EP4291909A1 - Verfahren zum bestimmen eines kapazitätsverlusts eines batteriespeichers, vorrichtung und computerprogrammprodukt - Google Patents
Verfahren zum bestimmen eines kapazitätsverlusts eines batteriespeichers, vorrichtung und computerprogrammproduktInfo
- Publication number
- EP4291909A1 EP4291909A1 EP22706035.7A EP22706035A EP4291909A1 EP 4291909 A1 EP4291909 A1 EP 4291909A1 EP 22706035 A EP22706035 A EP 22706035A EP 4291909 A1 EP4291909 A1 EP 4291909A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- charge
- capacity
- state
- load
- battery storage
- 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.)
- Withdrawn
Links
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]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
-
- 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
-
- 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]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
-
- 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
- G01R31/3865—Arrangements for measuring battery or accumulator variables related to manufacture, e.g. testing after manufacture
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries
- H02J7/80—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries including monitoring or indicating arrangements
- H02J7/82—Control of state of charge [SOC]
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries
- H02J7/80—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries including monitoring or indicating arrangements
- H02J7/84—Control of state of health [SOH]
Definitions
- the invention relates to a method for determining a loss of capacity in a battery storage device, a device for carrying out the method and a computer program product.
- an aging characteristic of the battery cell used is determined in the prior art by means of measurements during the design phase of a battery system.
- the real aging rate with real load profiles is often not tested. Rather, the aging rate, or the cycle stability, is determined using compressed load profiles in so-called shirring tests.
- empirical aging models are parameterized, from which the aging process in the application emerges.
- Future aging as a function of the load profile, the operating point and the ambient conditions determined by physical and/or chemical measurements is difficult to carry out due to the non-linearity of the underlying physical and chemical processes and their complex interactions.
- the object is achieved with a method for determining a capacity loss according to claim 1, a device according to claim 9 and a computer program product according to claim 12.
- the method according to the invention for determining at least one average capacity loss of a battery storage device comprises a number of steps.
- a first step a) at least two load cycles of the battery storage device are measured using a high-precision coulometry device, with a single load cycle comprising a first discharging in which a first amount of charge is measured from a first state of charge to a second state of charge.
- There is an closing first charging in which a second amount of charge is measured from the second state of charge to a third state of charge.
- a second discharge then takes place, in which a third quantity of charge is measured from the third charge state to a fourth charge state.
- Charging and discharging in the load cycle take place between a lower voltage and an upper voltage of the battery storage.
- the device according to the invention for carrying out a method for determining the average capacity loss of a battery store comprises a high-precision coulometry device.
- the high-precision coulometry device is set up to detect a load cycle of the battery storage device by measurement.
- a first discharge is carried out within the load cycle, in which a first amount of charge is measured from a first state of charge to a second state of charge.
- a subsequent first charge in which a second amount of charge occurs from the second charge state to a third charge state, is measured.
- a second discharging then takes place, in which a third amount of charge is measured from the third charge state to a fourth charge state.
- Charging and discharging in the load cycle take place between a lower voltage and an upper voltage of the battery storage.
- non-symmetrical charging and discharging cycles such as high current intensities for a load cycle.
- it can be any load cycle, in particular a constant current profile, a constant power profile, a transient current profile or a transient power profile.
- the load cycle can also have pauses in which no current flows, e.g. B. to the Reversal points, defined by the voltage limits.
- the load cycle is only run through periodically and encounters two fixed voltage limits. The selection of the voltage limits defines a specific operating point, characterized by an average state of charge (SOC) and a cycle depth (DOD).
- SOC average state of charge
- DOD cycle depth
- the average capacity loss is advantageously determined with the aid of a computer by means of a sliding linear fit using the values of the capacity loss and finding the smallest slopes in the linear equations generated in this way.
- the data set which includes the determined capacity losses, is continuously shortened and a new straight line is fitted.
- the fit is carried out up to a certain minimum remaining length of the data record, i.e. the loss of capacity.
- the equations of the straight lines are then sorted according to the values of their slopes in increasing order of magnitude.
