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Physics-Based Exhaust Pressure and Temperature Estimation for Low Pressure EGR Control in Turbocharged Gasoline Engines
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 05, 2016 by SAE International in United States
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Low pressure (LP) and cooled EGR systems are capable of increasing fuel efficiency of turbocharged gasoline engines, however they introduce control challenges. Accurate exhaust pressure modeling is of particular importance for real-time feedforward control of these EGR systems since they operate under low pressure differentials. To provide a solution that does not depend on physical sensors in the exhaust and also does not require extensive calibration, a coupled temperature and pressure physics-based model is proposed. The exhaust pipe is split into two different lumped sections based on flow conditions in order to calculate turbine-outlet pressure, which is the driving force for LP-EGR. The temperature model uses the turbine-outlet temperature as an input, which is known through existing engine control models, to determine heat transfer losses through the exhaust. Temperature output is used in the pressure model to estimate pressure losses in the two sections of the pipe starting from post-catalyst (ambient) conditions. Experimental data is used to calibrate a total of six parameters in the pressure and steady-state temperature models. Transient experiments are utilized to calibrate the dynamic behavior of the temperature model, which is captured by a low-pass filter to reduce computational effort. A turbocharged gasoline engine, equipped with a LP-EGR loop, is used for real-time transient validation of the coupled model. The newly presented model demonstrates an absolute pressure prediction error of less than 1 kPa with mean error of 0.15 kPa and standard deviation of 0.13 kPa over the validation range.
CitationSiokos, K., Koli, R., Prucka, R., Schwanke, J. et al., "Physics-Based Exhaust Pressure and Temperature Estimation for Low Pressure EGR Control in Turbocharged Gasoline Engines," SAE Technical Paper 2016-01-0575, 2016, https://doi.org/10.4271/2016-01-0575.
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