Battery SOF estimation method and system based on intelligent current sensor, and storage medium

Abstract

The invention provides a battery SOF estimation method and system based on an intelligent current sensor and a storage medium, and the method comprises the steps: obtaining and processing battery data to obtain target data, the target data comprising a battery SOC and a temperature parameter; table look-up is carried out based on the battery SOC and the temperature parameter to obtain an open-circuit voltage and an equivalent starting internal resistance, the table comprises an internal resistance table and an open-circuit voltmeter, and the internal resistance table is related to a starting condition type; extracting a starting peak current, and calculating a starting voltage in combination with the open-circuit voltage and the equivalent starting internal resistance; and comparing the starting voltage with a preset voltage threshold value, and outputting the SOF of the battery based on a comparison result. According to the method, the estimation precision and the environmental adaptability of the SOF are remarkably improved, the start failure caused by misjudgment is effectively avoided, the reliability of a vehicle start-stop system and the user experience are enhanced, and meanwhile the maintenance cost of the vehicle is reduced.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of data processing, and particularly relates to a battery SOF estimation method and system based on an intelligent current sensor and a storage medium. BACKGROUND

[0002] In the prior art, start-stop, as one of the core technologies of modern automobile energy-saving technology, has been far away from our life. It not only can significantly reduce fuel consumption and emissions, but also can prolong the service life of the power system and reduce the maintenance cost.

[0003] Whether the automobile can start is mainly realized by monitoring of an IBS (Intelligent Battery Sensor) sensor. The IBS can obtain relevant information such as voltage, current and temperature of the battery, and calculate the SOC (State of Charge), SOH (State of Health) and SOF (State of Function) of the battery according to the information. The SOF corresponds to whether the battery has the ability to successfully start the engine in a very short time. However, the SOF of the lead-acid battery is greatly affected by the running conditions of the battery and the environment, which leads to a large calculation error, thereby affecting the judgment of the automobile and making it impossible to start the automobile.

[0004] The traditional SOF prediction method of the lead-acid battery mainly predicts the current starting voltage according to the resistance voltage difference method. Usually, the static resistance or dynamic resistance of the battery is tested under a specific environment. This method involves limited working conditions and environment, and it is difficult to truly simulate the actual working conditions of the battery in the vehicle. Therefore, the test error of this method is large under complex working conditions, and it is easy to fluctuate. SUMMARY

[0005] In view of the above-mentioned shortcomings of the prior art, the purpose of the present application is to provide a battery SOF estimation method and system based on an intelligent current sensor and a storage medium, which solves the problem of low calculation accuracy and poor environmental adaptability of the lead-acid battery start function state estimation method due to the dependence on limited resistance test working conditions.

[0006] In a first aspect, the present application provides a battery SOF estimation method based on an intelligent battery sensor, which comprises:

[0007] obtaining battery data for processing to obtain target data, wherein the target data includes battery SOC and temperature parameters;

[0008] obtaining an open circuit voltage and an equivalent starting internal resistance based on the battery SOC and the temperature parameter by table lookup, wherein the table includes an internal resistance table and an open circuit voltage table, and the internal resistance table is related to a starting condition type;

[0009] extracting a starting peak current, and calculating a starting voltage based on the open circuit voltage and the equivalent starting internal resistance;

[0010] comparing the starting voltage with a preset voltage threshold, and outputting a battery SOF based on a comparison result.

[0011] In some embodiments of the first aspect of the present application, the method further comprises generating an internal resistance table, specifically comprising:

[0012] generating the internal resistance table based on bench testing, wherein the internal resistance test is performed based on the starting condition type, and the starting condition type includes a first starting and a second starting;

[0013] when performing the first starting internal resistance test, after the battery is fully charged and the temperature box is set to a target temperature, a first pulse discharge and data collection are performed to calculate the equivalent starting internal resistance of the first starting, wherein an open circuit or a small background current is used to simulate a vehicle parked and stationary state;

[0014] when performing the second starting internal resistance test, after the battery is fully charged and the temperature box is set to a target temperature, a second pulse discharge and data collection are performed to calculate the equivalent starting internal resistance of the second starting, wherein a large background current is used to simulate a vehicle turned off but powered on state;

[0015] obtaining the internal resistance table by combining the starting condition type and the equivalent starting internal resistance corresponding to different battery SOCs at the target temperature, wherein the internal resistance table includes a first starting equivalent starting internal resistance table and a second starting equivalent starting internal resistance table.

