The invention discloses a battery
hysteresis voltage characteristic and rebound
voltage characteristic-based
extended Kalman filter SOC
estimation method. The method comprises the following steps of (1), collecting parameter information such as a
voltage, a current, a historical SOC, an accumulated charging / discharging frequency N and the like in a current state; (2), building a three-order RC
equivalent circuit model of a battery based on a
hysteresis voltage characteristic and a rebound voltage characteristic of the battery; (3), establishing an SOC state equation based on an improved
ampere-hour integration method; (4), based on the established state equation and an observation equation, continuously correcting an SOC value at a current moment according to an extended Kalman
recursion principle, thereby enabling an estimated value to be gradually close to a real value; and (5), when an SOC error is smaller than 2%, ending an extended Kalman
recursion process of the SOC. According to the scheme, the shortcomings that an
open circuit voltage method cannot perform online
estimation and an
ampere-hour integration method has current error accumulation are overcome; the
estimation precision of the battery SOC is improved; and online estimation of the battery SOC is realized.