Engine Performance, Control, and Diagnosis," Energies, MDPI, vol. 16(3), pages 1-25, January.
    2. Galindo, José & Serrano, José Ramón & De la Morena, Joaquín & Gómez-Vilanova, Alejandro, 2022. "Physical-based variable geometry turbines predictive control to enhance new hybrid powertrains’ transient response," Energy, Elsevier, vol. 261(PB).

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