Prognostic Reasoner based adaptive power management system for a more electric aircraft

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dc.contributor.authorSebastian, Robin Kuttikkadan
dc.contributor.authorPerinpanayagam, Suresh
dc.contributor.authorJennions, Ian K.
dc.contributor.authorAlghassi, Alireza
dc.date.accessioned2017-01-13T12:43:04Z
dc.date.available2017-01-13T12:43:04Z
dc.date.issued2016-09-05
dc.description.abstractThis 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.A hybrid mathematical model based on the Direct-Quadrature (d-q) axis transformation of the generator have been formulated for studying various structural and parametric faults. 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 were 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 developeden_UK
dc.identifier.citationSebastian RK, Peripinayagam S, Jennions IK, Alghassi A. Prognostic Reasoner based adaptive power management system for a more electric aircraft. 2016 Annual Conference of the Prognostics and Health Management Society, 2-8 October 2016, Denver, Colorado, USAen_UK
dc.identifier.urihttp://www.phmsociety.org/node/2154/
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/11272
dc.language.isoenen_UK
dc.publisherPrognostics and Health Management Societyen_UK
dc.rightsAttribution 3.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/
dc.subjectPHMen_UK
dc.subjectEPGSen_UK
dc.subjectPower Manageenten_UK
dc.subjectMEAen_UK
dc.subjectAEAen_UK
dc.titlePrognostic Reasoner based adaptive power management system for a more electric aircraften_UK
dc.typeConference paperen_UK

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