EP2052271A1 - Procédé de détermination de la capacité d'une batterie au moyen de paramètres dépendants de la capacité - Google Patents

Procédé de détermination de la capacité d'une batterie au moyen de paramètres dépendants de la capacité

Info

Publication number
EP2052271A1
EP2052271A1 EP07730093A EP07730093A EP2052271A1 EP 2052271 A1 EP2052271 A1 EP 2052271A1 EP 07730093 A EP07730093 A EP 07730093A EP 07730093 A EP07730093 A EP 07730093A EP 2052271 A1 EP2052271 A1 EP 2052271A1
Authority
EP
European Patent Office
Prior art keywords
capacity
battery
calculated
function
battery size
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Withdrawn
Application number
EP07730093A
Other languages
German (de)
English (en)
Inventor
Eberhard Schoch
Burkhard Iske
Michael Merkle
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Robert Bosch GmbH
Original Assignee
Robert Bosch GmbH
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Robert Bosch GmbH filed Critical Robert Bosch GmbH
Publication of EP2052271A1 publication Critical patent/EP2052271A1/fr
Withdrawn legal-status Critical Current

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]
    • G01R31/367—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]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R27/00—Arrangements for measuring resistance, reactance, impedance, or electric characteristics derived therefrom
    • G01R27/02—Measuring real or complex resistance, reactance, impedance, or other two-pole characteristics derived therefrom, e.g. time constant
    • G01R27/26—Measuring inductance or capacitance; Measuring quality factor, e.g. by using the resonance method; Measuring loss factor; Measuring dielectric constants ; Measuring impedance or related variables

