CN113009361A - Battery state of charge estimation method based on open circuit voltage calibration - Google Patents
Battery state of charge estimation method based on open circuit voltage calibration Download PDFInfo
- Publication number
- CN113009361A CN113009361A CN202110273098.8A CN202110273098A CN113009361A CN 113009361 A CN113009361 A CN 113009361A CN 202110273098 A CN202110273098 A CN 202110273098A CN 113009361 A CN113009361 A CN 113009361A
- Authority
- CN
- China
- Prior art keywords
- battery
- terminal voltage
- ecm
- actual
- voltage
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/385—Arrangements for measuring battery or accumulator variables
- G01R31/387—Determining ampere-hour charge capacity or SoC
- G01R31/388—Determining ampere-hour charge capacity or SoC involving voltage measurements
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
Abstract
The invention relates to a battery state-of-charge estimation method based on open-circuit voltage calibration, which takes the difference value of the terminal voltage of a battery equivalent circuit model and the actual battery terminal voltage as the input of a feedback correction controller, regulates and controls the working state of the battery equivalent circuit model through the current value output by the feedback correction controller, and ensures that the terminal voltage of the battery equivalent circuit model changes along with the actual battery terminal voltage in real time, thereby continuously calibrating the open-circuit voltage of the battery equivalent circuit model and acquiring the actual battery state-of-charge estimation value. The method has the advantages of high estimation precision, simplicity, feasibility and easy realization.
Description
Technical Field
The invention belongs to the field of battery management systems of electric vehicles, and particularly relates to a battery state of charge estimation method based on open-circuit voltage calibration.
Background
The battery pack is an important part of a pure electric vehicle and is generally composed of hundreds of single batteries. However, during the operation of the electric vehicle, the battery pack life and capacity are greatly reduced due to the difference of the State-of-Charge (SOC), so that the cost and performance of the electric vehicle cannot meet the use requirements. In addition, the Battery SOC estimation is a decision basis for a Battery Management System (BMS), which directly reflects the remaining driving range of the electric vehicle. Therefore, the SOC of the battery is accurately and efficiently estimated, and the method has important significance for improving the performance of a battery system and ensuring safe and reliable operation of the pure electric vehicle.
The battery SOC is the ratio of the current available capacity of the battery to the rated capacity, and cannot be directly measured by a sensor. In addition, the driving condition of the electric vehicle is complex, and repeated acceleration and deceleration of the electric vehicle causes great difficulty in estimating the SOC of the battery. The current common methods include an open-Circuit voltage method, an ampere-hour integration method, an Equivalent-Circuit Model (ECM) estimation method, and a data-driven estimation method. Researchers mainly research SOC estimation methods based on equivalent circuit models and data driving, and the SOC estimation methods mainly comprise methods of extended Kalman, open-circuit voltage recursion, joint estimation, neural networks, support vector machines and the like. However, the above method is very complicated, and the control cost is high, which is not suitable for direct application in industrial fields. In addition, the accuracy of the ampere-hour integration method is limited by the measurement accuracy of the sensor, and accumulated errors occur in the use process, so that the SOC estimation accuracy is gradually reduced, and the SOC of the battery cannot be accurately obtained.
Disclosure of Invention
The invention aims to provide a battery state of charge estimation method based on open-circuit voltage calibration, which is high in estimation accuracy, simple, feasible and easy to implement.
In order to achieve the purpose, the invention adopts the technical scheme that: a battery state-of-charge estimation method based on open-circuit voltage calibration is characterized in that a difference value between the terminal voltage of a battery ECM and the actual battery terminal voltage is used as the input of a feedback correction controller, the working state of the battery ECM is regulated and controlled through a current value output by the feedback correction controller, the terminal voltage of the battery ECM is made to change along with the actual battery terminal voltage in real time, the open-circuit voltage of the battery ECM is continuously calibrated, and an actual battery state-of-charge estimation value is obtained.
Further, the method for estimating the state of charge of the battery based on open-circuit voltage calibration comprises the following steps:
establishing a battery equivalent circuit model ECM;
designing a feedback correction controller for terminal voltage calibration to ensure that the terminal voltage of the battery ECM always changes along with the terminal voltage of the actual battery, thereby simulating the working state of the actual battery;
acquiring the actual battery terminal voltage by using a battery charge and discharge tester, and inputting the difference value between the terminal voltage of the battery ECM and the actual battery terminal voltage into a feedback correction controller;
inputting the current value output by the feedback correction controller into the battery ECM, and correcting the terminal voltage output by the battery ECM;
through continuous feedback correction, the terminal voltage of the battery ECM approaches to the actual battery terminal voltage, even if the difference value of the terminal voltage and the actual battery terminal voltage is smaller than a set threshold value, so that the actual battery working state is simulated, and the estimated value of the battery charge state is obtained.
