Retired power battery complementary energy quick detection and rating method

Abstract

The invention discloses a retired power battery complementary energy quick detection and rating method, which comprises the following steps: constructing an MPSOBP model based on retired power batterycomplementary energy prediction, and setting initial parameters according to battery complementary energy evaluation requirements; obtaining a training sample and a test sample required by MPSOBP model training; training an MPSOBP model by using the training sample and detecting the prediction effect by using the test sample to obtain an MPSOBP model meeting the precision requirement; establishing an MPSOBP-BP composite neural network by utilizing the MPSOBP model, predicting battery capacity measurement data of the retired power battery to be measured, and performing complementary energy evaluation on the retired power battery; inputting the battery capacity measurement data and the measured battery structure condition data into a combined K-Means clustering algorithm, and grading the retired power battery; and outputting a complementary energy evaluation result and a rating result. According to the invention, quick and accurate complementary energy detection and rating can be carried out on the retired power battery, and the measurement time is within 15 min.

Description

technical field [0001] The invention belongs to the field of battery detection, and in particular relates to a rapid detection and rating method for residual energy of decommissioned power batteries. Background technique [0002] The average service life of the power battery is 5-8 years, and its performance decays with the increase of charging times. When the battery capacity decays below 80% of the rated capacity, the power battery is no longer suitable for electric vehicles. However, the decommissioned batteries can still be further utilized in many fields such as energy storage, distributed photovoltaic power generation, household electricity consumption, and low-speed electric vehicles after inspection, maintenance, and reorganization. Before the cascade utilization of these retired batteries, in order to ensure the safe use and optimal performance of the retired batteries, it is necessary to perform residual energy detection on the retired battery modules. [0003] Ac...

AI Technical Summary

Problems solved by technology

Therefore, the residual energy testing process of a battery cell or battery module in the greenhouse needs to occupy a testing instrument for 36 to 60 hours, which will undoubtedly lead to high time costs for residual energy testing and a large demand for testing instruments.

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