Evaluation and Parameterization of a Control Software Development-Oriented Real-Time Engine Model for Medium Speed Dual-Fuel Engine
Rikkonen, Viktor (2017)
Rikkonen, Viktor
2017
Automaatiotekniikka
Teknisten tieteiden tiedekunta - Faculty of Engineering Sciences
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Hyväksymispäivämäärä
2017-04-05
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201703221203
https://urn.fi/URN:NBN:fi:tty-201703221203
Tiivistelmä
Increasing engine performance requirements and demanding markets pose challenges for engine manufacturers, which has led to more complex control systems. Engine control software development is expensive and time consuming process especially in marine industry. Engine modeling and rapid prototyping are proposed to shorten control system development cycles. Model in the loop simulation can be used to test control system functionality. For this purpose, a zero dimensional mean value engine model is parameterized for a Wärtsilä 6 cylinder medium speed four stroke dual fuel engine.
Before parameterization, dual fuel engine operating cycle and combustion process are reviewed in order to model the processes based on physical phenomena. The Combustion Model is the most complex of all the modeled systems. Other systems of the mean value engine model are Engine Model that covers air flow through the engine, Gas System that models fuel gas admission, Fuel System that is in charge of diesel fuel injection, Lube Oil System that simulates heat transfer to lubricating oil and Cooling Water Circuit that handles engine and charge air cooling. These systems are modeled to a varying degree of accuracy. The equations used to model the components of each system are presented. Instrument and start air systems of the engine are not modeled.
The engine model is made with Matlab/Simulink. In order to test the control system against the model and ensure their compatibility, control inputs used to influence the plant model and measurement outputs for control system feedback are processed. Test run on the actual engine is made to collect reference data of the engine’s performance. Measured data is used to parameterize the engine model via simulation on development computer. The model is then discretized for real time simulation. During real time simulation on target computer, engine controllers are parameterized to get realistic response.
Engine model accuracy is validated by comparing steady-state performance and transient response of the model against measured engine data. Analysis of the results confirms that engine model accuracy is sufficient for control system functionality testing. However, the accuracy is not enough for control system calibration. Due to adequate accuracy, realistic cause and effect relationships between different engine systems and real time simulation capabilities, the engine model can be used for rapid prototyping based control system development.
Before parameterization, dual fuel engine operating cycle and combustion process are reviewed in order to model the processes based on physical phenomena. The Combustion Model is the most complex of all the modeled systems. Other systems of the mean value engine model are Engine Model that covers air flow through the engine, Gas System that models fuel gas admission, Fuel System that is in charge of diesel fuel injection, Lube Oil System that simulates heat transfer to lubricating oil and Cooling Water Circuit that handles engine and charge air cooling. These systems are modeled to a varying degree of accuracy. The equations used to model the components of each system are presented. Instrument and start air systems of the engine are not modeled.
The engine model is made with Matlab/Simulink. In order to test the control system against the model and ensure their compatibility, control inputs used to influence the plant model and measurement outputs for control system feedback are processed. Test run on the actual engine is made to collect reference data of the engine’s performance. Measured data is used to parameterize the engine model via simulation on development computer. The model is then discretized for real time simulation. During real time simulation on target computer, engine controllers are parameterized to get realistic response.
Engine model accuracy is validated by comparing steady-state performance and transient response of the model against measured engine data. Analysis of the results confirms that engine model accuracy is sufficient for control system functionality testing. However, the accuracy is not enough for control system calibration. Due to adequate accuracy, realistic cause and effect relationships between different engine systems and real time simulation capabilities, the engine model can be used for rapid prototyping based control system development.