WO2018025276A1 - Estimation of soc of a lead-acid battery - Google Patents

Estimation of soc of a lead-acid battery Download PDF

Info

Publication number
WO2018025276A1
WO2018025276A1 PCT/IN2017/050307 IN2017050307W WO2018025276A1 WO 2018025276 A1 WO2018025276 A1 WO 2018025276A1 IN 2017050307 W IN2017050307 W IN 2017050307W WO 2018025276 A1 WO2018025276 A1 WO 2018025276A1
Authority
WO
WIPO (PCT)
Prior art keywords
battery
soc
ocv
vehicle
battery controller
Prior art date
Application number
PCT/IN2017/050307
Other languages
French (fr)
Inventor
Nabal Kishore PANDEY
Satish THIMMALAPURA
Kannan SUBRAMANIAN
Kumarprasad TELIKEPALLI
Original Assignee
Mahindra & Mahindra Limited
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 Mahindra & Mahindra Limited filed Critical Mahindra & Mahindra Limited
Priority to EP17836529.2A priority Critical patent/EP3494006A4/en
Priority to US16/321,937 priority patent/US20190176657A1/en
Publication of WO2018025276A1 publication Critical patent/WO2018025276A1/en

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/382Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • G01R31/3828Arrangements for monitoring battery or accumulator variables, e.g. SoC using current integration
    • G01R31/3832Arrangements for monitoring battery or accumulator variables, e.g. SoC using current integration without measurement of battery voltage
    • G01R31/3833Arrangements for monitoring battery or accumulator variables, e.g. SoC using current integration without measurement of battery voltage using analog integrators, e.g. coulomb-meters
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/382Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/385Arrangements for measuring battery or accumulator variables
    • G01R31/387Determining ampere-hour charge capacity or SoC
    • HELECTRICITY
    • H01ELECTRIC ELEMENTS
    • H01MPROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00Secondary cells; Manufacture thereof
    • H01M10/06Lead-acid accumulators
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10Energy storage using batteries
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02TCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00Road transport of goods or passengers
    • Y02T10/60Other road transportation technologies with climate change mitigation effect
    • Y02T10/70Energy storage systems for electromobility, e.g. batteries

