High-capacity battery system charge state estimation method based on unscented Kalman filter

Abstract

The invention discloses a high-capacity battery system charge state estimation method based on unscented Kalman filter. A high-capacity battery system is an M*N battery system, wherein M individual batteries are connected in series to form a battery string, and N battery strings are connected in parallel to form the high-capacity battery system. The method comprises the steps that a high-capacity battery system equivalent circuit model based on a battery charge state is established; the battery charge state meaning is combined, and a battery system space state equation is established; unscented Kalman filter is used to carry out charge state estimation on the battery system; the output voltage of the battery system and a voltage estimation value are detected online to update an unscented Kalman filter gain matrix; and recurrence is carried out to acquire a new battery charge state estimation value. According to the invention, a high-capacity battery system charge state estimation algorithm is more accurate and robust than an extended Kalman filter algorithm, and the method is applicable to the battery system and individual batteries.

Description

technical field [0001] The invention belongs to the technical field of design and control of a MW-level battery energy storage system in a smart grid, and relates to a method for estimating the state of charge of a large-capacity battery system based on an unscented Kalman filter. Background technique [0002] With the vigorous development of renewable energy such as wind power and photovoltaic power generation and the intelligentization of power grids, battery systems, as the main carrier of energy storage in battery energy storage systems, have attracted more and more attention and applications from all over the world. At the same time, the continuous expansion of renewable energy scale and the rapid growth of electricity load will also promote the development of battery systems in the direction of large capacity (MW level). However, due to the complexity of the application environment (such as second-level fluctuating power smoothing, high-frequency occasions such as high...

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Problems solved by technology

[0004] The problem to be solved by the present invention is to provide a method for estimating the state of charge of a large-capacity battery system based on Unscented Kalman Filter (UKF), which solves the problem that the performance parameters of a large-capacity battery system are affected by the SOC and the calculation of the extended Kalman filter method is complicated. , The low accuracy leads to the problem that the SOC of the battery system is difficult to be accurately measured and estimated, so as to achieve the purpose of accurately estimating the SOC of the large-capacity battery system

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