- the measurement can be considered valid if at least two of the gradients have a value of less than 10% of the Have the mean value of the last 10% of the capacity losses. For example, if the mean of the last twenty capacity losses is 5 mAh/duty cycle, especially when measuring at least 200 capacity losses, then the slope of the two best fitted tangents ("fits") should be less than 0.05 mAh/duty cycle.
- capacity losses may only be used to determine the residual capacity after a transient phase of the load cycle.
- Capacitance losses which are determined at the beginning of the measurements, i.e. during the transient process, are subject to error and should therefore not be included in the determination of the average capacitance loss. It has been found that this transient phase has ended when at least two of the straight lines applied to the capacity loss in a fitting have slopes of less than 10% of the mean value of the last 10% of the measured capacity losses.
- the capacity losses are considered to be almost constant if two consecutive capacity losses and/or a moving average over at least 20 capacity losses show a change of less than 5% as capacity loss. This procedure advantageously ensures that the determination of the remaining capacity based on the loss of capacity can be carried out quickly and yet reliably.
- a constant temperature prevails in each successive load cycle within a determination of the loss of capacity.
- the temperature can be different for two consecutive determinations of capacity loss.
- the temperature during a load cycle is constant. In order to determine the average capacity loss, it is advantageous to combine load cycles that were recorded at different temperatures, as long as ge the temperature has remained constant within a load cycle.
- the battery or battery cell is operated in a temperature control chamber.
- the battery or battery cell is arranged in a temperature control chamber.
- the temperature control chamber makes it possible to ensure sufficiently high temperature stability during a load cycle of the battery.
- the use of temperature control advantageously ensures that the temperature remains constant during a determination of the capacity loss. This advantageously increases the reliability of the determination of the remaining capacity of the battery store.
- the lower voltage is selected from a first voltage range and the upper voltage is selected from a second voltage range.
- the second voltage range is expediently at higher voltages than the first voltage range.
- both the first voltage range and the second voltage range can be selected from the entire working voltage range of the battery storage device. In other words, no full cycles have to be carried out. It is therefore possible to use the approved voltage range of the battery storage according to the product sheet or beyond.
- this allows Measuring the capacity loss without performing full cycles, i.e. complete charging and discharging, a shorter measurement time.
- the battery storage is less heavily loaded by the measurement, which advantageously prevents rapid aging.
- At least two capacity losses are selected and averaged to determine the remaining capacity and multiplied by the number of selected load cycles.
- the moving average value for determining the average capacity loss is determined from at least 20 capacity losses.
- the residual capacity is determined based on at least two average capacity losses. It is particularly advantageous to select different conditions in the load cycle from a load collective for determining the mean capacity losses.
- a first and a second mean capacity loss are respectively determined for the first and second load profiles.
- a residual capacity is then determined based on the at least two average capacity losses. This determination can advantageously be made for two different battery stores, in particular with different specifications and/or different manufacturers. For a planned use that is similar or equal to the combination of the two load profiles, the optimal battery spoke can thus be advantageously determined.
- the conditions of the load cycles of the collective load are selected as a function of a predetermined battery operation.
- the determination of the remaining capacity then represents a prediction of the remaining capacity for battery operation.
- the remaining capacity can be included in a prediction of an aging behavior of the battery store for battery operation.
- the load spectrum is particularly advantageously defined in such a way that it reflects the stress on the battery storage system in specific battery operation, e.g. use in an electric vehicle or as a home storage system.
- the method for determining an average loss of capacity is carried out with the aid of a computer in a computing unit.
- the measuring method can thus advantageously be automated, which accelerates the evaluation.
- the product development of the electrochemical energy store or its application can thus advantageously be accelerated. This advantageously lowers the costs of product development. Furthermore, the utilization of the test equipment is reduced, which makes development more efficient.
- the computing unit is set up to determine the number of load cycles based on the selection of the capacity losses.
- the arithmetic unit can also determine the average capacity loss if an average value is formed over at least two capacity losses.
- the computing unit is set up to determine, while the load cycle is being measured, whether an almost constant value of the capacity loss is already reached and, depending on the result of the evaluation, another load cycle of the battery storage to toast It is advantageously possible to determine the remaining capacity in an automated manner.
