An algorithm based on joint estimation of power battery soc and soh

A technology of power battery and joint estimation, which is applied in battery/fuel cell control devices, measuring electricity, electric vehicles, etc. Algorithm running time, avoid falling into local optimal solution, good effect of robustness

Active Publication Date: 2021-12-31
XIAN UNIV OF SCI & TECH
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Problems solved by technology

[0005] The internal electrochemical reaction process of the power lithium-ion battery is complex, and the actual vehicle working conditions are complex and harsh. There are many methods for estimating the state of charge as an invisible state quantity, but each single method has both advantages and disadvantages.

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  • An algorithm based on joint estimation of power battery soc and soh
  • An algorithm based on joint estimation of power battery soc and soh
  • An algorithm based on joint estimation of power battery soc and soh

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Embodiment Construction

[0053] In order to further explain the technical means and effects of the present invention to achieve the intended purpose of the invention, the specific implementation, structure, features and effects of the application according to the present invention will be described in detail below in conjunction with the accompanying drawings and preferred embodiments. .

[0054] An algorithm based on joint estimation of power battery SOC and SOH is characterized in that it includes two parts: offline data extraction and online data acquisition.

[0055] The specific steps of the offline data extraction are as follows:

[0056] 2.1. Under the cycle test condition, the data of the power lithium-ion battery is collected offline, and the offline data is used to train the TSBSO-RF model, and the construction of the offline SOC estimation part model is completed;

[0057] 2.2. Under the cycle test condition, the data of the power lithium-ion battery is collected offline, and the offline d...

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Abstract

The invention relates to the technical field of electric vehicle power battery system battery charge state estimation, specifically an algorithm based on the joint estimation of power battery SOC and SOH. The method optimizes the parameters of the RF algorithm by including the TSBSO algorithm to achieve the algorithm pruning threshold, The number of pre-test samples and the number of decision trees are optimized. The optimized algorithm can quickly find the global optimal solution and improve the efficiency of the algorithm; estimate the SOH of the power battery through RBM, optimize the RBM with WOA, and avoid the model parameters from falling into local optimum, so as to achieve The purpose of correcting the maximum available capacity of the battery and improving the accuracy of the SOC estimation of the power battery under full-time working conditions; through the TSBSO-RF algorithm and the H ∞ The filter joint estimates the state of charge of the power battery, and the linear fusion algorithm is used to take advantage of the advantages of the two algorithms and avoid the shortcomings of the two algorithms, so that the SOC estimation accuracy of the power battery is higher.

Description

technical field [0001] The invention relates to the technical field of electric vehicle power battery system battery charge state estimation, in particular to an algorithm based on joint estimation of power battery SOC and SOH. Background technique [0002] Lithium-ion power batteries have the advantages of high energy density, high power density, long service life, high safety, high reliability, low self-discharge rate, light weight and no memory. Due to the irreversible overcharge and overdischarge process of lithium-ion power batteries, and the drastic changes in external characteristics with temperature changes, it is necessary to be equipped with a complete battery management system (BMS) in order to be able to feedback and control the real-time status of the battery pack to ensure power. The safety and reliability of the battery pack. [0003] The state of charge (SOC) is the most important parameter in the BMS, and it is also the most important part of the battery st...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/367G01R31/392G01R31/3842B60L58/12B60L58/16
CPCG01R31/367G01R31/392G01R31/3842B60L58/12B60L58/16Y02T10/70
Inventor 寇发荣王思俊王甜甜洪峰张海亮
Owner XIAN UNIV OF SCI & TECH
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