In this paper, a model-based boost pressure control of a turbocharged common-rail directed injected diesel engine is proposed. An advanced linear parameter varying (LPV) technique is adopted for model development and an H∞ control scheme is synthesized for control purposes. The LPV technique has an advantage in deriving a linear model from a complex non-linear system and guarantees higher linear model precision. The boost pressure model of the diesel engine is obtained as a simple second-order linear system and the parameters of the model are estimated by the LPV identification method. With the help of the LPV modelling method, the behaviour of boost pressure of the diesel engine is precisely characterized using a second-order linear model. Based on the simplified LPV boost pressure model, a robust H∞ controller is synthesized. The state-space representation is derived to follow the control design framework of an H∞ scheme, and weighting functions for improving control performance are added into the closed-loop control system. The experimental results show that the LPV model-based diesel engine boost pressure control allows better tracking performance than the production engine management system (EMS), which requires difficult calibration work.
GuzzellaL.AmstutzA.Control of diesel engines. IEEE Control System Mag., 1998, 18(5), 53–71.
2.
KaoM.MoskwaJ. J.Turbocharged diesel engine modeling for nonlinear engine control and state estimation. Trans. ASME, J. Dynamic Systems, Measmt Control, 1995, 117, 20–30.
3.
LarsenM.KokotovicP. V.Passivation design for a turbocharged diesel engine model. In Proceedings of the 37th IEEE Conference on Decision and control, 16–18 December 1998, vol. 2, pp. 1535–1540.
4.
KolmanovskyI.MoraualP.van NieuwstadtM.StepfanopoulouA. G.Issues in modeling and control of intake flow in variable geometry turbocharged engines. In Proceedings of the 18th IFIP Conference on System modeling and optimization, 1997, p. 436.
5.
KolmanovskyI.SunJ.DruzhininaM.Charge control for direct injection spark ignition engines with EGR. In Proceedings of the American Control Conference, June 2000, vol. 1, no. 6, pp. 34–38.
6.
van NieuwstadtM.KolmanovskyI.MoraualP.StepfanopoulouA. G.EGR-VGT control schemes: experimental comparison for high-speed diesel engine. IEEE Control System Mag., 2000, 20(3), 63–79.
7.
StotskyA.KolmanovskyI, Application of input estimation techniques to charge estimation and control in automotive engines. Control Engng Practice, 2002, 10(12), 1371–1383.
8.
StepfanopoulouA. G.Multivariable design limitations for advanced technology automotive powertrains. In Proceedings of the American Control Conference, June 2000, vol. 5, pp. 3006–3007.
9.
StepfanopoulouA. G.StorsetO. F.SmithR.Pressure and temperature-based adaptive observer of air charge for turbocharged diesel engines. Int. J. Robust Nonlinear Control, 2004, 14(6), 543–560.
10.
StorsetO. F.Air charge estimation for turbocharged diesel engines. In Proceedings of the American Control Conference, June 2000, vol. 1, pp. 39–44.
11.
AmstutzA.ReL. D.Ego sensor based robust output control of EGR in diesel engines. IEEE Trans. Control Systems Technol., 1995, 3(1), 39–48.
12.
FilipiZ.WangY.AssanisD.Variable geometry turbine(VGT) strategies for improving diesel engine in-vehicle response: a simulation study. Int. J. Heavy Vehicle Systems, 2004, 11(3), 303–326.
13.
WuB.FilipiZ.AssanisD.KramerD. M.Using artificial neural networks for representing the air flow rate through a 2.4 liter VVT engine. SAE paper 2004-01-3054, 2004.
14.
RajamaniR.Control of a variable-geometry turbocharged and wastegated diesel engine. Proc. IMechE, Part D: J. Automobile Engineering, 2005, 219(D11), 1361–1368.
15.
GreplR.LeeB.Modeling, parameter estimation and nonlinear control of automotive electronic throttle using a rapid-control prototyping technique. Int. J. Automot. Technol., 2010, 11(4), 601–610.
16.
