Cylinder pressure or heat release rate tracking algorithms for direct-injected compression ignition engines allow to account for various disturbances, such as changes in the fuel characteristics or the effects of engine wear. They are suited for flex-fuel engines and allow the use of multi-injection strategies; hence, they show potential for mobile applications. However, they are based on the assumption that the heat release rate or cylinder pressure correlates well with engine efficiency and emissions and therefore allows a clean and efficient engine operation. With the objective to evaluate the potential of such tracking algorithms, this assumption is investigated for conventional as well as for low-temperature combustion strategies with diesel as fuel of choice. Based on experimental data, exploratory data analysis methods are applied to evaluate how sensitive engine efficiency and emissions are to changes of the heat release rate or cylinder pressure. Furthermore, an extended tracking algorithm is proposed, which can be applied for premixed charge compression ignition combustion concepts.
StillerBHensleyRHirschbergCSchaufussPTschiesnerAVenusAWerraJ.Reboost—a comprehensive view on the changing powertrain component market and how suppliers can succeed. Technical report. McKinsey & Company, 2019.
3.
KalghatgiG.Is it really the end of internal combustion engines and petroleum in transport?Appl Energ2018; 225: 965–974.
4.
ReitzRDOgawaHPayriRFanslerTKokjohnSMoriyoshiY, et al. IJER editorial: the future of the internal combustion engine. Int J Eng Res2020; 21(1): 3–10.
5.
SrivastavaDKAgarwalAKDattaAMauryaRK.Advances in internal combustion engine research. Singapore: Springer, 2018.
6.
PachiannanTZhongWRajkumarSHeZLengXWangQ.A literature review of fuel effects on performance and emission characteristics of low-temperature combustion strategies. Appl Energ2019; 251: 113380.
AgarwalAKSinghAPMauryaRK.Evolution, challenges and path forward for low temperature combustion engines. Prog Energ Combust2017; 61: 1–56.
9.
TunestalPWilcuttsMLeeATHedrickJK. In-cylinder measurement for engine cold-start control. In: Proceedings of the 1999 IEEE international conference on control applications (Cat. No.99ch36328), vol. 1, Kohala Coast, HI, 22–27 August 1999, pp.460–464. New York: IEEE.
10.
DraperCSLiYT.Principles of optimalizing control systems and an application to the internal combustion engine. New York: American Society of Mechanical Engineers, 1951.
11.
HubbardMDobsonPDPowellJD.Closed loop control of spark advance using a cylinder pressure sensor. J Dyn Syst: T ASME1976; 98(4): 414–420.
TschanzFZentnerSÖzatayEOnderCHGuzzellaL.Cascaded multivariable control of the combustion in diesel engines. IFAC Proc Vol2012; 45(30): 25–32.
14.
DrewsPAlbinTHeßelerFJPetersNAbelD.Fuel-efficient model-based optimal MIMO control for PCCI engines. IFAC Proc Vol2011; 44(1): 12998–13003.
15.
YuSSongHHMinKChoiHChoSHanK. Development of engine control using the in-cylinder pressure signal in a high speed direct injection diesel engine. SAE technical paper 2011-01-1418, 2011.
16.
MohanBYangWChouSK.Fuel injection strategies for performance improvement and emissions reduction in compression ignition engines—a review. Renew Sust Energ Rev2013; 28: 664–676.
17.
ParkCBuschS.The influence of pilot injection on high-temperature ignition processes and early flame structure in a high-speed direct injection diesel engine. Int J Eng Res2018; 19(6): 668–681.
18.
PayriRGimenoJMartí-AldaravíPVieraA.Measurements of the mass allocation for multiple injection strategies using the rate of injection and momentum flux signals. Int J Eng Res. Epub ahead of print 6 January 2020. DOI: 10.1177/1468087419894854.
19.
LuoXDonkersMCDe JagerBWillemsF.Multi-pulse fuel injection controller design using a quadratic model. In: 2016 IEEE conference on control applications (CCA), Buenos Aires, Argentina, 19–22 September 2016, pp.305–310. New York: IEEE.
20.
ZweigelRThelenFAbelDAlbin RajasinghamT. Iterative learning approach for diesel combustion control using injection rate shaping. In: 2015 European control conference (ECC), Linz, Austria, 16–17 July 2015, pp.3168–3173. Institute of Electrical and Electronics Engineers Inc.
21.
JörgCSchnorbusTJarvisSNeavesBBandilaKNeumannD.Feedforward control approach for digital combustion rate shaping realizing predefined combustion processes. SAE Int J Eng2015; 8(3): 1041–1054.
22.
NeumannDMuthyalaPFrenkenCSchaubJJörgCKötterM.Flex-fuel capability via advanced digital combustion rate shaping and airpath control. In: LieblJBeidlCMausW (eds) Internationaler Motorenkongress 2019. Wiesbaden: Springer Fachmedien Wiesbaden, 2019, pp.333–350.
23.
MartinezWLMartinezAR.Exploratory data analysis with MATLAB®. 2nd ed.Boca Raton, FL: Taylor & Francis, 2011.
24.
RunklerTA.Data analytics: models and algorithms for intelligent data analysis. 2nd ed.Wiesbaden: Springer Fachmedien Wiesbaden, 2016.
25.
ArthurDVassilvitskiiS. k-means++: the advantages of careful seeding. In: Proceedings of the eighteenth annual ACM-SIAM symposium on discrete algorithms, New Orleans, Louisiana, 7–9 January 2007, pp.1027–1035. Philadelphia, PA: Society for Industrial and Applied Mathematics.
26.
SzékelyGJRizzoMLBakirovNK.Measuring and testing dependence by correlation of distances. Ann Stat2007; 35(6): 2769–2794.
27.
AnderssonMJohanssonBHultqvistANoehreC. A predictive real time NOx model for conventional and partially premixed diesel combustion. SAE technical paper 2006-01-3329, 2006.
28.
ErikssonLSivertssonM.Calculation of optimal heat release rates under constrained conditions. SAE Int J Eng2016; 9(2): 1143–1162.
GuzzellaLOnderCH.Introduction to modeling and control of internal combustion engine systems. Berlin, Heidelberg: Springer, 2010.
31.
WolfRS.Proof, logic, and conjecture: the mathematician’s toolbox. Gordonsville, VA: W.H. Freeman & Co Ltd, 2008.
32.
HartmanP.Ordinary differential equations. 2nd ed.Philadelphia, PA: Society for Industrial and Applied Mathematics, 2002.
33.
PischingerRKlellMSamsT. (2002). Thermodynamik der Verbrennungskraftmaschine. In Thermodynamik der Verbrennungskraftmaschine. Springer Vienna, 2002, https://doi.org/10.1007/978-3-7091-3826-7
