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Volumn 20, Issue 4, 2012, Pages 397-407

Operating regime based dynamic engine modelling

Author keywords

Dynamic modelling; Engine modelling; Internal combustion engines; Neural network models; Optimal experiment design; System identification

Indexed keywords

DYNAMIC MODELLING; ENGINE MODELLING; INTERNAL COMBUSTION; OPTIMAL EXPERIMENT DESIGN; SYSTEM IDENTIFICATIONS;

EID: 84857194707     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.conengprac.2011.10.003     Document Type: Article
Times cited : (20)

References (28)
  • 2
    • 85072459337 scopus 로고    scopus 로고
    • Dynamic model-based calibration optimization: An introduction and application to diesel engines
    • In SAE 2005 world congress and exhibition. Session: Electronic engine controls (Parts 1 and 2 of 8), Detroit, MI, USA, April.
    • Atkinson, C., & Mott, G. (2005). Dynamic model-based calibration optimization: An introduction and application to diesel engines. In SAE 2005 world congress and exhibition. Session: Electronic engine controls (Parts 1 and 2 of 8), Detroit, MI, USA, April.
    • (2005)
    • Atkinson, C.1    Mott, G.2
  • 5
    • 0031130380 scopus 로고    scopus 로고
    • Local model networks for nonlinear system identification
    • In IEE colloquium on industrial applications of intelligent control (Digest No: 1997/144), May.
    • Brown, M., Lightbody, G., & Irwin, G. (1997). Local model networks for nonlinear system identification. In IEE colloquium on industrial applications of intelligent control (Digest No: 1997/144) (pp. 4/1-4/3), May.
    • (1997)
    • Brown, M.1    Lightbody, G.2    Irwin, G.3
  • 6
    • 84857195147 scopus 로고    scopus 로고
    • Online dynamic black box modelling and adaptive experiment design in combustion engine calibration
    • In IFAC-symposium advances in automotive control, July.
    • Deflorian, M., Kloepper, F., & Rueckert, J. (2010). Online dynamic black box modelling and adaptive experiment design in combustion engine calibration. In IFAC-symposium advances in automotive control, July.
    • (2010)
    • Deflorian, M.1    Kloepper, F.2    Rueckert, J.3
  • 7
    • 53649102529 scopus 로고    scopus 로고
    • Dynamic calibration of fuelling in the PFI SI engine
    • Dickinson P., Shenton A. Dynamic calibration of fuelling in the PFI SI engine. Control Engineering Practice 2009, 17(1):26-38.
    • (2009) Control Engineering Practice , vol.17 , Issue.1 , pp. 26-38
    • Dickinson, P.1    Shenton, A.2
  • 8
    • 34548605410 scopus 로고    scopus 로고
    • Local model network identification with Gaussian processes
    • Gregorcic G., Lightbody G. Local model network identification with Gaussian processes. IEEE Transactions on Neural Networks 2007, 18(5):1404-1423.
    • (2007) IEEE Transactions on Neural Networks , vol.18 , Issue.5 , pp. 1404-1423
    • Gregorcic, G.1    Lightbody, G.2
  • 10
    • 46449098102 scopus 로고    scopus 로고
    • Neuro-fuzzy modelling using a logistic discriminant tree
    • In American control conference, 2007. ACC '07, July.
    • Hametner, C., & Jakubek, S. (2007). Neuro-fuzzy modelling using a logistic discriminant tree. In American control conference, 2007. ACC '07 (pp. 864-869), July.
    • (2007) , pp. 864-869
    • Hametner, C.1    Jakubek, S.2
  • 11
    • 74549201001 scopus 로고    scopus 로고
    • Optimisation of relative error criteria in nonlinear neuro-fuzzy identification
    • In MS 2009, 20th IASTED international conference on modelling and simulation, July.
    • Hametner, C., & Jakubek, S. (2009). Optimisation of relative error criteria in nonlinear neuro-fuzzy identification. In MS 2009, 20th IASTED international conference on modelling and simulation, July.
    • (2009)
    • Hametner, C.1    Jakubek, S.2
  • 14
    • 0029247140 scopus 로고
    • Identification of non-linear system structure and parameters using regime decomposition
    • Johansen T.A., Foss B.A. Identification of non-linear system structure and parameters using regime decomposition. Automatica 1995, 31(2):321-326.