Definitions

  • Embodiments herein relate to vehicle systems, and more particularly to lead acid batteries in vehicles.
  • Lead-acid batteries have been widely used in the automotive industry for starting-lighting-ignition (SLI) applications. But they are typically used as backup energy storage for powering vehicle ECU's during conventional engine off condition and for engine cranking and only add weight to the conventional powertrain during normal running. For optimization of lead acid battery system, it is required to increase the usage (battery cycling) of the battery during normal vehicle running conditions.
  • Typical applications wherein these batteries are being used are stop start applications and low voltage hybrid vehicle applications. In the stop start application, the engine can be automatically stopped and restarted which typically occurs at traffic signals. This application avoids unnecessary idling of vehicle, hence saving fuel.
  • Low voltage battery systems (lead acid battery based systems with management systems) are being used as cranking device during vehicle re-start.
  • hybrid function torque assist, brake energy recovery
  • SOC state of charge
  • the principal object of embodiments as disclosed herein is to provide methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle.
  • Another object of embodiments as disclosed herein is to provide methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle using discharge and charge correction factors.
  • Another object of embodiments as disclosed herein is to provide methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle using a master OCV table based SOC estimation (SOCocv) after the vehicle has been powered off, and a current throughput based SOC estimation (SOC EST ) based on coulomb count integration (amp-second (As) integration) when the vehicle is operational.
  • SOC State of Charge
  • SOCocv master OCV table based SOC estimation
  • SOC EST current throughput based SOC estimation
  • Another object of embodiments as disclosed herein is to provide methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle considering ageing of the battery and temperature.
  • FIG. 1 is a flow chart of the SOC estimation logic, according to embodiments as disclosed herein;
  • FIG. 2 depicts a system in a vehicle for estimating SOC of a battery, according to embodiments as disclosed herein;
  • FIG. 3 is a flowchart depicting the process of estimating SOCocv, according to embodiments as disclosed herein;
  • FIG. 4 is a flowchart depicting the process of estimating SOC using Coulomb counting, according to embodiments as disclosed herein; and
  • FIG. 5 is a flow chart depicting the process of the determining the correction factor that is applied when coulomb counting is performed, according to embodiments as disclosed herein.
  • the embodiments herein provide methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle.
  • SOC State of Charge
  • the vehicle as referred to herein can be any vehicle comprising of a lead acid battery.
  • the vehicle can be a hybrid vehicle.
  • the vehicle can comprise of only a conventional engine based powertrain.
  • Example of the vehicle can be a car, truck, van, bus, and so on.
  • FIG. 1 is a flow chart of the SOC estimation logic.
  • a check is made (101) if the vehicle has been powered off. If the vehicle has been powered off, the SOC (State of Charge) of a battery is estimated (102) based on OCV (Open Circuit Voltage) (hereinafter referred to as SOCocv)- If the vehicle has not been powered off, the SOC of the battery is estimated (103) based on coulomb counting (hereinafter referred to as SOC EST )-
  • SOCocv Open Circuit Voltage
  • SOC EST coulomb counting
  • the system in the vehicle 200 comprises of a battery controller 201 mounted on a negative terminal of the battery 202.
  • the battery controller 201 can be further connected to at least one Electronic Control Unit (ECU) 203 present in the vehicle and at least one electrical load 204 present in the vehicle 200.
  • ECU Electronic Control Unit
  • the battery controller 201 can check if the vehicle 200 has been powered off. If the vehicle has been powered off, the battery controller 201 can estimate the SOC of the battery 202 is estimated (102) based on OCV.
  • the battery controller 201 can generate a master OCV table by measuring the OCV of the battery 202, once the battery is full rested with no charge throughput, at pre-defined measurement intervals for a predefined time period (for example, every 30 minutes for a 4 hour duration).
  • the master OCV table comprising of a matrix with a pre-defined number of indices (for example, 8), is fully populated in the pre-defined time period.
  • the battery 202 achieves chemical, electrical and thermal equilibrium in the pre-defined time period.
  • the battery controller 201 If battery is not rested for the pre-defined time period, but is in rest for more than the pre-defined measurement intervals, the battery controller 201 generates a running OCV table.
  • the battery controller 201 can correct the running OCV table dynamically using a previous master OCV table (if present).
  • the battery controller 201 determines the SOCocv based on the OCV table (which can be either the master OCV table or the running OCV table) for the current ignition cycle. If the battery is not rested for more than 30 minutes, the battery controller 201 can consider the SOC from the previous ignition cycle as the battery SOC.
  • the battery controller 201 can estimate the SOC of the battery 202 based on coulomb counting.
  • Dynamic (run-time) energy throughput also known as Coulomb Counter, is an integration of current over time (Ampere-second) and the battery controller 201 can be calculated using the charging rates, discharge rates and the battery temperature.
  • the battery controller 201 can update the coulomb counter to a pre-defined level, if the battery charge current is saturated for a defined temperature to a pre-defined level.
