Modern Engine In-Cylinder Pressure Estimation
Nowadays, internal combustion engines are still the main power source for automobiles despite a growing number of greener alternatives, such as electrical motors. In order to fulfil rigorous ecological standards regarding the air pollution, more and more leading automobile manufacturers are investigating advanced internal combustion engines by involving the newest combustion control strategies. Cylinder pressure-based engine combustion control is one of the technologies to enhance the combustion efficiency of the engine, and simultaneously to reduce harmful emissions. In addition, knowledge of cylinder pressure traces can also provide information for both misfire detection and knock detection. Thus obtaining the information of the cylinder pressure signal is of importance for engine optimization and control. As a result, a variety of methods for the cylinder pressure reconstruction have been proposed. However, there still exist several kinds of drawbacks in existing methods.
To reconstruct cylinder pressure in a better way, in my research various methods have been proposed and validated by using experimental data from a four-stroke commercial engine.
- R. Han, C. Bohn, and G. Bauer, “A novel inverse filtering method for systems with multiple input signals,” in Proceedings of 18th International Conference on Control, Automation and Systems, Daegwallyeong, South Korea, 17-20 October 2018, pp. 369-374.
- R. Han, C. Bohn, and G. Bauer, “Recursive engine in-cylinder pressure estimation using Kalman filter and structural vibration signal,” IFACPapersOnLine, vol. 51, no. 31, pp. 700-705, 2018.
- R. Han, C. Bohn, and G. Bauer, “Virtual engine in-cylinder pressure sensor for automobiles and agricultural tractors,” IFACPapersOnLine, vol. 53, no. 1, pp. 543-548, 2020.
- R. Han, C. Bohn, and G. Bauer, “Recursive engine in-cylinder pressure estimation merely using structural vibration signal,” in Proceedings of 2020 European Control Conference, Saint Petersburg, Russia, 12-15 May 2020, pp. 240-245.
- R. Han, C. Bohn, and G. Bauer, “Recursive model-based order tracking filters for solving overlapping and interference problem in rotating machines,” in Proceedings of 2020 IEEE 16th International Conference on Control and Automation, Singapore, Singapore, 9-11 October 2020, pp. 240-246.