[0016] In some embodiments of the first aspect of the present application, the method further comprises generating an open circuit voltage table, specifically comprising:

[0017] generating the open circuit voltage table based on bench testing, wherein

[0018] after the battery is fully charged and the temperature box is set to a target temperature, gradient discharge is repeatedly performed and the battery voltage is recorded until the battery voltage is discharged to a preset cut-off voltage;

[0019] obtaining the open circuit voltage table by obtaining the open circuit voltage values corresponding to different battery SOCs at the target temperature.

[0020] In some embodiments of the first aspect of the present application, the obtaining an open circuit voltage and an equivalent starting internal resistance based on the battery SOC and the temperature parameter by table lookup specifically comprises:

[0021] Historical current data is read from the smart battery sensor, and the startup condition type is determined based on the historical current data, wherein the startup condition type includes first startup and restart.

[0022] The internal resistance table is determined based on the startup operating condition type, wherein the internal resistance table includes an equivalent startup internal resistance table for the first startup and an equivalent startup internal resistance table for subsequent startups;

[0023] Using battery SOC and temperature parameters as indexes, the equivalent starting internal resistance is obtained by looking up the internal resistance table, and the open circuit voltage is obtained by looking up the open circuit voltage table.

[0024] In some embodiments of the first aspect of this application, the step of extracting the startup peak current and calculating the startup voltage in combination with the open-circuit voltage and the equivalent startup internal resistance specifically includes:

[0025] Extract the startup peak current ;

[0026] The startup voltage is calculated based on a preset startup voltage calculation formula, wherein the startup voltage calculation formula is as follows:

[0027] ;

[0028] in, The battery level is And the temperature is Start-up voltage at that time It is the peak starting current. The battery level is And the temperature is Open circuit voltage at that time The battery level is And the temperature is The equivalent starting internal resistance at that time.

[0029] In some embodiments of the first aspect of this application, the acquisition of battery data is processed to obtain target data. The battery data includes battery voltage, battery current, and battery temperature. The target data includes battery SOC and temperature parameters, specifically including:

[0030] Battery data is acquired from a smart battery sensor, wherein the battery data includes battery voltage, battery current, and current temperature;

[0031] The battery SOC and temperature parameters are obtained by filtering and calculation based on the battery data.

[0032] In some embodiments of the first aspect of the present application, when the starting voltage is greater than or equal to the voltage threshold, the output battery SOF is capable of starting, otherwise the output battery SOF is not capable of starting.

[0033] To achieve the above object and other related objects, the second aspect of the present application provides a battery SOF estimation system based on an intelligent battery sensor, the system comprising:

[0034] An acquisition module is configured to acquire battery data for processing to obtain target data, the battery data comprising battery voltage, battery current and battery temperature, and the target data comprising battery SOC and temperature parameters;

[0035] A table lookup module is configured to perform table lookup based on the battery SOC and the temperature parameters to obtain open circuit voltage and equivalent starting internal resistance, the table comprising an internal resistance table and an open circuit voltage table, wherein the internal resistance table is related to starting working condition types;

[0036] A calculation module is configured to extract a starting peak current, and calculate a starting voltage in combination with the open circuit voltage and the equivalent starting internal resistance;

[0037] An output module is configured to compare the starting voltage with a preset voltage threshold, and output battery SOF based on the comparison result.

[0038] To achieve the above object and other related objects, the third aspect of the present application provides a computer readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the battery SOF estimation method based on an intelligent battery sensor as described in any of the above aspects.

[0039] To achieve the above object and other related objects, the fourth aspect of the present application provides an electronic device comprising a memory, a processor and a computer program stored on the memory, the processor executing the computer program to implement the battery SOF estimation method based on an intelligent battery sensor as described in any of the above aspects.

[0040] As described above, the battery SOF estimation method, system and storage medium based on an intelligent current sensor have the following beneficial effects: the intelligent battery sensor IBS can improve the effective monitoring accuracy of the starting function state of the storage battery, compared with the traditional starting function test method which calculates the starting voltage by measuring the resistance and the battery model method, the method of the present application can more accurately simulate the starting working condition and the battery environment of the vehicle, and can more accurately calculate the starting voltage of the battery from the mechanism, thereby improving the safety and user experience of the vehicle, reducing the probability of failure caused by low power, and effectively reducing the maintenance cost and stability of the vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 The diagram shows a step-by-step illustration of the battery SOF estimation method based on a smart battery sensor according to an embodiment of the present invention.

