Battery control method and device, battery management system, vehicle and storage medium

Abstract

The invention provides a battery control method and device, a battery management system, a vehicle and a storage medium. The method comprises the steps that a current sensor error model is obtained; wherein the current sensor error model represents change rules of system errors and random errors under different temperature and current conditions; determining an error compensation value by using the current sensor error model, and compensating the current current measurement value of the battery by using the error compensation value; determining a current state of charge (SOC) of the battery and an accumulative error range of the current SOC based on the compensated current value; and executing management operation on the battery according to the current SOC and the accumulated error range of the current SOC. The SOC calculation deviation can be remarkably reduced, and the safety of electric equipment is improved.

Description

Technical Field

[0001] This invention relates to the field of lithium battery management technology, and more specifically, to a battery control method, device, battery management system, vehicle, and storage medium. Background Technology

[0002] Lithium iron phosphate (LiFePO4) Due to its advantages in cost-effectiveness, safety performance, and cycle life, the market share of this type of battery in the electric vehicle sector continues to grow. However, the relationship between the open-circuit voltage (OCV) and the state of charge (SOC) of this type of battery exhibits a significant voltage plateau phenomenon in the middle range, characterized by a low slope of OCV changing with SOC. This poses a significant challenge to the accurate estimation of SOC based on voltage feedback.

[0003] Currently, the industry's commonly used solutions fall into two main categories: one is calibration through full charging; the other is voltage calibration correction when the battery voltage leaves the plateau region (such as the low SOC range). If the battery operates in the voltage plateau region for a long time, the SOC estimate based on the ampere-hour integration method will gradually deviate from the true value due to the continuous accumulation of current sensor sampling noise and cumulative integration error. When the SOC estimate is too high, it may lead to an overestimation of the vehicle's actual usable energy, resulting in unexpected power outages when the battery is low; conversely, if the SOC estimate is too low, the current demand calculated based on that SOC during charging will be abnormally high, potentially causing battery overcharging and increasing safety risks such as thermal runaway. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a battery control method, device, battery management system, vehicle, and storage medium that can significantly reduce SOC calculation deviation and improve the safety of electrical equipment. To achieve the above objective, the technical solution adopted by this invention is as follows: In a first aspect, the present invention provides a battery control method, the method comprising: obtaining a current sensor error model; wherein the current sensor error model characterizes the variation law of systematic error and random error under different temperature and current conditions; determining an error compensation value using the current sensor error model, and compensating the current current measurement value of the battery with the error compensation value; determining the current state of charge (SOC) of the battery and the cumulative error range of the current SOC based on the compensated current value; and performing management operations on the battery according to the current SOC and the cumulative error range of the current SOC.

[0005] In a second aspect, the present application provides a battery control device, comprising: an obtaining module configured to obtain a current sensor error model, wherein the current sensor error model characterizes variation of systematic error and random error under different temperature and current conditions; a determining module configured to determine an error compensation value using the current sensor error model, and compensate a current measurement value of a battery using the error compensation value; the determining module is further configured to determine a current state of charge (SOC) of the battery and a cumulative error range of the current SOC based on the compensated current value; and a management module configured to perform a management operation on the battery according to the current SOC and the cumulative error range of the current SOC.

[0006] In a third aspect, the present application provides a battery management system, comprising: a microcontroller, a current sensor, a temperature sensor, a non-volatile memory, and a communication interface; the non-volatile memory is configured to store a current sensor error model; the microcontroller is configured to execute a computer program to implement the method according to any one of the preceding embodiments.

[0007] In a fourth aspect, the present application provides a vehicle comprising the battery management system according to the preceding embodiments.

[0008] In a fifth aspect, the present application provides a storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the battery control method according to any one of the preceding embodiments.

