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Lithium battery online health state fast prediction method based on voltage key characteristics

A technology with key characteristics and health status, applied in the direction of measuring electricity, measuring devices, measuring electrical variables, etc., it can solve the problem that the power battery cannot reach the life value, etc., and achieve the effect of convenient and fast calculation and high prediction accuracy.

Active Publication Date: 2018-09-18
罗斯德尔智能汽车(重庆)有限公司
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Problems solved by technology

Under actual complex working conditions, the power battery often cannot achieve the expected life value

Method used

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  • Lithium battery online health state fast prediction method based on voltage key characteristics
  • Lithium battery online health state fast prediction method based on voltage key characteristics
  • Lithium battery online health state fast prediction method based on voltage key characteristics

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Embodiment Construction

[0034] The online health state rapid prediction method of the lithium battery based on the voltage key characteristics proposed by the present invention, the specific operation steps are:

[0035] The first step is to conduct cycle tests based on cycle test conditions for lithium batteries in different life states, obtain the full life data of lithium batteries, and then select r cycle data at equal intervals from the full life data as training samples, and p cycle data as a test sample.

[0036] In the second step, based on the training samples and test samples, the discharge capacity is selected as the current capacity of the battery, and the constant current charging data is selected as the basis for the next calculation, such as figure 2 As shown; based on the constant current charging data, the differential voltage z(v) is calculated by the differential voltage formula to obtain the differential voltage curve; based on the eigenvalue selection formula, a eigenvalue pre-s...

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Abstract

In order to design a battery online health state prediction model, quickly calculate a health state of a battery at any life stage based on partial battery charging data and realize accurate functionjudgment on the battery, the invention provides a lithium battery online health state fast prediction method based on voltage key characteristics. The lithium battery online health state fast prediction method comprises the steps of: step (1), conducting cyclic tests on lithium batteries in different life state based on cyclic test working conditions, so as to obtain full-life data of the lithiumbatteries; step (2), acquiring battery capacities and calculating a differential voltage, and further pre-selecting key eigenvalues; step (3), and training and testing a prediction model based on thepre-selected eigenvalues, and finally selecting an optimal model to perform lithium battery online health state prediction. The lithium battery online health state fast prediction method realizes theeffect of calculating the battery health states online based on few data, judges the battery performance accurately, and improves the working efficiency.

Description

【Technical field】 [0001] This patent belongs to the field of new energy vehicles, and specifically proposes a rapid online health status prediction method for lithium batteries based on key characteristics of voltage. 【Background technique】 [0002] The increasingly serious environmental problems have prompted countries to explore effective ways to solve energy and environmental problems. With the continuous development of the automobile industry, new energy vehicles have become an effective way to solve this problem. The development of new energy vehicles has reached a consensus around the world, and it is urgent to promote the strategic transformation of the traditional automobile industry. As an important part of electric vehicles, the battery industry is developing rapidly. However, there are still some problems to be solved urgently in the power battery. One of the problems is to devise a method for estimating the state of the battery with high accuracy. In practica...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/36
Inventor 朴昌浩王真林松马艺玮
Owner 罗斯德尔智能汽车(重庆)有限公司
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