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Li-ion power battery SOC estimation method based on improved adaptive double unscented Kalman filter

A technology of unscented Kalman and power battery, which is applied in the direction of instruments, measuring electricity, and measuring electric variables, etc., and can solve the problems of updating and increasing the amount of computation, algorithm influence, etc.

Active Publication Date: 2020-07-21
CHONGQING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Not only that, each update and iteration of the covariance matrix greatly increases the amount of calculations, which puts high demands on the computing power of the microcontroller, and sometimes may cause the algorithm to be affected by insufficient calculation speed. influence on

Method used

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  • Li-ion power battery SOC estimation method based on improved adaptive double unscented Kalman filter
  • Li-ion power battery SOC estimation method based on improved adaptive double unscented Kalman filter
  • Li-ion power battery SOC estimation method based on improved adaptive double unscented Kalman filter

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Embodiment 1

[0126] see Figure 1 to Figure 4 , based on the improved adaptive double unscented Kalman filter Li-ion power battery SoC estimation method, mainly includes the following steps:

[0127] 1) Obtain the type and operating parameters of the lithium-ion power battery to be tested, and establish the equivalent circuit model of the lithium-ion power battery.

[0128] The operating parameters mainly include nominal capacity C, charging cut-off voltage V c and discharge cut-off voltage V d .

[0129] The lithium-ion power battery equivalent circuit model is a second-order RC equivalent circuit model.

[0130] The circuit structure of the second-order RC equivalent circuit model is shown below:

[0131] Note that the end where the positive pole of the power supply is located is S, and the end where the negative pole of the power supply is located is W. The S terminal is connected in series with the resistor R 1 , resistance R 2 and resistor R 0 . The S terminal is connected in...

Embodiment 2

[0235] The Li-ion power battery SoC estimation method based on the improved adaptive double unscented Kalman filter mainly includes the following steps:

[0236] 1) Obtain the type and operating parameters of the lithium-ion power battery to be tested, and establish the equivalent circuit model of the lithium-ion power battery.

[0237] 2) Determine the characteristic parameters of the equivalent circuit model of the lithium-ion power battery.

[0238] 3) Establish the state filter and parameter filter based on the equivalent circuit model of the lithium-ion power battery.

[0239] 4) Coupling the state filter and parameter filter of the lithium-ion power battery based on the equivalent circuit model to establish a double unscented Kalman filter.

[0240] 5) Input the operating parameters of the lithium-ion power battery to be tested into the double unscented Kalman filter, and perform parameter correction and state-of-charge SoC estimation of the equivalent circuit model of ...

Embodiment 3

[0242] Based on the improved self-adaptive double unscented Kalman filter lithium-ion power battery SoC estimation method, the main steps are the same as in embodiment 2, wherein the operating parameters mainly include the nominal capacity C, the charging cut-off voltage V c and discharge cut-off voltage V d .

[0243] Take the AYP110161227N50 ternary material cell produced by Zhejiang Aoyou Power System Co., Ltd. as an example. Get its nominal capacity C (54Ah, 0.3C), charging cut-off voltage Vc (4.2V), discharge cut-off voltage Vd (2.75V) three basic operating parameters.

[0244] The lithium-ion power battery equivalent circuit model is a second-order RC equivalent circuit model, and a Rint model, a first-order model, a multi-order model, etc. can also be selected.

[0245] The circuit structure of the second-order RC equivalent circuit model is shown below:

[0246] Note that the end where the positive pole of the power supply is located is S, and the end where the nega...

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Abstract

The invention discloses a lithium-ion battery SoC (State-of-Charge) estimation method based on improved and self-adaptive dual unscented-Kalman-filters. The method mainly comprises the following steps: 1) establishing a state filter and a parameter filter of a lithium ion power battery based on an equivalent circuit model; 2) coupling the state filter and the parameter filter of the lithium ion power battery based on the equivalent circuit model, and building dual unscented-Kalman-filters; and 3) inputting operation parameters of a to-be-detected lithium ion power battery into the dual unscented-Kalman-filters, and carrying out parameter correction and stage-of-charge (SoC) estimation on a lithium ion power battery equivalent circuit model. According to the method in the invention, the effectiveness of cholesky decomposition is guaranteed, the problem that iteration is stopped due to the fact that a covariance matrix is indefinite caused by reasons such as an initial value error, noisedisturbance, calculation module floating point error and the like is overcome, and the numerical stability of the filtering process and the robustness of the algorithm are enhanced.

Description

technical field [0001] The invention relates to the field of charge state prediction, in particular to a lithium-ion power battery SoC estimation method based on an improved self-adaptive double unscented Kalman filter. Background technique [0002] The state-of-charge (SoC, State-Of-Charge) of the power battery of an electric vehicle is an important parameter of the operating state of the power battery, and it is also a basic parameter for related control of the power battery in the battery management system (BMS, Battery-Management-System) . The estimation accuracy of SoC will directly affect the control effect of BMS. [0003] Under the estimation method based on the equivalent circuit model in the existing SoC estimation method, the Kalman filter algorithm is widely used in microcontrollers because of its tracking characteristics and real-time performance. Due to the nonlinear characteristics of the state equation and observation equation established based on the equiv...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/367G01R31/3842
CPCG01R31/367G01R31/3842
Inventor 余传祥谢延敏桑曌宇杨诗雅刘和平黄鹏黄远胜董治平游逍遥杨生博
Owner CHONGQING UNIV
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