Motion-Specific Battery Health Assessment for Quadrotors Using High-Fidelity Battery Models

TL;DR

This paper introduces a comprehensive framework for assessing battery health in quadrotors by capturing motion-specific current profiles and using high-fidelity models to understand how different flight motions impact battery degradation pathways.

Contribution

It presents a novel end-to-end system combining real-time current sensing and high-fidelity battery modeling to analyze motion-induced degradation in quadrotor batteries.

Findings

Different flight motions cause distinct degradation modes.

Transient load structures significantly influence battery aging.

Motion-aware management can optimize battery lifespan.

Abstract

Quadrotor endurance is ultimately limited by battery behavior, yet most energy aware planning treats the battery as a simple energy reservoir and overlooks how flight motions induce dynamic current loads that accelerate battery degradation. This work presents an end to end framework for motion aware battery health assessment in quadrotors. We first design a wide range current sensing module to capture motion specific current profiles during real flights, preserving transient features. In parallel, a high fidelity battery model is calibrated using reference performance tests and a metaheuristic based on a degradation coupled electrochemical model.By simulating measured flight loads in the calibrated model, we systematically resolve how different flight motions translate into degradation modes loss of lithium inventory and loss of active material as well as internal side reactions. The results demonstrate that even when two flight profiles consume the same average energy, their transient load structures can drive different degradation pathways, emphasizing the need for motion-aware battery management that balances efficiency with battery degradation.