- FIG. 1 shows a device for determining the average capacity loss and a residual capacity using a high-precision coulometry device
- FIG. 2 shows a voltage-time diagram of a load cycle
- FIG. 3 shows a voltage-charge diagram of a load cycle
- FIG. 4 shows a capacity loss per cycle-number of cycles diagram of at least 200 load cycles
- FIG. 5 shows a residual capacity-number of cycles diagram of at least 200 load cycles
- FIG. 6 shows a process diagram for determining the average capacity loss of the remaining capacity of the battery store.
- FIG. 1 shows a device for determining the average capacity loss and the remaining capacity with a high-precision coulometry device 1.
- the device 1 includes a battery store 2, the battery store having at least one battery cell.
- the battery store is arranged in a temperature control chamber 3 .
- the battery memory 2 is connected to a high-precision coulometry device 4 via a power cable 11 .
- the high-precision coulometry device 4 is in turn connected to a computing unit 10 via a data cable 12 .
- the high-precision coulometry device 4 records a charge-time diagram of the battery store 2 with very high accuracy. In this case, the battery storage device 2 is operated with a periodic load cycle 100 .
- FIG. 2 shows a voltage-time diagram which the high-precision coulometry device 4 recorded during a periodic load cycle 100 of the battery storage device 2 .
- a load cycle 100 includes discharging from a first state of charge 21 to a second state of charge 22 , the first state of charge 21 being at an upper voltage 25 and the second state of charge 22 being at a lower voltage 26 . Then, in the load cycle 100, the battery storage device 2 is charged from the second state of charge 22 to a third state of charge 23. As the next step, the third state of charge 23 is discharged to a fourth state of charge 24 in the load cycle 100 . In each individual charging/discharging step, an upper voltage 25 and a lower voltage 26 are maintained as voltage limits. The loading lasts the loading period t c .
- FIG. 3 shows a diagram in which the voltage of the battery store is plotted against the cumulative charge quantity Q.
- the load cycle 100 begins again at the first state of charge 21.
- the battery storage 2 is up to the second state of charge 22 in the first discharge 31 the entla.
- a first amount of charge Ql from the battery storage 2 is removed.
- the first amount of charge Ql can be calculated using Equation 1, where I denotes the current flow and t D denotes the discharge period:
- the battery storage device 2 is then discharged from the third state of charge 23 to the fourth state of charge 24 by means of a second discharging 33.
- the amount of charge Q3 removed can in turn be calculated analogously to Equation 1 from the period of discharging and the associated current flow.
- FIG. 4 now shows the capacity loss per load cycle for 250 load cycles.
- the x-axis shows the number of load cycles Z, i.e. the running number of the respective load cycle 100, and the y-axis shows the capacity loss dCap per load cycle 100 100 load cycles occurs.
- the length of the transient phase PI depends on the operating point and the history of the battery storage or battery cell.
- the transient phase PI can advantageously z. This can be shortened, for example, by measuring the subsequent operating point at the same mean state of charge (SOC) as the previous measurement.
- SOC mean state of charge
- the measurement can be regarded as valid if at least two of the gradients have a value of less than 10% of the mean value of the last 10% of the capacity losses dCap. If, for example, the mean value of the last twenty capacity losses is 5 mAh/duty cycle, in particular when measuring at least 200 capacity losses, then the slope of the two best fitted tangents ("fits") should be less than 0.05 mAh/duty cycle.
- the measurement must be repeated, especially with a larger number of reference points, because the system has not reached a sufficiently steady state. from the a certain number, e.g. B. rounded 3% of the total length of the data set, or a minimum number of two measured values, selected and the corresponding starting indices of the fitted straight line determined.
- a certain number e.g. B. rounded 3% of the total length of the data set, or a minimum number of two measured values, selected and the corresponding starting indices of the fitted straight line determined.
- an average capacity loss is specified as the arithmetic mean of the included capacity losses dCap.
- the value of the mean capacity loss dCap Mean is then determined as the mean value of the averaged individual capacity losses.
