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Storage battery capacity predication method based on multi-factor grey correlation model

A grey relational and grey model technology, applied in the measurement of electrical variables, measurement of electricity, measurement devices, etc., can solve the problems of poor method prediction accuracy, model error difference, etc., to achieve easy implementation, avoid deep discharge, and high prediction accuracy. Effect

Active Publication Date: 2014-04-16
CHINA JILIANG UNIV
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Problems solved by technology

Although this method is simple to operate and only requires short-term discharge to obtain the capacity value, the prediction accuracy of the method is poor. For batteries of different types, the difference in model error is very obvious

Method used

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  • Storage battery capacity predication method based on multi-factor grey correlation model
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  • Storage battery capacity predication method based on multi-factor grey correlation model

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Embodiment Construction

[0021] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0022] as attached figure 1 Shown, the present invention comprises the following steps:

[0023] 1) When the battery is discharging, measure the terminal voltage and internal resistance of the battery four times at equal intervals, and obtain the initial capacity value by integrating the discharge current and discharge time measured each time, so as to obtain the terminal voltage, internal resistance and initial capacity value, with the same interval time between the first four measurements;

[0024] 2) After the first four measurements of the battery, measure the terminal voltage and internal resistance of the battery for the fifth time during discharge, and the interval between the fifth measurement and the fourth measurement is the same as the interval between the first four measurements ;

[0025] 3) Taking the terminal voltage of the battery obt...

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Abstract

The invention discloses a storage battery capacity predication method based on a multi-factor grey correlation model. The storage battery capacity predication method based on the multi-factor grey correlation model comprises measuring the terminal voltage, the internal resistance and capacity values of a storage battery by four times in an interval mode during discharging of the storage battery; measuring the terminal voltage and the internal resistance at a fifth time; performing increasing iteration on a weighting parameter with the terminal voltage and the internal resistance serving as predication objects; obtaining predicating values of the terminal voltage sequentially through a GM (1,1) grey model; obtaining differences between the predicating values and the terminal voltage in the fifth time and selecting weighting parameter values of minimum values of absolute values of the differences; selecting the terminal voltage and the internal resistance to serve as connected factors to construct a GM (1,N) model; enabling a final weighting parameter value to be an average number of the two weighting parameter values; substituting the average weighting parameter value and measuring data of the first four times and obtaining remaining volume of the storage battery. The storage battery capacity predication method based on the multi-factor grey correlation model has the advantages of being easy to achieve, good in instantaneity and high in prediction accuracy, achieving the predication with only a small amount of data, avoiding battery damage caused by deep discharging in a traditional method and effectively improving the service life of the storage battery.

Description

technical field [0001] The invention relates to a storage battery capacity prediction method, in particular to a storage battery capacity prediction method based on a multi-factor gray relational model. Background technique [0002] With the rapid development of power electronic technology and the progress and development of the national economy, the society's demand and dependence on electricity are getting higher and higher, especially for those important and critical power loads. Once the power supply is interrupted, it will often lead to very serious, Even catastrophic consequences. At the same time, people's awareness of emergency prevention is getting higher and higher, and the centralized emergency power supply system or emergency power supply has been paid more and more attention by people, and has become a necessary centralized emergency power supply system in enterprises, substations, hospitals and other related occasions. [0003] Due to its large capacity, low c...

Claims

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Application Information

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IPC IPC(8): G01R31/36
Inventor 陈乐李鹏富雅琼谢敏黄艳岩
Owner CHINA JILIANG UNIV
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