[0042] Figure 2 The diagram shows a flowchart of an embodiment of the battery SOF estimation method based on a smart battery sensor according to the present invention.

[0043] Figure 3 A- Figure 3 B shows a flowchart of the equivalent start-up internal resistance test in one embodiment of the battery SOF estimation method based on a smart battery sensor of the present invention.

[0044] Figure 4 The diagram shows a test bench structure in one embodiment of the battery SOF estimation method based on a smart battery sensor according to the present invention.

[0045] Figure 5 The flowchart shown is a startup condition type determination flowchart in one embodiment of the battery SOF estimation method based on intelligent battery sensor of the present invention.

[0046] Figure 6 The diagram shown is a structural schematic of a battery SOF estimation system based on a smart battery sensor according to an embodiment of the present invention.

[0047] Figure 7 The diagram shown is a structural schematic of an embodiment of the electronic device of the present invention.

[0048] Component designation explanation

[0049] S102~S108 Step 1 Test bench 2 Oven 3 Charging and discharging device 4 Control device 5 Battery to be tested 60 Battery SOF estimation system based on intelligent battery sensor 61 Acquisition module 62 Table lookup module 63 Calculation module 64 Output module 701 Processor 702 Memory 7021 Operating system 7022 Application program 703 Network interface 704 Bus system 705 User interface Detailed Implementation

[0050] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0051] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0052] Furthermore, the use of terms such as "first" and "second" in this application is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of the various embodiments can be combined with each other, but only on the basis of being achievable by those skilled in the art. If the combination of technical solutions is contradictory or impossible to implement, such a combination of technical solutions should be considered non-existent and not within the scope of protection claimed in this application.

[0053] In existing technologies, automotive start-stop systems widely rely on intelligent battery sensors to monitor battery status. Among these, the start-up function status is a key parameter for determining whether a vehicle can start successfully. However, traditional methods have the following drawbacks: First, the calculation accuracy is low and the error is large because the SOF of lead-acid batteries is significantly affected by actual operating conditions and ambient temperature. Since the battery models used in traditional methods are relatively simple, they are difficult to accurately reflect battery behavior under complex and variable conditions. Second, the testing methods have poor operating condition simulation capabilities and environmental adaptability. Testing is conducted under limited environmental and operating conditions, which cannot effectively simulate the vehicle's start-up process in the real world.

[0054] Therefore, this application proposes a battery SOF estimation method, system, and storage medium based on an intelligent current sensor, applicable to vehicles equipped with an intelligent battery sensor (IBS) and start-stop system, particularly for online health management and fault early warning of lead-acid batteries. In the application scenario of this application, real-time, high-precision battery SOF determination can be performed. Regardless of whether it is cold winter or hot summer, or whether the battery is in different aging states and charge levels, it can accurately predict whether the battery has the ability to successfully start the engine, thereby greatly improving the vehicle starting success rate and system reliability, reducing faults caused by sudden battery depletion, ensuring smooth driving, and extending battery life. The technical solutions in the embodiments of this invention will be described in detail below with reference to the accompanying drawings.

[0055] like Figure 1 As shown, in one embodiment of the invention, the battery SOF estimation method based on a smart battery sensor of the present invention includes the following steps:

[0056] Step S102: Obtain battery data and process it to obtain target data, wherein the target data includes battery SOC and temperature parameters;

[0057] Step S104: Based on the battery SOC and the temperature parameters, look up the table to obtain the open circuit voltage and equivalent starting internal resistance. The table includes an internal resistance table and an open circuit voltage table.

[0058] Step S106: Extract the peak starting current and calculate the starting voltage by combining the open-circuit voltage and the equivalent starting internal resistance;

[0059] Step S108: Compare the starting voltage with a preset voltage threshold, and output the battery SOF based on the comparison result.

[0060] It should be noted that, in this embodiment, as Figure 2 As shown, the flowchart illustrates the method. First, during application, battery data is acquired based on the smart battery sensor to further calculate the battery SOC and temperature parameters. Then, based on the battery SOC and temperature parameters, a lookup table is performed to obtain the open-circuit voltage and equivalent starting internal resistance. The tables include an internal resistance table and an open-circuit voltage table. The lookup table is stored in the smart battery sensor. The subsequent instructions will explain in detail how to perform bench testing to generate the corresponding tables.