Definitions

  • the invention relates to a method for determining a battery size, in particular the capacity, of an energy store according to the preamble of patent claim 1, as well as a corresponding device according to the preamble of patent claim 11.
  • the electrical consumers are usually supplied by a battery and a generator with electrical power.
  • an energy and consumer management is usually performed in which individual consumers are automatically switched on or off as needed, for. B. to respond to supply bottlenecks or to perform certain functions.
  • the knowledge of the battery condition is essential.
  • the known from the prior art battery models include a number of state variables and parameters that are constantly adapted to the current state of the battery in the active electrical system operation.
  • Certain parameters of the Battery models such as the minimum open circuit discharge voltage (U c omi ⁇ ), however, can only be accurately determined at very low battery states, typically below about 50% of the removable charge. Such deep discharges occur in the vehicle electrical system, however, only very rarely and are also prevented by the energy management of the vehicle to the
  • the method should moreover be able to be carried out in the case of the electrical excitations present in normal on-board electrical system operation, and in particular of any additional excitations, as described e.g. occur at engine start require.
  • An essential aspect of the invention is to calculate the desired battery size as a function of at least one capacity-dependent parameter.
  • the invention is based on the recognition that change different battery parameters in the course of operation of the battery compared to the new state and thus the parameters or their change is a measure of the battery condition, especially the capacity (loss capacity or available capacity) of the battery.
  • the sought battery size can thus be determined very easily and accurately taking into account the at least one capacity-dependent parameter.
  • no additional suggestions of the battery such as actively triggered charging or discharging current pulses, are required in order to carry out the calculation.
  • the sought-after battery size is calculated as a function of a minimum rest voltage, which in turn is a function of at least one capacitance-dependent parameter.
  • a parameter (eg RK025) of the acid diffusion resistance (R K ) of the battery and / or a parameter (eg Vgr25) of the passage resistance (Rd P ) between electrolyte and an electrode of the battery can be used as capacity-dependent parameters .
  • the mentioned parameters have the particular advantage that they change relatively strongly with increasing capacity loss, ie are relatively sensitive, and can be accurately identified in vehicle electrical system operation without additional active excitation.
  • the sought-after battery size is preferably calculated as a function of the deviation of one or more capacity-dependent parameters from a reference value, in particular an initial value in the new state of the battery.
  • Degree of deviation from the reference value is a measure of the loss capacity of the battery.
  • the at least one capacity-dependent parameter is weighted with a predetermined factor, which preferably depends on the error variance with which the parameter was determined.
  • a predetermined factor which preferably depends on the error variance with which the parameter was determined.
  • the desired battery size such as a capacity of the battery, is preferably also calculated as a function of the maximum rest voltage of the fully charged battery.
  • the maximum rest voltage is preferably learned by means of an adaptation algorithm at high states of charge.
  • the calculation is preferably carried out by means of an extended Kalman filter.
  • FIG. 1 shows a device for calculating a battery state variable, in particular the removable from the battery charge.
  • Fig. 2 is an equivalent circuit diagram for a lead-acid battery
  • Fig. 1 shows a device for determining a battery size, such as the removable from a battery charge Qe (capacity).
  • the device essentially comprises a state variable and parameter estimator 1, as well as a charge predictor 2 (estimator), in which a mathematical energy storage model is stored.
  • the state quantity and parameter estimator 1 calculates from the actual operating quantities of the battery 4, namely the battery voltage U ⁇ att, the battery current I Batt and the battery temperature T ⁇ att, state variables Z and / or parameter P, on the basis of which the charge predictor 2 searches for the desired battery state variable Qe, or other sizes such as the state of charge SOC or the capacity SOF of the battery 4 is calculated.
  • the battery 4 in the following example is a lead-acid battery.
  • the calculation of the battery capacity Qe is based on the current state of the energy storage.
  • the mathematical models stored in the charge predictor 2 are therefore initially initialized to the current operating state of the energy store 4.
  • the state quantity and parameter estimator 1 supplies the corresponding initial values.
  • State variable and parameter estimators can be used, for example, a known Kalman filter.
  • the state variables Z and parameter P are constantly adapted to the current state and thus the functions of the battery model are adapted.
  • Ri (Uco, Uk, Tßatt, RiO25, UcOmi ⁇ , UcOmax) Ohmic internal resistance, depending on the rest voltage Uco, the concentration polarization U k of the acid temperature T Ba tt the to 25 ° C u. Full charge related internal resistance RiO25 and the minimum rest voltage Ucomi ⁇ at discharge and the maximum rest voltage Ucomax at full charge,
  • Rk (Uco, Tßatt, RkO25, UcOmax) acid diffusion resistance, depending on the quiescent voltage Uco, the positive electrode penetration polarization, the acid temperature T Ba tt, the to 25 ° C u. Full charge related acid diffusion resistance RkO25 and the maximum rest voltage Ucomax at full charge, C k capacity of acid diffusion,
  • Electrode and electrolyte depending on the rest voltage Uco, the penetration polarization of the positive electrode UD P , the acid temperature T Ba tt, the passage current of the pos. Electrode 1 Dp , the saturation voltage of the penetration polarization v gr25 , referred to 25 ° C., and the maximum rest voltage Uco max
  • RK f (Uc ⁇ , Tßatt, RkO25, Ucomax)
  • R k o25 is the diffusion resistance of the acid at 25 ° C and fully charged battery.
  • RkO25 is a capacity-dependent parameter.
  • the following function can be used for the passage resistance R DP between the electrolyte and the positive electrode of the lead-acid battery 3:
  • Vgr25 is the polarization voltage of the positive electrode at high discharge currents and 25 ° C. vgr25 is a capacity-dependent parameter.
  • the charge predictor 2 comprises correspondingly different mathematical approaches.
  • Co is the acid capacity of the battery 3
  • U c omax the open circuit voltage with fully charged battery
  • U c omi ⁇ the open circuit voltage at discharge.
  • the parameters Co, U c omi ⁇ and U c omax must be determined with sufficient accuracy.
  • the parameters Co and U c oma ⁇ this is easily possible in normal battery operation (near full charge).
  • the parameter U c omi ⁇ can only be calculated accurately at low charge states ⁇ 50%. Since these operating conditions occur only very rarely, the desired accuracy of the capacity calculation is rarely achieved. It is therefore proposed to use the parameter U c omi ⁇ on the basis of the parameters R ⁇ o25 and vgr25, which are derived from the
  • Capacity of the battery 3 are dependent to calculate.
  • the available capacity Qe of the battery 3 can be determined in the normal electrical system operation, without additional suggestions of the battery, the battery must not be discharged to low states of charge.
  • UcOmi ⁇ _corr U c 0mi ⁇ + gl ⁇ ⁇ R K 25 - g2 ⁇ ⁇ vgr25.
  • ⁇ R ⁇ 25 and ⁇ vgr25 are the changes of the parameters R ⁇ 25 and vgr25 compared to a corresponding reference value, in particular the value in the new state of the battery 3.
  • the factors gl and g2 are weighting factors.
  • the changes ⁇ R ⁇ 25 and ⁇ vgr25 are here weighted in proportion to the accuracy with which the parameters R K 25 and vgr25 were estimated by the state quantity and parameter estimator 1.
  • the Kalman filter 1 outputs corresponding error variances P, which are included in the weighting factors gl and g2.
  • the weighting factors gl and g2 can be expressed, for example, as follows:
  • P 0 (R K025 ) and P 0 (vgr25) are the initial error variances of the corresponding parameters
  • P (R K025 ) and P (vgr25) are the current error variances of the parameters R K025 and vgr25 estimated by the Kalman filter 1.
  • the deviation of one parameter of the double-layer capacitance C DP between the positive electrode and the electrolyte could optionally or additionally also be used.
  • the parameter Ri O 2 5 of the internal resistance or its change in the calculation of the quiescent voltage U c0 mi ⁇ at the end of discharge can also be included.