Further, continuously carrying out feedback regulation on the input current of the battery ECM according to the terminal voltage data of the actual battery, and enabling the difference value between the terminal voltage of the battery ECM and the terminal voltage of the actual battery to be smaller than a set threshold value, so that the open-circuit voltage of the battery ECM is continuously calibrated; in the process, the step response of the battery ECM is approximate to that of the actual battery, so that the running state of the battery ECM, including the working current, the working voltage and the SOC, is approximately equal to that of the actual battery, and the estimated value of the SOC of the actual battery is obtained.
Further, the battery ECM adopts a second-order RC battery ECM, firstly, an OCV-SOC curve of the battery is obtained through fitting according to the obtained pulse discharge curve, and the calculation formula is as follows:
whereinV OCV Is the open-circuit voltage of the battery ECM,V m the terminal voltage of the second order RC battery ECM,V R0 in the second order RC battery ECMR 0 The voltage of (a) is set to be,V 1 、V 2 the voltages of 1-order RC links and 2-order RC links are respectively obtained, RC parameters in the battery ECM can be obtained through interpolation, and the calculation formula is as follows:
further, the accuracy of the established model of the battery ECM is tested, during testing, the actual battery and the battery ECM are respectively tested under the pulse charging and discharging working condition of the amplitude 1/3C, and terminal voltage responses of the actual battery and the battery ECM are compared.
Further, a Proportional-Integral (PI) feedback controller and a Sliding-mode-Control (SMC) feedback controller are respectively adopted as a feedback correction controller to perform feedback regulation on the input current of the battery ECM, which are respectively as follows:
whereinK p Is a coefficient of proportionality that is,K i in order to be the integral coefficient of the light,V a in order to be the actual terminal voltage of the battery,V m for the terminal voltage of the battery ECM,I Bat is the input current of the battery ECM.
Further, a battery SOC estimation precision test platform is set up, the obtained battery current and terminal voltage data are loaded into the battery SOC estimation precision test platform, battery SOC estimation results are obtained, the battery SOC estimation results respectively comprise estimation results based on a PI feedback controller and an SMC feedback controller, and the battery SOC estimation precision of different feedback correction controllers under different working conditions is analyzed.
Further, the battery SOC estimation accuracy test platform uses a battery charge and discharge tester to respectively perform charge and discharge tests on the single battery under the electrical working conditions obtained by the american city cycling condition (UDDS) and the New European Driving Cycle (NEDC), and analyzes the battery SOC estimation accuracy of different feedback correction controllers under different working conditions: compared with the SOC estimation precision based on the PI feedback controller, the SOC estimation precision based on the SMC feedback controller is higher; compared with SOC estimation accuracy under different working conditions, the maximum estimation error of the battery under the NEDC electrical working condition is larger, and the maximum estimation error under the UDDS working condition is smaller.
Compared with the prior art, the invention has the following beneficial effects: the method mainly realizes the estimation of the state of charge of the battery through the battery ECM and a feedback correction controller, takes the difference value between the terminal voltage of the battery ECM and the actual battery terminal voltage as the input of the feedback correction control, and outputs a current value as the input of the battery ECM to calibrate the working state of the battery ECM, so that the terminal voltage of the battery ECM approaches to the actual battery terminal voltage, thereby obtaining the estimated value of the state of charge of the battery. The method can lead the terminal voltage output by the battery ECM to change along with the actual battery terminal voltage in real time, thereby continuously calibrating the open-circuit voltage of the battery ECM, obtaining the actual SOC of the battery, and leading the obtained SOC error of the battery to be within about 4 percent and having higher estimation precision. In addition, the method has low requirement on the complexity of a control circuit, is simple and feasible, is easy to realize, can efficiently and stably operate in an embedded system, and is applied to the fields of energy storage power supplies, power batteries of electric vehicles, power supplies of consumer electronics and the like.
Drawings
Fig. 1 is a schematic diagram of the operation of an embodiment of the present invention.
