Paper Info
Title
On-Board map learning-based combustion phase control in spark ignition engines
Abstract
The combustion phase control is a significant research topic in spark ignition (SI) engines since it affects the fuel efficiency, combustion variability and knocking. Managing the combustion phase, which can be set in the crank angle of 50% mass burnt (CA50), at the optimal reference value where the maximal thermal efficiency can be obtained is challenging due to the engine transient operation, the cyclic variability of combustion process and the optimal operation point drift caused by engine aging, fuel quality, etc. This research addresses this problem in two loops: an outer loop providing the optimal CA50 reference (CA50*) and an inner loop tracking CA50* by managing the spark advance (SA). CA50* is obtained by looking up a 3-dimensional map that can be updated by the stochastic gradient-based on-board map learning algorithm. Then a SA feedforward-feedback controller is designed to track CA50*. The closed loop is of benefit to the fast response of transient operation condition and the on-board learning loop compensates the map drift. Experimental validations of the proposed scheme have been carried out on a six-cylinder SI gasoline engine test bench at transient operation mode.
Year
DOI
Venue
2017
10.1109/CCTA.2017.8062477
2017 IEEE Conference on Control Technology and Applications (CCTA)
Keywords
Field
DocType
closed loop,six-cylinder SI gasoline engine test bench,transient operation mode,combustion phase control,spark ignition engines,fuel efficiency,combustion variability,engine transient operation,combustion process,fuel quality,optimal CA50 reference,spark advance,SA feedforward-feedback controller,thermal efficiency,on-board map learning,inner loop tracking,stochastic gradient
Inner loop,Combustion,Ignition timing,Ignition system,Automotive engineering,Spark (mathematics),Thermal efficiency,Simulation,Petrol engine,Homogeneous charge compression ignition,Engineering
Conference
ISBN
Citations 
PageRank 
978-1-5090-2183-3
0
0.34
References 
Authors
3
2
Name
Order
Citations
PageRank
Yahui Zhang112.46
Tielong Shen224340.52