[0061] Furthermore, in this embodiment, the starting peak current is then extracted, and the starting voltage is calculated by combining the open-circuit voltage and the equivalent starting internal resistance. Specifically, the calculation is based on Ohm's law. Finally, when outputting the battery SOF, the starting voltage is compared with a preset voltage threshold, and the battery SOF is output based on the comparison result. If the starting voltage is greater than or equal to the voltage threshold, the output battery SOF has the ability to start; otherwise, the output battery SOF does not have the ability to start.

[0062] Furthermore, in one embodiment of the invention, the method further includes generating an internal resistance meter, specifically including:

[0063] The internal resistance table is generated based on bench testing, wherein the internal resistance test is performed based on the startup condition type, which includes first startup and subsequent startup.

[0064] When conducting the first start-up internal resistance test, after the battery is fully charged and the temperature chamber is set to the target temperature, the first pulse discharge and data acquisition are performed to calculate the equivalent start-up internal resistance for the first start-up. The vehicle is parked and stationary based on an open circuit or low background current.

[0065] When performing the restart internal resistance test, after the battery is fully charged and the temperature chamber is set to the target temperature, the second pulse discharge and data acquisition are performed to calculate the equivalent restart internal resistance. The large background current is used to simulate the vehicle's off-state but powered-on state.

[0066] The equivalent starting internal resistance corresponding to different battery SOCs at the target temperature is obtained by combining the starting operating condition type to obtain the internal resistance table, wherein the internal resistance table includes an equivalent starting internal resistance table for the first start and an equivalent starting internal resistance table for subsequent starts.

[0067] It should be noted that, in this embodiment, as Figure 3 A- Figure 3 Figure B shows the flowchart for the equivalent starting internal resistance test. Specifically, Figure 3 A corresponds to the initial internal resistance test. The main process includes full battery charging, temperature chamber setting, pulse discharge, constant current discharge, resting, and full discharge detection. During full battery charging, constant voltage and current limiting charging is used. The battery is charged using a preset charging and discharging device that sets the voltage and current limit, and a current threshold is set. When the charging current is less than the full charge current threshold, charging stops, the battery is considered fully charged, and the process ends. A typical value for the full charge current threshold is "0.5A". The charging method refers to GB / T5008.1. A preset constant temperature resting setting is used to bring the battery to a preset temperature. Correspondingly, a pulse is set to simulate the battery startup conditions. In this embodiment, the first pulse discharge is performed, and parameters such as initial current, pulse current, and pulse width are set to discharge the battery. During the process, the battery's current and voltage signals are acquired through high-frequency sampling, and the battery's internal resistance is calculated using Ohm's law. The initial current, pulse current, and pulse width are obtained through actual vehicle calibration. Taking passenger cars as an example, the typical range of the initial current is "0~0.25A". Constant current discharge involves gradient discharge of the battery to bring it to a preset charge value. In application, different constant current discharge parameters (corresponding to different discharge ratios) can be adjusted. The smaller the discharge ratio, the more accurate the voltage calculation. Correspondingly, the resting process simulates the vehicle's parking and resting state by discharging with an open circuit or a small background current (e.g., 0.1A). Full discharge detection determines whether the battery has completed full discharge by the discharge voltage. For a "12V" lead-acid battery, the typical threshold is "10.5V".

[0068] Furthermore, in this embodiment, Figure 3B corresponds to the restart internal resistance test. The main process includes full battery charging, temperature chamber setting, pulse discharge, constant current discharge, and full discharge detection. The intermediate processes are the same as the initial restart internal resistance test. The difference is that the restart internal resistance test uses a second pulse discharge. Parameters such as initial current two, pulse current two, and pulse width two are set to discharge the battery. The initial current two, pulse current two, and pulse width two are derived from actual vehicle calibration. Taking passenger vehicles as an example, the typical range of initial current two is "5A~50A"; the typical range of pulse current two is "100~600A"; and the typical range of pulse width two is "0.05~0.3S". Furthermore, before applying the second pulse... The system simulates a vehicle's off-state but powered-on state using a large background current (e.g., 20A to simulate the power consumption of onboard equipment). Finally, it combines the starting condition type to obtain the equivalent starting internal resistance corresponding to different battery SOCs at the target temperature, resulting in the internal resistance table. The internal resistance table includes an equivalent starting internal resistance table for the first start and an equivalent starting internal resistance table for subsequent starts. The internal resistance table is a two-dimensional array. The first dimension is the SOC value, typically at a ratio of "10%" with a range of "0%~100%". The second dimension is the temperature, typically at a ratio of "10°C" with a range of "-30~115°C". Different combinations of temperature and SOC correspond to different equivalent starting internal resistances.

