I am developing a Simulink battery model to estimate state of health of a battery using MATLAB/Simulink. I want to use a Extended Kalman Filter for the model, but in one article I read that a Adaptive Extended Kalman Filter gives better estimates. I can also use Unscented Kalman Filter but rather I want to know about Adaptive Extended Kalman Filter.

Also the basic idea to simulate state of health of battery by using simulink model is by estimating the growth in its Internal Ohmic Resistance with Increase in temperature which results in aging process of battery (both Cycle aging and Calender aging). So the EKF or AEKF will perform online parameter estimation to determine this Internal Resistance. So based on priori estimates ,how come exactly this internal resistance given by online parameter estimation , what exactly will the recursive algorithm in this case will happen, i need bit clarification.

Can anyone clarify what basically is the difference between Adaptive Extended Kalman Filter and Extended Kalman Filter? How does exactly Adaptive Extended Kalman Filter works.


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