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Method for estimating residual capacity of iron-lithium phosphate power cell

A power battery and lithium iron phosphate technology, which is applied in the direction of measuring electrical variables, measuring electricity, and measuring devices, can solve the problems that the estimation method is not easy to satisfy, and achieve the effects of simple algorithm, reduced usage, and small cumulative error

Inactive Publication Date: 2010-01-20
CHONGQING UNIV
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Problems solved by technology

The current national standard requires that the error should not exceed 8%, but the estimation method of the existing technology is not easy to meet

Method used

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  • Method for estimating residual capacity of iron-lithium phosphate power cell
  • Method for estimating residual capacity of iron-lithium phosphate power cell
  • Method for estimating residual capacity of iron-lithium phosphate power cell

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Embodiment Construction

[0023] A method for estimating the remaining capacity of a lithium iron phosphate power battery, comprising the steps of:

[0024] 1. Establish the electrochemical model of the lithium iron phosphate power battery [the battery electrochemical model sees the (6) formula of the embodiment];

[0025] 2. According to the voltage equation of the electrochemical model, use the Kalman filter algorithm to obtain the remaining battery capacity:

[0026] Battery remaining capacity = the ratio of the average concentration of solid-phase lithium ions in the negative electrode of the battery to the maximum concentration of lithium ions when fully charged;

[0027] Among them, the solid-phase lithium ion concentration in the negative electrode of the battery is obtained through the extended Kalman filter algorithm; the maximum concentration of lithium ions during full charge is the calibration value at the factory, which is a constant.

[0028] In order to match the electrochemical model o...

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Abstract

The invention provides a method for estimating the residual capacity of an iron-lithium phosphate power cell, comprising the following steps: establishing an electrochemical model of the iron-lithium phosphate power cell; obtaining the residual capacity of the cell, namely the average concentration of solid-phase lithium ions in the anode and the cathode of the cell / the maximum concentration of the lithium ions when charging fully according to the voltage equation of the electrochemical model by using a Kalman filtration algorithm. The method is based on the electrochemical model of the iron-lithium phosphate power cell and has good model accuracy and high accuracy; the method adopts the expanded Kalman filtration algorithm to carry out recursive estimation and has the characteristics of accurate estimation and small totalized error. In the expanded Kalman filtration algorithm, information provided by observed data is utilized to continuously modify state estimation when recursive filtering is carried out, and the state estimation error is decreased.

Description

technical field [0001] The invention relates to a method for estimating the remaining capacity of a lithium iron phosphate power battery, in particular to a method for estimating the remaining capacity of a lithium iron phosphate power battery by combining an electrochemical model of the lithium iron phosphate power battery and an extended Kalman filter algorithm. Background technique [0002] Because electric vehicles can well solve the environmental protection and energy problems that have always plagued people, they have flourished. The power batteries currently used in electric vehicles mainly include lead-acid batteries, nickel-metal hydride batteries and lithium-ion batteries. These three power batteries have their own advantages and disadvantages, and the lithium iron phosphate power battery can better meet the requirements of electric vehicles for on-board batteries, and with its high efficiency output, the performance is very stable even at high temperatures, and th...

Claims

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Application Information

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IPC IPC(8): G01R31/36
Inventor 邓力崔健马君伟朱可张国松徐骋曦郑群英刘和平
Owner CHONGQING UNIV
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