[0069] Furthermore, in one embodiment of the invention, the method further includes generating an open-circuit voltmeter, specifically including:

[0070] The open-circuit voltmeter is generated based on bench testing, wherein...

[0071] After the battery is fully charged, set the temperature chamber to the target temperature and let it stand. Then repeat the gradient discharge and record the battery voltage until the battery voltage is discharged to the preset cutoff voltage.

[0072] The open-circuit voltage meter is obtained by acquiring the open-circuit voltage values ​​corresponding to different battery SOCs at the target temperature.

[0073] It should be noted that, in this embodiment, the process of generating an open-circuit voltmeter based on bench testing mainly includes battery full charge, temperature chamber setting, pulse discharge, constant current discharge, resting, and full discharge detection, which is consistent with the process of equivalent starting internal resistance mentioned above. However, after the discharge is completed, the load is disconnected and the battery is allowed to rest (for example, resting for 2 hours). After the resting period, the battery voltage at this time is recorded. The voltage obtained is the open-circuit voltage at the current temperature and the current battery SOC. Then, the open-circuit voltage value corresponding to different battery SOCs at the target temperature can be obtained to obtain the open-circuit voltmeter. The open-circuit voltmeter is a two-dimensional array. The first dimension is the SOC value, with a typical ratio of "10% and a range of 0% to 100%"; the second dimension is the temperature, with a typical ratio of "10°C" and a range of "-30 to 115°C". Different combinations of temperature and SOC correspond to different open-circuit voltages.

[0074] Furthermore, it should be noted that the reference Figure 4 The diagram shows the structural layout of a test bench 1. The test bench 1 comprises a temperature chamber 2, a charging / discharging device 3, a control device 4, and a battery under test 5. The control device 4 is connected to and communicates with the temperature chamber 2 and the charging / discharging device 3 via a wiring harness. The battery under test 5 is installed inside the temperature chamber 2 and connected to the charging / discharging device via the wiring harness. The charging / discharging device has a current sensor, a voltage sensor, and a temperature sensor to collect signals during battery testing and to charge and discharge the battery via the wiring harness. Furthermore, during the test on the test bench, the control device... 4. The charging and discharging device 3 is configured with the current and pulse width time during vehicle startup, and the battery under test 5 is discharged in the form of pulse discharge. The charging and discharging device 3 records the current and voltage parameters during the test. The temperature to be tested is set in the temperature chamber 2, and the equivalent starting internal resistance at a specific temperature and the battery SOC is obtained by the internal resistance test calculation formula. In other embodiments, a water bath can be used to replace the temperature chamber 2 to adjust the battery temperature, or an ammeter or voltmeter can be used to replace the current, voltage and temperature data collection in the charging and discharging device 3.

[0075] Furthermore, in one embodiment of the invention, the step of obtaining the open-circuit voltage and equivalent start-up internal resistance by looking up a table based on the battery SOC and the temperature parameters specifically includes:

[0076] Historical current data is read from the smart battery sensor, and the startup condition type is determined based on the historical current data, wherein the startup condition type includes first startup and restart.

[0077] The internal resistance table is determined based on the startup operating condition type, wherein the internal resistance table includes an equivalent startup internal resistance table for the first startup and an equivalent startup internal resistance table for subsequent startups;

[0078] Using battery SOC and temperature parameters as indexes, the equivalent starting internal resistance is obtained by looking up the internal resistance table, and the open circuit voltage is obtained by looking up the open circuit voltage table.

[0079] It should be noted that, in this embodiment, as Figure 5 The diagram shows a flowchart for determining the startup condition type. Historical current data is read from the smart battery sensor, and the startup condition type is determined based on this data. The startup condition type includes first startup and restart. The internal resistance table can then be determined based on the startup condition type. The internal resistance table includes an equivalent startup internal resistance table for first startup and an equivalent startup internal resistance table for restart. This allows for table lookup using battery SOC and temperature parameters as indexes to obtain the equivalent startup internal resistance and the open-circuit voltage table to obtain the open-circuit voltage. Typical lookup methods include interpolation and curve fitting, which are common choices for those skilled in the art and will not be elaborated upon in this embodiment.