[0009] The battery control method, device, battery management system, vehicle and storage medium provided by the embodiments of the present application can accurately depict the variation of systematic error and random error under different temperature and current conditions by establishing a current sensor error model, and provide a theoretical basis for subsequent compensation; then, the error compensation value is calculated in real time using the error model, and is applied to the correction of the current measurement value of the battery, so that the measured current is closer to the true value, and a data foundation is laid for accurate calculation of the SOC; on this basis, the current state of charge (SOC) and the cumulative error range thereof are updated by integrating the compensated high-precision current value, which not only improves the accuracy of the initial value of the SOC, but also quantitatively evaluates the credibility of the SOC by continuously tracking the error boundary; finally, the battery management operation is implemented according to the corrected current SOC and the corresponding cumulative error range, so that the control decision is more scientific and reliable, thereby achieving the technical effects of significantly reducing the SOC calculation deviation and improving the safety of the electrical equipment as a whole. In order to make the above objectives, characteristics and advantages of the present application more apparent and easy to understand, the following preferred embodiments are described in detail below, and the accompanying drawings are referred to. BRIEF DESCRIPTION OF DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some of the embodiments of the present application, and therefore should not be regarded as a limitation to the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0011] Figure 1 A schematic flow chart of the battery control method provided by the embodiments of the present application is shown; Figure 2 A structural block diagram of the battery management system provided by the embodiments of the present application is shown; Figure 3 A structural schematic diagram of the vehicle provided by the embodiments of the present application is shown; Figure 4 A functional module diagram of the battery control device provided by the embodiments of the present application is shown. DETAILED DESCRIPTION

[0012] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations.

[0013] Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. All other embodiments obtained by those skilled in the art on the basis of the embodiments of the present application without creative labor are within the scope of protection of the present application.

[0014] It should be noted that the relational terms such as "first" and "second" and the like are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus including a series of elements includes not only those elements, but also other elements not explicitly listed or inherent to such a process, method, article or apparatus. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or apparatus including the element.

[0015] In view of the influence of the measurement error of the current sensor in the existing battery management system on the calculation accuracy of the state of charge (SOC) and the vehicle safety and reliability problems caused thereby, the battery control method provided by the embodiment of the present application can solve the above problems.

[0016] Please refer to Figure 1 , Figure 1 The schematic flowchart of the battery control method provided by the embodiment of the present application is shown, which can include steps S101 to S104, which are described as follows: S101: Obtain a current sensor error model; wherein the current sensor error model represents the variation law of the systematic error and the random error under different temperature and current conditions; In the embodiment of the present application, the current sensor error model is a mathematical expression (or functional relationship) for predicting or describing the deviation (i.e. error) between the output value and the true value of the current sensor under a specific working condition (i.e. temperature and current combination).

[0017] S102: Determine an error compensation value using the current sensor error model, and compensate the current measurement value of the battery by the error compensation value; S103: Determine the current state of charge SOC of the battery and the cumulative error range of the current SOC based on the compensated current value; S104: Perform a management operation on the battery according to the current SOC and the cumulative error range of the current SOC.

[0018] The difference from the prior art is that the embodiment of the present application can accurately depict the variation law of the systematic error and the random error under different temperature and current conditions by establishing a current sensor error model, providing a theoretical basis for subsequent compensation; then, the error compensation value is calculated in real time using the error model, and is applied to the correction of the current measurement value of the battery, so that the measured current is closer to the true value, laying a data foundation for the accurate calculation of the SOC; on this basis, the current state of charge SOC and its cumulative error range are updated based on the compensated high-precision current value, which not only improves the accuracy of the initial value of the SOC, but also realizes the quantitative evaluation of the credibility of the SOC by continuously tracking the error boundary; finally, the battery management operation is implemented according to the corrected current SOC and its corresponding cumulative error range, so that the control decision is more scientific and reliable, thereby achieving the technical effects of significantly reducing the calculation deviation of the SOC and improving the safety of the electrical equipment as a whole. Next, the battery control process shown by the embodiment of the present application will be described in detail. Figure 1

[0019] ​In step S101, the current sensor is affected by factors such as temperature, current size, etc. in actual work, and there are systematic errors and random errors. The systematic error refers to the error component that remains constant or shows regular deviation when repeatedly measuring under the same working condition, while the random error reflects the uncertainty component that fluctuates around the mean value in multiple measurements under the same conditions, and the two together constitute the main source of output deviation of the current sensor.