Fig. 2 is an equivalent circuit model of an n-order RC battery in the embodiment of the present invention.
FIG. 3 is a graph of a battery model dynamic response in an embodiment of the invention.
Fig. 4 is a battery terminal voltage variation graph based on a PI feedback controller under the UDDS current condition in the embodiment of the present invention.
FIG. 5 is a diagram of a PI feedback controller based battery SOC estimation under UDDS current conditions in an embodiment of the present invention.
Fig. 6 is a graph of variation of battery terminal voltage based on a PI feedback controller under the NEDC current condition in the embodiment of the present invention.
FIG. 7 is a diagram of a PI feedback controller based battery SOC estimation under the NEDC current condition in an embodiment of the present invention.
Fig. 8 is a graph of the variation of the terminal voltage of the battery based on the SMC feedback controller under the UDDS current condition in an embodiment of the present invention.
FIG. 9 is a graph of a battery SOC estimation based on an SMC feedback controller under UDDS current conditions in an embodiment of the present invention.
Fig. 10 is a graph of variation of battery terminal voltage based on SMC feedback controller under NEDC current conditions in an embodiment of the present invention.
FIG. 11 is a graph of a battery SOC estimation based on an SMC feedback controller under a NEDC current condition in an embodiment of the present invention.
In the figure: the method comprises the following steps of 1-battery charge and discharge tester (BTS 5V12A), 2-18650 type ternary lithium battery, 3-battery equivalent circuit model, 4-feedback correction controller, 11-self-discharge resistor, 12-battery capacitor, 13-battery internal resistance, 14-first-order RC of battery, and 15-nth-order RC of battery.
Detailed Description
In order to more clearly demonstrate the content and features of the present invention, a specific implementation process of the battery state of charge estimation method based on open-circuit voltage calibration will be described below with reference to the accompanying drawings and technical solutions. The invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein.
The implementation principle of the method for estimating the state of charge of the battery based on open-circuit voltage calibration in the embodiment is shown in fig. 1, wherein a test system is respectively composed of a battery charge and discharge tester, a battery ECM and a feedback correction controller. The specific working process is as follows: firstly, initializing a battery SOC initial value, then adjusting the input current of the battery ECM in real time by a feedback correction controller according to the difference value between the terminal voltage output by the battery ECM and the actual battery terminal voltage obtained by measurement, enabling the terminal voltage output by the battery ECM to change along with the actual battery terminal voltage all the time, further obtaining the calibrated open-circuit voltage of the battery ECM, and finally obtaining the battery SOC value in the battery ECM, namely considering the battery SOC estimated value as the actual battery SOC estimated value.
The method concretely comprises the following steps:
(a) analyzing the working principle of the battery SOC estimation method based on open-circuit voltage calibration according to the figure 1;
(b) establishing a second-order RC battery ECM of the battery by taking a 18650 type ternary lithium battery as an experimental object;
(c) carrying out charge and discharge tests on the 18650 type ternary lithium battery by using a battery charge and discharge tester, and respectively acquiring experimental data under the UDDS and NEDC electrical working conditions;
(d) testing the working performance of the battery state of charge estimation method based on open circuit voltage calibration, which is provided by applying the experimental data acquired in the step (c) respectively;
in the present embodiment, step (a) includes the following processes:
a. referring to fig. 1, a battery charge/discharge tester performs charge/discharge tests on a 18650 type ternary lithium battery to simulate a normal operating state of the battery, and a battery SOC estimation method based on open-circuit voltage calibration makes the terminal voltage of the battery ECM approximately equal to the terminal voltage of the actual battery by continuously correcting the input current of the battery ECM according to the terminal voltage data of the actual battery, thereby obtaining a calibrated open-circuit voltage and obtaining the actual SOC of the battery. In the process, as the step response of the battery ECM is similar to that of an actual battery, the running state of the battery ECM, including the working current, the working voltage and the SOC, is similar to that of the actual battery, and then the actual battery SOC value is obtained.
