Model-Based Combustion Control to Reduce the Brake Specific Fuel Consumption and Pollutant Emissions under Real Driving Maneuvers

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Authors Abstract
Content
A previously developed piston damage and exhaust gas temperature models are coupled to manage the combustion process and thereby increasing the overall energy conversion efficiency. The proposed model-based control algorithm is developed and validated in a software-in-the-loop simulation environment, and then the controller is deployed in a rapid control prototyping device and tested online at the test bench. In the first part of the article, the exhaust gas temperature model is reversed and converted into a control function, which is then implemented in a piston damage-based spark advance controller. In this way, more aggressive calibrations are actuated to target a certain piston damage speed and exhaust gas temperature at the turbine inlet. A more anticipated spark advance results in a lower exhaust gas temperature, and such decrease is converted into lowering the fuel enrichment with respect to the production calibrations. Moreover, the pollutant emissions associated with production calibrations and the implementation of the developed controller are compared through a GT-Power combustion model.
Finally, the complete controller is validated for both the transient and steady-state conditions, reproducing a real vehicle maneuver at the engine test bench. The results demonstrate that the combination of an accurate estimation of the damage induced by knock and the value of the exhaust gas temperature allows to reduce the brake specific fuel consumption by up to 20%. Moreover, the stoichiometric area of the engine operating field is extended by 20%, and the GT-Power simulations show a maximum CO reduction of about 50%.
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DOI
https://doi.org/10.4271/03-17-01-0007
Pages
17
Citation
Brusa, A., Mecagni, J., Shethia, F., and Corti, E., "Model-Based Combustion Control to Reduce the Brake Specific Fuel Consumption and Pollutant Emissions under Real Driving Maneuvers,"https://doi.org/10.4271/03-17-01-0007.
Additional Details
Publisher
Published
Aug 18, 2023
Product Code
03-17-01-0007
Content Type
Journal Article
Language
English