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Secondary Cells (AREA)
  • Tests Of Electric Status Of Batteries (AREA)

Abstract

L'invention concerne un procédé servant à déterminer la taille d'une batterie (Qe, Uc0min), en particulier la capacité (Qe) de la batterie (3), à l'aide d'un estimateur (1) de variables d'état et de paramètres qui calcule les valeurs d'état (Z) et les paramètres (P) d'un modèle mathématique d'accumulateur d'énergie à partir des valeurs de fonctionnement (UBatt, IBatt, TBatt) de la batterie (3). La capacité (Qe) de la batterie (3) peut être déterminée très précisément pendant le fonctionnement normal de la batterie, si elle est calculée comme fonction d'au moins un paramètre (RK025, vgr25) dépendant de la capacité.
EP07730093A 2006-08-07 2007-06-12 Procédé de détermination de la capacité d'une batterie au moyen de paramètres dépendants de la capacité Withdrawn EP2052271A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102006036784A DE102006036784A1 (de) 2006-08-07 2006-08-07 Verfahren zum Bestimmen der Batteriekapazität anhand kapazitätsabhängiger Parameter
PCT/EP2007/055771 WO2008017530A1 (fr) 2006-08-07 2007-06-12 Procédé de détermination de la capacité d'une batterie au moyen de paramètres dépendants de la capacité

Publications (1)

Publication Number Publication Date
EP2052271A1 true EP2052271A1 (fr) 2009-04-29

Family

ID=38353615

Family Applications (1)

Application Number Title Priority Date Filing Date
EP07730093A Withdrawn EP2052271A1 (fr) 2006-08-07 2007-06-12 Procédé de détermination de la capacité d'une batterie au moyen de paramètres dépendants de la capacité

Country Status (7)

Country Link
US (1) US20100066377A1 (fr)
EP (1) EP2052271A1 (fr)
JP (1) JP2010500539A (fr)
KR (1) KR20090045227A (fr)
CN (1) CN101501518A (fr)
DE (1) DE102006036784A1 (fr)
WO (1) WO2008017530A1 (fr)

