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Combined estimation method for lithium ion battery state of charge, state of health and state of function

A lithium-ion battery, state of charge technology, applied in the estimation of health state and power state, battery state of charge field, can solve the problem of less research on SOF estimation method, and achieve the effect of improving the state estimation effect

Active Publication Date: 2016-02-03
TSINGHUA UNIV
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, there are few studies on SOF estimation methods

Method used

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  • Combined estimation method for lithium ion battery state of charge, state of health and state of function
  • Combined estimation method for lithium ion battery state of charge, state of health and state of function
  • Combined estimation method for lithium ion battery state of charge, state of health and state of function

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Embodiment Construction

[0024] The combined estimation method of the state of charge, state of health and power state of the lithium-ion battery of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0025] Firstly, explain some nouns involved in the description of the present invention.

[0026] The "online" mentioned in the description of the present invention refers to the state that the lithium-ion battery is in actual work and use, such as the state installed in the electric vehicle, the online state is a complex dynamic working condition, and the current and / or voltage are uncertain. Change with time. This online state is different from the state in which lithium-ion batteries are charged and discharged by charging and discharging equipment in the laboratory, also known as the "offline" state. In this state, the charging and discharging current and / or voltage of the battery is controlled by the charging and discharging equipment to fo...

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Abstract

The invention provides a combined estimation method for lithium ion battery state of charge, state of health and state of function. The combined estimation method comprises the steps that the state of he---alth of a battery is estimated online: open circuit voltage and internal resistance are identified online by adopting a recursive least square method with a forgetting factor, the state of charge is indirectly acquired according to a pre-established OCV-SOC corresponding relation, and then the size of battery capacity is estimated according to cumulative charge and discharge electric charge between two SOC points; the state of charge of the battery is estimated online: the state of charge of the battery is estimated by adopting the Kalman filter algorithm based on a two-order RC equivalent circuit model, and the battery capacity parameter in the Kalman filter algorithm is updated according to the estimation result of battery capacity; and the state of function of the battery is estimated online: the maximum chargeable and dischargeable current is calculated based on the voltage limit and the current limit of the battery according to internal resistance obtained by online identification, and then the maximum chargeable and dischargeable function can be obtained through further calculation.

Description

technical field [0001] The invention belongs to the technical field of battery management, and in particular relates to a method for estimating the state of charge, the state of health and the state of power of a battery. Background technique [0002] Lithium-ion battery state includes state of charge (SOC, StateofCharge), state of health (SOH, StateofHealth) and power state (SOF, StateofFunction). Among them, SOC reflects the remaining power of the battery, SOH reflects the aging condition of the battery, and SOF reflects the available power that the battery can provide. The current state of the battery will affect the energy management decision of the battery management system (BMS, Battery Management System) for electric vehicles, such as battery pack charging of pure electric vehicles, battery pack energy distribution of hybrid electric vehicles, etc. Therefore, battery state estimation is one of the most important functions of BMS. [0003] The state of charge SOC ref...

Claims

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Application Information

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IPC IPC(8): G01R31/36
Inventor 沈萍卢兰光欧阳明高任东生冯旭宁
Owner TSINGHUA UNIV
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