SOC estimation method for lithium iron phosphate battery pack

A lithium iron phosphate battery, lithium iron phosphate technology, applied in the direction of measuring electricity, measuring electrical variables, measuring devices, etc., can solve the problems of not considering the nonlinear characteristics of the battery, low efficiency, low precision, etc., to improve the SOC estimation accuracy, The effect of improving estimation efficiency and suppressing oscillations

Active Publication Date: 2018-12-18
湖南安华源电力科技有限公司
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Problems solved by technology

[0008] These prediction methods in the prior art do not take into account the complex nonlinear characteristics of the battery, and need to train a large number of sample data. The efficiency is low in the area where the SOC changes relatively flat, and the accuracy is low in the area where the SOC changes.

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  • SOC estimation method for lithium iron phosphate battery pack
  • SOC estimation method for lithium iron phosphate battery pack
  • SOC estimation method for lithium iron phosphate battery pack

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Embodiment Construction

[0029] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0030] The SOC estimation method of the lithium iron phosphate battery pack based on BP neural network of the present invention comprises the following steps:

[0031] Step 1, construct BP neural network.

[0032] The lithium iron phosphate battery pack to be evaluated is selected, and the lithium iron phosphate battery pack is monitored in an online real-time manner. Online real-time measurement of relevant technical parameters, including: battery pack voltage U(t), battery pack current I(t), battery pack internal resistance R(t), battery pack temperature T(t). The rated capacity C of the lithium iron phosphate battery pack 0 It can be directly obtained from relevant manufacturers, and the relationship formulas (1) and (2) are constructed:

[0033]

[0034] C （t） Indicates the online real-time monitoring capacity...

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Abstract

The invention provides a method for estimating SOC of a lithium iron phosphate battery pack using a BP neural network. The BP neural network adopts a hidden layer, three inputs, and one output networkstructure, and the number of nodes of the hidden layer is 11. The estimation method comprises the following steps: adjusting a connection weight adjustment link of the BP neural network, inserting aninertia coefficient, using smooth weighted calculation to improve the connection weight adjustment, increasing an original connection weight item when performing the connection weight adjustment calculation, and giving a heavier weight. The method uses the current integral correction method to change the parameters of the BP neural network, which reduces the influence of the capacity decay of thelithium iron phosphate battery pack on the SOC estimation accuracy.

Description

technical field [0001] The application belongs to the technical field of electrochemical energy storage monitoring, and relates to a method for estimating the SOC of a lithium iron phosphate battery pack, in particular to a method for estimating the SOC of a lithium iron phosphate battery pack based on a BP neural network. Background technique [0002] During use, the remaining power of the lithium iron phosphate battery pack directly affects the decision-making of energy dispatch management, while overcharging or overdischarging directly affects the service life of the lithium iron phosphate battery pack. ofCharge, SOC) has become an important reference index for power management. Since the SOC estimation of the lithium iron phosphate battery pack involves complex electrochemical reactions, the voltage and current of the energy storage lithium iron phosphate battery pack are constantly changing under working conditions, and the accurate estimation of the SOC has become a he...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/36
Inventor 肖慧明周青熊露丹吴任
Owner 湖南安华源电力科技有限公司
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