[0020] In an embodiment of the present application, the current sensor error model can be constructed by experimental calibration method, see steps a1 to a4, as follows: Step a1: collect the current output value of the current sensor under each calibration condition point; wherein the calibration condition point is the combination of each set temperature value and current value; In the embodiment of the present application, during the battery pack offline detection stage, the battery pack is placed in a high-low temperature test box, and a high-precision standard current source (precision 0.05%) is connected. A plurality of temperature points (such as -30°C, -10°C, 10°C, 25°C, 45°C, 60°C) are set in the high-low temperature test box, and a series of standard currents (such as [-500A, 500A] range every 50A) are applied. Each set temperature point and current value form a calibration condition point, denoted as (T, I). Under each calibration condition point (T, I), the current output value of the current sensor is recorded .

[0021] Step a2: compare each current output value with the preset standard current value to obtain an error data set, and fit the error data set to generate a system error model; wherein the system error model represents the variation of the system error under different temperature and current conditions; In the embodiment of the present application, a standard current value can be preset, and then the error between the current output value under each (T, I) and the standard current value is calculated, denoted as , thereby obtaining an error data set.

[0022] Further, the error data set can be fitted by a polynomial, such as a binary cubic polynomial fitting of the data using the least squares method, thereby establishing a system error model, denoted as:

[0023] Wherein a~f are model coefficients of the system error model, which can be stored in the non-volatile memory for real-time error prediction.

[0024] Step a3: the preset multiple standard deviation corresponding to the error of each calibration condition point is taken as the random error; In the embodiment of the present application, for each calibration operating point (T, I), the preset multiple standard deviation of the error obtained under the condition can be used as the random error under the condition , wherein the multiple of the standard deviation can be flexibly set, such as three times the standard deviation .

[0025] Step a4: constructing a current sensor error model from the systematic error model and the random error under each calibration operating point.

[0026] Finally, the current sensor error model obtained by the embodiment of the present application is shaped as In the embodiment of the present application, the model coefficients a-f and the random error values under each calibration operating point (T, I) can be written into a non-volatile memory for subsequent error prediction.

[0027] In an optional implementation, in addition to using the above experimental calibration method to construct the current sensor error model, a neural network, support vector regression (SVR), etc. can also be used to train a non-linear mapping model with temperature and current as input and error as output, thereby obtaining the current sensor error model, which is not limited by the embodiment of the present application.

[0028] Based on the current sensor error model constructed in the above embodiment, in step S102, the embodiment of the present application determines the error compensation value using the current sensor error model, and compensates the current measurement value of the battery by the error compensation value.

[0029] In step S102, the embodiment of the present application can collect the current measurement value I_meas and the temperature T of the battery in real time according to the set data collection frequency (such as every 100 ms), and then determine the error compensation value Error(I_meas, T) using the current sensor error model. Specifically: The embodiment of the present application can read the voltage value of the current sensor by ADC and convert it into a current value, and the conversion process is shown in the formula: (unit: A), and synchronously read the temperature T of the battery. Then, the collected I_meas and temperature T are substituted into the pre-stored current sensor error model to calculate the current systematic error ΔI_systematic and query the random error , and the error compensation value . The current measurement value of the battery is compensated by the error compensation value to obtain the compensated current value, which is used for subsequent accurate estimation of SOC and its deviation range, see step S103.

[0030] ​In step S103, the current state of charge SOC of the battery and the accumulated error range of the current SOC are determined based on the compensated current value. The accumulated error range of the current SOC, which can also be referred to as an uncertain deviation range, refers to the possible range of SOC calculation deviation caused by current measurement error, model error and other uncertain factors within a certain time range. By estimating the SOC deviation range, the reliability and uncertainty of the SOC can be more accurately evaluated, thereby providing more reliable data support for the battery management system.

[0031] In the embodiments of the present application, in order to obtain an accurate SOC value, the traditional ampere-hour integral formula is improved. Specifically, the traditional ampere-hour integral formula is:

[0032] wherein, is the initial state of the battery (t=0); Qnom is the rated capacity of the battery; is an efficiency factor; is the charging and discharging current of the battery at time .

