Service life prediction method of secondary cell and power supply management method

Abstract

A service life prediction method of a secondary cell and a power supply management method are disclosed. The service life prediction method comprises the following steps of recording a capacity after each charge and discharge cycle during usage of the cell and acquiring cell capacity data corresponding to a cycle frequency; setting a fitting curve fetch period; acquiring a corresponding capacity trend curve and a capacity prediction formula in the fitting curve fetch period; and when the cycle frequency reaches the fitting curve fetch period, repeating a step3, and using the capacity trend curve and the capacity prediction formula acquired by a next fitting curve fetch period to replace the capacity trend curve and the capacity prediction formula acquired by a previous fitting curve fetch period. In the invention, according to an actual usage condition, prediction is performed, and a service life prediction curve can be continuously corrected and the capacity prediction formula can be updated so that the curve and the formula approach to the actual usage condition as close as possible and a cell service life is accurately predicted. By using the power supply management method based on the prediction method, according to the actual usage condition of the cell, correction and strategy adjusting are performed on a usage preference of the cell, and a cycle life of the cell is prolonged.

Description

technical field [0001] The invention belongs to the technical field of secondary batteries, and in particular relates to a life prediction method of a secondary battery and a power management method based on the life prediction method. Background technique [0002] Secondary batteries, such as lithium-ion batteries, lead-acid batteries, nickel-metal hydride batteries, etc., which provide power for various consumer electronics equipment, power vehicles, power tools, drones, industrial equipment and other mobile equipment, are in the process of development and production Multi-item, multi-environment, and repetitive test verification will be carried out to ensure that it has a good cycle life during use. For example, the Chinese invention patent application with the publication number CN103698710A and the Chinese invention patent application with the publication number CN105068009A respectively disclose the method for predicting the battery life cycle under the set test condit...

AI Technical Summary

Problems solved by technology

[0003] The aforementioned methods realize the estimation of battery capacity and life prediction based on test data. However, due to the ever-changing actual use conditions and the influence of various factors such as ambient temperature, user habits, and equipment status, the previous test verification conditions are difficult to simulate. Based on the actual use of the battery, it is impossible to predict the change in the cycle life of the battery in the actual use process only based on the test results. There will be a large deviation between the actual life of the battery and the expected life, which will greatly reduce the user experience of the end customer. The service life of the battery is far below the psychological expectations of customers, which leads to large-scale customer complaints

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