Abstract
One effective possibility to reduce pollutant emissions and fuel consumption of an internal combustion engine is the use of improved process control. It is made viable by the implementation of additional actuators and sensors which allow to operate the process more flexible. For full exploitation of the setup an appropriate control algorithm is necessary. Classical engine control structures rely on the use of many calibration parameters which result in high demands on the calibration time. Model predictive control (MPC) is an advanced control algorithm which is able to overcome this drawback. It allows to use a mathematical plant model for control synthesis which reduces calibration time and makes reusability possible. The present paper introduces the MPC algorithm and discusses the benefits of MPC for engine control. A special emphasis is put on the application for gasoline airpath control. For clarification, the benefits are demonstrated by numerical simulation studies. For the example of gasoline two stage turbocharging, the advantage concerning control performance are shown as well as the possibility to easily adapt to changed specifications for the closed-loop control dynamics.
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Acknowledgements
This research was performed as part of the Research Unit (Forschergruppe) FOR 2401 “Optimization based Multiscale Control for Low Temperature Combustion Engines” which is funded by the German Research Association (Deutsche Forschungsgemeinschaft, DFG). The support is gratefully acknowledged.
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Albin, T. Benefits of model predictive control for gasoline airpath control. Sci. China Inf. Sci. 61, 70204 (2018). https://doi.org/10.1007/s11432-017-9342-7
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DOI: https://doi.org/10.1007/s11432-017-9342-7