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

An unscented Kalman and battery system technology, applied in the direction of measuring electricity, measuring electrical variables, and measuring devices, can solve the problems of difficult SOC of battery systems, performance parameters of large-capacity battery systems affected by SOC, and low accuracy.

Inactive Publication Date: 2015-12-23
YANCHENG INST OF TECH
View PDF3 Cites 22 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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 S

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • High-capacity battery system charge state estimation method based on unscented Kalman filter
  • High-capacity battery system charge state estimation method based on unscented Kalman filter
  • High-capacity battery system charge state estimation method based on unscented Kalman filter

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] The present invention will be further described in detail below in conjunction with specific examples, which are for explanation of the present invention rather than limitation.

[0023] 1. Large-capacity battery system and its equivalent circuit model

[0024] 1.1 Large capacity battery system

[0025]The large-capacity battery system is composed of M battery cells connected in series to form a battery string, and then N batteries connected in series and parallel. Its structure diagram is as follows: figure 1 shown. For the convenience of analysis, in this example, it is assumed that the large-capacity battery system is composed of 12 battery cells connected in series to form a battery string, and then 2 battery strings are connected in parallel, that is, a 12×2 large-capacity battery system, such as figure 2 shown. The rated voltage of each battery cell in the battery system is 3.2V, the rated capacity is 25Ah, and the discharge cut-off voltage is 2.5V.

[0026] ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

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...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G01R31/36
Inventor 彭思敏沈翠凤薛迎成何坚强胡国文阚加荣
Owner YANCHENG INST OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products