Smart Instrument for Automotive Battery Application

The battery management system (BMS) for charge and health monitoring has always been a challenge for automotive industry. This paper presents the design and development of an intelligent online battery monitoring instrument. The instrument is designed using non-linear behavior modeling of the battery and is implemented using PIC micro controller coupled with battery parameter sensors. The instrument takes battery terminal voltage, current drawn, internal resistance, temperature and time as input parameters. Algorithms define uses neuro-fuzzy approach to indicate state of charge (SoC) of the battery. The prototype of the instrument has been tested successfully on 12V Lead-Acid battery, Exide make MF40sv used for automotive application. The average error (RSS) of the instrument is 8.7921% and the total response time of the system is 4.8 seconds.