  • the battery controller 201 can perform dynamic charge and discharge correction using factors such as discharge and charge related efficiency on the overall system. With coulomb counter and correction factor, the battery controller 201 determines the SOC EST for a current vehicle ignition cycle.
  • the battery controller 201 applies battery-ageing factor, to accommodate capacity degradation, to the overall SOC calculation.
  • the vehicle 200 comprises of a memory storage location, wherein the battery controller 201 can store data (such as the OCV values, master OCV table, estimated SOC, and so on) in the memory storage location.
  • the battery controller 201 can also fetch data from the battery storage location, as and when required.
  • FIG. 3 is a flowchart depicting the process of estimating SOCocv-
  • the battery controller 201 checks (301) for how much time the vehicle has been off. If the time elapsed is more than a pre-defined off-time period, the battery controller 201 measures (302) OCV of the fully rested battery 202, no charge throughput, at pre-defined measurement intervals for a pre-defined time period. Based on the measurements, the battery controller 201 populates (303) the master OCV table in the pre-defined time period, wherein the master OCV table comprises of a matrix with a pre-defined number of indices.
  • the master OCV table with 8 indices matrix, can be fully populated in 4 hours, which is the time in which the battery 202 achieves chemical, electrical and thermal equilibrium.
  • the battery controller 201 estimates (304) the battery SOC using the master OCV table.
  • the battery SOC can be estimated by mapping every value of the master OCV with the battery SOC. If the time elapsed is less than the pre-defined off-time peri od , the battery controller 201 checks (305) if the vehicle 200 has been at rest for more than the pre-defined measurement intervals. If the vehicle 200 has been at rest for more than the pre-defined measurement intervals, the battery controller 201 corrects (306) OCV values based on a previously generated master OCV table (if available).
  • the battery controller 201 can be configured to analyze the previously generated master OCV table to identify the values in the previously generated master OCV table corresponding to the pre-defined measurement intervals.
  • the battery controller 201 further updates (307) the SOC with the corrected OCV values.
  • the battery controller 201 can be configured identify the corrected OCV by correlating the difference between the measured currents OCV and the corresponding OCV from the previously generated master OCV table to updated the SOC with the corrected OCV values. If the vehicle 200 has been at rest for less than the pre-defined measurement intervals, the battery controller 201 retains (308) the previous OCV.
  • the various actions in method 300 may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some actions listed in FIG. 3 may be omitted.
  • FIG. 4 is a flowchart depicting the process of estimating SOC using Coulomb counting.
  • the battery controller 201 checks (401) if the battery 202 is currently being charged. In an embodiment herein, the battery controller 201 can check if the battery 202 is currently being charged by checking if the charging flag is active. If the battery 202 is currently being charged, the battery controller 201 determines (402) the coloumb counter for battery charge. The battery controller 201 can determine the coulomb counter for battery charge as follows:
  • I is the current throughput
  • Ktc is the charging temperature factor
  • Kcc is the charge rate factor.
  • the battery controller 201 further determines (403) a correction factor that is applied to the SOC. If the battery 202 is currently not being charged, the battery controller 201 determines (404) the coloumb counter for battery discharge. The battery controller 201 can determine the coulomb counter as follows:
  • Ktd is the discharging temperature factor
  • Kdc is the discharge rate factor.
  • the battery controller 201 determines (405) the SOC by adding the determined coulomb counter to an initial SOC, at pre-defined estimation time intervals and applying the correction factor.
  • the initial SOC can depend on the previous state of the vehicle. If the vehicle 200 is starting after power off, the battery controller 201 can consider SOCocv as the initial SOC. If the vehicle 200 is not starting after power off, the battery controller 201 considers a previously estimated SOC using coulomb counting as the initial SOC.
  • the battery controller 201 further sets (406) the flag for SOC based on coulomb counting flag to high.
  • the various actions in method 400 may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some actions listed in FIG. 4 may be omitted.
  • FIG. 5 is a flow chart depicting the process of the determining the correction factor that is applied when coulomb counting is performed.
  • the battery controller 201 checks (501) if the initial SOC is less than a threshold. If the initial SOC is less than the threshold, the battery controller 201 starts (502) a timer Tl. With the timer on, the battery controller 201 checks (503) if all values of a charge current of the battery 202 are below a pre-defined current threshold. If all values of the charge current of the battery 202 are below the pre-defined current threshold, the battery controller 201 then checks (504) the master OCV table for charge current saturation, based on the saturation current, and the battery temperature.
  • the battery controller 201 resets (506) the timer to zero on every update (505) to the SOC EST -
  • the various actions in method 500 may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some actions listed in FIG. 5 may be omitted.
  • the embodiments disclosed herein can be implemented through at least one software program running on at least one hardware device and performing network management functions to control the network elements.
  • the network elements shown in Fig. 2 includes blocks which can be at least one of a hardware device, or a combination of hardware device and software module.