[0033] The traditional ampere-hour integral formula is improved in the embodiments of the present application, and a current sensor error compensation value is introduced, and the improved ampere-hour integral formula is:

[0034] wherein, is obtained by querying a pre-stored error model. The above-described ampere-hour integral formula with compensation provided by the embodiments of the present application independently removes the sensor accumulated error from the integral, which can significantly improve the accuracy of SOC calculation.

[0035] In step S103, the embodiments of the present application can calculate the current SOC based on the compensated current value by using the above-described improved ampere-hour integral formula, i.e., the compensated current value is taken as I_meas and substituted into the above-described improved ampere-hour integral formula to obtain the current SOC.

[0036] Further, the embodiments of the present application can determine the accumulated error range of the current SOC value based on the error compensation value and the ampere-hour integral time length. Specifically, the product of the error compensation value and the integral time length is taken as the accumulated error range In actual calculation, since the unit of battery rated capacity is ampere-hour (Ah), and the data acquisition period is usually in milliseconds (ms), the amount of time needs to be converted from milliseconds to hours (h), that is, multiplied by the conversion coefficient 1 / 3600, to ensure the consistency of the units of physical quantities and avoid introducing additional errors due to unit mismatch. Through the above method, the system can dynamically and real-timely estimate the cumulative error range of SOC, which not only reflects the cumulative characteristics of sensor error evolution over time, but also provides a quantitative basis for SOC uncertainty modeling.

[0037] For example, the current measurement value at time t is The ampere-hour integral calculation process after compensation is as follows:

[0038] Wherein, Qnom is the nominal capacity of the battery (such as 75 Ah), and 0.01 is the unit coefficient for converting the data acquisition period 100 ms into hours in the embodiment of the present application.

[0039] After determining the current SOC and its cumulative error range ±ΔSOC through the above implementation, in step S104, the embodiment of the present application can perform management operations on the battery based on this information.

[0040] In an embodiment of the present application, during the battery charging phase, the current maximum allowable charging current can be obtained by querying the pre-stored charging allowable current query table according to the current SOC and the cumulative error range, and the current maximum allowable charging current can be adjusted.

[0041] In the embodiment of the present application, the charging allowable current query table (i.e., the charging MAP table) is a pre-set two-dimensional table, with the horizontal axis as SOC and the vertical axis as the maximum allowable charging current. The lower the SOC, the larger the allowable charging current; the higher the SOC, the charging current gradually decreases. In the embodiment of the present application, the maximum allowable charging current is dynamically limited and adjusted in combination with the real-time calculated SOC cumulative error range, which can avoid the risk of overcurrent caused by underestimation of SOC.

[0042] Specifically, when the real-time calculated SOC cumulative error range is large, the system will automatically reduce the maximum allowable charging current to ensure that the actual charging current does not exceed the safety threshold of the battery even if the SOC is underestimated. This can effectively prevent overcharging caused by inaccurate SOC estimation, protect the battery from damage, and prolong its service life. At the same time, this dynamic adjustment mechanism can also fully utilize the charging capacity of the battery when the SOC estimation is relatively accurate, improving the charging efficiency and user experience.

[0043] For example, if a charging gun connection signal (CC signal) is detected, the current maximum allowed charging current is 120A according to the current SOC of 60% querying the charging MAP table. Assuming the cumulative error range of SOC is ±1.5%, then query. According to the SOC value of 61.5% in the charging MAP table, the more conservative current maximum allowed charging current is 110A. Then, this more conservative maximum allowed charging current value is sent to the on-board charger (OBC) through the CAN bus. In this way, the system can dynamically adjust the maximum allowed charging current to ensure that even if the SOC is underestimated, the actual charging current will not exceed the safety threshold of the battery, effectively avoiding the risk of overcurrent and protecting the battery from damage, prolonging its service life.

[0044] In an embodiment of the present application, considering that the battery state of health (SOH) estimated based on the ampere-hour integration method will deviate due to the reference error of SOC, which is usually manifested as an overestimation of SOH, which will affect the accuracy of battery life prediction and energy management strategy. Therefore, in the process of determining the state of health SOH of the battery, the cumulative error range can be introduced as a calculation factor to ensure that the final estimation error of SOH is within a preset range (such as ±2%). In this way, not only the accuracy of battery life prediction can be improved, but also the energy management strategy can be optimized to ensure the reliability and efficiency of the system.