- FIG. 4 also makes it clear that the transient phase PI is followed by a determination phase P2. These phases can shift during the evaluation of the capacity losses dCap.
- the mean capacity loss dCap Mean is advantageously used to determine the remaining capacity.
- the mean capacity loss dCap Mean is multiplied by the number of load cycles included in the evaluation and subtracted from the starting capacity CS. out of it the residual capacity CR results, as shown in Equation 4.
- FIG. 6 shows a process diagram of the method for determining the average capacity loss dCap Mean and the residual capacity CR of a battery store 2.
- a first step S1 at least ten load cycles of the battery store are measured using a high-precision coulometry device.
- a load cycle includes a first discharge, a first charge and a second discharge.
- the charge transfers are determined.
- a capacity loss is determined based on the charge shifts.
- the capacity loss is checked for constancy. If the at least two capacity losses are not regarded as constant, then another load cycle is started, beginning with step S1.
- the average capacity loss dCap Mean for the measured operating point ie the defined load profile
- the measurement result can then, in particular together with the results for further work points, or load profiles, for e.g. B. the design or modeling of a battery storage can be used.
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Manufacturing & Machinery (AREA)
- Secondary Cells (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Testing Electric Properties And Detecting Electric Faults (AREA)
- Tests Of Electric Status Of Batteries (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP21164160.0A EP4063882B1 (de) | 2021-03-23 | 2021-03-23 | Verfahren zum bestimmen eines kapazitätsverlusts eines batteriespeichers, vorrichtung und computerprogrammprodukt |
| PCT/EP2022/053363 WO2022199933A1 (de) | 2021-03-23 | 2022-02-11 | Verfahren zum bestimmen eines kapazitätsverlusts eines batteriespeichers, vorrichtung und computerprogrammprodukt |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP4291909A1 true EP4291909A1 (de) | 2023-12-20 |
Family
ID=75173072
Family Applications (2)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP21164160.0A Active EP4063882B1 (de) | 2021-03-23 | 2021-03-23 | Verfahren zum bestimmen eines kapazitätsverlusts eines batteriespeichers, vorrichtung und computerprogrammprodukt |
| EP22706035.7A Withdrawn EP4291909A1 (de) | 2021-03-23 | 2022-02-11 | Verfahren zum bestimmen eines kapazitätsverlusts eines batteriespeichers, vorrichtung und computerprogrammprodukt |
Family Applications Before (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP21164160.0A Active EP4063882B1 (de) | 2021-03-23 | 2021-03-23 | Verfahren zum bestimmen eines kapazitätsverlusts eines batteriespeichers, vorrichtung und computerprogrammprodukt |
Country Status (7)
| Country | Link |
|---|---|
| US (1) | US12540982B2 (de) |
| EP (2) | EP4063882B1 (de) |
| JP (1) | JP2024511082A (de) |
| KR (1) | KR20230158103A (de) |
| CN (1) | CN117043613A (de) |
| CA (1) | CA3212100A1 (de) |
| WO (1) | WO2022199933A1 (de) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP4123321B1 (de) | 2021-07-23 | 2024-10-30 | Siemens Aktiengesellschaft | Verfahren, vorrichtung und computerprogrammprodukt zur restwertbestimmung von batteriespeichern |
