Lithium battery SOC (Stress Optical Coefficient) estimation method based on EKF (Extended Kalman Filter)

Abstract

The invention discloses a lithium battery SOC (Stress Optical Coefficient) estimation method based on an EKF (Extended Kalman Filter). The estimation method comprises the following steps: (1) acquiring a calculation formula of Ak and Ck according to a Thevenin model of a monomer phosphoric acid iron battery and the definitions of Ak and Ck; (2) in the estimation process of the EKF, selecting a filtering initial value from a certain range, and performing continuous parameter debugging on the initial values of Pk and R; (3) substituting a parameter into a Kalman filter framework, and performing continuous iteration and data update to obtain the optimal estimation of an SOC. By adopting the lithium battery SOC estimation method based on the EKF, the defects of short service life, poor safety, low reliability and the like in the prior art can be overcome to realize the advantages of long service life, high safety and high reliability.

Description

technical field [0001] The invention relates to the technical field of lithium batteries, in particular to an EKF-based method for estimating the SOC of lithium batteries. Background technique [0002] In recent years, the automobile industry has developed rapidly, especially in China. From 2004 to 2012, the number of automobiles in my country has increased. As of 2012, the number of private automobiles in my country has reached 93.09 million, and the growth trend will be obvious in the next few years. A series of problems, such as energy security and environmental pollution, have become the key factors restricting the development of automobiles. In terms of energy security, the growth trend of my country's oil production and consumption from 2004 to 2010. As of 2010, my country's dependence on foreign oil has reached 53%, exceeding the warning line of 50%. The energy consumption of automobiles accounts for nearly 60% of the total energy consumption of refined oil. Accordin...

AI Technical Summary

Problems solved by technology

[0006] (2) Lithium batteries are poor in safety, and overcharging and overdischarging must be prevented;

[0007] (3) SOC is an important parameter when electric vehicles are running, and it is used to judge whether the battery is overcharged. However, the lithium battery itself is a closed and complex electrochemical reaction, and its estimation is difficult.

[0008] In the process of realizing the present invention, the inventor found that there are at least defects such as short service life, poor safety and low reliability in the prior art

Images