Estimation strategies for state of charge and state of power of lithium-ion batteries

This chapter aims to improve the characterization accuracy of battery performance parameters and mainly conducts the construction optimization and experimental verification of battery state estimation methods from four aspects. (1) Analyze the characteristics of lithium-ion batteries and construct experiments under different working conditions for verification. (2) The full parameter online identification method of real-time tracking data is constructed to improve the accuracy of lithium-ion battery parameter identification. The improved algorithm has higher accuracy and the voltage simulation error is lower than 0.04 V. (3) An online Square Root Unscented Kalman algorithm based on temperature correction is designed to achieve high-precision and high-adaptability tracking analysis of SOC (state of charge). The SOC simulation error of the improved algorithm is less than 2.36%. (4) An online SOP (state of power) estimation method based on multi-limiting factor fusion analysis is designed to reduce the computational applicability and improve the credibility of the algorithm, the SOP estimation error is less than 68.7 W.