[0045] In an embodiment of the present application, the current SOC and the cumulative error range can also be sent to the display device for display, and in addition, the SOH calculated this time and its final estimation error can also be sent to the display device for display, which can provide real-time and intuitive data feedback for the driver or maintenance personnel, effectively avoiding the risk of vehicle breakdown caused by false high power display.

[0046] The above-mentioned battery control method provided by the embodiments of the present application has the following advantages: by establishing a current sensor error model and compensating for the cumulative error of the ampere-hour integration process in real time, the SOC calculation deviation is significantly reduced, high-precision state of charge estimation is achieved, and the accuracy of power display is improved; on this basis, by introducing the SOC uncertainty range The electric quantity credibility is reflected in the form of intervals in the instrument display, and the deviation is combined in the charging control to dynamically adjust the charging current limit value, which effectively avoids the risk of vehicle low power stranded due to high SOC and the safety hazards of over-current and over-charging caused by low SOC estimation. Meanwhile, the SOC deviation information is integrated into the state of health (SOH) estimation process as a weight factor or correction term, which enhances the robustness of the algorithm and improves the accuracy of aging trend prediction and life management. In addition, the error calibration method used does not depend on specific hardware and can be adapted to various types of current sensors, has good universality and portability, and is easy to popularize and apply on different vehicle models and battery management system (BMS) platforms, and has strong engineering practical value and industrialization prospect.

[0047] Based on the inventive concept of Figure 1 , the embodiment of the present application also provides a battery management system, please see Figure 2 , Figure 2 The structure block diagram of the battery management system 20 provided by the embodiment of the present application is shown, and the system includes a microcontroller MCU 201, a current sensor 202 and a temperature sensor 203. The microcontroller MCU 201 further includes a voltage sampling circuit 2011, a non-volatile memory 2012 and a CAN communication module 2013.

[0048] The microcontroller MCU 201 serves as the system control core, is responsible for executing the battery control method, coordinating the work of each module and realizing data processing and communication. The voltage sampling circuit 2011 integrated in the microcontroller MCU 201 is used for high-precision collection of battery monomer or total voltage, and converts analog signals into digital quantities for SOC and SOH calculation; the non-volatile memory 2012 is used for storing the current sensor error model parameters generated during offline calibration, the charging current MAP table, the battery historical data and the fault record, to ensure that the key information is not lost after power failure; the CAN communication module 2013 supports high-speed and reliable data interaction between the vehicle controller (VCU), the on-board charger (OBC), the instrument panel and other ECUs.

[0049] The current sensor 202 is used for real-time detection of battery charging and discharging current, and outputs analog or digital signals proportional to the actual current. The working accuracy of the sensor directly affects the accuracy of ampere-hour integration method, therefore, the present application dynamically corrects the systematic deviation of the sensor under different temperature and current conditions through the subsequent error compensation mechanism.

[0050] The temperature sensor 203 is used for monitoring the temperature distribution of the environment where the current sensor is located and the inside of the battery pack, providing a key temperature input variable for the error model and improving the accuracy of error prediction.

[0051] For example, in the battery management system of a certain pure electric passenger vehicle, the current sensor 202 can use an open-loop Hall current sensor with a rated measurement range of ±500 A and an output of an analog voltage signal (0.5 V~4.5 V). The temperature sensor 203 can use an NTC thermistor arranged near the current sensor and in the battery pack, with a total of 4 measuring points, and the average value is taken as the compensation temperature T. The non-volatile memory 2012 can use the 4MB DFlash integrated in the microcontroller MCU 201 for storing error model coefficients and charging MAP tables; the CAN communication module 2013 can communicate with the vehicle gateway, instrument panel and on-board charger (OBC) through the CAN-FD controller (connected with the physical transceiver TJA1145) built in the microcontroller MCU 201.

[0052] In combination Figure 2 , the microcontroller MCU 201 executes the above-mentioned battery control method as follows: In the initial stage, the microcontroller MCU 201 loads the pre-stored current sensor error model, initial state of charge (SOC0), battery nominal capacity (Qnom) and other key parameters.

