Estimation method of state of charge of battery system on the basis of Unscented Kalman Filter

Abstract

The present invention discloses an estimation method of state of charge of a battery system on the basis of Unscented Kalman Filter. The battery system is a M*N type battery system, namely, M battery monomers are connected in series to be a battery string and then N battery strings are connected in parallel to be the battery system. The estimation method provided by the invention comprises the following steps: establishing a battery system equivalent circuit model based on the battery state of charge; building a battery system spatial state equation through combination of the battery state of charge implication; estimating the state of charge of the battery system through adoption of the Unscented Kalman Filter; and updating the gain matrix of the unscented kalman filter according to the output voltage of an on-line detection battery system and a estimated voltage value, and obtaining an new estimated value of battery state of charge through the cycling recursion like this. Compared with the Extended Kalman Filter algorithm, the estimation method of state of charge of a battery system on the basis of Unscented Kalman Filter is more accurate, has better robustness, is applicable to a battery system, and is also applicable to a battery monomer.

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 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 frequency) and...

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Problems solved by technology

[0004] The problem to be solved by the present invention is to provide a battery system state of charge estimation method based on Unscented Kalman Filter (UKF), which solves the problem that the performance parameters of the battery system are affected by the SOC, and the extended Kalman filter method has complex calculations and low precision. This 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 battery system

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