Lithium battery SOC estimation algorithm based on dual adaptive unscented Kalman filter

A Kalman filter and estimation algorithm technology, which is applied in the direction of instruments, measuring electricity, and measuring electrical variables, etc., can solve the problem of harsh application environment of base stations

Inactive Publication Date: 2016-10-12
WUHAN UNIV OF TECH
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AI Technical Summary

Problems solved by technology

For the wireless communication industry, the base station has increasingly stringent requirements on the application environment, such as temperature, room area and environmental protection. Traditional batteries can no longer meet the requirements.

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  • Lithium battery SOC estimation algorithm based on dual adaptive unscented Kalman filter
  • Lithium battery SOC estimation algorithm based on dual adaptive unscented Kalman filter
  • Lithium battery SOC estimation algorithm based on dual adaptive unscented Kalman filter

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Embodiment Construction

[0091] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0092] A lithium battery SOC estimation algorithm based on double adaptive infinite Kalman filter, including:

[0093] Step 1, initialize the battery open circuit voltage Voc and SOC, and obtain the functional relationship between the battery open circuit voltage Voc and SOC at room temperature;

[0094] The specific method to obtain the functional relationship between the battery open circuit voltage Voc and SOC at room temperature is: use the constant current battery discharge experiment to record the open circuit voltage Voc and the corresponding SOC (using the ampere-hour integration method) value of the battery in the discharge state, and use n The function relationship between the open circuit voltage Voc and the SOC value is obtained by fitting the order curve. The constant current discharge experiment process is as follows:

[0095] First char...

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Abstract

The invention provides a lithium battery SOC estimation algorithm based on dual adaptive unscented Kalman filter. The algorithm utilizes the advantages of a Kalman filter to track the accurate state value of SOC and is free of cumulative errors caused by a traditional time integration method. In particular, through the use of an adaptive unscented Kalman filter, the SOC value of a lithium battery can be estimated in real time; a covariance matrix of process noise and measurement noise can be estimated on-line; this avoids the filter estimation performance degradation of a traditional Kalman filter due to the only assumption that there exists Gaussian white noise in an estimation process and even the problem that filter divergence deviates from the true value, etc. The algorithm provided by the invention conducts filter calculations and utilizes a noise statistic estimator to perform on-line correction to the statistics of the unknown or inaccurate noise in real time so as to realize on-line estimation of a lithium battery SOC and to improve the precision and accuracy of SOC estimation. The convergence speed is greatly enhanced under the condition with erroneous initial SOC.

Description

technical field [0001] The invention belongs to the field of new energy electric vehicles, and specifically relates to a lithium battery SOC estimation algorithm based on a double adaptive infinite Kalman filter, which is especially suitable for vanadium-based power batteries, lithium iron phosphate batteries, ternary lithium batteries, etc. SOC estimation of different types of lithium batteries. Background technique [0002] In recent years, with the energy crisis and environmental problems caused by oil resources and tail gas emissions becoming more and more serious, more and more countries in the world have begun to pay attention to the development of new energy sources, to improve people's awareness of energy conservation and emission reduction, and various countries have also begun to cooperate with each other Actively promote relevant energy support policies. With the development and research of new energy sources, power batteries have become a hot spot for entreprene...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/36
CPCG01R31/367G01R31/3842
Inventor 谢长君曹夏令麦立强全书海曾春年石英黄亮陈启宏张立炎
Owner WUHAN UNIV OF TECH
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