[0080] Furthermore, in one embodiment of the invention, the step of extracting the starting peak current and calculating the starting voltage by combining the open-circuit voltage and the equivalent starting internal resistance specifically includes:

[0081] Extract the startup peak current ;

[0082] The startup voltage is calculated based on a preset startup voltage calculation formula, wherein the startup voltage calculation formula is as follows:

[0083] ;

[0084] in, The battery level is And the temperature is Start-up voltage at that time It is the peak starting current. The battery level is And the temperature is Open circuit voltage at that time The battery level is And the temperature is The equivalent starting internal resistance at that time.

[0085] It should be noted that, in this embodiment, Ohm's law is used to calculate the starting voltage. In other embodiments, it can also be calculated based on the equivalent conversion of a first-order battery or a second-order battery. Specifically, in this embodiment, the starting peak current is first extracted. Then, the corresponding starting voltage is calculated based on the starting voltage calculation formula, which is as follows: , The battery level is And the temperature is Start-up voltage at that time It is the peak starting current. The battery level is And the temperature is Open circuit voltage at that time The battery level is And the temperature is The equivalent starting internal resistance at that time.

[0086] Furthermore, in one embodiment of the invention, the acquisition of battery data is processed to obtain target data. The battery data includes battery voltage, battery current, and battery temperature. The target data includes battery SOC and temperature parameters, specifically including:

[0087] Battery data is acquired from a smart battery sensor, wherein the battery data includes battery voltage, battery current, and current temperature;

[0088] The battery SOC and temperature parameters are obtained by filtering and calculation based on the battery data.

[0089] It should be noted that, in this embodiment, reading battery data is the basis for all calculations. Battery data is obtained from the smart battery sensor, including battery voltage, battery current, and current temperature. Based on the battery data, filtering can be performed, for example, by moving average filtering, to calculate the battery SOC and temperature parameters, which can then be used for lookup in the internal resistance meter and the switching voltage meter.

[0090] The scope of protection of the battery SOF estimation method based on smart battery sensors described in this application is not limited to the execution order of the steps listed in this embodiment. Any solution implemented by adding, subtracting, or replacing steps in the prior art based on the principles of this application is included within the scope of protection of this application.

[0091] This application also provides a battery SOF estimation system based on a smart battery sensor. The battery SOF estimation system based on a smart battery sensor can implement the battery SOF estimation method based on a smart battery sensor described in this application. However, the implementation device of the battery SOF estimation method based on a smart battery sensor described in this application includes, but is not limited to, the structure of the battery SOF estimation system based on a smart battery sensor listed in this embodiment. All structural modifications and substitutions of the prior art made according to the principles of this application are included within the protection scope of this application.

[0092] Please see Figure 6 In one embodiment, this embodiment provides a battery SOF estimation system 60 based on a smart battery sensor, the system comprising:

[0093] The acquisition module 61 is used to acquire battery data and process it to obtain target data. The battery data includes battery voltage, battery current and battery temperature. The target data includes battery SOC and temperature parameters.

[0094] The lookup module 62 is used to look up the open circuit voltage and equivalent starting internal resistance based on the battery SOC and the temperature parameters. The table includes an internal resistance table and an open circuit voltage table, wherein the internal resistance table is related to the starting operating condition type.

[0095] Calculation module 63 is used to extract the peak current at startup and calculate the startup voltage by combining the open-circuit voltage and the equivalent internal resistance at startup.

[0096] Output module 64 is used to compare the start-up voltage with a preset voltage threshold and output the battery SOF based on the comparison result.

[0097] It should be noted that, in this embodiment, since the specific implementation method corresponds to the aforementioned method embodiment, the same details will not be repeated here, and those skilled in the art should also understand this. Figure 6 The division of the modules in the embodiments is only a logical functional division. In actual implementation, they can be fully or partially integrated into one or more physical entities. These modules can be fully implemented in software through processing element calls, fully implemented in hardware, or some modules can be implemented in software through processing element calls and some modules can be implemented in hardware.

[0098] In the embodiments provided by this invention, it should be understood that the disclosed apparatus or method can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of the apparatus or module or unit may be electrical, mechanical, or other forms.

[0099] The modules / units described as separate components may or may not be physically separate. The components shown as modules / units may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules / units can be selected to achieve the objectives of the embodiments of the present invention, depending on actual needs. For example, the functional modules / units in the various embodiments of the present invention may be integrated into one processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into one module / unit.