Landscapes

  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Chemical & Material Sciences (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Electrochemistry (AREA)
  • General Chemical & Material Sciences (AREA)
  • Secondary Cells (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Energy (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Sustainable Development (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

Estimation of SOC of a lead-acid battery. Embodiments herein disclose methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle. Embodiments herein disclose methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle using discharge and charge correction factors. Embodiments herein disclose methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle using a master OCV table based SOC estimation (SOCOCV) after the vehicle has been powered off, and a current throughput based SOC estimation (SOCEST) based on coulomb count integration (amp- second (As) integration) when the vehicle is operational. Embodiments herein disclose methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle considering ageing of the battery and temperature.

Description

ESTIMATION OF SOC OF A LEAD-ACID BATTERY
CROSS REFERENCE TO RELATED APPLICATION
This application is based on and derives the benefit of Indian Provisional Application 201641026864, the contents of which are incorporated herein by reference.
FIELD OF INVENTION
[001] Embodiments herein relate to vehicle systems, and more particularly to lead acid batteries in vehicles.
BACKGROUND OF INVENTION
[002] In today's automotive scenario, when emission control and dependence of conventional fossil fuel are seen as bigger challenges, a variety of propulsion technologies are being considered to power vehicles. The increasing demand to improve fuel economy and reduce emissions in present vehicles calls for a big push towards powertrain electrification (development of hybrid and electric vehicle).
[003] Lead-acid batteries have been widely used in the automotive industry for starting-lighting-ignition (SLI) applications. But they are typically used as backup energy storage for powering vehicle ECU's during conventional engine off condition and for engine cranking and only add weight to the conventional powertrain during normal running. For optimization of lead acid battery system, it is required to increase the usage (battery cycling) of the battery during normal vehicle running conditions. [004] Typical applications wherein these batteries are being used are stop start applications and low voltage hybrid vehicle applications. In the stop start application, the engine can be automatically stopped and restarted which typically occurs at traffic signals. This application avoids unnecessary idling of vehicle, hence saving fuel. Low voltage battery systems (lead acid battery based systems with management systems) are being used as cranking device during vehicle re-start. In the low voltage hybrid vehicle application with an electric machine (which can act as alternator and motor) using low voltage battery, hybrid function (torque assist, brake energy recovery) can be achieved. This helps in supporting engine during acceleration and recovering braking energy and hence increasing the overall efficiency of the system.
[005] Both the above said applications, as compared to standard vehicles driven by an ICE (Internal Combustion Engine), bring in improved fuel economy and consequently reduced emissions. For efficient operation, a lead-acid battery needs to operate near to its optimal SOC to maximize its discharge, charge power capabilities and defined life.
[006] Determination of state of charge (SOC) of a lead acid system is a challenging task, as discharge and charge characteristics of a lead-acid battery system are not symmetric. The discharge battery resistance is typically lower than the charge battery resistance. Direct prediction of SOC based on voltage and throughput is not straightforward.
OBJECT OF INVENTION
[007] The principal object of embodiments as disclosed herein is to provide methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle. [008] Another object of embodiments as disclosed herein is to provide methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle using discharge and charge correction factors.
[009] Another object of embodiments as disclosed herein is to provide methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle using a master OCV table based SOC estimation (SOCocv) after the vehicle has been powered off, and a current throughput based SOC estimation (SOCEST) based on coulomb count integration (amp-second (As) integration) when the vehicle is operational. [0010] Another object of embodiments as disclosed herein is to provide methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle considering ageing of the battery and temperature. BRIEF DESCRIPTION OF FIGURES
[0011] This invention is illustrated in the accompanying drawings, through out which like reference letters indicate corresponding parts in the various figures. The embodiments herein will be better understood from the following description with reference to the drawings, in which: [0012] FIG. 1 is a flow chart of the SOC estimation logic, according to embodiments as disclosed herein;
[0013] FIG. 2 depicts a system in a vehicle for estimating SOC of a battery, according to embodiments as disclosed herein;
[0014] FIG. 3 is a flowchart depicting the process of estimating SOCocv, according to embodiments as disclosed herein; [0015] FIG. 4 is a flowchart depicting the process of estimating SOC using Coulomb counting, according to embodiments as disclosed herein; and
[0016] FIG. 5 is a flow chart depicting the process of the determining the correction factor that is applied when coulomb counting is performed, according to embodiments as disclosed herein.
DETAILED DESCRIPTION OF INVENTION
[0017] The embodiments herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting embodiments that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well- known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
[0018] The embodiments herein provide methods and systems for determining State of Charge (SOC) of a lead acid battery in a vehicle. Referring now to the drawings, and more particularly to FIGS. 1 through 5, where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments.
[0019] The vehicle, as referred to herein can be any vehicle comprising of a lead acid battery. In an embodiment herein, the vehicle can be a hybrid vehicle. In an embodiment herein, the vehicle can comprise of only a conventional engine based powertrain. Example of the vehicle can be a car, truck, van, bus, and so on.
[0020] FIG. 1 is a flow chart of the SOC estimation logic. A check is made (101) if the vehicle has been powered off. If the vehicle has been powered off, the SOC (State of Charge) of a battery is estimated (102) based on OCV (Open Circuit Voltage) (hereinafter referred to as SOCocv)- If the vehicle has not been powered off, the SOC of the battery is estimated (103) based on coulomb counting (hereinafter referred to as SOCEST)- The various actions in method 100 may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some actions listed in FIG. 1 may be omitted. [0021] FIG. 2 depicts a system in a vehicle for estimating SOC of a battery. The system in the vehicle 200 comprises of a battery controller 201 mounted on a negative terminal of the battery 202. The battery controller 201 can be further connected to at least one Electronic Control Unit (ECU) 203 present in the vehicle and at least one electrical load 204 present in the vehicle 200.
