A novel safety anticipation estimation method for the aerial lithium-ion battery pack based on the real-time detection and filtering

Lithium-ion battery packs have become increasingly important for power supply applications, in which the state of charge estimation and output voltage tracking should be very critical for the safety protection. A novel real-time estimation method is proposed by using the improved extended Kalman filtering algorithm together with the two-order resistance and capacitance circuit network battery model, aiming to solve its security protection issues. Experimental results show that this method can track the voltage signals effectively along with the real-time state estimation in the discharging and charging maintenance operation processes. The battery cell voltage detection accuracy is found to be 1.00 mV and the pack voltage measurement error is less than 20.00 mV. Meanwhile, the state of charge value can be estimated with a great accuracy of 2.00%, in which the state of balance parameter is considered for the internal connected battery cells. The developed experimental associated battery management system can be used for the working state monitoring in the aerial power supply application of the lithium-ion battery pack.