Development of an energy-efficient battery management system

Battery Management Systems (BMS) plays a key role in the recent energy storage systems which are intended for a longer life span, safety, and better performance metrics which are crucial for modern electric vehicle applications. Better evaluation and estimation of the state-of-X (SOX) characteristics of a battery stack namely the state-of-charge (SOC), state-of-power (SOP) and the state-of-health (SOH) are vital for ensuring the life of a battery management system. The critical metrics of state-of-X (SOX) characteristics of a battery stack is essential for predictive and maintenance control thereby preventing any thermal runaway conditions and for enhancing the efficacy of the battery stack system. This paper offers a framework model for state-of-X (SOX) characteristics of a battery stack specifically designed for lithium-ion batteries. The validation of the proposed methodology is done by computational methods and also verified using the real-time data using hardware implementation of the model and the outcomes of the same as been evaluated and presented.