[0022] The battery controller 201 can check if the vehicle 200 has been powered off. If the vehicle has been powered off, the battery controller 201 can estimate the SOC of the battery 202 is estimated (102) based on OCV. The battery controller 201 can generate a master OCV table by measuring the OCV of the battery 202, once the battery is full rested with no charge throughput, at pre-defined measurement intervals for a predefined time period (for example, every 30 minutes for a 4 hour duration). The master OCV table, comprising of a matrix with a pre-defined number of indices (for example, 8), is fully populated in the pre-defined time period. In an embodiment herein, the battery 202 achieves chemical, electrical and thermal equilibrium in the pre-defined time period. If battery is not rested for the pre-defined time period, but is in rest for more than the pre-defined measurement intervals, the battery controller 201 generates a running OCV table. The battery controller 201 can correct the running OCV table dynamically using a previous master OCV table (if present). The battery controller 201 determines the SOCocv based on the OCV table (which can be either the master OCV table or the running OCV table) for the current ignition cycle. If the battery is not rested for more than 30 minutes, the battery controller 201 can consider the SOC from the previous ignition cycle as the battery SOC.
[0023] If the vehicle 200 has not been powered off, the battery controller 201 can estimate the SOC of the battery 202 based on coulomb counting. Dynamic (run-time) energy throughput, also known as Coulomb Counter, is an integration of current over time (Ampere-second) and the battery controller 201 can be calculated using the charging rates, discharge rates and the battery temperature. The battery controller 201 can update the coulomb counter to a pre-defined level, if the battery charge current is saturated for a defined temperature to a pre-defined level. The battery controller 201 can perform dynamic charge and discharge correction using factors such as discharge and charge related efficiency on the overall system. With coulomb counter and correction factor, the battery controller 201 determines the SOCEST for a current vehicle ignition cycle. The battery controller 201 applies battery-ageing factor, to accommodate capacity degradation, to the overall SOC calculation.
[0024] In an embodiment herein, the vehicle 200 comprises of a memory storage location, wherein the battery controller 201 can store data (such as the OCV values, master OCV table, estimated SOC, and so on) in the memory storage location. The battery controller 201 can also fetch data from the battery storage location, as and when required.
[0025] FIG. 3 is a flowchart depicting the process of estimating SOCocv- The battery controller 201 checks (301) for how much time the vehicle has been off. If the time elapsed is more than a pre-defined off-time period, the battery controller 201 measures (302) OCV of the fully rested battery 202, no charge throughput, at pre-defined measurement intervals for a pre-defined time period. Based on the measurements, the battery controller 201 populates (303) the master OCV table in the pre-defined time period, wherein the master OCV table comprises of a matrix with a pre-defined number of indices. In an example, the master OCV table, with 8 indices matrix, can be fully populated in 4 hours, which is the time in which the battery 202 achieves chemical, electrical and thermal equilibrium. The battery controller 201 estimates (304) the battery SOC using the master OCV table. The battery SOC can be estimated by mapping every value of the master OCV with the battery SOC. If the time elapsed is less than the pre-defined off-time period, the battery controller 201 checks (305) if the vehicle 200 has been at rest for more than the pre-defined measurement intervals. If the vehicle 200 has been at rest for more than the pre-defined measurement intervals, the battery controller 201 corrects (306) OCV values based on a previously generated master OCV table (if available). The battery controller 201 can be configured to analyze the previously generated master OCV table to identify the values in the previously generated master OCV table corresponding to the pre-defined measurement intervals. The battery controller 201 further updates (307) the SOC with the corrected OCV values. The battery controller 201 can be configured identify the corrected OCV by correlating the difference between the measured currents OCV and the corresponding OCV from the previously generated master OCV table to updated the SOC with the corrected OCV values. If the vehicle 200 has been at rest for less than the pre-defined measurement intervals, the battery controller 201 retains (308) the previous OCV. The various actions in method 300 may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some actions listed in FIG. 3 may be omitted.
[0026] FIG. 4 is a flowchart depicting the process of estimating SOC using Coulomb counting. The battery controller 201 checks (401) if the battery 202 is currently being charged. In an embodiment herein, the battery controller 201 can check if the battery 202 is currently being charged by checking if the charging flag is active. If the battery 202 is currently being charged, the battery controller 201 determines (402) the coloumb counter for battery charge. The battery controller 201 can determine the coulomb counter for battery charge as follows:
Coulomb counting (charge) = P(Ktc*Kcc)
Wherein
I is the current throughput;
Ktc is the charging temperature factor; and
Kcc is the charge rate factor. [0027] The battery controller 201 further determines (403) a correction factor that is applied to the SOC. If the battery 202 is currently not being charged, the battery controller 201 determines (404) the coloumb counter for battery discharge. The battery controller 201 can determine the coulomb counter as follows:
Coulomb counting (discharge) = P(Ktd*Kdc)
Wherein
Ktd is the discharging temperature factor; and
Kdc is the discharge rate factor.
[0028] The battery controller 201 determines (405) the SOC by adding the determined coulomb counter to an initial SOC, at pre-defined estimation time intervals and applying the correction factor. The initial SOC can depend on the previous state of the vehicle. If the vehicle 200 is starting after power off, the battery controller 201 can consider SOCocv as the initial SOC. If the vehicle 200 is not starting after power off, the battery controller 201 considers a previously estimated SOC using coulomb counting as the initial SOC. The battery controller 201 further sets (406) the flag for SOC based on coulomb counting flag to high. The various actions in method 400 may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some actions listed in FIG. 4 may be omitted.
[0029] FIG. 5 is a flow chart depicting the process of the determining the correction factor that is applied when coulomb counting is performed. The battery controller 201 checks (501) if the initial SOC is less than a threshold. If the initial SOC is less than the threshold, the battery controller 201 starts (502) a timer Tl. With the timer on, the battery controller 201 checks (503) if all values of a charge current of the battery 202 are below a pre-defined current threshold. If all values of the charge current of the battery 202 are below the pre-defined current threshold, the battery controller 201 then checks (504) the master OCV table for charge current saturation, based on the saturation current, and the battery temperature. The battery controller 201 resets (506) the timer to zero on every update (505) to the SOCEST- The various actions in method 500 may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some actions listed in FIG. 5 may be omitted.
[0030] The embodiments disclosed herein can be implemented through at least one software program running on at least one hardware device and performing network management functions to control the network elements. The network elements shown in Fig. 2, includes blocks which can be at least one of a hardware device, or a combination of hardware device and software module.
[0031] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.

