Method for predicting remaining useful life of lithium ion battery based on long-correlation fractional order degradation model

Abstract

The invention discloses a method for predicting the remaining useful life of a lithium ion battery based on a long-correlation fractional order degradation model. The method comprises the following steps: S1, acquiring historical degradation data of the capacity of the lithium ion battery as a prediction input sequence; s2, calculating estimated values of a Hurst index H and a feature index alphaof the prediction input sequence; s3, judging whether the prediction input sequence meets a long correlation characteristic or not according to the estimated values of H and alpha, and if so, calculating estimated values of a drift parameter mu and a diffusion parameter delta; if not, returning to the step S1; s4, presetting a failure threshold, and obtaining the actual residual effective life ofthe lithium ion battery; s5, establishing a long correlation fractional order Levy degradation model; s6, calculating a predicted value of the end-of-life time of the lithium ion battery; and S7, calculating the predicted residual effective life of the lithium ion battery. The method provided by the invention can accurately predict the residual effective life of the lithium ion battery.

Description

technical field [0001] The invention relates to a method for predicting the remaining effective life of a lithium-ion battery based on a long-term correlation fractional-order degradation model, and belongs to the technical field of prediction of the remaining effective life of the lithium-ion battery. Background technique [0002] The remaining effective life prediction of lithium-ion batteries is a series of prediction work carried out on the degradation index objects such as the capacity of lithium-ion batteries. As a power supply module for large electric equipment and complex electronic equipment, the reliability of lithium-ion batteries directly affects the durability and safety of these equipment. Lithium-ion battery damage or performance degradation can cause the overall shutdown or failure of electric equipment, and even safety accidents. Through the reliability analysis of lithium-ion batteries with the prediction of remaining effective life as the core, it provid...

AI Technical Summary

Problems solved by technology

However, in the current methods for predicting the remaining effective life of lithium-ion batteries, the model method based on the working principle usually has cumbersome prediction steps, it is difficult to achieve perfect results, and the scope of application is narrow, and the above-mentioned degradation data-driven method cannot fit the degradation data. The complex characteristics and low prediction accuracy lead to the inability of the existing lithium-ion battery remaining effective life prediction method to be widely used.

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