[0053] During system operation, the microcontroller MCU 201 periodically collects the raw current value output by the current sensor 202, the ambient temperature measured by the temperature sensor 203 and the battery voltage obtained by the voltage sampling circuit 2011; based on the current sensor error model pre-stored in the non-volatile memory 2012, the MCU 201 calculates the error compensation amount Error(Imeas,T) at the current time, and introduces it into the improved ampere-hour integral formula to obtain more accurate SOC estimation results; at the same time, the SOC deviation range ±ΔSOC is estimated in real time according to the cumulative error analysis; In the charging scenario, the current SOC and its cumulative error range are combined to query the charging MAP, the maximum allowed charging current is dynamically adjusted, and is sent to the external charging device through the CAN communication module 2013, to realize safe closed-loop control; In the battery health state SOH estimation process, the SOC compensation result and deviation information are also used to optimize the SOH estimation algorithm, and improve the robustness of battery aging judgment; Finally, the compensated SOC and its confidence interval The output is uploaded to the instrument display through the CAN communication module, improves the accuracy and driving safety of user perception, and completes data interaction with the vehicle controller (VCU) and other key nodes through the CAN communication network, improves the coordination and safety of the whole vehicle energy management.

[0054] The embodiment of the application also provides a vehicle, please see Figure 3 , Figure 3A structural schematic diagram of a vehicle provided by an embodiment of the present application is shown, and the vehicle comprises Figure 2 The battery management system 20 and the battery shown. Optionally, the vehicle in the embodiment of the present application can be, but is not limited to, various new energy vehicle models such as a pure electric vehicle (BEV), a plug-in hybrid electric vehicle (PHEV), a range-extended electric vehicle (EREV), a hybrid electric vehicle (HEV), and a fuel cell electric vehicle (FCEV). The battery management system can be integrated in a power battery pack of the vehicle, and cooperatively controlled with a vehicle controller (VCU), a motor controller (MCU), an on-board charger (OBC), a thermal management system, and an instrument display system through a CAN / CAN-FD communication network. By compensating for current sensor errors in real time, accurately estimating the SOC and its cumulative error range, and introducing an uncertainty interval in charging management and power display, the present application effectively improves the energy utilization efficiency, driving safety, and user experience of the vehicle under complex working conditions, and is particularly suitable for medium and high-end electric vehicle models and intelligent networked automobile platforms with high requirements for battery safety and accuracy.

[0055] It can be understood that Figure 3 The structure shown is only schematic, and the vehicle 30 can further include more or fewer components than those shown, or have a different configuration of components than those shown, all without departing from the scope of the present application. The embodiments of the present application will not be described here again. Figure 3 It can be understood that Figure 3 The structure shown is only schematic, and the vehicle 30 can further include more or fewer components than those shown, or have a different configuration of components than those shown, all without departing from the scope of the present application. The embodiments of the present application will not be described here again.

[0056] In order to perform the corresponding steps in the above embodiments and various possible manners, an implementation of a battery control device 40 is given below, as shown in Figure 4 , Figure 4 A functional module diagram of a battery control device provided by an embodiment of the present application is shown. The battery control device 40 comprises an acquisition module 401, a determination module 402, and a control module 403.

[0057] The acquisition module 401 is configured to obtain a current sensor error model, wherein the current sensor error model represents the variation law of systematic errors and random errors under different temperature and current conditions; The determination module 402 is configured to determine an error compensation value using the current sensor error model, and compensate for the current current measurement value of the battery by the error compensation value; The determination module 402 is further configured to determine the current state of charge (SOC) of the battery and the cumulative error range of the current SOC based on the compensated current value; The control module 403 is configured to perform a management operation on the battery according to the current SOC and the cumulative error range of the current SOC.

[0058] It can be understood that the acquisition module 401, the determination module 402, and the control module 403 can be executed in coordination Figure 1Each step in the process is used to achieve the corresponding technical effect.

