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Robustness Analysis of Dual Actuator EGR Controllers in Marine Two-Stroke Diesel Engines

Exhaust Gas Recirculation (EGR) has recently been introduced in large marine two-stroke diesel engines to reduce $NO_x$ emissions. During accelerations, controlling the amount of EGR flow while still keeping good acceleration performance can be quite challenging. The main difficulties to overcome are the delay in the scavenge receiver oxygen measurement and the upper limit in the amount of fuel that can be burned with EGR diluted air without producing black smoke. Previous oxygen feedback controllers struggled during accelerations, but a new approach to EGR control based on adaptive feedforward (AFF) has been tested successfully. Nevertheless, further analysis and tests are required before deploying the new controller to more EGR ships. A simulation platform is a great asset to test the controllers before expensive and time-limited real-world experiments have to be conducted on board of ships. With this purpose, a new EGR flow controller is introduced to track the AFF controller EGR flow setpoint in a complete ship simulation model. Several acceleration scenarios are simulated, and they identify the low load area as the most challenging concerning EGR control performance due to the slower air path engine dynamics. Controller robustness in this low load area against errors in the flow estimates used by the controller is analysed. Pressure sensor bias in the EGR flow estimator is identified as the most critical factor, which could lead to black smoke formation. This issue could be prevented with better sensor calibration or by using a differential pressure sensor in the estimator instead of two absolute pressure sensors. Errors in the parameters of the flow estimators do not affect the performance as much. This is a useful result because, for a newly built engine, the right parameters of the flow estimators might be difficult to obtain.

Lars Eriksson and Xavier Llamas

Journal of Marine Engineering & Technology, Taylor & Francis, 2020

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Last updated: 2021-11-10