Lithium ion battery life prediction method based on unscented Kalman filtering (UKF)

Abstract

The invention discloses a lithium ion battery life prediction method based on unscented Kalman filtering (UKF), for the purposes of accurately estimating a battery capacity state, reducing the calculation complexity of a conventional algorithm and improving the accuracy of life predication. According to the method, a dual-exponent capacity attenuation model is taken as a lithium ion battery capacity degeneration model, and a state transition equation and a measurement equation of a lithium ion battery capacity are obtained; according to known life attenuation data of other batteries, distribution of state variable initial values of the dual-exponent capacity attenuation model is obtained; for a battery to be predicted needing life predication, a corresponding predication start point is determined; by use of a UKF method, state tracking is carried out on capacity data of the battery to be predicted which is already charged and discharged for certain frequency, state variables in the capacity attenuation model are updated, and corresponding state variables after the charge frequency are obtained; and corresponding state variables after the charge and discharge frequency and the battery capacity are predicted, a capacity prediction curve is drawn, and the life of the battery to be predicted is determined.

Description

technical field [0001] The invention belongs to the technical field of lithium-ion battery fault prediction and health management, and in particular relates to a lithium-ion battery life prediction method based on an unscented Kalman filter. Background technique [0002] As a new type of storage battery, lithium-ion batteries have great application prospects, especially in occasions where the electrical performance and reliability of energy storage are required to be high, such as aerospace equipment such as low earth orbit, geosynchronous orbit, and space stations. [0003] The remaining service life of the battery is also called the cycle life, which refers to the number of charge and discharge cycles that the battery undergoes before the capacity drops to the specified value under a certain charge and discharge system. For many applications of lithium-ion batteries, the lithium-ion battery is considered to be invalid when the actual capacity drops to 70%-80% of the rated ...

AI Technical Summary

Problems solved by technology

However, most of the life prediction methods based on Kalman filter or extended Kalman filter in the prior art have certain limitations in practical applications. When dealing with the state problem of a linear non-Gaussian random system, there will be a large error and there may even be divergence

In addition, the complex electrochemical reaction process inside the lithium-ion battery is difficult to characterize, and it is difficult to establish a battery capacity decay model that combines the entire life-span degradation process of the battery and the characteristics of the degradation data, which brings certain difficulties to life prediction. The estimation of battery life is inaccurate and fails to truly reflect the law of battery life, which brings many difficulties to the failure prediction and health management of lithium-ion batteries used in the future.

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