| EP4123319B1 (de) | 2021-07-23 | 2024-02-14 | Siemens Aktiengesellschaft | Verfahren, vorrichtung und computerprogrammprodukt zur lebensdauerabschätzung von batteriespeichern |
| EP4346053A1 (de) * | 2022-09-29 | 2024-04-03 | Siemens Aktiengesellschaft | Verfahren zum laden eines elektrischen energie-speichers, elektrisches energie-management-system und computerprogramm-produkt zum durchführen des verfahrens sowie deren verwendung |
| EP4375685A1 (de) * | 2022-11-24 | 2024-05-29 | Siemens Aktiengesellschaft | Verfahren zum bestimmen der alterung eines batteriespeichers, vorrichtung und computerprogrammprodukt |
| EP4607745A1 (de) * | 2024-02-21 | 2025-08-27 | Siemens Aktiengesellschaft | Regelung eines hpc-verfahrens sowie hpc-verfahren für eine batteriezelle |
Family Cites Families (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09257890A (ja) | 1996-03-21 | 1997-10-03 | Nissan Motor Co Ltd | 電気自動車用二次電池の総容量検出方法とそれを用いた残存容量計および残寿命計 |
| JP4110637B2 (ja) | 1998-10-27 | 2008-07-02 | 株式会社デンソー | 電池の残存容量演算装置 |
| JP3997646B2 (ja) | 1999-04-05 | 2007-10-24 | 株式会社デンソー | 電池の残存容量演算方式 |
| JP4875235B2 (ja) | 2000-04-03 | 2012-02-15 | レノボ シンガポール プライヴェート リミテッド | 電源装置、電源容量情報補正装置、電源容量情報補正方法及びコンピュータ |
| US6892148B2 (en) | 2002-12-29 | 2005-05-10 | Texas Instruments Incorporated | Circuit and method for measurement of battery capacity fade |
| US8653793B2 (en) | 2009-09-25 | 2014-02-18 | Toyota Jidosha Kabushiki Kaisha | Secondary battery system |
| US20140232411A1 (en) * | 2011-09-30 | 2014-08-21 | KPIT Cummins Infosytems Ltd | System and method for battery monitoring |
| CN103969585B (zh) | 2013-01-31 | 2018-03-30 | 国际商业机器公司 | 评估电池的使用状况的方法和装置、相关系统和车辆 |
| EP2803996A1 (de) | 2013-05-15 | 2014-11-19 | Merck Patent GmbH | Messvorrichtung der Leitfähigkeit einer Flüssigkeit zum Bestimmen sehr niedriger Mengen an gesamtem organisch gebundenem Kohlenstoff (TOC) in reinem und ultrareinem Wasser |
| KR102225667B1 (ko) * | 2014-07-02 | 2021-03-12 | 삼성전자주식회사 | 배터리의 상태를 추정하는 방법 및 장치 |
| KR102035679B1 (ko) * | 2016-11-29 | 2019-10-23 | 주식회사 엘지화학 | 배터리 노화상태 산출 방법 및 시스템 |
| EP4123319B1 (de) * | 2021-07-23 | 2024-02-14 | Siemens Aktiengesellschaft | Verfahren, vorrichtung und computerprogrammprodukt zur lebensdauerabschätzung von batteriespeichern |
| EP4123321B1 (de) * | 2021-07-23 | 2024-10-30 | Siemens Aktiengesellschaft | Verfahren, vorrichtung und computerprogrammprodukt zur restwertbestimmung von batteriespeichern |
-
2021
- 2021-03-23 EP EP21164160.0A patent/EP4063882B1/de active Active
-
2022
- 2022-02-11 CN CN202280023110.2A patent/CN117043613A/zh active Pending
- 2022-02-11 CA CA3212100A patent/CA3212100A1/en active Pending
- 2022-02-11 JP JP2023557817A patent/JP2024511082A/ja active Pending
- 2022-02-11 EP EP22706035.7A patent/EP4291909A1/de not_active Withdrawn
- 2022-02-11 US US18/551,445 patent/US12540982B2/en active Active
- 2022-02-11 KR KR1020237035739A patent/KR20230158103A/ko active Pending
- 2022-02-11 WO PCT/EP2022/053363 patent/WO2022199933A1/de not_active Ceased
Also Published As
| Publication number | Publication date |
|---|---|
| EP4063882A1 (de) | 2022-09-28 |
| KR20230158103A (ko) | 2023-11-17 |
| EP4063882C0 (de) | 2024-02-14 |
| US12540982B2 (en) | 2026-02-03 |
| EP4063882B1 (de) | 2024-02-14 |
| JP2024511082A (ja) | 2024-03-12 |
| CN117043613A (zh) | 2023-11-10 |
| WO2022199933A1 (de) | 2022-09-29 |
| CA3212100A1 (en) | 2022-09-29 |
| US20240168097A1 (en) | 2024-05-23 |
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