Engine torque imbalance is a wide-ranging problem which is caused due to variance of the combustion mixture in the engine cylinder. In this research work, cyclic torque imbalance detection is carried out by formulating a uniform second-order sliding mode observer using the First Principle–based Engine Model. Oscillations in the crankshaft angular speed were modeled in the novel First Principle–based Engine Model, which were suppressed in the Mean Value Engine Models. Cyclic torque imbalance is simulated at multiple instances by varying the injected fuel mass. Estimation of the net piston force is carried out for cyclic torque imbalance detection using rotational dynamics of the engine model. This force is treated as unknown input to the torque production subsystem of the model. Cyclic torque imbalance detection is validated using the GT-Power engine model. Variations in the cyclic torque were detected proximate to actual values which demonstrated validity of the proposed technique.
HeywoodJB.Internal combustion engine fundamentals, vol. 930. New York: McGraw-Hill, 1988.
2.
OzdorNDulgerMSherE.An experimental study of the cyclic variability in spark ignition engines. SAE technical paper 960611, 1996.
3.
SchollDRussS. Air-fuel ratio dependence of random and deterministic cyclic variability in a spark-ignited engine. SAE technical paper 1999-01-3513, 1999.
4.
SenAKZhengJHuangZ.Dynamics of cycle-to-cycle variations in a natural gas direct-injection spark-ignition engine. Appl Energ2011; 88: 2324–2334.
5.
ManzieCWatsonHCBakerP. Modeling the effects of combustion variability for application to idle speed control in SI engines. SAE technical paper 2002-01-2734, 2002.
6.
WenigMGrillMBargendeM.A new approach for modeling cycle-to-cycle variations within the framework of a real working-process simulation. SAE Int J Engine2013; 6: 1099–1115.
7.
SjericMKozaracDTaritasI. Experimentally supported modeling of cycle-to-cycle variations of SI engine using cycle-simulation model. SAE technical paper 2014-01-1069, 2014.
8.
SuyabodhaAPennycottABraceCJ.A preliminary approach to simulating cyclic variability in a port fuel injection spark ignition engine. Proc IMechE, Part D: J Automobile Engineering2013; 227: 665–674.
9.
ChenYWangYRaineR.Correlation between cycle-by-cycle variation, burning rate, and knock: a statistical study from PFI and DISI engines. Fuel2017; 206: 210–218.
10.
MeyerJ.Calibration reduction in internal combustion engine fueling control: modeling, estimation and stability robustness. PhD Thesis, The Ohio State University, Columbia, OH, 2011.
11.
SaxénJEHyvämäkiTBjörkqvistJ, et al. Power balancing of internal combustion engines—a time and frequency domain analysis. IFAC Proc Vol2014; 47: 10802–10807.
12.
AliSASaraswatiS.Cycle-by-cycle estimation of cylinder pressure and indicated torque waveform using crankshaft speed fluctuations. T I Meas Control2015; 37: 813–825.
13.
MoroDCavinaNPontiF.In-cylinder pressure reconstruction based on instantaneous engine speed signal. J Eng Gas Turb Power2002; 124: 220–225.
14.
CavinaNPontiFRizzoniG. Fast algorithm for on-board torque estimation. SAE technical paper 1999-01-0541, 1999.
15.
SchagerbergSMcKelveyT.Instantaneous crankshaft torque measurements—modeling and validation. SAE technical paper 2003-01-0713, 2003.
16.
LeeBRizzoniGGuezennecY, et al. Engine control using torque estimation. SAE technical paper 2001-01-0995, 2001.
17.
SaraswatiSChandS.Reconstruction of cylinder pressure for SI engine using recurrent neural network. Neural Comput Appl2010; 19: 935–944.
18.
NaJChenASHerrmannG, et al. Vehicle engine torque estimation via unknown input observer and adaptive parameter estimation. IEEE T Veh Technol2018; 67: 409–422.
19.
Al-DurraA.Adaptive sliding mode observer for engine cylinder pressure imbalance under different parameter uncertainties. IEEE Access2014; 2: 1085–1091.
20.