Claims

STATEMENT OF CLAIMS We claim:
1. A system for monitoring SOC (State of Charge) of a lead-acid battery in a vehicle (200), the system comprising of a battery controller (201) configured for
estimating SOC of the battery using Open Circuit Voltage (OCV), if the vehicle (200) is powered off;
estimating SOC of the battery using coulomb counting, if the vehicle (200) is not powered off; and
wherein the battery controller (201) is connected to a negative lead of the lead-acid battery.
2. The system, as claimed in claim 1, wherein the battery controller (201) is configured for estimating SOC of the battery using OCV by
measuring OCV of the battery (202), no charge throughput, for a pre-defined time period at pre-defined measurement intervals, if the vehicle (200) has been off for more than a pre-defined time period;
populating a master OCV table with the measured OCV, wherein the master OCV table comprises of a matrix with a pre-defined number of indices; and
estimating battery SOC using the master OCV table.
3. The system, as claimed in claim 1, wherein the battery controller (201) is configured for estimating SOC of the battery using OCV by correcting OCV values based on a previously generated master OCV table, if the vehicle has not been off for more than the pre-defined off-time period.
4. The system, as claimed in claim 1, wherein the battery controller (201) is configured for estimating SOC of the battery using OCV by correcting OCV values based on a previously generated master OCV table, if the vehicle has not been off for more than the pre-defined off-time period and the vehicle has been off for less than the pre-defined measurement intervals.
5. The system, as claimed in claim 1, wherein the battery controller (201) is configured for estimating SOC of the battery using OCV by
determining coulomb counter for battery charge as the product of current throughput, a charging temperature factor and a charge rate factor, if a charging flag is active;
determining coulomb counter for battery discharge as the product of current throughput, a discharging temperature factor and a discharge rate factor, if the charging flag is not active;
determining SOC by adding the determined coulomb counter to an initial SOC.
6. The system, as claimed in claim 5, wherein the battery controller (201) is configured to determine the initial SOC depending on previous state of the vehicle (200).
7. The system, as claimed in claim 5, wherein the battery controller (201) is further configured to setting a flag for SOC based on coulomb counting flag to high.
8. The system, as claimed in claim 5, wherein the battery controller (201) is further configured to apply a correction factor to the determined SOC.
9. A method for monitoring SOC (State of Charge) of a lead-acid battery in a vehicle (200), the method comprising
estimating SOC of the battery using Open Circuit Voltage (OCV) by a battery controller (201), if the vehicle (200) is powered off; and estimating SOC of the battery using coulomb counting by a battery controller (201) by the battery controller (201), if the vehicle (200) is not powered off;
wherein the battery controller (201) is connected to a negative lead of the lead-acid battery.
10. The method, as claimed in claim 9, wherein estimating SOC of the battery using OCV further comprises
measuring OCV of the battery (202) by the battery controller (201), no charge throughput, for a pre-defined time period at pre-defined measurement intervals, if the vehicle (200) has been off for more than a pre-defined time period;
populating a master OCV table with the measured OCV by the battery controller (201), wherein the master OCV table comprises of a matrix with a pre-defined number of indices; and
estimating battery SOC by the battery controller (201) using the master OCV table.
11. The method, as claimed in claim 9, wherein estimating SOC of the battery using OCV comprises correcting OCV values based on a previously generated master OCV table by the battery controller (201), if the vehicle has not been off for more than the pre-defined off-time period.
12. The method, as claimed in claim 9, wherein estimating SOC of the battery using OCV comprises correcting OCV values based on a previously generated master OCV table by the battery controller (201), if the vehicle has not been off for more than the pre-defined off-time period and the vehicle has been off for less than the pre-defined measurement intervals.
13. The method, as claimed in claim 9, wherein estimating SOC of the battery using OCV comprises determining coulomb counter for battery charge as the product of current throughput by the battery controller (201), a charging temperature factor and a charge rate factor, if a charging flag is active;
determining coulomb counter for battery discharge as the product of current throughput by the battery controller (201), a discharging temperature factor and a discharge rate factor, if the charging flag is not active;
determining SOC by adding the determined coulomb counter to an initial SOC by the battery controller (201).
14. The method, as claimed in claim 13, wherein determining the initial SOC by the battery controller (201) depending on previous state of the vehicle (200).
15. The method, as claimed in claim 13, wherein the method further comprises setting a flag for SOC based on coulomb counting flag to high by the battery controller (201).
16. The method, as claimed in claim 13, wherein method further comprises applying a correction factor to the determined SOC by the battery controller (201).
PCT/IN2017/050307 2016-08-05 2017-07-26 Estimation of soc of a lead-acid battery WO2018025276A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP17836529.2A EP3494006A4 (en) 2016-08-05 2017-07-26 Estimation of soc of a lead-acid battery
US16/321,937 US20190176657A1 (en) 2016-08-05 2017-07-26 Estimation of soc of a lead-acid battery

