چکیده مقاله
The electrical power subsystem EPS is one of the most mission critical subsystems in low Earth orbit LEO small satellites because it supports power generation, energy storage, voltage regulation, power distribution, and load availability Conventional Failure Mode and Effects Analysis FMEA is widely used during early reliability assessment, but its static scoring structure is not fully suitable for satellite missions where battery degradation, eclipse cycles, thermal conditions, load profiles, and detection confidence vary over time This paper proposes a dynamic FMEA framework for satellite EPS risk assessment by integrating conventional FMEA logic with Long Short Term Memory LSTM based battery prognostics Real lithium ion battery aging data from the NASA Ames Prognostics Center of Excellence PCoE dataset are used as the reference data source for degradation sensitive indicators such as discharge capacity, voltage response, temperature behavior, and state of health SOH The predicted battery SOH is mapped into a time varying occurrence score, while prediction error is mapped into a time varying detection score Therefore, the Risk Priority Number RPN is updated dynamically instead of remaining fixed after design review A representative LEO small satellite EPS architecture is considered, including solar arrays, a maximum power point tracking unit, a rechargeable battery pack, a power conditioning and distribution unit, DC DC converters, protection circuits, and telemetry sensors The proposed framework links battery degradation prediction to system level operational responses such as enhanced telemetry monitoring, payload duty cycle reduction, load shedding, battery protection, and safe mode transition The method provides a practical bridge between data driven prognostics and systems engineering based risk management for early phase satellite design and mission operation planning
کلیدواژهها
نویسندگان
مصطفی محمد علی نژاد
۱ Master’s Student of Satellite Technology Engineering, Iran University of Science and Technology
Mahdi Nasiri Sarvi
۲- Assistant Professor, Satellite Technology Engineering Department, Iran University of Science and Technology
Mahdi Nasiri Sarvi
۲ Assistant Professor, Satellite Technology Engineering Department, Iran University of Science and Technology
شیوه ارجاع
Ali Nezhad, Mostafa Mohammad and Nasiri Sarvi, Mahdi,1405,Dynamic FMEA and LSTM-Based Prognostics for Electrical Power Subsystems of LEO Small Satellites Using Real Battery Aging Data,31th National Conference on Electrical, Computer and Mechanical Engineering,Shirvan
ارائهشده در
مجموعه مقالات سی و یکمین کنفرانس ملی مهندسی برق، کامپیوتر و مکانیک30 تیر 1405 · شیروان