Satellite lithium ion battery residual life prediction system and method based on RVM (relevance vector machine) dynamic reconfiguration

Abstract

The invention provides a satellite lithium ion battery residual life prediction system and a satellite lithium ion battery residual life prediction method based on RVM (relevance vector machine) dynamic reconfiguration, and relates to a lithium ion battery residual life prediction system and a lithium ion battery residual life prediction method. The uncertainty expression of the lithium ion battery predication is realized, and the lithium ion battery residual life prediction method is more applicable to satellite system environment with limited resources. A dynamic reconfiguration module of the prediction system comprises a reconfiguration unit A and a reconfiguration unit B, the reconfiguration unit A and the reconfiguration unit B realize the time sharing multiplex of logic resources of the dynamic reconfiguration module, and the RVM training and predication is realized; and the Gaussian kernel function flowing water calculation is realized by a multistage flowing water segmented linear proximity method and a parallel computing structure, and the computational efficiency is enabled to be fully improved. The inverse calculation of symmetric positive definite matrices is realized by a Cholesky decomposition method, the computing resources consumption is reduced by a multiplying and gradually decreasing device, and the computing delay is reduced. Experiments show that the system and the method have the advantages that FPGA (field programmable gate array) finite computing resources are utilized for realizing the computational accuracy similar to a PC (personal computer) platform, the four-times computing efficiency improvement relative to the PC platform is obtained, and the utilization rate of hardware resources is effectively improved through dynamic reconfiguration strategies.

Description

technical field [0001] The invention relates to a lithium-ion battery remaining life prediction system and a prediction method. Background technique [0002] Lithium-ion batteries have become the third generation of satellite energy storage batteries in my country due to their superior performance (literature [1]: Wang Dong, Li Guoxin, Pan Yanlin. Application of lithium-ion battery technology in the aerospace field [J]. Shanghai Aerospace, 2000, 17 (1):54-58), but it has safety problems, especially for satellite applications, the failure of lithium-ion batteries will cause serious consequences (literature [2]: Goebel K, Saha B, Saxena A, et al.Prognostics in battery health management[J].Instrumentation&Measurement Magazine,IEEE,2008,11(4):33-40). Therefore, the management of lithium-ion batteries has become one of the key technologies of satellite power systems. Traditional battery management systems mainly include functions such as charge and discharge control, balance mana...

AI Technical Summary

Problems solved by technology

However, the RUL prediction of lithium-ion batteries is still in its infancy, the method system framework for RUL prediction of lithium-ion batteries is not perfect, and the hardware implementation method of RVM algorithm has not been reported yet.

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