Lithium battery online aging diagnosis method based on two-point aging characteristics
A diagnostic method, lithium battery technology, applied in the direction of measuring electricity, measuring electrical variables, measuring devices, etc., can solve problems such as inability to diagnose aging, and achieve the effects of reducing the burden of data storage, safe and reliable operation, and accurate aging diagnosis
Active Publication Date: 2021-09-28
ZHEJIANG UNIV
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At the same time, since the discharge mode of lithium batteries in most practical application scenarios is random, it is not possible to extract features based on specific discharge test data for aging diagnosis
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[0030] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.
[0031] like figure 1 Shown, the present invention comprises the following steps:
[0032] 1) Collect the charging voltage and charging capacity in the first 20 charge-discharge cycles of the new lithium battery, select the charging voltage and charge capacity in the kth charge-discharge cycle, obtain the voltage-capacity curve and use it as the voltage-capacity benchmark curve of the current lithium battery; k=1,2,...,20; in specific implementation, k=1, collect the charging voltage and charging capacity in the first charging and discharging cycle of the new lithium battery, and obtain the voltage capacity reference curve of the current lithium battery.
[0033] 2) Sequentially collect the charging voltage, charging capacity and total capacity of the lithium battery in each charge-discharge cycle of the current lithium battery, that is, coll...
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The invention discloses a lithium battery online aging diagnosis method based on two-point aging characteristics. The method comprises the following steps: 1, acquiring and calculating a voltage capacity reference curve of a current lithium battery; 2, calculating and obtaining a capacity difference curve corresponding to each charge-discharge cycle of the current lithium battery; 3, calculating two-point aging characteristics corresponding to all charging voltage combinations of each charge-discharge cycle of the current lithium battery; 4, repeating the steps 1-3 to obtain two-point aging characteristics of each charge-discharge cycle of each lithium battery and the total capacity of the lithium battery; 5, selecting an optimal charging voltage combination and an optimal two-point aging characteristic and forming a training set; 6, obtaining a trained lithium battery aging diagnosis regression model; and 7, during online diagnosis, acquiring and calculating the optimal two-point aging characteristics to be predicted of the lithium battery to be diagnosed, and obtaining the total capacity of the lithium battery after diagnosis so as to judge the aging state of the lithium battery to be diagnosed. Accurate lithium battery aging diagnosis is realized, and the data storage burden, the calculation burden and the cost burden are reduced.
Description
technical field [0001] The invention belongs to the field of lithium battery application and relates to an online aging diagnosis method for lithium batteries, and relates to an online aging diagnosis method for lithium batteries based on two-point aging characteristics. Background technique [0002] Due to many advantages such as high energy density, low cost, fast response to power demand, and long cycle life, lithium batteries have been commercially used in various fields on a large scale. Aging diagnosis technology plays an important role in the safe and reliable operation of lithium batteries. However, due to the complex aging mechanism of lithium batteries, and the aging path is affected by many factors in the design, production and application process, it is a challenge to achieve simple, fast and accurate lithium battery aging diagnosis under complex dynamic operating conditions . In addition, for a large battery pack composed of thousands of individual lithium bat...
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IPC IPC(8): G01R31/36
CPCG01R31/36Y02E60/10
Inventor 陈剑刘浩
Owner ZHEJIANG UNIV