Battery SOH (section of health) estimation method of energy storage power station BMS (battery management system)

An energy storage power station and battery technology, applied in the direction of measuring electricity, measuring electrical variables, measuring devices, etc., can solve problems such as poor accuracy, poor adaptability, and large errors, and achieve the effect of high estimation accuracy and strong adaptability

Inactive Publication Date: 2015-11-04
深圳拓普科新能源科技有限公司
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Problems solved by technology

The most important thing is the poor adaptability. Adjust the parameters on the test battery pack according to the sample test data. The estimated accuracy i...

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  • Battery SOH (section of health) estimation method of energy storage power station BMS (battery management system)

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Embodiment Construction

[0018] In order to fully understand the technical content of the present invention, the technical solution of the present invention will be further introduced and illustrated below in conjunction with specific embodiments.

[0019] The flowchart of the embodiment of the present invention is as figure 1 shown.

[0020] The battery SOH estimation method of the energy storage power station BMS in this embodiment includes the following steps:

[0021] Step S1: power on and run the system;

[0022] Step S2: Collect the real-time data of the battery periodically, and extract the voltage of the battery, the internal resistance of the battery, the temperature of the battery, the charging and discharging current and the charging and discharging power from the real-time battery data;

[0023] Step S3: Combining the rated parameters of the battery and the collected real-time data of the battery, the battery SOH is estimated respectively by the open circuit voltage method, the ampere-ho...

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Abstract

The present invention relates to a battery SOH estimation method of an energy storage power station BMS. The method comprises the following steps: the step S1: electric operation on a system; the step S2: circle and timing collection of battery real time data and extraction of a single voltage, a single internal resistance, a battery temperature, a charge-discharge current and a charge-discharge electric quantity from the real time data; the step S3: respective estimation of a battery SOH through an open-circuit voltage method, an ampere-hour integral method, a Kalman filtering method and a resistance method via the combination of nominal parameter of the battery and collected real time data of the battery; and the step S4: comprehensive calculation of the battery SOH obtained by estimation through a historical data amendment method to work out a model for calculating SOH coefficients, wherein the model for calculating SOH coefficients may be used in subsequent each SOH analytical calculation. The estimation method described herein is strong adaptable to storage batteries under various environments, and has a self-calibration function and high estimation accuracy, wherein the estimated value is approximate to the real value, thereby the real health status of the battery may be relatively accurately reflected.

Description

technical field [0001] The invention relates to a battery life estimation method, in particular to a battery SOH estimation method for an energy storage power station BMS. Background technique [0002] The existing energy storage system BMS usually only monitors and manages the voltage, internal resistance, and temperature of the battery, and some estimates SOC, SOH (section of health, battery health) is usually a negligible quantity, that is, some manufacturers estimate SOH, the error It is also very large, and some errors exceed 50%. The main reasons are that the aging mechanism of the battery is not clear, the use process of the battery is not well grasped, and the calculation methods and algorithms used have not been studied clearly. Second, use the same algorithm for the battery uncertainty. [0003] At present, there are many BMS systems for lithium batteries, lead-acid batteries, and nickel-metal hydride batteries on the market. Some products also analyze and estimat...

Claims

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Application Information

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IPC IPC(8): G01R31/36
Inventor 张志正
Owner 深圳拓普科新能源科技有限公司
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