A Battery Management System Design Including a SOC Estimation Approach for Lead-Acid Batteries

Storage is one of the most important issues of the last decades. In particular, storage systems are needed in order to benefit more effectively from renewable energy systems where production cannot be controlled. One of the most important problems in storage is that as the amount of energy desired to be stored increases, the need for space also increases. Therefore, it is of great importance to manage energy effectively in such systems. In this study, a battery management system (BMS) that can be used for lead acid batteries has been designed. This BMS has a measurement and control system based on STM 32 microcontroller and is controlled via an interface prepared in the MATLAB Simulink environment and the test data is imported into the MATLAB Workspace environment. The designed system can also perform battery charge-discharge experiments in accordance with the battery characteristics. Charge-discharge experiments were carried out using the designed system, and a model was developed to determine the state of charge (SOC) of the battery using the data collected during these experiments. With the model developed based on Elman Neural Networks, the SOC of battery could be estimated at an error level of less than 1%.