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SOC (Stress Optical Coefficient) estimation method for power batteries based on RC (Remote Control) equivalent model

An equivalent model and power battery technology, applied in calculation, measurement of electricity, measurement of electrical variables, etc., can solve the problems of inability to estimate in real time and high precision of measurement equipment

Active Publication Date: 2013-03-20
SHANDONG ACAD OF SCI INST OF AUTOMATION
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Problems solved by technology

The ampere-hour measurement method focuses on application occasions, online, convenient, and accurate, but requires high-precision measuring equipment; the open-circuit voltage method is only suitable for estimation after the battery has been left for a long enough time, and cannot be estimated in real time; the neural network can be estimated online, but the disadvantage is that it needs Extensive training data for similar batteries

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  • SOC (Stress Optical Coefficient) estimation method for power batteries based on RC (Remote Control) equivalent model
  • SOC (Stress Optical Coefficient) estimation method for power batteries based on RC (Remote Control) equivalent model
  • SOC (Stress Optical Coefficient) estimation method for power batteries based on RC (Remote Control) equivalent model

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Embodiment Construction

[0044] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0045] Such as figure 2 Described, the implementation method example of the present embodiment:

[0046] 1. The parameters of the data model identified through the charging and discharging experimental data of the power battery, R pa =0.02844, C pa =1054.85,R 0 =0.07,τ pa = R pa C pa =30, we know that A 0 , B 0 、C 0 , A 0 , B 0 、C 0 Respectively A when k=0 k , B k 、C k ;

[0047] 2. Initial calculation, when k=0, according to the initial value x of the state variable 0 The statistical properties of can be known:

[0048] x o + = E ( x o ) , E(x 0 ) for x 0 expectations; P 0 - = E [ ...

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Abstract

The invention discloses an SOC (Stress Optical Coefficient) estimation method for power batteries based on a RC (Remote Control) equivalent model, which comprises the following steps: determining an estimation equation based on the RC equivalent model and expanding an estimation method of a Kalman filter. The SOC estimation method has the beneficial effects that the charge states of the power batteries can be accurately estimated, and as SOC values directly reflect the states of the batteries, the maximum discharge current of each battery can be limited, the driving mileage of an electric vehicle can be forecasted; and the performance difference among all the batteries in a battery pack can be identified according to the SOC values of the batteries, and equalizing charging is performed to keep the uniformity of battery performance and finally achieve the purpose of prolonging the service lives of the batteries.

Description

technical field [0001] The invention belongs to the field of pure electric vehicle battery management, and relates to a power battery SOC estimation method based on an RC equivalent model. Background technique [0002] As the power source of electric vehicles, the power battery is a key factor affecting the performance of the electric vehicle. It will have a direct impact on the mileage, acceleration capability, and maximum gradeability. Battery state of charge (SOC) estimation is the core and difficult point of battery management system research. The nonlinear characteristics of power batteries make it difficult for many filtering methods to obtain accurate estimation results. Therefore, it is necessary to establish a suitable mathematical model to characterize the external characteristics of the battery. . The better the consistency between the battery model and the characteristics of the power battery, the more accurate results can be obtained when using the filtering al...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/36G06F17/50
Inventor 侯恩广乔昕李小伟刘广敏李杨崔立志贺冬梅王知学
Owner SHANDONG ACAD OF SCI INST OF AUTOMATION
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