An accurate estimation method of battery discharge state of charge based on cell temperature prediction

Abstract

The invention provides a power battery discharge charge state accurate estimating method based on battery cell inner temperature prediction. The power battery discharge charge state accurate estimating method based on the battery cell inner temperature prediction is characterized in that prediction is based on battery cell inner temperature but not battery cell surface temperature or environment temperature; during a prediction process, DOD (Depth of Discharge) of a discharge end position and Qmax of the current discharge process can be directly predicted by skipping model parameters of a battery cell, and the power battery discharge charge state accurate estimating method based on the battery cell inner temperature prediction is a method for estimation and correction based on empirical data, wherein the DOD represents depth of discharge of a battery cell, the DOD is 0 when in ideal full charging, and the DOD is 100 percent when in ideal full discharging; the Qmax represents the totalchemical capacity of the battery cell under a current state.

Description

technical field [0001] The present invention relates to power management technology, in particular to a method for estimating the remaining capacity of a battery, in particular to a method for estimating the remaining capacity of a battery in a discharge phase of a power battery. Background technique [0002] Existing equipment, instruments, and even cars are powered by batteries in large quantities. With the increasing use of batteries, it is becoming more and more urgent to obtain the remaining power or state of charge of the battery, and the required accuracy is also increasing. high. However, there are many factors affecting the capacity estimation of the battery. Most of the reported patents or documents use complex mathematical operations or complex circuit models. Completing these complex operations or model establishment requires a lot of resources, which makes the capacity of the battery Estimated to become unfavorable to industrialization and marketization. [00...

AI Technical Summary

Problems solved by technology

[0006] The estimation of the remaining capacity of the battery often has higher requirements on its accuracy during the battery discharge stage, that is, the requirements are more stringent in the equipment use stage, and the working conditions in the discharge stage are complex, the discharge current may change at any time, and the temperature change law is difficult to explore and utilize. Coupled with the influence of battery aging and other factors, in order to meet the accuracy requirements, the generally selected algorithms are more complicated, such as Kalman filtering, etc.

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