Abstract
In electric vehicles (EVs), the online state-of-health (SOH) estimation is a challenging issue because of the unpredictable load behavior and the limited computational resources. In this study, a novel online SOH estimation algorithm for EVs is proposed based on the compression ratio of open circuit voltage (OCV)-to-charged capacity curve. The OCV-to-charged capacity curve has a clear correlation with the capacity degradation to be compressed with the same ratio of SOH, and this correlation is verified using five battery cells at the different aging states. The proposed algorithm estimates the degraded capacity at every sampling time during the driving operation through a first-order low-pass filter, which does not require complex mathematical tools and numerous offline data. For the robustness to the system noise in EVs, the estimated capacities are fed into a recursive average filter, and the SOH is updated to the output value of the average filter after sufficient driving operation. The experimental verifications were performed using five battery cells with different aging states, and these results represent the robustness and superiority of the proposed algorithm.
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