Battery model parameter identification method based on multi-innovation recursive Bayesian algorithm

A Bayesian algorithm and parameter identification technology, applied in the field of lithium-ion batteries, which can solve problems such as large amount of calculation and premature convergence.
CN112526348AActive Publication Date: 2021-03-19NANTONG UNIVERSITY

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
NANTONG UNIVERSITY
Publication Date
2021-03-19

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention provides a battery model parameter identification method based on a multi-innovation recursive Bayesian algorithm. The method comprises the following steps of: 1), measuring the terminalvoltage and load current data of a lithium ion battery in a certain period of time through an intermittent constant-current discharge method, and determining the function relation of an OCV-SOC of the lithium ion battery through a polynomial fitting method; 2) determining a dual-polarization equivalent circuit model of the lithium ion battery, and establishing a system equation representing a relation between a battery parameter identification vector and system output; and 3) constructing an identification process of the multi-innovation recursive Bayesian algorithm. According to the method of the invention, an ARX model for lithium ion battery parameter identification is established; the result of the previous moment is corrected by utilizing an innovation correction technology; an innovation length parameter is introduced based on the multi-innovation identification method, so that the influence of bad data on parameter estimation is overcome, and the parameter estimation precisionis improved; and the parameter identification result shows that the method is high in identification precision and has engineering value.
Need to check novelty before this filing date? Find Prior Art

Description

Technical field

[0001] The present invention relates to the field of lithium ion batteries, and in particular, to a battery model parameter identification method based on multi-new symbol-based Bayesian algorithm.Background technique

[0002] With the development of the transportation industry, the shortage of resources, environmental pollution and safety problems are growing, and the new energy industry has risen, and new energy vehicles have received more and more attention. Accordingly, the energy storage system has become a revolutionary technology that promotes renewable energy consumption due to its ability to flexibly configure, response speed and easy operation maintenance, and battery energy storage has a wide range of application prospects in new energy access. Lithium-ion batteries have long life, low self-discharge effect, and energy density, and have become the main battery energy storage element. Lithium-ion batteries are electrochemical systems that are nonlinear, affected ...

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