    • (1995) Automatica , vol.31 , Issue.2 , pp. 321-326
    • Johansen, T.A.1    Foss, B.A.2
  • 15
    • 79961019705 scopus 로고    scopus 로고
    • Perspectives on system identification
    • In Proceedings of the 17th IFAC world congress.
    • Ljung, L. (2008). Perspectives on system identification. In Proceedings of the 17th IFAC world congress.
    • (2008)
    • Ljung, L.1
  • 16
    • 70449637954 scopus 로고    scopus 로고
    • Diesel engine emissions prediction using parallel neural networks
    • In American control conference, 2009. ACC '09, June.
    • Maass, B., Stobart, R., & Deng, J. (2009). Diesel engine emissions prediction using parallel neural networks. In American control conference, 2009. ACC '09 (pp. 1122-1127), June.
    • (2009) , pp. 1122-1127
    • Maass, B.1    Stobart, R.2    Deng, J.3
  • 17
    • 79952072065 scopus 로고    scopus 로고
    • Modeling and control of the air system of a turbocharged gasoline engine
    • Moulin P., Chauvin J. Modeling and control of the air system of a turbocharged gasoline engine. Control Engineering Practice 2011, 19(3):287-297.
    • (2011) Control Engineering Practice , vol.19 , Issue.3 , pp. 287-297
    • Moulin, P.1    Chauvin, J.2
  • 19
    • 84883526149 scopus 로고    scopus 로고
    • Global dynamic models for XiL-based calibration
    • In SAE 2010 world congress and exhibition. Session: Engine control and calibration (Parts 1 of 2), Detroit, MI, USA, April.
    • Nebel, M., Vogels, M.-S., Combe, T., Pfluegl, H., Winsel, T., & Hametner, C. (2010). Global dynamic models for XiL-based calibration. In SAE 2010 world congress and exhibition. Session: Engine control and calibration (Parts 1 of 2), Detroit, MI, USA, April.
    • (2010)
    • Nebel, M.1    Vogels, M.-S.2    Combe, T.3    Pfluegl, H.4    Winsel, T.5    Hametner, C.6
  • 21
    • 0035249923 scopus 로고    scopus 로고
    • NNSYSID and NNCTRL tools for system identification and control with neural networks
    • Norgaard M., Ravn O., Poulsen N. NNSYSID and NNCTRL tools for system identification and control with neural networks. Computing & Control Engineering Journal 2001, 12(1):29-36.
    • (2001) Computing & Control Engineering Journal , vol.12 , Issue.1 , pp. 29-36
    • Norgaard, M.1    Ravn, O.2    Poulsen, N.3
  • 23
    • 0010242173 scopus 로고
    • Smooth hinging hyperplanes-An alternative to neural networks
    • Pucar P., Millnert M. Smooth hinging hyperplanes-An alternative to neural networks. Proceedings of the 3rd ECC 1995.
    • (1995) Proceedings of the 3rd ECC
    • Pucar, P.1    Millnert, M.2
  • 24
    • 26944497186 scopus 로고    scopus 로고
    • Perspectives of fuzzy systems and control
    • (40th Anniversary of Fuzzy Sets)
    • Sala A., Guerra T.M., Babuska R. Perspectives of fuzzy systems and control. Fuzzy Sets and Systems 2005, 156(3):432-444. (40th Anniversary of Fuzzy Sets).
    • (2005) Fuzzy Sets and Systems , vol.156 , Issue.3 , pp. 432-444
    • Sala, A.1    Guerra, T.M.2    Babuska, R.3
  • 26
    • 85072504834 scopus 로고    scopus 로고
    • Automated model-based GDI engine calibration adaptive online DoE approach
    • In SAE 2005 world congress and exhibition. Session: Direct injection SI engine technology (Part A), Detroit, MI, USA, March.
    • Stuhler, H., Kruse, T., Stuber, A., Gschweitl, K., Piock, W., Pfluegl, H., et al. (2002). Automated model-based GDI engine calibration adaptive online DoE approach. In SAE 2005 world congress and exhibition. Session: Direct injection SI engine technology (Part A), Detroit, MI, USA, March.
    • (2002)
    • Stuhler, H.1    Kruse, T.2    Stuber, A.3    Gschweitl, K.4    Piock, W.5    Pfluegl, H.6
  • 28
    • 84857195389 scopus 로고    scopus 로고
    • iLinkRT high performance ECU calibration
    • ATZ elektronik, February.
    • Vogels, M. S., Heindl, A., Krenn, M., Leithgoeb, R., & Heppner, B., 2008. iLinkRT high performance ECU calibration. ATZ elektronik, February.
    • (2008)
    • Vogels, M.S.1    Heindl, A.2    Krenn, M.3    Leithgoeb, R.4    Heppner, B.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.