PHM Based Adaptive Power Management System for a More Electric Aircraft



Published Nov 13, 2020
Robin K.Sebastian Suresh Peripinayagam Alireza Alghassi


This research work presents a novel approach that addresses the concept of an adaptive power management system design and development framed in the Prognostics and Health Monitoring(PHM) perspective of an Electrical power Generation and distribution system(EPGS).PHM algorithms were developed to detect the health status of EPGS components which can accurately predict the failures and also able to calculate the Remaining Useful Life(RUL), and in many cases reconfigure for the identified system and subsystem faults. By introducing these approach on Electrical power Management system controller, we are gaining a few minutes lead time to failures with an accurate prediction horizon on critical systems and subsystems components that may introduce catastrophic secondary damages including loss of aircraft. The warning time on critical components and related system reconfiguration must permits safe return to landing as the minimum criteria and would enhance safety. A distributed architecture has been developed for the dynamic power management for electrical distribution system by which all the electrically supplied loads can be effectively controlled. The different failure modes were generated by injecting faults into the electrical power system using a fault injection mechanism. The data captured during these studies have been recorded to form a “Failure Database” for electrical system. A hardware in loop experimental study was carried out to validate the power management algorithm with FPGA-DSP controller. In order to meet the reliability requirements a Tri-redundant electrical power management system based on DSP and FPGA has been developed.

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Ferrell, B. L. (1999), JSF Prognostics and Health Management. Proceedings of IEEE Aerospace Conference. March 6-13, Big Sky, MO. doi: 10.1109/AERO.1999.793190
Schwabacher, M., & Goebel, K. F. (2007). A survey of artificial intelligence for prognostics. Proceedings of AAAI Fall Symposium, November 9–11, Arlington, VA.
Vachtsevanos, G., Lewis, F. L., Roemer, M., Hess, A., & Wu, B. (2006). Intelligent fault diagnosis and prognosis for engineering system. Hoboken, NJ: John Wiley & Sons, Inc.
Felder,J.L., Kim,H. DandBrown,G.V(2009), Turboelectric Distributed Propulsion Engine Cycle Analysis for Hybrid-Wing Body Aircraft,AIAA-2009 1132,presented at 47th AIAA Aerospace sciences meeting,5-8 January 2009.Orlando,Florida,USA.
Rosero, J.A, OrtegaJ.a, Aldabas, E.Romeral, L, (2007), Moving towards a more electric aircraft, Aerospace and Electronic Systems Magazine, IEEE, Vol: 22, Issue: 3, Page (s):3-9.
A.Tantawy and G Biswas, (2008), Aircraft AC Generators: Hybrid system Modelling and Simulation, International Conference on Prognostics and Health Management, IEEE.
Todd D. Batzel and D.C. Swanson, Prognostic Health Management of Aircraft Power Generators, Aerospace and Electronics System, IEEE, Vol.45, No: 2, Page(s) 473-482.
Connally, H.M, Lodge, I, Jackson, R.J and Roberts.I, Detection of Interturn faults in generator rotor windings using airgap search coil, (1985),IEEE page(s),11-15.
Sottile,J,Trutt,F.C,and Leedy,A.W. Condition monitoring of brushless 3-phase synchronous generators with stator winding or rotor circuit deterioration,Industry Applications,IEEE,2001,page(s)1587-1594.
Zouaghi, T, and Poloujadoff. M. Modelling of polyphase brushless exciter behaviour for failing diode operation, IEEE Transactions on Energy Conversion, B, 3(Sept.1998), 214-220.
H.Pan, E.Dong,Y.Jiang,P Zhang A Prognostics and Health Management for Aircraft Electrical Power Supply System, IEEE conference on Prognostics & system health Management PHM-2012.
Aircraft Electrical Power Characteristics, Department of Defence of USA, March 2004.
A.Ginart, I.Barlas, J.L.Dorrity, P.Kalgen and M.J Roemer Self-healing from a PHM perspective, IEEE transactions 2006, page(s) 697-703.
L. Andrade and C. Tenning, Design of the Boeing 777 Electric system, AES Magazine, IEEE, July 1992.
A.A.AbdElhafez and A.J.Forsyth, A review of more-electric aircraft”, in 13th international conference on Aerospace Science and Aviation Technology, ASAT-13, 2009.
D.Schlabe,J.Lienig, Energy Management of aircraft Electrical systems-state of the art and further direction, IEEE proceedings Railway and ship propulsion (ESARS),2012.
X.Xia, and C.P.Lawson, The development of a design methodology for dynamic power distribution management on a civil transport all electric aircraft, Aerospace Science and Technology 25(2013), 125-131.
Procedures for performing failure Mode Effects and criticality Analysis US MIL-STD-1629A, Nov, 1980.
Fitzgerald, A.E, Kingsley.C,and Umans.S.D, Electrical Machinery, (6th ed.)New York McGraw-Hill, 2003.
H.Pan,E.Dong,Y.Jiang,P.Zhang, Prognostic and Health Management for Aircraft Electrical Power Supply system,(2002),IEEE,Prognostics&System Health Management Conference, Beijing.
D.Schlabe and J.Lieneg Energy Management of Aircraft Electrical System-State of the Art and Further Direction In Proc. Electrical Systems for Aircraft, Railway and Ship Propulsion,2012.
J. Joupes, S.Nellis D, Hamblays and M.Peabody, Load distribution and Management System, EP Patent 1,143,593,A1,2001.
Chee Mun Ong, Dynamic Simulation of Electric Machinery by MATLAB Simulink, Prentice Hall PTR.
Schlabe.D, and Zimmer.D , Model based Energy Management Function for Aircraft Electrical System, In Proc. SAE, 2012.
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