  Fault diagnosis is extremely important to the safe operation of Lithium-ion
batteries. To avoid severe safety issues (e.g., thermal runaway), initial
faults should be timely detected and resolved. In this paper, we consider
parallel-connected battery cells with only one voltage and one current sensor.
The lack of independent current sensors makes it difficult to detect individual
cell degradation. To this end, based on the high-frequency response of the
battery, a simplified fault detection-oriented model is derived and validated
by a physics-informed battery model. The resistance of the battery string,
which is significantly influenced by the faulty cell, is estimated and used as
the health indicator. The statistical resistance distribution of battery
strings is first analyzed considering the distribution of fresh and aged cells.
A fault diagnosis algorithm is proposed and the thresholds (i.e., 2 standard
deviation interval) are obtained through statistical analysis. Monte Carlo
simulation results show that the proposed fault diagnosis algorithm can balance
false alarms and missed detections well. In addition, it is verified that the
proposed algorithm is robust to the uniform parameter changes of individual
battery cells.