ShammaJ. S.AthansM.Analysis of gain scheduled control for nonlinear plants. IEEE Trans. on Autom. Control, 1990, 35(8), 898–907.
17.
ShammaJ. S.AthansM.Gain scheduling: potential hazards and possible remedies. IEEE Control Systems Mag., 1992, 12(3), 101–107.
18.
ShammaJ. S.Gain-scheduling missile autopilot design using linear parameter varying transformations. J. Guidance, Control Dynamics, 1993, 16(2), 256–263.
19.
RughW. J.Analytical framework for gain scheduling. IEEE Control System Mag., 1991, 11(1), 79–82.
20.
RughW. J.ShammaJ. S.Research on gain scheduling. Automatica, 2000, 36(10), 1401–1425.
21.
LawrenceD. A.RughW. J.Input–output pseudolinearization for nonlinear systems. IEEE Trans. on Automatic Control, 1994, 39(11), 2207–2218.
22.
FujimoriA.LjungL.Model identification of linear parameter varying aircraft systems. Proc. IMechE, Part G: J. Aerospace Engineering, 2006, 220(G4), 337–346.
23.
KarimiH. R.Parameter-dependent adaptive H∞ control design for a class of linear parameter-varying systems using polynomially parameter-dependent quadratic functions. Proc. IMechE, Part I: J. Systems and Control Engineering, 2007, 221(I4), 589–600.
24.
NatesanK.GuD.-W.PostlethwaiteI.Design of linear parameter varying trajectory tracking controllers for an unmanned air vehicle. Proc. IMechE, Part G: J. Aerospace Engineering, 2010, 224(G4), 395–402.
25.
JungM.Mean-value modeling and robust control of the air path of a turbocharged diesel engine. PhD Dissertation, University of Cambridge, 2003.
26.
MohammadpourJ.GrigoriadisK.FranchekM.WangY.HaskaraI.LPV decoupling and input shaping for control of diesel engines. In Proceedings of the American Control Conference, 30 June–2 July 2010, pp. 1477–1482.
27.
WeiX.Del ReL.On persistent excitation for parameter estimation of quasi-LPV systems and its application in modeling of diesel engine torque. In Proceedings of the 14th IFAC Symposium on System identification, 29–31 March 2006, vol. 14, no. 1, pp. 517–522,.
28.
LiuL.WeiX.ZhuT.Quasi-LPV gain scheduling control for the air path system of diesel engines. In Proceedings of the Control and Decision Conference, China, 2–4 July 2008, pp. 4893–4898.
29.
SalcedoJ. V.MartinezM.LPV identification of a turbocharged diesel engine. Appl. Numer. Mathematics, 2008, 58(10), 1553–1571.
30.
ChungN.Nonlinear dynamic modeling of common-rail direct injection diesel engines for control applications. PhD Dissertation, Hanyang University, Seoul, Republic of Korea, 2005.
31.
HeywoodJ. B.Internal combustion engine fundamentals, 1988 (McGraw-Hill, New York).
32.
GuzzllaL.OnderC. H.Introduction to modeling and control of internal combustion engine system, 2004 (Springer).
33.
BamiehB.GiarreL.Identification for a general class of LPV models. In Proceedings of the 11th IFAC Symposium on System identification, 2000.
34.
BamiehB.GiarreL.Identification of linear parameter varying models. In Proceedings of the 38th IEEE Conference, 2002, vol. 2, pp. 1505–1510.
35.
WeiX.Del ReL.Gain scheduled H∞ control for air path systems of diesel engines using LPV techniques. IEEE Trans. Control Systems Technol., 2007, 15(3), 406–415.
36.
HuJ.BohnC.WuH.Systematic H∞ weighting function selection and its application to the real-time control of a vertical take-off aircraft. Control Engng Practice, 2000, 8(3), 241–252.
37.
BeavenR. W.WrightM. T.SeawardD. R.Weighting function selection in the H∞ design process. Control Engng Practice, 1996, 4(5), 625–633.
38.
ZhouK.DoyleJ.Essentials of robust control, 1998 (Prentice-Hall, Englewood Cliffs, New Jersey).
