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Method for predicting remaining life of vehicle lithium battery

A technology of life prediction and lithium battery, applied in the direction of measuring electricity, measuring devices, measuring electrical variables, etc., can solve the problems of low accuracy and speed, and achieve the effect of improving accuracy

Inactive Publication Date: 2018-11-06
CAPITAL NORMAL UNIVERSITY
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AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to propose a method for predicting the remaining life of a lithium battery for vehicles in view of the problem that the remaining life prediction algorithm for a lithium battery for a vehicle is not high in accuracy and speed in the prior art

Method used

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  • Method for predicting remaining life of vehicle lithium battery
  • Method for predicting remaining life of vehicle lithium battery
  • Method for predicting remaining life of vehicle lithium battery

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Embodiment Construction

[0035] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings.

[0036] A method for predicting the remaining life of lithium batteries for vehicles, such as figure 1 As shown, the steps are as follows:

[0037] Step 1. Initialize the parameter values ​​of the ELM predictor. Set the number of nodes in the hidden layer to 10, and the output of the single-step prediction to 1. The number of parameters (weights and thresholds) to be optimized is 40.

[0038] Step 2, setting heuristic Kalman HKA parameters. The number N of particle groups is 25, and the number N of the best candidate groups ξ is 5 and the deceleration factor α is set to 0.7, the number of iterations k=0 and the maximum number of iterations is 300.

[0039] Step three, produce At each iteration, according to the mean m of the Gaussian generator k and standard deviation S k generate a normally distributed set The latitude of is consi...

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Abstract

The invention discloses a method for predicting the remaining life of a vehicle lithium battery. The method comprises in combination with the historical data of the capacity of the lithium battery andbased on an extreme learning network model, optimizing the input weight and offset of the extreme learning network by a heuristic Kalman algorithm and constructing a new heuristic Kalman-extreme learning prediction model. The method for predicting the remaining life of a vehicle lithium battery has advantages and effects of greatly improving the accuracy and the real-time performance of the prediction of the lithium battery.

Description

technical field [0001] The invention relates to a method for predicting the remaining life of a lithium battery for vehicles, which belongs to the technical field of lithium battery management for vehicles, and in particular to a method for predicting the life of a lithium battery in the health state prediction and management of the lithium battery. Background technique [0002] Lithium batteries have become the energy choice of electric vehicles due to their good safety performance, high energy density, and long cycle life. However, due to the influence of the complex operating environment of electric vehicles, the performance of lithium batteries will gradually degrade, and the remaining number of charge and discharge cycles before the battery performance drops to the rated threshold becomes its remaining life. Effective prediction of remaining life can provide technical support for predictive maintenance of electric vehicle battery management system. [0003] At present,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/36
Inventor 吴立锋杨晶张震宇关永袁慧梅
Owner CAPITAL NORMAL UNIVERSITY
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