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
IN201641026864 2016-08-05
IN201641026864 2016-08-05

Publications (1)

Publication Number Publication Date
WO2018025276A1 true WO2018025276A1 (en) 2018-02-08

Family

ID=61072849

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/IN2017/050307 WO2018025276A1 (en) 2016-08-05 2017-07-26 Estimation of soc of a lead-acid battery

Country Status (3)

Country Link
US (1) US20190176657A1 (en)
EP (1) EP3494006A4 (en)
WO (1) WO2018025276A1 (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109398154A (en) * 2018-10-26 2019-03-01 湖南晟芯源微电子科技有限公司 The battery management system and method for electric car 48V start stop system
CN110324383A (en) * 2018-03-30 2019-10-11 比亚迪股份有限公司 Cloud Server, electric car and the wherein management system, method of power battery
CN114636936A (en) * 2022-03-16 2022-06-17 长兴太湖能谷科技有限公司 Correction method and device for SOC prediction curve of lead-acid battery in charging stage

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP7172690B2 (en) * 2019-02-12 2022-11-16 トヨタ自動車株式会社 BATTERY SYSTEM AND SECONDARY BATTERY SOC ESTIMATION METHOD
CN111487537B (en) * 2020-05-29 2022-05-27 重庆金康新能源汽车有限公司 Method and system for modifying state of charge estimation
CN113002363B (en) * 2021-03-03 2023-03-17 一汽解放汽车有限公司 Method and device for correcting battery charge, vehicle and medium
CN113109717B (en) * 2021-03-27 2022-02-18 浙江大学 Lithium battery state of charge estimation method based on characteristic curve optimization
CN113945849B (en) * 2021-09-01 2024-03-29 深圳拓邦股份有限公司 SOC value calculation method in charging process of lead-acid storage battery, storage battery and electric appliance

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6417668B1 (en) * 2001-01-31 2002-07-09 International Truck International Property Company, L.L.C. Vehicle battery condition monitoring system
US6646419B1 (en) * 2002-05-15 2003-11-11 General Motors Corporation State of charge algorithm for lead-acid battery in a hybrid electric vehicle
US20100138176A1 (en) * 2008-12-02 2010-06-03 Broadcom Corporation System for accurate battery run time estimation utilizing voltage capture and coulomb counting
US7795874B1 (en) * 2007-10-10 2010-09-14 Commissariat A L'energie Atomique Method of estimation of the state of charge of a lead-acid battery
US8669741B2 (en) * 2006-08-11 2014-03-11 Samsung Sdi Co., Ltd. Battery management system and driving method thereof
US20140368208A1 (en) * 2012-03-21 2014-12-18 Sanyo Electric Co., Ltd. Cell state estimation device
WO2017078606A1 (en) * 2015-11-05 2017-05-11 Ctek Sweden Ab A system and a method for determining state-of-charge of a battery

