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This implementation assumes that the system is a linear dynamical system with Gaussian noise. It uses the state transition matrix A to predict the state at the next time step, and the measurement matrix H to transform the state vector into the measurement space. The Kalman filter then uses the Kalman gain K to correct the predicted state based on the difference between the measured and predicted values.
Additional Link: 47.pdf (stanford.edu)
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Coulomb counting is a method for estimating the remaining charge in a battery. It works by measuring the current flowing into or out of the battery and integrating this value over time to obtain the total charge that has been transferred. This value can then be used to estimate the remaining charge in the battery.
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