Method for carrying out battery parameter identification and precision optimization by adopting simulated annealing method

A simulated annealing method and battery parameter technology, applied in multi-objective optimization, design optimization/simulation, electrical measurement, etc., can solve the problems of time-varying systems that cannot track parameters, poor accuracy of parameter identification results, and cannot track time-varying parameters. Achieve good application value, improve the accuracy of identification, and achieve strong operability

Pending Publication Date: 2021-12-10
东方电气集团科学技术研究院有限公司 +1
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Problems solved by technology

When performing online parameter identification of battery energy storage systems, due to the limitation of online data acquisition, there is only one set of voltage and current data at each moment; at the same time, the setting of initial parameter values ​​will affect the identification results. When it is reasonable, the accuracy of parameter identification results is often poor, and it cannot track time-varying parameters well.
In the currently commonly used lithium battery parameter identification algorithm, the recursive least squares algorithm will cause data saturation and other problems as the amount of data increases during the parameter identification process, and cannot track the parameters well for time-varying systems.
The deviation-compensated least-squares algorithm requires the system input to be stationary and ergodic, which is difficult to satisfy in practice.

Method used

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  • Method for carrying out battery parameter identification and precision optimization by adopting simulated annealing method

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Embodiment 1

[0029] As a specific real-time solution of the present invention, such as figure 1 , this embodiment discloses a method for battery parameter identification and precision optimization using simulated annealing, including model building steps, testing steps, initial value calculation steps and simulated annealing steps, using simulated annealing for battery parameter identification and precision optimization The method overcomes the deficiency of low accuracy of the existing battery parameter identification, specifically:

[0030] The model building step is to set up a first-order equivalent circuit model for describing the static performance of the battery and a first-order equivalent circuit model for dynamic performance Among them, R 1 is the polarization internal resistance of the battery, C 1 is the polarization capacitance of the battery;

[0031] Then the polarization voltage U 1 (t)=A*U 1 (t-1)+B*I(t), the terminal voltage U(t) of the first-order equivalent circ...

Embodiment 2

[0037] As a more preferred real-time solution of the present invention, such as figure 1 , this embodiment discloses a method for battery parameter identification and precision optimization using the simulated annealing method, specifically:

[0038] The model building step is to set up a first-order equivalent circuit model for describing the static performance of the battery and a first-order equivalent circuit model for dynamic performance Among them, R 1 is the polarization internal resistance of the battery, C 1 is the polarization capacitance of the battery;

[0039] Then the polarization voltage U 1 (t)=A*U 1 (t-1)+B*I(t), the terminal voltage U(t) of the first-order equivalent circuit model RC loop=OCV(t)-*U 1 (t)-R 0 I(t), where R 0is the ohmic internal resistance of the battery, which can be obtained by the formula R 0 = U / I is calculated, OCV(t) is the open circuit voltage of the RC loop, and I(t) is the current of the loop;

[0040] Here it is assumed t...

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Abstract

The invention discloses a method for carrying out battery parameter identification and precision optimization by adopting a simulated annealing method, which relates to the technical field of new energy. The method comprises a model building step, a test step, an initial value calculation step and a simulated annealing step, is based on a simulated annealing algorithm, and overcomes the defect that a traditional hill-climbing algorithm can be caught in a local optimal solution, According to the disclosed method, an accurate experiment result can be quickly obtained in a short time on the premise of reducing resource occupation, and the parameter identification precision is improved.

Description

technical field [0001] The invention relates to the field of new energy technologies, in particular to a method for battery parameter identification and precision optimization using a simulated annealing method. Background technique [0002] In the field of battery management technology, in order to achieve accurate battery management, various battery state estimations are often required, including battery remaining capacity estimation (SOC), battery state of health estimation (SOH), battery state of power estimation (SOP) and battery energy state estimation (SOE), etc., and the estimation of these states often needs to obtain real-time key parameters of the battery. [0003] The quality of the battery parameter identification algorithm directly determines the accuracy and reliability of the identification results. When performing online parameter identification of battery energy storage systems, due to the limitation of online data acquisition, there is only one set of vol...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/367G01R31/385G01R31/388G06F30/27G06N3/00
CPCG01R31/367G01R31/385G01R31/388G06F30/27G06N3/006G06F2111/06G06F2119/08G06F2111/08
Inventor 阮晓莉张中伟李明科李玉龙
Owner 东方电气集团科学技术研究院有限公司
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