Lithium-ion battery remaining life prediction method based on wde optimized lstm network
A lithium-ion battery, life-span technology, applied in the field of lithium-ion batteries, can solve problems such as the need to improve the feasibility, the large uncertainty of the fusion model, and the high computational complexity
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[0097] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.
[0098] In this embodiment, the lithium-ion battery degradation data from the NASA Prognostic Center of Excellence (PCoE) is selected, and the first group of lithium-ion battery sample battery capacity data labeled B0005 is selected as a specific implementation case data used in . The method for predicting the remaining life of the lithium ion battery based on the WDE optimized LSTM network of the present invention is used to indirectly predict the remaining life of the lithium ion battery.
[0099] Lithium-ion battery remaining life prediction method based on WDE optimized LSTM network, such as figure 1 shown, including the following steps:
[0100] Step 1: Construct tw...
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