Lithium battery heuristic residual life prediction method based on implicit nonlinear Wiener process
A Wiener process and life prediction technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., to achieve the effects of avoiding economic losses, good engineering application value, and reducing relative errors
Pending Publication Date: 2021-06-11
ROCKET FORCE UNIV OF ENG
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[0003] The purpose of the present invention is: to provide a method that makes full use of lithium battery life data and on-site degradation information to overcome the influence of imperfect prior information, and scientifically predicts the individual life and overall life characteristics of high-reliability lithium batteries to solve imperfect prior information. Lithium battery remaining life prediction problem under the condition
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[0102] In order to make the purpose, 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 in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments.
[0103] Accordingly, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.
[0104] The validity of the present invention is verified based on the lithium battery experiment...
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The invention provides a lithium battery heuristic residual life prediction method based on an implicit nonlinear Wiener process. The method comprises the following steps: 1, establishing a lithium battery performance degradation model implying a nonlinear Wiener process; 2, estimating a priori parameter offline; 3, carrying out posteriori distribution on the drift coefficient and determining the length of an iteration interval; 4, updating parameters based on field information; and 5, proposing a life prediction expression. Results show that the method not only can predict and analyze the characteristic quantity of the reliability life of the lithium battery, but also can be used as an effective analysis tool for predicting the residual life of the lithium battery, and provides powerful theoretical basis and technical support for equipment to maintain, guarantee and replace the lithium battery, so that the expenditure is saved, and unnecessary economic loss is avoided; and the method has good engineering application value.
Description
technical field [0001] The invention belongs to the technical field of reliability engineering, and in particular relates to a lithium battery heuristic remaining life prediction method based on an implicit nonlinear Wiener process. Background technique [0002] In practical engineering applications, in the process of system random degradation, prior information is often not accurate enough, or even lacks prior information, that is, imperfect prior information. When there is imperfect prior information, the prediction accuracy of remaining life will also decrease. In order to overcome the influence of imperfect prior information on remaining life prediction and improve the accuracy of remaining life prediction, a heuristic method for remaining life prediction based on the parameter update method based on expectation maximization is proposed for the nonlinear degradation process with measurement error. Contents of the invention [0003] The purpose of the present invention...
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IPC IPC(8): G06F30/20G06F111/08G06F119/04G06F119/02
CPCG06F30/20G06F2111/08G06F2119/02G06F2119/04
Inventor 唐圣金韩洋洋马长林孙晓艳司小胜叶辉
Owner ROCKET FORCE UNIV OF ENG