A Battery Management System with Charge Balancing and Aging Detection Based on ANN

A battery management system with aging detection based on artificial neural network (ANN) for the state of charge (SOC) balancing is proposed in this paper. The charger adopts a single-inductor multiple-output architecture to achieve charge balancing among different battery cells. In constant current mode, the pulse charging is utilized to improve the charging speed and slow down the aging rate. Moreover, an ANN is proposed to detect the state of health (SOH) of the battery cells and improve the accuracy of the SOC estimation. TSMC 0.35-pm process and TensorFlow are used for simulations. A 94% power efficiency of the charger is achieved. The active area of this design is 1.5 × 1.5 mm². Experimental results show that 0.32% root-mean square errors for the SOC estimation is obtained.