LSTM-based Temperature-Compensated LFP Battery State Monitoring System for Future Aviation Mobility

Key Points

• The research aims to enhance the stability and reliability of battery systems for aviation mobility by proposing a novel estimation algorithm.
• Developed a hybrid thermal management structure based on heat sinks and thermal conductors.
• Proposed an LSTM-based estimation algorithm for State of Charge (SOC) and State of Health (SOH).
• Utilized voltage, current, temperature, and cumulative charge for SOC estimation.
• Incorporated predicted SOC values with existing variables for SOH estimation.
• The proposed LSTM-based algorithm demonstrated stable SOC and SOH estimation across various degradation levels.
• Simulation results confirmed the effectiveness of the introduced algorithm in managing battery performance.

Abstract