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Prediction method for discharge capacity of lithium ion battery

A lithium-ion battery and discharge capacity technology, applied in the field of lithium-ion battery capacity prediction, can solve the problems of complicated steps and unsuitable for large-scale industrial production, etc.

Inactive Publication Date: 2009-08-12
HENAN SENYUAN HEAVY IND
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Because this method needs to test the open circuit voltage and internal resistance of batteries under different discharge states, the steps are complicated and suitable for laboratory research, but not suitable for large-scale industrial production applications.

Method used

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  • Prediction method for discharge capacity of lithium ion battery
  • Prediction method for discharge capacity of lithium ion battery
  • Prediction method for discharge capacity of lithium ion battery

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0040] Randomly select 68 SL412454 soft-pack lithium-ion batteries produced by BYD with a rated capacity of 520mAh (1C current is 520mA). Constant current 0.5C, end voltage 4.2V, constant voltage 4.2V, end current 0.02C charge, constant current 0.2C end voltage 2.75V discharge, test and calculate the discharge capacity of these batteries, recorded as the measured capacity. Then, after all 68 batteries are fully charged according to the above method, 26 of them are randomly selected and discharged at 0.5C at T=30°C, and a series of road terminal voltage data of the first 15 minutes of discharge process are recorded with Lankey BK3512L detection cabinet, and the It is used as an input to train the BP neural network in MATLAB software, and output the predicted capacity until the error between the predicted value and the measured value is ~5%. It is considered that the BP network model at this time is the best, and the best BP network model is output The discharge capacity is reco...

Embodiment 2

[0059] 197 LP053450ARUL lithium-cobalt batteries produced by BYD were randomly selected, with a rated capacity of 700mAh (1C current of 700mA). The discharge capacity of these batteries is tested by traditional methods, which is recorded as the measured capacity. The test method is first 0.3C constant current, end voltage 4.2V, then 4.2V constant voltage, end current 0.02C charge, then 0.5C constant current, end voltage 2.75V discharge. Then randomly select 58 batteries among them, discharge at 1C current at T=30°C, use Lankey BK3512L detection cabinet to record a series of road terminal voltages in the first 10 minutes of the discharge process as input, train the BP neural network in MATLAB software, and output the predicted capacity , until the error between the predicted value and the measured value is ~5%, it is considered that the BP network model at this time is optimal, and the discharge capacity output by the optimal BP network model is recorded as the predicted capaci...

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Abstract

The invention provides a method for predicting discharge capacity of a lithium ion battery through partial discharge process by a BP neural network. The terminal voltage of the lithium ion battery in the at least previous 10 minute constant-current discharge process is taken as input, and a BP neural network model outputs the discharge capacity of the battery. The method solves the technical problems of long test period and high energy consumption in the conventional industrial method, also overcomes the defect that a laboratory method has complicated steps and is not suitable for massive industrial production, and guarantees that the average forecasting error is about 2.0 percent which is less than the error range of about 5percent allowable in the industrial production.

Description

technical field [0001] The invention relates to a method for predicting the capacity of a lithium-ion battery, in particular to a method for predicting the discharge capacity of a lithium-ion battery by using a feedforward neural network. Background technique [0002] Lithium-ion batteries have been more and more widely used in communication, electronics, automobile and other fields due to their excellent performance. However, the actual capacity of lithium-ion batteries currently produced in China is not the same as the rated capacity due to limitations in technology, battery materials, etc., and even batteries of the same type produced in the same batch may have inconsistent electrochemical characteristics. defect. Therefore, in order to ensure the quality of the battery, each battery must be sorted for discharge capacity and internal resistance before leaving the factory. The current traditional capacity detection method is to fully charge the battery with constant curr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/36G06N3/02
Inventor 王勇吴光麟沈晞
Owner HENAN SENYUAN HEAVY IND
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