In this embodiment, step (b) of establishing the battery ECM according to fig. 2, takes the second-order RC battery ECM as an example to implement the proposed battery SOC estimation method, and the establishing of the battery ECM includes the following processes:
b1, firstly, designing parameters of an RC equivalent circuit in the ECM: the pulse discharge test is designed to discharge the battery according to a fixed capacity percentage, and the battery is kept still to enable the open-circuit voltage of the battery to tend to be stable when the discharge is finished, so that the circulation is carried out until the battery is emptied. And secondly, respectively carrying out the tests at different temperatures to obtain pulse discharge curves of the battery at different temperatures.
b2, firstly fitting the obtained pulse discharge curve to obtain a battery OCV-SOC curve, and finally obtaining the following formula:
whereinV OCV Is the open-circuit voltage of the battery ECM,V m the terminal voltage of the second order RC battery ECM,V R0 in the second order RC battery ECMR 0 The voltage of (a) is set to be,V 1、V 2the voltages of 1 and 2-order RC links are respectively, and RC parameters in the ECM can be obtained through interpolation, so that a formula (3) is determined:
b3, testing the model accuracy of the established battery ECM, namely respectively carrying out charge and discharge tests on the actual battery and the ECM under the working condition of amplitude 1/3C pulse charge and discharge, and comparing terminal voltage responses of the actual battery and the ECM, wherein the result is shown in figure 3.
In this embodiment, in the step (c), a battery charge and discharge tester is used to charge and discharge the 18650 type ternary lithium battery, and experimental data under UDDS and NEDC electrical conditions are respectively obtained. The UDDS and the NEDC electrical working conditions are respectively acquired by adopting Advisor based on actual electric vehicle parameter simulation, and the experimental steps for acquiring the running state data of the battery working process are as follows: firstly, a battery charge-discharge tester is adopted to charge 18650 at 25 ℃ at 1C, and when the charge cut-off voltage reaches 4.2V, the battery is kept still for 1 h. And then loading the battery with the UDDS and the NEDC working conditions respectively to continuously and circularly charge and discharge the battery, and standing for a period of time after the battery is discharged to the cut-off voltage to finish the experiment. The 18650 type ternary lithium battery terminal voltage responses under the two working conditions are respectively shown in fig. 4, fig. 8, fig. 6 and fig. 10.
In this embodiment, the experimental data obtained in step (c) are respectively applied in step (d) to test the working performance of the proposed battery state of charge estimation method, and the specific flow is as follows:
d1, designing a feedback correction controller for terminal voltage calibration, so that the voltage of the output end of the battery ECM always changes along with the voltage of the actual battery terminal, thereby simulating the working state of the actual battery and acquiring the SOC of the battery. The invention respectively adopts a PI controller and an SMC controller to carry out feedback regulation on the input current of the battery ECM, and the feedback regulation is respectively as follows:
whereinK p Is a coefficient of proportionality that is,K i in order to be the integral coefficient of the light,V a in order to be the actual terminal voltage of the battery,V m for the terminal voltage of the battery ECM,I Bat is the input current of the battery ECM.
d2, building the proposed battery SOC estimation precision test platform according to the figure 1, and loading the acquired battery current and terminal voltage data into a battery state of charge estimation simulation platform based on open circuit voltage calibration to obtain a battery SOC estimation result, wherein the test results based on a PI feedback controller are respectively shown in figures 4, 5, 6 and 7, and the test results based on an SMC feedback controller are respectively shown in figures 8, 9, 10 and 11.
d3, analyzing the estimation accuracy of the battery SOC of different feedback correction controllers under different working conditions: from the estimation results in fig. 5, 7, 9 and 11, the SOC estimation accuracy based on the SMC feedback controller is higher, not exceeding 4.8% at the maximum, while the SOC estimation accuracy based on the PI feedback controller is slightly worse, not exceeding 8.8% at the maximum; and respectively comparing SOC estimation accuracy under different working conditions, wherein the result shows that the maximum estimation error of the battery under the NEDC electrical working condition is larger, and the maximum estimation error under the UDDS working condition is smaller.
The battery state of charge estimation method based on open-circuit voltage calibration provided by the invention ensures the estimation precision of the battery SOC and reduces the estimation difficulty, thereby reducing the cost of a control system and reducing the complexity of battery state of charge estimation.
It will be apparent to those skilled in the art that various modifications can be made in the invention without departing from the scope of the invention. Therefore, if modifications of the present invention are within the scope of the claims of the present invention and their equivalents, the present invention also includes such modifications.