[0100] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0101] This invention also provides an electronic device, such as... Figure 7 As shown, the electronic device includes a processor and a memory.

[0102] like Figure 7 As shown, the electronic device includes: at least one processor 701, a memory 702, at least one network interface 703, and a user interface 705. The various components in the device are coupled together via a bus system 704. It is understood that the bus system 704 is used to implement communication between these components. In addition to a data bus, the bus system 704 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 7 The general will label all buses as bus systems.

[0103] The user interface 705 may include a monitor, keyboard, mouse, trackball, clicker, button, touchpad, or touch screen.

[0104] It is understood that memory 702 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM) or programmable read-only memory (PROM), used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM) and synchronous static random access memory (SSRAM). The memories described in the embodiments of this invention are intended to include, but are not limited to, these and any other suitable categories of memory.

[0105] In this embodiment of the invention, the memory 702 is used to store various types of data to support the operation of the electronic terminal 700. Examples of this data include: any executable program for operation on the electronic terminal 700, such as operating system 7021 and application program 7022; operating system 7021 includes various system programs, such as framework layer, core library layer, driver layer, etc., for implementing various basic services and handling hardware-based tasks. Application program 7022 may include various applications, such as media player, browser, etc., for implementing various application services. The implementation of the XX method provided in this embodiment of the invention may be included in application program 7022.

[0106] The methods disclosed in the above embodiments of the present invention can be applied to or implemented by processor 701. Processor 701 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 701 or by instructions in software form. The processor 701 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 701 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. General-purpose processor 701 may be a microprocessor or any conventional processor, etc. The steps of the accessory optimization method provided in the embodiments of the present invention can be directly reflected as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium, which is located in memory. The processor reads the information in the memory and combines it with its hardware to complete the steps of the aforementioned method.

[0107] In an exemplary embodiment, the electronic terminal 700 may be used by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), or complex programmable logic devices (CPLDs) to execute the aforementioned method.

[0108] According to the method provided in the embodiments of this application, this application also provides a computer program product, which includes: computer program code, which, when run on a computer, causes the computer to perform the method described in any of the above embodiments.

[0109] According to the method provided in the embodiments of this application, this application also provides a computer-readable storage medium storing program code, which, when run on a computer, causes the computer to perform the method described in any of the above embodiments.

[0110] The terms “component,” “module,” “system,” etc., used in this specification are used to refer to computer-related entities, hardware, firmware, combinations of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, and / or a computer. As illustrated, applications running on computing devices and computing devices can both be components. One or more components may reside in a process and / or an execution thread, and components may be located on a single computer and / or distributed among two or more computers. Furthermore, these components can be executed from various computer-readable media on which various data structures are stored. Components can communicate, for example, via local and / or remote processes based on signals having one or more data packets (e.g., data from two components interacting with another component between a local system, a distributed system, and / or a network, such as the Internet interacting with other systems via signals).

[0111] Those skilled in the art will recognize that the various illustrative logical blocks and steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0112] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0113] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0114] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0115] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0116] In the above embodiments, the functions of each functional unit can be implemented entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. A computer program product includes one or more computer instructions (programs). When the computer program instructions (programs) are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., high-density digital video discs, DVDs), or semiconductor media (e.g., solid-state disks, SSDs, etc.).

[0117] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0118] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0119] In summary, this application provides a battery SOF estimation method, system, and storage medium based on an intelligent current sensor. This method can improve the accuracy of the intelligent battery sensor (IBS) in effectively monitoring the battery's start-up function status. Compared with traditional start-up function testing methods that calculate the start-up voltage by measuring resistance and using battery models, the method of this invention can more accurately simulate the vehicle's start-up conditions and battery environment. From a mechanistic perspective, it can also more accurately calculate the battery's start-up voltage, thereby improving vehicle safety and user experience, reducing the probability of failures caused by low battery levels, and effectively reducing vehicle maintenance costs and stability.

[0120] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A method for battery SOF estimation based on smart battery sensor, characterized in that, The method comprises: acquiring battery data for processing to obtain target data, wherein the target data comprises battery SOC and temperature parameters; based on the battery SOC and the temperature parameters, performing table lookup to obtain open circuit voltage and equivalent starting internal resistance, the table comprising an internal resistance table and an open circuit voltage table, wherein the internal resistance table is related to starting working condition type; extracting starting peak current, combining the open circuit voltage and the equivalent starting internal resistance to calculate starting voltage; comparing the starting voltage with a preset voltage threshold, and outputting battery SOF based on the comparison result.

