Current consumption measurements are useful in a wide variety of applications including power monitoring and fault detection within a lithium-ion battery management system (BMS). This measurement is typically taken using either a shunt resistor or a Hall-effect current sensor. This work explores a novel alternative to sensing battery current by measuring terminal voltages and cell temperatures, using an unknown input observer (UIO) to estimate the battery current. An accurate model of a LiFePO4 cell is created, validated, and used to characterize a model of the proposed current estimation technique. A practical model of a LiFePO4 cell was developed which performed similarly to other models in the literature. Using this model, an unknown input observer was developed which attempted to estimate the cell current. The model of the current estimator was used in conjunction with the model of the cell and simulations were conducted, which showed that the current estimator converged toward the true measured current. Another novel study focuses on fault detection based on the interclass correlation coefficient (ICC) method for guaranteeing safe and reliable electric vehicles (EVs). The proposed method calculates ICC values by capturing the off-trend voltage drop and the voltages are extracted from Service and management center of electric vehicles. The ICC value not only has advanced fault resolution by amplifying the voltage difference but also can prolong the fault memory by setting moving windows. Moreover, a loop joints the first and last voltages is designed to locate faults in the battery pack. In addition, simulation and experiment are employed to validate and analyze the voltage faults. The ICC method, which eliminates the voltage sensors noise and inconsistency in batteries, can amplify the fluctuations in the group, and the method can avoid false diagnosis with the battery at different states. In addition, this work collects the real-time voltage data from the service and management center for electric vehicles system (SMCEVS) and the fault detection process on computer center, which not only reduces the computing load for
BMS but also improves safety and reliability. This method has a feasible calculation processing, which does not need to build model and redundant hardware design.