Method and device for estimating SOC value of battery, vehicle and storage medium

Abstract

The invention discloses a method and a device for estimating the SOC value of a battery, a medium and a vehicle. The method comprises the steps of: building a battery model which employs a second-order RC equivalent circuit model; determining battery characteristic parameters according to the second-order RC equivalent circuit model, obtaining a state equation and an observation equation of self-adaptive square root volume Kalman filtering according to the battery characteristic parameters, taking the battery SOC value in the second-order RC equivalent circuit model and the voltage values on two RC networks as state variables, taking the terminal current value of the battery as an input variable, and taking the terminal voltage value of the battery as an observed quantity; and estimating the SOC value of the battery by adopting an adaptive square root volume Kalman filtering method according to the state equation and the observation equation. According to the method for estimating theSOC value of a battery, the divergence phenomenon generated by error iteration is reduced through a self-adaptive square root volume Kalman filtering method, the filtering effect is improved, and theSOC value estimation precision is improved.

Description

technical field [0001] The invention relates to the field of vehicle manufacturing, in particular to a method for estimating a battery SOC value, a device for estimating a battery SOC value, a vehicle, and a computer-readable storage medium. Background technique [0002] With the promotion of new energy vehicles by national policies, the sales of new energy vehicles have increased year by year, and electric drive vehicles have received more and more attention. State of Charge (SOC) evaluation is one of the most important functions in the power battery management system. Many functional decisions in the system are evaluated based on the remaining power, such as cruising range, charge and discharge management, battery life, etc. , so improving the SOC estimation accuracy is of great significance for battery management. [0003] Common methods for SOC value evaluation include the classic ampere-hour integration method, charge accumulation method, open circuit voltage method, a...

AI Technical Summary

Problems solved by technology

When using the Kalman filter to estimate the SOC value of the power battery, the known and zero-mean white noise is used as the given noise value, but in practice, the external interference is usually unknown, and the difference between the given noise value and the real value There is a deviation between them. Since the Kalman algorithm is an iterative cycle that continuously estimates the value at the next moment based on the previous value, the error will gradually increase with continuous iterations, resulting in divergence and reducing the accuracy of SOC value estimation.

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