[0059] It should be noted that the battery control device 40 provided in this embodiment of the invention can be specific hardware on the device or installed on the device (e.g., Figure 3 The software or firmware on the vehicle shown. The device provided in this embodiment of the invention has the same implementation principle and technical effects as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the aforementioned method embodiment. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices and units described above can all be referred to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0060] Optionally, the above modules can be stored in the form of software or firmware. Figure 2 The non-volatile memory 2012 shown is either stored in or embedded in the operating system (OS) of the MCU 201. Simultaneously, the data and program code required to execute the aforementioned modules can be stored in the memory.

[0061] Based on the above embodiments, the present invention also provides a storage medium storing a computer program. When the computer program is executed by a computer, it causes the computer to execute the battery control method provided in the above embodiments. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

[0062] The present invention can also provide a computer program product for executing a battery control method, including a computer storage medium storing program code. The instructions included in the program code can be used to execute the methods in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0063] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interface; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0064] In addition, the units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment of the present application.

[0065] Furthermore, the functional modules in the various embodiments of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0066] It should be noted that if the function is realized in the form of a software function module and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the part of the present application that essentially contributes to the prior art or the part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, an electronic device, or a network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program code storage media.

[0067] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A battery control method characterized by, The method comprises: obtaining a current sensor error model; wherein the current sensor error model represents the variation law of system error and random error under different temperature and current conditions; determining an error compensation value using the current sensor error model, and compensating the current current measurement value of the battery by the error compensation value; determining the current state of charge SOC of the battery and the cumulative error range of the current SOC based on the compensated current value; performing a management operation on the battery according to the current SOC and the cumulative error range of the current SOC.

2. The battery control method according to claim 1, characterized by, After determining the current state of charge SOC of the battery and the cumulative error range of the current SOC based on the compensated current value, the method further comprises: In the process of determining the state of health SOH of the battery, the cumulative error range is introduced as a calculation factor, so that the final estimation error of the SOH is within a preset range.

3. The battery control method according to claim 1, characterized by, Performing a management operation on the battery according to the SOC and the cumulative error range, comprising: sending the current SOC and the cumulative error range to a display device for display; and / or, In the battery charging stage, querying a pre-stored charging allowable current query table according to the current SOC and the cumulative error range to obtain a current maximum allowable charging current, and adjusting the current maximum allowable charging current.

4. The battery control method according to claim 1, characterized by, Obtaining a current sensor error model comprises: collecting current output values of the current sensor at each calibration operating point; wherein the calibration operating point is a combination of each set temperature value and current value; comparing each current output value with a preset standard current value to obtain an error data set, and fitting the error data set to generate a system error model; wherein the system error model represents the variation law of system error under different temperature and current conditions; taking the preset multiple standard deviation corresponding to the error at each calibration operating point as a random error; constructing the current sensor error model from the system error model and the random error at each calibration operating point.

5. The battery control method according to claim 4, wherein The method further comprises: saving the model coefficients and random errors corresponding to the system error model at the calibration operating point.

6. The battery control method according to claim 1, wherein Determining the current state of charge SOC of the battery and the cumulative error range of the current SOC based on the compensated current value comprises: calculating the current SOC by ampere-hour integration based on the compensated current value; determining the cumulative error range according to the error compensation value and the ampere-hour integration length.

7. A battery control device characterized by comprising: Comprise: an acquisition module for obtaining a current sensor error model; wherein the current sensor error model represents the variation law of system error and random error under different temperature and current conditions; a determination module for determining an error compensation value using the current sensor error model, and compensating the current current measurement value of the battery by the error compensation value; the determination module is also used for determining the current state of charge SOC of the battery and the cumulative error range of the current SOC based on the compensated current value; A control module configured to perform a management operation on the battery according to the current SOC and a cumulative error range of the current SOC.

8. A battery management system, comprising: Comprising: a microcontroller, a current sensor, a temperature sensor, a non-volatile memory, and a communication interface; the non-volatile memory is configured to store a current sensor error model; the microcontroller is configured to execute a computer program to implement the method of any one of claims 1-6.

9. A vehicle characterized by comprising: The battery management system of claim 8.

10. A storage medium having stored thereon a computer program, characterized in that The computer program, when executed by a processor, implements the battery control method of any one of claims 1-6.

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