The Effect of Alternative Fuel on the On-Board Diagnostics System at Compression-Ignition (Diesel) Combustion Engines
Keywords:
alternative fuel, exhaust gas emission, on-board diagnostics OBD, readiness codeAbstract
The aim of our study was to monitor the alterations of the on-board diagnostics (OBD) system of compression-ignition combustion engines, when alternative fuels were used as a source of energy. We described a theory of emissions formation, diagnostics of standards defects of diesel engines and the formation of opacity. We also focused on processing and evaluation of readiness code, which is used to control various functions of the engine. Diesel fuel and alternative fuel were used for realized measurements in accordance with selected methodology. By means of measurements, we detected conditions of readinesscode and the coefficient values of light absorption factors of exhaust gases. Compared to the reference fuel, we detected no alterations in readinesscode, when we monitored the impact of fuel on the on-board diagnostics system. The components controlled by on-board diagnostics system (complex components, fuel system, exhaust gas recirculation) operate with the alternative fuel without detected defects of conditions.
References
Thring, R., Homogeneous-charge compression-ignition engines, SAE Paper 892068, 1989
Mizuta, J., Sato, Y., Aoyama, T., Hattori, Y., An experimental study on premixed charge compression ignition gasoline engine, International Congress & Exposition, Detroit, MI, USA, SAE Paper 960081, 1996
Johansson, R., Tunestal, P., Bengtsson, J., Strandh, P., Johansson, B., Model predictive control of homogeneous charge compression ignition (HCCI) engine Dynamics. Proc. IEEE International Conference on Control Applications, 2006
Bechtold, R., Epping, K., Aceves, S., Dec, J., The potential of HCCI combustion for high efficiency and low emissions, SAE Powertrain & Fluid Systems Conference & Exhibition, SAE Technical Paper 2002-01-1923, San Diego, CA, 2002
Abd-Alla, G. H., Using exhaust gas recirculation in internal combustion engines: a review, Energy Conversion and Management, 2002, 43, 1027-1042
Johansson, B., Christensen, M., Einewall, P., Homogeneous charge compression ignition using iso-octane, ethanol and natural gas – a comparison to spark ignition operation, International Fuels & Lubricants Meeting & Exposition, Tulsa, OK, USA, SAE Paper 972874, 1997
Chiang, C., Chen, C. Constrained control of homogeneous charge compression ignition (HCCI) engines. Proc. 5th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2010.
Liao, H. H. Jungkunz, A. F., Chang, C. F. Park, S., Ravi, N., Roelle, M. J., Gerdes, J. C., Model-based control of HCCI engines using exhaust recompression. Proc. IEEE Transactions on Control Systems Technology, 2010
Wang, Z., Shuai, S., J., Wang, J. X., Tian, G. H., A computational study of direct injection gasoline HCCI engine with secondary injection, Fuel, 2006, 85, 1831-1841
Kong, S. C., A study of natural gas/DME combustion in HCCI engines using CFD with detailed chemical kinetics, Fuel, 2007, 86 1483-1489
Zheng, Z., Yao, M., Charge stratification to control HCCI: experiments and CFD modeling with n-heptane as fuel, Fuel, 2009, 88, 354-365
Yao, M., Zheng, Z., Liu, H., Progress and recent trends in homogeneous charge compression ignition (HCCI) engines, Progress in Energy and Combustion Science, 2009, 35, 398-437
Shaver, G. M., Gerdes, J. C., Roelle, M. J., Physics-based modeling and control of residual-affected HCCI engines, Journal of Dynamic Systems, Measurement, and Control, 2009, 131, 021002.
S-EKA, 2011. Vznetové motory so systémom palubnej diagnostiky (D-OBD). Home page address:
http://cs.autolexicon.net/articles/cdi-common-rail- diesel-injection/.
Methodical instruction, 2006. Methodical instruction laying down the technical requirements for instruments used in emission control of motor vehicles. File: 11552 - 2100/06, Bratislava
de Kleer, J., Williams, J. B. Diagnosing multiple faults, Artificial Intelligence, 1987, 32, 1, 97-130
Reiter, R., A theory of diagnosis from first principles, Artificial Intelligence, 1987, 32, 1, 57-95
Dvorak, D. L., Kuipers, B., Model-based monitoring of dynamic systems, Proc. IJCAI-89, Detroit, MI, 1989, pp. 1238-1243
Poole, D. Normality and faults in logic-based diagnosis, Proc. IJCAI-89, Detroit, MI, 1989, pp. 1129-1135
Guckenbiehl, T., Schäfer-Richter, G., Sidia, A., Extending prediction based diagnosis to dynamic models, Proc. First International Workshop on Principles of Diagnosis, Stanford, CA, 1990, pp. 74-82
Lackinger, F., Nejdl, W., Integrating model-based monitoring and diagnosis of complex dynamic systems, Proc. IJCAI-91, Sydney, Australia, 1991, pp. 2893-2898
Friedrich, G., Lackinger, F., Diagnosing temporal misbehaviour, Proc. IJCAI-91, Sydney, Australia, 1991, pp. 1116-1122
Hamscher, W., Modeling digital circuits for troubleshooting, Artificial Intelligence, 1991, 51, 1–3, 223-271
Ng, H. T., Model-based, multiple-fault diagnosis of dynamic, continuous physical devices, IEEE Expert, 1991, 6, 6, 38-43
Dressler, O., Freitag, F., Prediction sharing across time and contexts, Proc. AAAI-94, Seattle, WA, 1994, pp. 1136-1141
Struss, P., Fundamentals of model-based diagnosis of dynamic systems, Proc. IJCAI-97, Nagoya, Japan, 1997, pp. 480-485
Brusoni, V., Console, L., Terenziani, P., Theseider Dupré, D., A spectrum of definitions for temporal model-based diagnosis, Artificial Intelligence, 1998, 102, 1, 39-80.