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Power battery multi-dimensional fusion SOC and SOH online joint estimation method

A power battery, multi-dimensional technology, applied in the direction of measuring electricity, measuring electrical variables, measuring devices, etc., can solve the problems of cumbersome work and insufficient accuracy of SOC and SOH, and achieve the goal of improving overall operating speed and efficiency, improving compatibility, The effect of reducing complexity

Active Publication Date: 2020-06-26
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

[0004] In order to solve the problem of insufficient precision and cumbersome work of estimating SOC and SOH separately, the present invention provides a multi-dimensional fusion SOC and SOH online joint estimation method for power batteries, Real-time and accurate assessment of the state of charge and state of health of electric vehicle power batteries

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  • Power battery multi-dimensional fusion SOC and SOH online joint estimation method
  • Power battery multi-dimensional fusion SOC and SOH online joint estimation method
  • Power battery multi-dimensional fusion SOC and SOH online joint estimation method

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Embodiment Construction

[0022] The present invention will be described in further detail below in conjunction with the accompanying drawings. It should be understood that the examples described here are only used to explain the present invention, not to limit the present invention.

[0023] The implementation of the present invention provides a method for online joint estimation of power battery multi-dimensional fusion SOC and SOH, the flow chart of the method is as follows figure 1 As shown, it specifically includes the following steps: Step 1: The present invention builds a second-order RC circuit based on the Thevenin equivalent circuit model of the battery. This model more accurately simulates the dynamic characteristics of the battery and can be used for joint estimation of battery SOC and SOH . Such as figure 2 Shown, including: load current I, battery open circuit voltage U oc , the polarization resistance R 1 and R 2 , polarized capacitance C 1 and C 2 , ohmic internal resistance R 0...

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Abstract

The invention relates to a power battery multi-dimensional fusion SOC and SOH online joint estimation method. According to the invention, the method comprises the steps: selecting a dual extended Kalman filter (Dual-EKF) method and a multi-dimensional fusion estimation method to solve the problems of large workload, low estimation precision and the like of separately designing SOC and SOH estimation systems; obtaining related data through a mixed pulse power performance test, and establishing second-order RC equivalent circuit model identification model parameter values R1, R2, C1 and C2; performing online accurate estimation on three state parameters of SOC, internal resistance and rated capacity by using a Dual-EKF method so as to determine SOHRi and SOHQi; and finally, calculating health state weight coefficients alpha R and alpha Q of two dimensions by using a normalized least square method, and performing fusing to obtain a comprehensive health state value SOHTi; finally, accurately estimating the SOH value of the power battery, achieving the SOC and SOH combined online estimation, and improving the estimation precision of the SOC and SOH values. Therefore, the applicability of the method to an embedded power battery management system is high.

Description

technical field [0001] The invention belongs to the field of real-time estimation of power battery state parameters in a power battery management system, and in particular relates to a method for online joint estimation of power battery multi-dimensional fusion SOC and SOH. Background technique [0002] Accurate online real-time estimation of battery state of charge SOC and battery state of health SOH is particularly important for real-time control of power battery working process. SOC reflects the current remaining capacity of the battery, and SOH reflects the current service life of the battery. At present, most of the power battery SOC and SOH estimations are studied separately. The online estimation methods of SOC and SOH mainly include: extended Kalman filter EKF, neural network method, fuzzy logic control method. Among them, EKF is a method based on the battery equivalent model. Its principle is relatively simple and its complexity is low. The estimation accuracy of ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/367G01R31/392G01R31/388
CPCG01R31/367G01R31/392G01R31/388Y02T10/70
Inventor 李玉芳张玉梅徐国放徐炳钦章波
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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