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Algorithm based on SOC and SOH joint estimation of power battery

A power battery and joint estimation technology, which is applied in the direction of battery/fuel cell control devices, measuring electricity, electric vehicles, etc., can solve the problems of complex and harsh working conditions of real vehicles, complex electrochemical reaction process of power lithium-ion batteries, etc., and achieve shortening The effect of algorithm running time, avoiding random selection of parameters, and improving algorithm efficiency

Active Publication Date: 2020-03-17
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.

Method used

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  • Algorithm based on SOC and SOH joint estimation of power battery
  • Algorithm based on SOC and SOH joint estimation of power battery
  • Algorithm based on SOC and SOH joint estimation of power battery

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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 battery state-of-charge estimation of an electric vehicle power battery system, in particular to an algorithm based on SOC and SOH joint estimation of apower battery. The method optimizes parameters of an RF algorithm through a TSBSO algorithm so as to optimize an algorithm pruning threshold, the number of pre-test samples and the number of decisiontrees, and the optimized algorithm can quickly find a globally optimal solution and improve the algorithm efficiency. The SOH of the power battery is estimated through the RBM, the RBM is optimized through the WOA, and model parameters are prevented from falling into local optimum and thus the purposes of correcting the maximum available capacity of the battery and improving the SOC estimation precision of the power battery under the full-time working condition are achieved; the SOC of the power battery is estimated through the combination of a TSBSO-RF H-infinity calculation method and filtering, the advantages of the two algorithms are exerted by adopting a linear fusion algorithm, the defects of the two algorithms are avoided and the SOC estimation precision 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 Applications(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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