OPEN ACCESS
Common rail systems are conventionally employed in diesel and gasoline engines. Pressure, precision and velocity are key factors for correct engine power management. Current systems are based on digital computers and PID control systems. When anomalies occur, recovery strategies are used and engine performance is significantly reduced. Then technical assistance is required to restore normal condition. For safety reasons this approach cannot be used in aeronautical, naval and energy-supply applications. In some cases it is necessary to utilize all the possible energy from the power unit causing significant life-reduction of the engine. In this case a progressive reduction strategy should be used and injection law should be reduced accordingly. For this purpose injection control based on fuzzy logic is more effective . In this case, traditional PID control systems are substituted by fuzzy logic control. A reference map is introduced in the Full Authority Digital Electronic Control, this map is interpreted by the fuzzy logic control system that adapts the injection law to the current engine situation. For example, if fuel temperature tends to increase over the normal level, injection pressure is reduced by the fuzzy control system and injection time is increased to obtain the maximum possible power output. This approach can be easily implemented with very simple and effective fuzzy logic controllers. This method has been experimented on a common-rail test bed and results are compared with traditional “binary recovery strategy” FADEC. Maximum power output is slightly reduced since fuzzy controllers are less effective than PID in “near reference” conditions. However, when anomalies take place or are simply beginning to appear the fuzzy FADEC behaviour is more effective and preserves engine performance more effectively. Aim of this paper it to define rules and fuzzy controllers to optimize the performance of a diesel engine in various operating conditions with particular attention to the power output.
[1] W. KEMMETMÜLLER, F. FUCHSHUMER, A. KUGI, “Nonlinear pressure control of self-supplied variable displacement axial piston pumps”, Control Engineering Practice, Volume 18, Issue 1, January 2010, Pages 84-93.
[2] R.E. BELLMAN and L.A. ZADEH, "Local and fuzzy logics," in Modern Uses of Multiple-Valued Logic, J. M. Dunn and G. Epstein, Eds., Dordrecht, The Netherlands: D. Reidel Publishing Co., 1977, pp. 103-165.
[3] L.A. ZADEH, “Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers of Lotfi A. Zadeh”, G. J. Klir and B. Yuan, Eds., Advances in Fuzzy Systems -- Applications and Theory, Vol. 6, River Edge, NJ: World Scientific, 1996.
[4] E.H. MAMDANI, “Application of Fuzzy Logic to approximate reasoning using linguistic synthesis”: Department of Electrical and Electronic Engineering, Queen Mary College, University of London, London, 1976.
[5] E.H. MAMDANI, “Application of Fuzzy Algorithms for the Control of a Dynamic Plant”, Proc. IEE, 121, pp. 1585-1588, Dec. 1974.
[6] D. DUBOIS and H. PRADE, “Decision Making under fuzziness”, in M.M. Gupta, R.K. Ragade, and R.R. Yager, editors, Advances in fuzzy set theory and applications. North Holland, Amsterdam, 1979.
[7] A. DONNARUMMA, “Disegno di macchine”, Utet, 1986
[8] PEREIRA, John, “A comparison of PID and Fuzzy Control of a model car: Electrical and Computer Engineering”, University of South Carolina, Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on, 26-29 June 1994.
[9] KÄLLSTRÖM, Johan, “Embedded software for new engine controller”, Department of Electrical Engineering, Sweden, 2001.
[10] LEE, S.H.; HOWLETT, R.J.; WALTERS S.D., “Intelligent Systems & Signal Processing Laboratories”, Engineering Research Centre, University of Brighton, Moulsecoomb, Brighton, Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, Volume 18 Issue 1, January 2007.
[11] HOLZMANN, H.; HALFMANN Ch.; ISERMANN R.. “Representation of 3-D Mappings for Automotive Control Applications using Neural Networks and Fuzzy Logic”, IEEE Conference on Control Applications Proceedings, pp. 229-234, 1997.
[12] BASTIAN, Andreas, “Modeling Fuel Injection Control Maps Using Fuzzy Logic”, Laboratory for International Fuzzy Engineering Research (LIFE), Siber Hegner Bldg. 4F1., 89-1 Yamashita-cho, Naka-ku, Yokohama, 231 Japan, 1994.
[13] BIDAN, P.; BOVERIE, S., “Nonlinear control of a spark-ignition engine”, IEEE Transactions on Control Systems Technology, Vol.3, No.1, 1995, pp.4-13.
[14] V. K., Jones; B. A., Ault; G. F., Franklin and J. D. Powell,” Identification and air-fuel ratio control of a spark ignition engine”, IEEE Transactions on Control Systems Technology, Vol.3, No.1, 1995, pp.14-21.
[15] AMSTUTZ, A.; Del Re, L. R., EGO, “Sensor based robust output control of EGR in diesel engines”, IEEE Transactions on Control Systems Technology, Vol.3, No.1, 1995, pp.39-48. [16] ABATE, Maurizio; DOLSI, Norberto, “Use fuzzy logic for engine idle speed control”, SAE 900594, 1990, pp.873-880.