Short name
21.1A : Predictive analytics for electric aviation battery systems
Emerging electric aircraft promise to drastically reduce operating costs, but will need to achieve high levels of safety. The present regulatory basis calls for the manufacturer to develop a means of safety assurance and to determine when the energy storage system has reached end of life. This proposal is focused on developing the battery pack analysis methods necessary to accurately determine both state-of-health and early failure indication.
The goal of this project is to leverage Astrolabe’s data collection and analytics capabilities to develop recommended standards for end-of-life determination. Astrolabe will build a prototype analytics solution (comprised of both a software product and services) that can be deployed both for online monitoring during flight, and offline battery system maintenance and prognostics.
We plan to help answer key questions that manufacturers have when designing their battery systems: e.g. how accurate their algorithms are for estimating flight or hover time, estimating whether or not a pack is airworthy for its next mission, and how many such missions a battery system can service before it should be retired.
The goal of this project is to leverage Astrolabe’s data collection and analytics capabilities to develop recommended standards for end-of-life determination. Astrolabe will build a prototype analytics solution (comprised of both a software product and services) that can be deployed both for online monitoring during flight, and offline battery system maintenance and prognostics.
We plan to help answer key questions that manufacturers have when designing their battery systems: e.g. how accurate their algorithms are for estimating flight or hover time, estimating whether or not a pack is airworthy for its next mission, and how many such missions a battery system can service before it should be retired.
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