HaskaraIMianzoL.Real-time cylinder pressure and indicated torque estimation via second order sliding modes. In: Proceedings of the 2001 American control conference, Arlington, VA, 25–27 June 2001, vol. 5, pp.3324–3328. New York: IEEE.
21.
KangMAlamirMShenT.Nonlinear constrained torque control for gasoline engines. IFAC PapersOnLine2016; 49: 784–789.
22.
AnjumRBhattiAIYarA, et al. Cyclic torque imbalance detection in gasoline engines using second order sliding mode. In: Proceedings of the 2nd IEEE conference on control technology and application, Copenhagen, 21–24 August 2018. New York: IEEE.
23.
YarABhattiAAhmedQ.First principle-based control oriented model of a gasoline engine. J Dynam Syst Meas Control2017; 139: 051002.
24.
YarABhattiAAhmedQ.First principle based control oriented gasoline engine model including lumped cylinder dynamics. J Dynam Syst Meas Control2018; 140: 081011.
25.
GuzzellaLOnderC.Introduction to modeling and control of internal combustion engine systems. New York: Springer, 2009.
26.
YarABhattiAIAhmedQ.First principle based control oriented model of a gasoline engine including multi-cylinder dynamics. Control Eng Pract2018; 70: 63–76.
27.
ErikssonLAnderssonI. An analytic model for cylinder pressure in a four stroke SI engine. SAE technical paper 2002-01-0371, 2002.
28.
ErikssonLNielsenL.Modeling and control of engines and drivelines. Hoboken, NJ: John Wiley & Sons, 2014.
29.
CooneyCWormJMichalekD, et al. Wiebe function parameter determination for mass fraction burn calculation in an ethanol-gasoline fuelled SI engine. J KONES Int Combust Eng2008; 15: 567–574.
HendricksESorensonSC.Mean value modelling of spark ignition engines. SAE technical paper 900616, 1990.
32.
JohanssonEWagnborgS.Analysis of engine cold start simulation in GT-power. Master’s Thesis, Department of Applied Mechanics, Division of Combustion, Chalmers University of Technology, Gothenburg, Sweden, 2014.
33.
NilssonMLarssonJ.The potential of increased efficiency and power for a turbocharged PFI-SI engine through variable valve actuation and DEP. Master’s Thesis, Department of Combustion Engines, Faculty of Eengineering, Lund University, Lund, 2015.
34.
SrinivasaBanavathyKSShankaregowda, et al. A novel approach to a two-stroke dual stage expansion engine concept. Master’s Thesis, Department of Applied Mechanics, Chalmers University of Technology, Gothenburg, 2016.
35.
TechnologiesG.GT-Power user manual Version 7.4, 2013. Gamma Technologies.
36.
RichardJP.Time-delay systems: an overview of some recent advances and open problems. Automatica2003; 39: 1667–1694.
37.
LeeKLeeW.State estimation for motorized seat belt system using sliding-mode observer. Int J Auto Technol2015; 16: 301.
38.
AhmedQBhattiAI.Estimating SI engine efficiencies and parameters in second-order sliding modes. IEEE T Ind Electron2011; 58: 4837–4846.
39.
SalehiRVossoughiGAlastyA.A second-order sliding mode observer for fault detection and isolation of turbocharged SI engines. IEEE T Ind Electron2015; 62: 7795–7803.
40.
FridmanLShtesselYEdwardsC, et al. Higher-order sliding-mode observer for state estimation and input reconstruction in nonlinear systems. Int J Robust Nonlin Control2008; 18: 399–412.
41.
FloquetTBarbotJP.Super twisting algorithm-based step-by-step sliding mode observers for nonlinear systems with unknown inputs. Int J Syst Sci2007; 38: 803–815.
42.
DavilaJFridmanLLevantA.Second-order sliding-mode observer for mechanical systems. IEEE T Automat control2005; 50: 1785–1789.
43.
Cruz-ZavalaEMorenoJAFridmanL. Uniform second-order sliding mode observer for mechanical systems. In: Proceedings of the 11th international workshop on variable structure systems (VSS), Mexico City, Mexico, pp.14–19. New York: IEEE.