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5321627A (en) * 1992-03-11 1994-06-14 Globe-Union, Inc. Battery monitor and method for providing operating parameters
US6356083B1 (en) * 2001-02-07 2002-03-12 General Motors Corporation State of charge algorithm for a battery
FR2917178B1 (en) * 2007-06-07 2009-09-04 Peugeot Citroen Automobiles Sa SYSTEM AND METHOD FOR DETERMINING THE LOSS OF CAPACITY AND ENERGY OF A BATTERY.
US9108524B2 (en) * 2013-10-22 2015-08-18 GM Global Technology Operations LLC Battery SOC estimation with automatic correction

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6417668B1 (en) * 2001-01-31 2002-07-09 International Truck International Property Company, L.L.C. Vehicle battery condition monitoring system
US6646419B1 (en) * 2002-05-15 2003-11-11 General Motors Corporation State of charge algorithm for lead-acid battery in a hybrid electric vehicle
US8669741B2 (en) * 2006-08-11 2014-03-11 Samsung Sdi Co., Ltd. Battery management system and driving method thereof
US7795874B1 (en) * 2007-10-10 2010-09-14 Commissariat A L'energie Atomique Method of estimation of the state of charge of a lead-acid battery
US20100138176A1 (en) * 2008-12-02 2010-06-03 Broadcom Corporation System for accurate battery run time estimation utilizing voltage capture and coulomb counting
US20140368208A1 (en) * 2012-03-21 2014-12-18 Sanyo Electric Co., Ltd. Cell state estimation device
WO2017078606A1 (en) * 2015-11-05 2017-05-11 Ctek Sweden Ab A system and a method for determining state-of-charge of a battery

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
CHANG, W-Y.: "The State of Charge Estimating Methods for Battery: A Review", ISRN APPLIED MATHEMATICS, vol. 2013, 2013, pages 1 - 7, XP055460880, DOI: 10.1155/2013/953792 *
See also references of EP3494006A4 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110324383A (en) * 2018-03-30 2019-10-11 比亚迪股份有限公司 Cloud Server, electric car and the wherein management system, method of power battery
CN110324383B (en) * 2018-03-30 2021-09-03 比亚迪股份有限公司 Cloud server, electric automobile and management system and method of power battery in electric automobile
CN109398154A (en) * 2018-10-26 2019-03-01 湖南晟芯源微电子科技有限公司 The battery management system and method for electric car 48V start stop system
CN114636936A (en) * 2022-03-16 2022-06-17 长兴太湖能谷科技有限公司 Correction method and device for SOC prediction curve of lead-acid battery in charging stage

Also Published As

Publication number Publication date
US20190176657A1 (en) 2019-06-13
EP3494006A1 (en) 2019-06-12
EP3494006A4 (en) 2020-04-08

Similar Documents

Publication Publication Date Title
US20190176657A1 (en) Estimation of soc of a lead-acid battery
US9855854B2 (en) Charge control device and charge control method
US10054097B2 (en) Vehicular control apparatus
JP5840116B2 (en) Secondary battery state estimation apparatus and method
US20150331055A1 (en) Vehicle control apparatus
CN109387790B (en) Power supply system
JP5684172B2 (en) Secondary battery state detection device and secondary battery state detection method
JP2009214839A (en) Vehicular power supply device
CN107444313B (en) Control device for power supply system
KR20200075929A (en) Periodic supplementary charging method for battery of vehicle
WO2018131683A1 (en) Control device
US10498154B2 (en) Electric power system
US20150166046A1 (en) Vehicle control apparatus
CN110962677A (en) Monitoring method and system for vehicle standing
JP6350886B2 (en) Lithium-ion battery deterioration judgment method
JP2016195495A (en) Secondary battery charging control device and secondary battery charging control method
JP2018157694A (en) Charge control device for on-vehicle battery
KR100906872B1 (en) Method for battery performance improvement and SOC reset of HEV
US11644514B2 (en) Deterioration amount estimation device, energy storage system, deterioration amount estimation method, and computer program
JP2017150975A (en) High-rate deterioration index estimation controller
JP2004325263A (en) Self-discharge amount detection device of battery
JP6725399B2 (en) Electronic control unit for automobile
CN104467072A (en) Charge control device, vehicle having same and charge control method
JP2018098992A (en) Voltage detector and voltage detection method
JP5764584B2 (en) Charge control apparatus and method

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 17836529

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

ENP Entry into the national phase

Ref document number: 2017836529

Country of ref document: EP

Effective date: 20190305