Quantitative diagnosis method of battery micro-short circuit based on artificial neural network
A technology of artificial neural network and diagnosis method, which is applied in the field of quantitative diagnosis of battery micro-short circuit based on artificial neural network, can solve the problems of battery micro-short circuit, thermal runaway, electrode drying, etc., and achieves the effect of small online calculation and reliable diagnosis.
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[0015] In order to make the technical means, creative features, goals and effects of the present invention easy to understand, the following embodiments will specifically describe the artificial neural network-based battery micro-short-circuit quantitative diagnosis method of the present invention in conjunction with the accompanying drawings.
[0016] The artificial neural network-based battery micro-short circuit quantitative diagnosis method of the present invention is used for diagnosing the micro-short circuit state of the current battery. The current battery can be a single battery cell or all the battery cells in the battery pack.
[0017] figure 1 It is a flowchart of the quantitative diagnosis method for battery micro-short circuit based on artificial neural network in the embodiment of the present invention.
[0018] Such as figure 1 As shown, the diagnostic method mainly includes the following steps:
[0019] Step 1, measuring battery aging parameters of the batte...
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