2. The smart battery sensor based battery SOF estimation method according to claim 1, wherein, The method further comprises generating an internal resistance table, specifically comprising: generating the internal resistance table based on bench testing, wherein the internal resistance test is based on the starting working condition type, and the starting working condition type comprises first starting and re-starting; when performing first starting internal resistance test, after the battery is fully charged, the oven is set to target temperature, and the first pulse discharge and data acquisition are performed to calculate the equivalent starting internal resistance of first starting, wherein the open circuit or small background current is used to simulate the vehicle parked and stationary state; when performing re-starting internal resistance test, after the battery is fully charged, the oven is set to target temperature, and the second pulse discharge and data acquisition are performed to calculate the equivalent starting internal resistance of re-starting, wherein the large background current is used to simulate the vehicle off but powered state; combining the starting working condition type to obtain the equivalent starting internal resistance corresponding to different battery SOC at the target temperature to obtain the internal resistance table, wherein the internal resistance table comprises first starting equivalent starting internal resistance table and re-starting equivalent starting internal resistance table. 3.The smart battery sensor based battery SOF estimation method of claim 1, wherein, The method further comprises generating an open circuit voltage table, specifically comprising: generating the open circuit voltage table based on bench testing, wherein, after the battery is fully charged, the oven is set to target temperature and left stationary, and gradient discharge is repeatedly performed and the battery voltage is recorded until the battery voltage is discharged to a preset cut-off voltage; obtaining the open circuit voltage value corresponding to different battery SOC at the target temperature to obtain the open circuit voltage table. 4.The smart battery sensor based battery SOF estimation method of claim 1, wherein, The method further comprises generating an open circuit voltage table, specifically comprising: reading historical current data from the intelligent battery sensor, and determining the starting working condition type based on the historical current data, wherein the starting working condition type comprises first starting and re-starting; determining the internal resistance table based on the starting working condition type, wherein the internal resistance table comprises first starting equivalent starting internal resistance table and re-starting equivalent starting internal resistance table; using battery SOC and temperature parameters as index, performing internal resistance table lookup to obtain equivalent starting internal resistance, and performing open circuit voltage table lookup to obtain open circuit voltage.

5. The smart battery sensor based battery SOF estimation method according to claim 1, wherein, The method further comprises generating an open circuit voltage table, specifically comprising: extracting the start peak current ; calculating the starting voltage based on a preset starting voltage calculation formula, wherein the starting voltage calculation formula is as follows: ； wherein, is the starting voltage at a temperature of and a charge of , is the starting peak current, is the open circuit voltage at a temperature of and a charge of , is the equivalent starting internal resistance at a temperature of and a charge of .

6. The smart battery sensor based battery SOF estimation method of claim 1, wherein, The method further comprises generating an open circuit voltage table, specifically comprising: acquiring battery data from the intelligent battery sensor, wherein the battery data comprises battery voltage, battery current and battery temperature; filtering and calculating the battery SOC and the temperature parameter based on the battery data.

7. The smart battery sensor based battery SOF estimation method according to claim 1, wherein, When the starting voltage is greater than or equal to the voltage threshold, the output battery SOF is capable of starting, otherwise the output battery SOF is not capable of starting.

8. A smart battery sensor based battery state of function (SOF) estimation system, comprising: comprise: an acquiring module, configured to acquire battery data for processing to obtain target data, wherein the battery data comprises battery voltage, battery current and battery temperature, and the target data comprises battery SOC and temperature parameter; a table searching module, configured to search a table based on the battery SOC and the temperature parameter to obtain open circuit voltage and equivalent starting internal resistance, wherein the table comprises an internal resistance table and an open circuit voltage table, and the internal resistance table is related to starting working condition type; a calculating module, configured to extract starting peak current, and calculate starting voltage in combination with the open circuit voltage and the equivalent starting internal resistance; an outputting module, configured to compare the starting voltage with a preset voltage threshold, and output battery SOF based on comparison result.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the battery SOF estimation method based on the intelligent battery sensor according to any one of claims 1 to 7.

10. An electronic device, comprising: The electronic device comprises a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the battery SOF estimation method based on the intelligent battery sensor according to any one of claims 1 to 7.

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