Transient exhaust gas improvement by adaptive neural network |
| |
| Institution: | 1. Osaka City University Graduate School, Osaka, Japan;2. Osaka City University, 3-3-138, Sugimoto, Sumiyoshi-ku, 558, Osaka, Japan;3. Matsushita Electric Industrial Co., Ltd., 3-1-1, Yakumonakamachi, Moriguchi, 570, Osaka, Japan;1. Department of Mechanical Engineering, Pontifical Catholic University of Parana, Curitiba, Brazil;2. Department of Electrical Engineering, Federal University of Parana, Curitiba, Brazil;3. Department of Mechanical Engineering, Federal University of Parana, Curitiba, Brazil;4. Industrial and Systems Engineering Graduate Program (PPGEPS), Pontifical Catholic University of Parana, Curitiba, Brazil;5. CORIA-UMR6614, Normadie Université, CNRS, INSA et Université de Rouen, 76800 Saint Etienne du Rouvray, France;1. Laboratory of Thermodynamics and Energy Systems, Faculty of Physics, University of Science and Technology Houari Boumediene, BP 32 Bab Ezzouar, 16111, Algiers, Algeria;2. GEPEA, UMR 6144 DSEE, IMT Atlantique, 44307, Nantes, France;1. Department of Electromechanical Engineering, University of Macau, Macau, PR China;2. Department of Computer and Information Science, University of Macau, Macau, PR China |
| |
| Abstract: | Three-way catalyzer (TWC) is the most common exhaust gas treatment device for gasoline engines. A/F must be, however, kept within very narrow range. The conventional engine control system can maintain this by OZ feedback in a steady state, but not in a transient state. To overcome this, feed-forward control was provided using the neural network (NN) which is suitable to nonlinear behavior. Moreover, the NN has an adaptive ability by providing an on-line backpropagation loop, so that it can deal with different characteristics of same-type engines, aging in the same engine, and so on. In the experiments, relatively good results were obtained. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
