Reduced order model with non-linear parameter optimization for hydrogen combustion engine control *

IEEE Conference on Control Technology and Applications (CCTA), pp. 287–294

Abstract

Using hydrogen as a fuel in spark ignition (SI) internal combustion engines offers an environmentally friendly alternative to fossil fuels, while retaining many benefits of conventional powertrains. Even though the hydrogen SI engine can rely on mature mechanical parts from conventional gasoline engines, the control software has to be adapted to the change in fuel. This includes a rapid switching between lean and stochiometric operation while ensuring engine protection and very low pollutant emissions. A model predictive controller (MPC) offers the possibility to systematically consider opposing control objectives and constraints for transient operation while reducing the development and calibration effort. As a basis for the real-time capable MPC, a reduced order physical model with empirical components is developed to describe the processes in the combustion chamber. Taking single cylinder engine testbench measurements into account from early stages of the engine development, some of the model’s parameters are optimized to increase prediction accuracy. The resulting non-linear parameter optimization reduces the mean square errors of the main outputs relative air-fuel-ratio and indicated mean effective pressure from 0.1475 and 0.5426 bar2to 0.0218 and 0.1020 bar2within a wide operating area.

Authors 6

1. Kevin Kluge Aachen Institute of Automatic Control (IRT)

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Institute of Automatic Control,Germany

   Institute of Automatic Control, RWTH Aachen University, Germany

2. Benjamin Pehlivanlar Aachen Chair of Thermodynamics of Mobile Energy Conversion Systems (TME)

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Thermodynamics of Mobile Energy Conversion Systems,Germany

   Chair of Thermodynamics of Mobile Energy Conversion Systems, RWTH Aachen University, Germany

3. Henrik Wenzel Aachen Institute of Automatic Control (IRT)

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Institute of Automatic Control,Germany

   Institute of Automatic Control, RWTH Aachen University, Germany

4. Marco Günther Aachen Chair of Thermodynamics of Mobile Energy Conversion Systems (TME)

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Thermodynamics of Mobile Energy Conversion Systems,Germany

   Chair of Thermodynamics of Mobile Energy Conversion Systems, RWTH Aachen University, Germany

5. Stefan Pischinger Aachen Chair of Thermodynamics of Mobile Energy Conversion Systems (TME)

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Thermodynamics of Mobile Energy Conversion Systems,Germany

   Chair of Thermodynamics of Mobile Energy Conversion Systems, RWTH Aachen University, Germany

6. Dirk Abel Aachen Institute of Automatic Control (IRT)

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Institute of Automatic Control,Germany

   Institute of Automatic Control, RWTH Aachen University, Germany