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Method and system for joint estimation of lithium-ion battery model parameters and SOC with noise immunity

A technology for lithium-ion batteries and model parameters, which is applied in the measurement of electricity, measurement of electrical variables, and complex mathematical operations. It can solve problems such as low SOC estimation accuracy and noise, and achieve high SOC estimation accuracy, broad application prospects, and easy implementation. Effect

Active Publication Date: 2021-08-10
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the inventor found that due to the measurement accuracy of the sensors used in electric vehicles and the complex and harsh electromagnetic interference, the signals such as current and voltage obtained by sampling must contain noise
This will lead to RLS biased model parameter estimation results, which in turn will lead to lower SOC estimation accuracy of the observer or filter

Method used

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  • Method and system for joint estimation of lithium-ion battery model parameters and SOC with noise immunity
  • Method and system for joint estimation of lithium-ion battery model parameters and SOC with noise immunity
  • Method and system for joint estimation of lithium-ion battery model parameters and SOC with noise immunity

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Embodiment 1

[0032] Such as figure 2 As shown, the present embodiment provides a joint estimation method of lithium-ion battery model parameters and SOC with noise resistance, including:

[0033] S101: Perform a pulse charge and discharge test on the lithium-ion battery, obtain the open circuit voltage OCV at different SOCs, and determine the OCV-SOC mapping relationship; specifically, it can be expressed as

[0034]

[0035] In the formula, S k Indicates the SOC of the battery at time k, U oc,k Indicates the open circuit voltage of the battery at time k, d i denote the coefficients of the m-order polynomial obtained by fitting the OCV-SOC relationship offline, .

[0036] S102: Initialize the RC parameters of the lithium-ion battery model and the SOC of the battery.

[0037] S103: Determine the OCV according to the OCV-SOC mapping relationship and SOC, and then use the recursively limited total least squares method to solve the lithium-ion battery equivalent circuit according to th...

Embodiment 2

[0089] The present embodiment provides a joint estimation system with noise resistance lithium-ion battery model parameters and SOC, including:

[0090] (1) OCV-SOC mapping module, which is used to perform pulse charge and discharge tests on lithium-ion batteries, obtain the open circuit voltage OCV at different SOCs, and determine the OCV-SOC mapping relationship;

[0091] (2) an initialization module, which is used to initialize the RC parameters of the lithium-ion battery model and the SOC of the battery;

[0092] (3) RC parameter identification module, which is used to determine the OCV according to the OCV-SOC mapping relationship and SOC, and then according to the statistical characteristics of the real-time measured battery current and voltage signals and the noise contained in them, use the recursively limited overall least squares The multiplication method solves the discrete domain regression equation of the lithium-ion battery equivalent circuit model, and identifie...

Embodiment 3

[0136] This embodiment provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps in the joint estimation method of lithium-ion battery model parameters and SOC with noise resistance as described above are realized .

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Abstract

The invention provides a joint estimation method and system for lithium ion battery model parameters and SOC with noise resistance. Wherein, the method includes performing a pulse charge and discharge test on the lithium-ion battery, obtaining the open circuit voltage OCV at different SOCs, and determining the OCV-SOC mapping relationship; initializing the RC parameters of the lithium-ion battery model and the SOC of the battery; according to the OCV-SOC Mapping relationship and SOC to determine OCV, and then according to the statistical characteristics of the real-time measured battery current and voltage signals and the noise they contain, use the recursive restricted total least squares method to solve the discrete domain regression equation of the lithium-ion battery equivalent circuit model , to identify the RC parameters at the current moment; based on the RC parameters at the current moment and the updated state space expression of the lithium-ion battery system, an observer or filter is selected to estimate the SOC of the lithium-ion battery at the current moment.

Description

technical field [0001] The invention belongs to the field of joint estimation of battery model parameters and SOC, in particular to a method and system for joint estimation of lithium ion battery model parameters and SOC with noise resistance. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] With its unique advantages in energy density, power density, cycle life, and self-discharge rate, lithium-ion batteries have become the first choice for electric vehicle power sources. In order to ensure the safe and efficient operation of the power battery, a battery management system (Battery Management System, BMS) must be equipped to accurately estimate and predict the various internal states of the battery. Among them, accurate state of charge (State of Charge, SOC) estimation can alleviate the user's mileage anxiety, prolong the service life of t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/367G01R31/385G06F17/18
CPCG06F17/18G01R31/367G01R31/385
Inventor 张承慧朱瑞段彬张君鸣张奇
Owner SHANDONG UNIV