The invention discloses an anti-disturbance parameterization method for a battery
equivalent circuit model. The method comprises the following steps: S1, establishing the
equivalent circuit model of the battery, determining parameters of a model to be identified, and determining a relational expression of a
state of charge (SOC) and an open-circuit
voltage (OCV) through fitting; S2, carrying out real-time acquisition on the load current and the
terminal voltage at the moment k; S3, calculating the SOC of the battery at the moment k, and calculating an OCV value; S4, establishing a discrete domain regression equation for
model parameter identification, and updating
model parameters online by adopting a recursive least square method (RLS); S5, constructing a tool vector constraint condition,calculating a
current noise variance at the moment k on line, and further calculating a
voltage noise variance at the moment k according to a FrischScheme method; and S6, correcting the RLS result inthe step S4 according to the estimated values of the current and
voltage variances to obtain an unbiased
model parameter vector at the moment k. According to the method, current and voltage measurement
noise statistical characteristics can be estimated on line, so that model identification deviation in a
noise interference environment is compensated, and unbiased
model parameter identification isrealized.