Online estimation method for battery capacity loss

Abstract

The invention discloses an online estimation method for the battery capacity loss. The method at least comprises the following steps that an electrochemical model is established according to electrochemical features of a battery, a battery second-order circuit model is established according to the electrochemical model, and parameters of the battery second-order circuit model comprise ohmic internal resistance and polarized internal resistance of the battery; according to the battery second-order circuit model, an output equation of the battery second-order circuit model and an observation equation for estimating the ohmic internal resistance R0 are determined; the parameters of the battery second-order circuit model are identified; the state quantity and state equation of the ohmic internal resistance are determined, and a robust UKF algorithm is used to carry out iteration o the state quality of the ohimic internal resistance to obtain the real-time estimation value of the ohmic internal resistance; and a relation equation between the circulation times N of the battery and the ohmic internal resistance R0 is established according to aging test of the battery, and a calculation equation for estimating the state of health (SOH) of the battery via the circulation times N is established.

Description

technical field [0001] The invention relates to the technical field of batteries, in particular to an online estimation method for battery capacity loss. Background technique [0002] Battery capacity loss is one of the important indicators to measure the state of health (StateOfHealth, SOH) of a battery or battery pack. Detecting and estimating battery capacity loss is usually done in the laboratory using sophisticated instruments and equipment. However, for batteries used online, it is generally difficult to directly detect the characteristic parameters of the battery due to the limitations of the environment and conditions. Therefore, estimating the state of health of the battery by detecting or estimating the remaining capacity of the battery online is a difficult problem in the field of lithium-ion battery management technology at present. [0003] At present, there are two main online estimation methods for the residual capacity of batteries or battery packs: one is f...

AI Technical Summary

Problems solved by technology

Its disadvantage is that the Thevenin model is a first-order model, which cannot simulate the nonlinear characteristics of the battery to a large extent, and the accuracy of predicting battery model parameters using the Kalman filter algorithm is highly dependent on the accuracy of the battery model. The accuracy of this method is difficult to guarantee

In addition, this method only considers online estimation or acquisition of battery internal resistance and battery state of charge (SOC) information, which cannot directly indicate the SOH or capacity loss of the battery, and cannot meet the requirements of use.

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