Energy storage lithium battery pack aging mode automatic identification method based on BP neural network
A BP neural network and aging model technology, applied in biological neural network models, neural learning methods, measurement electricity and other directions, can solve problems such as equipment sampling and measurement accuracy requirements are relatively high, the amount of calculation is huge, and the aging model cannot be automatically identified.
Pending Publication Date: 2022-07-08
CHINA THREE GORGES CORPORATION
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The establishment of the first type of model is very complicated and the amount of calculation is huge, and it is difficult to apply it in engineering; the establishment of the second type of model needs to select a suitable circuit model to fit the impedance curve, and whether the model is suitable directly affects the fitting result, and the model The requirements for equipment sampling and measurement accuracy are also relatively high, and are susceptible to interference from external noise
The establishment of the third model is relatively simple, but the error of the quantitative result is large, and the aging model cannot be automatically identified
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[0048] In order to make the purposes, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments These are some embodiments of the present invention, but not all embodiments. The components of the embodiments of the invention generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations.
[0049] Thus, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but is merely representative of selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary ski...
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The invention provides an energy storage lithium battery pack aging mode automatic identification method based on a BP neural network, and relates to the technical field of lithium batteries. The method comprises the following steps: acquiring operation data of a lithium battery set, and preprocessing the operation data to obtain voltage, current and temperature data meeting subsequent calculation requirements; establishing corresponding IC curves for the lithium ion battery packs with different cycle times, extracting characteristic parameters of the IC curves, comparing characteristic parameter changes of the lithium ion battery packs in different aging states, and performing BP neural network model training by taking a characteristic parameter change set as input and an aging mode type as output; and after the training is completed, extracting the characteristic quantity of the IC curve through the preprocessed operation data, and realizing the automatic classification and identification of the aging mode based on the trained BP neural network model. According to the method, aging mode type judgment suitable for engineering data can be realized, and health management on lithium iron phosphate battery sets in different aging states is facilitated.
Description
technical field [0001] The invention relates to the technical field of lithium batteries, in particular to an automatic identification method for the aging mode of an energy storage lithium battery pack based on a BP neural network. Background technique [0002] Lithium-ion batteries have outstanding advantages such as high energy density, zero emissions, high cost performance, no memory effect, light weight and easy portability. At present, lithium iron phosphate batteries are widely used in the field of power grid energy storage. Automatic identification of the internal aging mode of lithium batteries is the key and difficult technology in the use of lithium batteries, which is related to the health and safety of batteries, use efficiency and product changes. [0003] There are six main types of aging modes of lithium iron phosphate batteries: Loss of Lithium Inventory (LLI), Loss of Active material–delithiation in Negative electrode (LAM_deNE), negative electrode Loss of...
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IPC IPC(8): G01R31/367G01R31/392G01R31/396G06N3/08
CPCG01R31/367G01R31/392G01R31/396G06N3/084Y02E60/10
Inventor 吴卓彦尹立坤贾俊肖伟赵霁钟卫东熊然李立理高浪
Owner CHINA THREE GORGES CORPORATION