Claims (8)
1. A battery state-of-charge estimation method based on open-circuit voltage calibration is characterized in that a difference value between a terminal voltage of a battery equivalent circuit model and an actual battery terminal voltage is used as an input of a feedback correction controller, and a working state of the battery equivalent circuit model is regulated and controlled through a current value output by the feedback correction controller, so that the terminal voltage of the battery equivalent circuit model changes along with the actual battery terminal voltage in real time, the open-circuit voltage of the battery equivalent circuit model is continuously calibrated, and an actual battery state-of-charge estimation value is obtained.
2. The method of claim 1, comprising the steps of:
establishing a battery equivalent circuit model ECM;
designing a feedback correction controller for terminal voltage calibration to ensure that the terminal voltage of the battery ECM always changes along with the terminal voltage of the actual battery, thereby simulating the working state of the actual battery;
acquiring the actual battery terminal voltage by using a battery charge and discharge tester, and inputting the difference value between the terminal voltage of the battery ECM and the actual battery terminal voltage into a feedback correction controller;
inputting the current value output by the feedback correction controller into the battery ECM, and correcting the terminal voltage output by the battery ECM;
through continuous feedback correction, the terminal voltage of the battery ECM approaches to the actual battery terminal voltage, even if the difference value of the terminal voltage and the actual battery terminal voltage is smaller than a set threshold value, so that the actual battery working state is simulated, and the estimated value of the battery charge state is obtained.
3. The method of claim 2, wherein the input current of the battery ECM is continuously feedback-regulated according to the terminal voltage data of the actual battery, so that the difference between the terminal voltage of the battery ECM and the actual battery terminal voltage is smaller than a predetermined threshold, thereby obtaining the calibrated battery open-circuit voltage of the battery ECM; in the process, the step response of the battery ECM is approximate to that of the actual battery, so that the running state of the battery ECM, including the working current, the working voltage and the SOC, is approximately equal to that of the actual battery, and the estimated value of the SOC of the actual battery is obtained.
4. The method for estimating the state of charge of the battery based on the open-circuit voltage calibration as claimed in claim 2, wherein the battery ECM adopts a second-order RC battery ECM, firstly, a battery OCV-SOC curve is obtained by fitting the obtained pulse discharge curve, and the calculation formula is as follows:
whereinV OCV Is the open-circuit voltage of the battery ECM,V m the terminal voltage of the second order RC battery ECM,V R0 in the second order RC battery ECMR 0 The voltage of (a) is set to be,V 1、V 2the voltages of 1-order RC links and 2-order RC links are respectively obtained, RC parameters in the battery ECM can be obtained through interpolation, and the calculation formula is as follows:
5. the method of claim 4, wherein the accuracy of the established model of the battery ECM is tested, and the actual battery and the battery ECM are tested under 1/3C pulse charging and discharging conditions respectively, and the terminal voltage responses of the two are compared.
6. The method of claim 2, wherein the PI feedback controller and the SMC feedback controller are respectively used as feedback correction controllers to perform feedback regulation on the input current of the battery ECM, and the method comprises:
whereinK p Is a coefficient of proportionality that is,K i in order to be the integral coefficient of the light,V a in order to be the actual terminal voltage of the battery,V m for the terminal voltage of the battery ECM,I Bat is the input current of the battery ECM.
7. The method for estimating the state of charge of the battery based on the open-circuit voltage calibration as claimed in claim 6, wherein a battery SOC estimation accuracy test platform is built, and the obtained battery current and terminal voltage data are loaded into the battery SOC estimation accuracy test platform to obtain a battery SOC estimation result, and the method comprises analyzing the battery SOC estimation accuracy of different feedback correction controllers under different working conditions based on the estimation results of a PI feedback controller and an SMC feedback controller respectively.
