Implementation of Second-Order RC Circuit Charge-Discharge Model Using Kalman Filter

This document discusses battery charge-discharge modeling based on Kalman filter design principles. Through simulation implementation, we establish a second-order RC circuit charge-discharge model to better understand battery operational mechanisms. This model incorporates state-space representation where the Kalman filter algorithm recursively estimates the system states (voltages across RC branches) while accounting for process and measurement noise. The implementation typically involves defining system matrices (A, B, C, D) for the circuit dynamics, implementing prediction and correction steps for real-time state estimation, and tuning covariance matrices for optimal performance. Such models enable accurate prediction of battery lifespan and performance while providing guidance for battery design and optimization. Furthermore, this modeling approach can be extended to other applications such as solar panels and electric vehicle batteries. Therefore, research on battery charge-discharge models holds significant theoretical and practical importance, particularly for developing robust battery management systems with real-time state-of-charge estimation capabilities.