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US8552687B2 (en) 2008-06-05 2013-10-08 GM Global Technology Operations LLC Method and system for characterizing a battery
WO2009148160A1 (fr) * 2008-06-06 2009-12-10 株式会社 明電舎 Dispositif de diagnostic de la durée de vie résiduelle d'un condensateur et dispositif de compensation de l'énergie électrique équipé du dispositif de diagnostic de la durée de vie résiduelle
FR2948771B1 (fr) * 2009-07-28 2011-08-26 Commissariat Energie Atomique Procede de caracterisation d'une batterie electrique
DE102009049589A1 (de) * 2009-10-16 2011-04-21 Bayerische Motoren Werke Aktiengesellschaft Verfahren zur Bestimmung und/oder Vorhersage der maximalen Leistungsfähigkeit einer Batterie
JP4689755B1 (ja) * 2010-03-23 2011-05-25 古河電気工業株式会社 電池内部状態推定装置および電池内部状態推定方法
EP2551687B1 (fr) * 2010-03-23 2020-07-15 Furukawa Electric Co., Ltd. Dispositif et procédé d'évaluation de l'état intérieur d'une batterie
DE102010031050A1 (de) * 2010-07-07 2012-01-12 Bayerische Motoren Werke Aktiengesellschaft Verfahren und Vorrichtung zum Betreiben eines Energiespeichers
US9201121B2 (en) 2010-12-06 2015-12-01 Texas Instruments Incorporated System and method for sensing battery capacity
JP5307113B2 (ja) * 2010-12-20 2013-10-02 古河電気工業株式会社 満充電検知装置および満充電検知方法
FR2975190B1 (fr) * 2011-05-13 2013-05-17 Valeo Equip Electr Moteur Procede d'estimation de l'etat de fonctionnement d'une batterie pour un systeme d'arret/relance automatique du moteur thermique d'un vehicule, capteur et systeme de gestion de batterie adaptes
WO2013016188A1 (fr) * 2011-07-22 2013-01-31 Navitas Solutions, Inc. Procédé, système et appareil pour une estimation de paramètres de modèle de circuit équivalent de batterie
DE102012209375A1 (de) * 2012-06-04 2013-12-05 Robert Bosch Gmbh Verfahren und Vorrichtung zum Ermitteln einer physikalischen Größe in einem Stellgebersystem
JP5851965B2 (ja) * 2012-10-02 2016-02-03 株式会社日立製作所 放電容量予測装置、プログラム、および電池の製造方法
US9182449B2 (en) * 2012-10-12 2015-11-10 GM Global Technology Operations LLC Method and system for estimating battery capacity in a vehicle
DE102012224417A1 (de) 2012-12-27 2014-07-17 Robert Bosch Gmbh Verfahren zum Bestimmen eines Ladezustands
US10473723B2 (en) * 2013-08-30 2019-11-12 Ford Global Technologies, Llc Parameter and state limiting in model based battery control
FR3010797B1 (fr) * 2013-09-18 2015-10-02 Renault Sa Procede d'estimation du vieillissement d'une cellule de batterie d'accumulateurs
KR101708885B1 (ko) * 2013-10-14 2017-02-21 주식회사 엘지화학 혼합 양극재를 포함하는 이차 전지의 상태 추정 장치 및 그 방법
CN103529399B (zh) * 2013-10-28 2015-04-22 湖南大学 一种基于铅酸电池改进型pngv模型的模拟方法
FR3029315B1 (fr) * 2014-11-28 2016-12-09 Renault Sa Procede automatique d'estimation de la capacite d'une cellule d'une batterie
JP6414558B2 (ja) 2016-02-01 2018-10-31 株式会社デンソー 電池状態推定装置
WO2021004599A1 (fr) * 2019-07-05 2021-01-14 Volvo Truck Corporation Procédé d'estimation d'un paramètre de fonctionnement d'une unité de batterie
CN110673041B (zh) * 2019-09-05 2021-10-01 合肥国轩高科动力能源有限公司 一种基于副反应量化的锂电池容量预测方法
CN113064089B (zh) * 2021-03-10 2023-11-07 北京车和家信息技术有限公司 动力电池的内阻检测方法、装置、介质以及系统
CN116500468B (zh) * 2023-06-26 2023-09-12 浙江金开物联网科技有限公司 蓄电池的电量计算方法、电池管理系统及电瓶车

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Also Published As

Publication number Publication date
WO2008017530A1 (fr) 2008-02-14
KR20090045227A (ko) 2009-05-07
CN101501518A (zh) 2009-08-05
JP2010500539A (ja) 2010-01-07
DE102006036784A1 (de) 2008-02-14
US20100066377A1 (en) 2010-03-18

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