8. The method according to claim 7, wherein the battery SOC estimation accuracy test platform adopts a battery charge and discharge tester to perform charge and discharge tests on single batteries under electrical working conditions obtained under automotive UDDS and NEDC working conditions respectively; the SOC estimation accuracy of different feedback correction controllers under different working conditions is analyzed, and compared with the SOC estimation accuracy based on a PI feedback controller, the SOC estimation accuracy based on an SMC feedback controller is higher; compared with SOC estimation accuracy under different working conditions, the maximum estimation error of the battery under the NEDC electrical working condition is larger, and the maximum estimation error under the UDDS working condition is smaller.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110273098.8A CN113009361B (en) | 2021-03-13 | 2021-03-13 | Battery state of charge estimation method based on open circuit voltage calibration |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110273098.8A CN113009361B (en) | 2021-03-13 | 2021-03-13 | Battery state of charge estimation method based on open circuit voltage calibration |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113009361A true CN113009361A (en) | 2021-06-22 |
| CN113009361B CN113009361B (en) | 2022-06-17 |
Family
ID=76406672
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110273098.8A Active CN113009361B (en) | 2021-03-13 | 2021-03-13 | Battery state of charge estimation method based on open circuit voltage calibration |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113009361B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113466728A (en) * | 2021-07-13 | 2021-10-01 | 北京西清能源科技有限公司 | Method and system for online identification of parameters of two-stage battery model |
| CN113900026A (en) * | 2021-09-23 | 2022-01-07 | 盐城工业职业技术学院 | Method for estimating state of charge of battery pack of environment-friendly mower |
| CN114200317A (en) * | 2021-11-11 | 2022-03-18 | 一汽奔腾轿车有限公司 | SOC estimation method of dynamically corrected ampere-hour integration method |
| WO2023027049A1 (en) * | 2021-08-26 | 2023-03-02 | 株式会社Ｇｓユアサ | Correcting method, computer program, correcting apparatus, and electricity storage device |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2568303A2 (en) * | 2011-09-12 | 2013-03-13 | EaglePicher Technologies, LLC | Systems and methods for determining battery state-of-health |
| WO2013043123A1 (en) * | 2011-09-19 | 2013-03-28 | Nanyang Technological University | Devices for testing a battery and methods for testing a battery |
| CN103293485A (en) * | 2013-06-10 | 2013-09-11 | 北京工业大学 | Model-based storage battery SOC (state of charge) estimating method |
| CN104882931A (en) * | 2015-05-27 | 2015-09-02 | 沈阳航空航天大学 | Aviation power supply battery management system and method |
| CN105044606A (en) * | 2015-07-01 | 2015-11-11 | 西安交通大学 | SOC estimation method based on parameter adaptive battery model |
| CN108445402A (en) * | 2018-02-28 | 2018-08-24 | 广州小鹏汽车科技有限公司 | A kind of lithium-ion-power cell state-of-charge method of estimation and system |
| CN108829911A (en) * | 2018-04-16 | 2018-11-16 | 西南科技大学 | A kind of open-circuit voltage and SOC functional relation optimization method |
| CN110361652A (en) * | 2019-06-26 | 2019-10-22 | 河南理工大学 | A kind of Kalman filtering lithium battery SOC estimation method based on Model Parameter Optimization |
| CN111208439A (en) * | 2020-01-19 | 2020-05-29 | 中国科学技术大学 | Quantitative detection method for micro short circuit fault of series lithium ion battery pack |
| CN111426967A (en) * | 2020-05-22 | 2020-07-17 | 枣庄职业学院 | Parameter online real-time identification method of battery equivalent circuit model |
-
2021
- 2021-03-13 CN CN202110273098.8A patent/CN113009361B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2568303A2 (en) * | 2011-09-12 | 2013-03-13 | EaglePicher Technologies, LLC | Systems and methods for determining battery state-of-health |
| US20130066573A1 (en) * | 2011-09-12 | 2013-03-14 | Eaglepicher Technologies, Llc | Systems and methods for determining battery state-of-health |
| WO2013043123A1 (en) * | 2011-09-19 | 2013-03-28 | Nanyang Technological University | Devices for testing a battery and methods for testing a battery |
| CN103293485A (en) * | 2013-06-10 | 2013-09-11 | 北京工业大学 | Model-based storage battery SOC (state of charge) estimating method |
| CN104882931A (en) * | 2015-05-27 | 2015-09-02 | 沈阳航空航天大学 | Aviation power supply battery management system and method |
| CN105044606A (en) * | 2015-07-01 | 2015-11-11 | 西安交通大学 | SOC estimation method based on parameter adaptive battery model |
| CN108445402A (en) * | 2018-02-28 | 2018-08-24 | 广州小鹏汽车科技有限公司 | A kind of lithium-ion-power cell state-of-charge method of estimation and system |
