Design of the Power Management System for Electrical Power Systems in More Electric Engine / Aircraft

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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Engineering and execution challenges in power management system implementation for industrial power systems

2016 Petroleum and Chemical Industry Technical Conference (PCIC) ◽

10.1109/pcicon.2016.7589214 ◽

2016 ◽

Author(s):

Sunita Singh ◽

Dragan Ristanovic ◽

Neeraj Bhatia ◽

Matthew Murray

Keyword(s):

Power Systems ◽

Power Management ◽

Management System ◽

System Implementation ◽

Power Management System

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Study of Decentralized Power Management for Electrical Power Systems in More Electric Aircraft

2020 24th International Conference on Circuits, Systems, Communications and Computers (CSCC) ◽

10.1109/cscc49995.2020.00045 ◽

2020 ◽

Author(s):

Jenica Ileana Corcau ◽

Liviu Dinca

Keyword(s):

Power Systems ◽

Power Management ◽

Electrical Power ◽

Electrical Power Systems ◽

Electric Aircraft ◽

More Electric Aircraft

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Decentralized Power Management for Electrical Power Systems in More Electric Aircrafts

Electronics ◽

10.3390/electronics7090187 ◽

2018 ◽

Vol 7 (9) ◽

pp. 187 ◽

Cited By ~ 7

Author(s):

Myungchin Kim ◽

Sung Lee ◽

Sungwoo Bae

Keyword(s):

Power Systems ◽

Power Management ◽

Electrical Power ◽

Transient State ◽

Cost Effective ◽

Power Sharing ◽

Management Approach ◽

Electrical Power Systems ◽

Power Sources ◽

Virtual Impedance

In order to implement reliable and flexible power management among energy sources, a decentralized power management approach for electrical power systems (EPSs) in the more electric aircraft (MEA) is studied. Considering the increased use of electrical power for various functions, the performance of MEA would be determined by the design and operation of the EPS. By using a virtual impedance that includes both a resistive term and an inductive term, autonomous power sharing is realized. Because of the frequency dependence in the virtual impedance, different power sharing ratios between steady state and transient state can be considered. Not only the operation of various power sources is coordinated without supervision of a centralized controller, but also the operation profile of each source can be adjusted to meet output characteristics of each source. To demonstrate the effectiveness of the proposed approach, a series of simulations that consider various virtual impedance configurations were conducted. The proposed approach contributes to a higher level of operational flexibility, while enabling reliable and cost-effective management of MEAs.

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