*3.3. Method Used to Diagnose Battery Fault*

Figure 9 illustrates the proposed battery fault diagnosis algorithm.

The fault diagnosis algorithm considers two situations. After the battery information is sensed through the BMS and the battery efficiency is evaluated regarding whether the value corresponds to the over range, charging proceeds. If the battery efficiency is not higher than the over range, the charge-discharge process is performed; however, if the battery efficiency is higher than the over range and the battery SoH is 40% or less, the charge-discharge process is terminated.

This over range value changes depending on the battery state, battery type, and other factors, and this value should be set before the operation. In this paper, the fault state was set when the efficiency was below 80% and the SoH was below 40%.

Although the battery's charge-discharge SoC is used correctly at 0–100% for the ESS, in this paper, the SoC was charged at 20–80%, the optimal operation region for lithium-ion batteries from a safety viewpoint. Furthermore, the SoH was subjected to charge-discharge cycles up to the maximum region of the battery. Charging was terminated based on the experimental requirements and safety considerations—when the SoH reached 40% or less—to confirm the disposal of the battery through a signal.

**Figure 9.** Proposed fault diagnosis algorithm.

The BMS senses the final output values of Equations (1) and (9), then a chargedischarge termination signal is transmitted through CAN communication if the value is within the over range. The paper predicted the correct battery state through BMS and diagnosed the fault using the proposed method during the charge-discharge process to propose a BMS algorithm for an ESS that uses a large battery capacity.