| CN108829911A (en) * | 2018-04-16 | 2018-11-16 | 西南科技大学 | A kind of open-circuit voltage and SOC functional relation optimization method |
| CN110361652A (en) * | 2019-06-26 | 2019-10-22 | 河南理工大学 | A kind of Kalman filtering lithium battery SOC estimation method based on Model Parameter Optimization |
| CN111208439A (en) * | 2020-01-19 | 2020-05-29 | 中国科学技术大学 | Quantitative detection method for micro short circuit fault of series lithium ion battery pack |
| CN111426967A (en) * | 2020-05-22 | 2020-07-17 | 枣庄职业学院 | Parameter online real-time identification method of battery equivalent circuit model |
Non-Patent Citations (4)
| Title |
|---|
| KAIYUAN LI 等: "Energy efficiency of lithium-ion battery used as energy storage devices in micro-grid", 《IECON 2015 - 41ST ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY》 * |
| 皮钒 等: "基于扩展PSO和离散PI观测器的电池SoC估计", 《电子测量与仪器学报》 * |
| 陈峥 等: "基于迁移模型的老化锂离子电池SOC估计", 《储能科学与技术》 * |
| 黄凯: "锂离子电池成组应用技术及性能状态参数估计策略研究", 《中国优秀博硕士学位论文全文数据库（博士） 工程科技II辑》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113466728A (en) * | 2021-07-13 | 2021-10-01 | 北京西清能源科技有限公司 | Method and system for online identification of parameters of two-stage battery model |
| CN113466728B (en) * | 2021-07-13 | 2024-04-05 | 北京西清能源科技有限公司 | Method and system for online identification of two-stage battery model parameters |
| WO2023027049A1 (en) * | 2021-08-26 | 2023-03-02 | 株式会社Ｇｓユアサ | Correcting method, computer program, correcting apparatus, and electricity storage device |
| CN113900026A (en) * | 2021-09-23 | 2022-01-07 | 盐城工业职业技术学院 | Method for estimating state of charge of battery pack of environment-friendly mower |
| CN114200317A (en) * | 2021-11-11 | 2022-03-18 | 一汽奔腾轿车有限公司 | SOC estimation method of dynamically corrected ampere-hour integration method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113009361B (en) | 2022-06-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113009361B (en) | Battery state of charge estimation method based on open circuit voltage calibration | |
| Xiong et al. | A robust state-of-charge estimator for multiple types of lithium-ion batteries using adaptive extended Kalman filter | |
| KR101846690B1 (en) | System and Method for Managing Battery on the basis of required time for Charging | |
| US9440552B2 (en) | Estimation and compensation of battery measurement | |
| Sun et al. | Improved parameter identification and state-of-charge estimation for lithium-ion battery with fixed memory recursive least squares and sigma-point Kalman filter | |
| Huang et al. | A model-based state-of-charge estimation method for series-connected lithium-ion battery pack considering fast-varying cell temperature | |
| Hu et al. | Online estimation of an electric vehicle lithium-ion battery using recursive least squares with forgetting | |
| Thanagasundram et al. | A cell level model for battery simulation | |
| Li et al. | A novel parameter and state-of-charge determining method of lithium-ion battery for electric vehicles | |
| CN109839599B (en) | Lithium ion battery SOC estimation method based on second-order EKF algorithm | |
| CN108445422B (en) | Battery state of charge estimation method based on polarization voltage recovery characteristics | |
| KR100901252B1 (en) | Method and Apparatus for estimation of State Of Charge using sliding mode observer | |
| CN112098849B (en) | Lithium battery residual electric quantity estimation method based on integral Kalman filtering | |
| CN105425154A (en) | Method for estimating charge state of power cell set of electric vehicle | |
| CN108828448B (en) | Battery state of charge on-line estimation method based on charging voltage curve fusion Kalman filtering | |
| Tan et al. | Joint estimation of ternary lithium-ion battery state of charge and state of power based on dual polarization model | |
| CN109752660B (en) | Battery state of charge estimation method without current sensor | |
| CN111856282A (en) | Vehicle-mounted lithium battery state estimation method based on improved genetic unscented Kalman filtering | |
| CN113777501A (en) | SOH estimation method of battery module | |
| Xu et al. | State estimation of lithium batteries for energy storage based on dual extended kalman filter | |
| Guoliang et al. | State of charge estimation for NiMH battery based on electromotive force method | |
| Barcellona et al. | Cycle aging effect on the open circuit voltage of lithium-ion battery | |
| CN114280376A (en) | Equivalent circuit model of super capacitor and construction method | |
| CN111027203A (en) | Super capacitor SOC calculation method | |
| Huang et al. | State of charge estimation of lithium-ion battery based on second-order extended Kalman filter |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |