Lithium-ion battery disturbance current estimation, with application to a self-balancing photovoltaic battery storage system

This paper develops a model-based algorithm for combined state and disturbance estimation in a lithium-ion battery cell. The 'disturbance', in this context, is the external current applied to the cell. The algorithm estimates this current based solely on terminal voltage measurement, which is valuable for applications where current sensors are too costly. Furthermore, the paper presents a theoretical analysis of the disturbance estimation covariance achievable by this algorithm. The algorithm is particularly valuable for applications where estimates of battery current are needed, but measurements of this current are too costly. One example comes from the authors' previous work on a self-balancing hybrid photovoltaic/battery system. We apply the proposed algorithm, in simulation, to this system, and use a moving average filter to attenuate the noise in its disturbance current estimates. The results of this simulation study show that the proposed algorithm is indeed successful in tracking both the internal battery state and photovoltaic current in the above hybrid photovoltaic/battery system.