ICUAS'23 Paper Abstract

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Paper ThA3.4

An, Di (University of California - Merced), Krzysiak, Rafal (University of California - Merced), Hollenbeck, Derek (University of California - Merced), Chen, YangQuan (University of California - Merced)

Battery-Health-Aware UAV Mission Planning Using a Cognitive Battery Management System

Scheduled for presentation during the Regular Session "Path Planning III" (ThA3), Thursday, June 8, 2023, 10:00−10:20, Room 464

2023 International Conference on Unmanned Aircraft Systems (ICUAS), June 6-9, 2023, Lazarski University, Warsaw, Poland

This information is tentative and subject to change. Compiled on March 28, 2024

Keywords Path Planning, Perception and Cognition, Energy Efficient UAS

Abstract

Lithium-ion and Lithium Polymer batteries have been widely used in electric and unmanned aircraft vehicles, enabling many applications and developing a highly commercialized and demanding market. Precisely estimating the battery capacity (State of the charge (SOC)) is still a challenging problem due to many limitations. Prior work assessing battery capacity relies more on the battery's internal physical model and less considers surrounding factors, which makes the accuracy of estimation capacity fluctuation under different scenarios. Therefore, we presented a cognitive battery management system to empower intelligence to the battery so that battery can justify the current capacity and whether it would be enough for the mission and safe landing. Our system leverages the battery temperature as the essential factor for estimating the capacity during flight. We evaluated our capacity estimation function parameters using the least squares. Results show that our approach shows the battery temperature significantly affects assessing capacity, which perfectly accomplishes the first step towards a cognitive battery management system.

 

 

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