Title :
On control of HCCI combustion-neural network approach
Author :
Mirhassani, Mitra ; Chen, Xiang ; Tahmasebi, Ali ; Ahmadi, Majid
Author_Institution :
Dept. of Electr. & Comput. Eng., Windsor Univ., Ont.
Abstract :
Due to environmental consideration and recent regulations on the car emission, new technologies are explored. HCCI engine, thanks to its low NOx emission and high efficiency may be one of the candidate solutions. Therefore, exploration of enhanced HCCI combustion control is of strong interest to both the auto industry and the academic community and of a challenge due to complexities in ignition timing prediction. In this paper, application of a neural network assisted controller for a control-based model of an HCCI combustion engines is explore. The model is updated on-line and is used to predict the ignition timing. Simulation results show that the controller is able to predict the proper inputs to the model and to track the desired peak pressure accurately. Hence a neural-network-based control strategy could be potentially established for HCCI combustion control
Keywords :
automotive components; ignition; internal combustion engines; neurocontrollers; NO; car emission; combustion control; homogeneous charge compression ignition engine; ignition timing prediction; neural network; Adaptive control; Chemicals; Diesel engines; Fuels; Ignition; Internal combustion engines; Kinetic theory; Neural networks; Predictive models; Timing;
Conference_Titel :
Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006 IEEE
Conference_Location :
Munich
Print_ISBN :
0-7803-9797-5
Electronic_ISBN :
0-7803-9797-5
DOI :
10.1109/CACSD-CCA-ISIC.2006.4776892
