Abstarct: Industrial batteries have a variety of applications and are of great importance in various industries. This thesis first explores the importance of monitoring the status of the industrial battery (BMS). Subsequently, the components and overall infrastructure of a battery status monitoring system are reviewed and the differences between the battery monitoring system and the UPS monitoring system are noted, but battery monitoring systems can not estimate and predict battery faults. In this thesis, three electrical modeling protocols are first expressed in industrial batteries, then a fault vector is applied at a particular moment to the internal resistance of the battery model and added to the input. Changes in internal resistance cause a fault in the battery. This test is repeated in different states in terms of the number of fault vector, quantity, and also the disturbance at the input. The effect of the disturbance signal on the input is also investigated. To detect a battery fault, was used by Lüneburger observer and LO observer. Finally, the results of the LO observer function are displayed on a nonlinear system and the benefits of using this observer to identify the fault are expressed.