Probabilistic Voltage Fault Correction Method for Lithium-Ion Batteries Using a Decentralized Cell Voltage Measurement Approach

This article proposes a bias detection method in the voltage measurement of lithium-ion (Li-ion) battery cells to identify faulty sensor(s). The proposed method is based on a Bayesian probabilistic approach that detects possible measurement bias in any battery cell in real-time. A hypothesis bank is constructed for possible bias magnitudes in each cell. Subsequently, the fault detection algorithm computes the probability associated with all hypotheses. Once the probability of a certain hypothesis converges to unity, the faulty sensor and its associated bias are identified. The quantified bias can then be compensated in the measurement model of the associated cell. Details on the proposed method followed by experimental verification using commercial lithium-ion battery datasets are provided.