Method for estimating SOC of power battery based on anti-outlier robust unscented Kalman filter

Abstract

The invention discloses a method for estimating an SOC of a power battery based on anti-outlier robust unscented Kalman filter, and belongs to the technical field of power batteries. The method comprises the following steps that a state and observation equation of the power battery is designed through the combination of a composite model method and an ampere-hour method, a model equation of the vehicle-mounted battery is determined, and a battery equivalence model is established; model parameters are identified, relevant parameters of the battery model observation equation are identified by means of a recursive least square method, the iteration frequency is identified with the system input amount as continuous excitation, and therefore a final result is converged and tends to be stable; an improved anti-outlier robust unscented Kalman filter algorithm is adopted for estimating the SOC of the battery. By means of the method, a measurement error model is corrected into a normalized contaminated normal distribution model, a posterior probability of the occurrence of outliers is calculated in combination with the Bayesian theorem to serve as a weighting coefficient for the self-adaptive adjustment to measure and predict related variances and gain matrices, and the problem of outlier interference can be effectively solved.

Description

technical field [0001] The invention relates to a method for estimating the SOC of a power battery, in particular to a method for estimating the SOC of a power battery with robust unscented Kalman filtering against outliers, and belongs to the technical field of power batteries. Background technique [0002] In the past, the SOC estimation of the power battery state of charge usually assumes that the measurement noise is a normal random sequence a priori. contains some erroneous observations, which are called outliers in the engineering field. SOC cannot be measured directly, but can only be estimated indirectly by measuring other state quantities of the battery. At this time, if there are outliers in the observed data, it will have a more serious impact on the system, and the accuracy and stability of the filter will be significantly reduced. When there are continuous outliers in patches, it is likely to cause the filter to diverge. Therefore, researching a robust filteri...

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to provide a robust unscented Kalman filtering power battery SOC estimation method against outliers, which combines the normalized contaminated normal distribution model

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