SOC calibration method combining whole-course rated ampere-hour calibration and tail-end electric quantity calibration

Abstract

The invention provides a whole-course rated ampere-hour calibration and tail-end electric quantity calibration combined SOC calibration method, and the method comprises the steps: obtaining an ampere-hour change value and an energy change value of a battery pack in each period from the start of charging and discharging of the battery pack; obtaining a residual ampere-hour value at the current moment based on the ampere-hour change value so as to obtain a current estimated value of the state of charge; judging whether the battery pack reaches a terminal calibration condition or not, and if yes, obtaining a terminal residual energy prediction value based on the trained prediction model, the energy change value and the terminal operation temperature at the current moment; obtaining a current calibration step length based on the terminal residual energy predicted value, the current charging and discharging power, the current estimated value of the state of charge and the preset value of the state of charge; and calibrating the current estimated value of the state of charge based on the current calibration step until the current estimated value of the state of charge reaches a preset value of the state of charge, thereby completing calibration.

Description

Technical Field

[0001] The present invention relates to the technical field of battery management, and in particular to a SOC calibration method combining full-range rated ampere-hour calibration with terminal power calibration. Background Art

[0002] State of Charge (SOC) is an indicator used to quantify the remaining capacity of a battery. The industry generally uses the ampere-hour integration method to estimate the battery SOC, but this method will continuously accumulate small errors when the battery is working, and the error will become larger and larger over time. In addition, this method is very dependent on the accurate setting of the initial SOC. Inaccurate initial SOC setting and accumulated errors will cause the estimated SOC value to deviate seriously from the actual value at the end of charging and discharging, especially at the end. Summary of the invention

[0003] The present invention aims to solve one of the technical problems in the related art at least to a certain extent.

[0004] To this end, the first object of the present invention is to propose an SOC calibration method that combines full-range rated ampere-hour calibration with terminal power calibration, so that the SOC value calculated when reaching the end of charging and discharging is more accurate.

[0005] The second object of the present invention is to provide a SOC calibration system that combines full-range rated ampere-hour calibration with terminal electrical quantity calibration.

[0006] A third objective of the present invention is to provide an electronic device.

[0007] A fourth object of the present invention is to provide a computer-readable storage medium.

[0008] To achieve the above-mentioned object, the first aspect of the present invention proposes a SOC calibration method combining full-range rated ampere-hour calibration with terminal power calibration, comprising:

[0009] Since the battery pack starts to charge and discharge, obtaining the ampere-hour change value and energy change value of the battery pack in each cycle;

[0010] Obtaining a remaining ampere-hour value at a current moment based on the ampere-hour change value to obtain a current estimated value of the state of charge;

[0011] Determine whether the battery pack reaches the terminal calibration condition, and if so, obtain the terminal remaining energy prediction value based on the trained prediction model, the energy change value, and the terminal operating temperature at the current moment;

[0012] Obtaining a current calibration step length based on the terminal remaining energy prediction value, the current charging and discharging power, the current estimated value of the state of charge, and the preset value of the state of charge;

[0013] The current estimated value of the state of charge is calibrated based on the current calibration step until the current estimated value of the state of charge reaches the preset value of the state of charge, thereby completing the calibration.

[0014] In the method of the first aspect of the present invention, the battery pack reaching the terminal calibration condition means that the voltage of the battery cells in the battery pack reaches the calibration voltage.

[0015] In the method of the first aspect of the present invention, a prediction model is trained using a training data set to obtain a trained prediction model, and the training data set is obtained based on multiple groups of battery data; wherein, for a charging or discharging process, a corresponding group of battery data is obtained based on the complete ampere-hour value and complete energy value of the charging or discharging process, the terminal ampere-hour value and terminal energy value of the charging or discharging process, and the terminal operating temperature and terminal operating power of the charging or discharging process.

[0016] In the method of the first aspect of the present invention, the prediction model adopts a linear fitting algorithm or a nonlinear fitting algorithm.

[0017] In the method of the first aspect of the present invention, the terminal remaining energy prediction value is obtained based on the trained prediction model, the energy change value, and the terminal operating temperature at the current moment, including: inputting the terminal operating temperature at the current moment into the trained prediction model to obtain the terminal energy prediction value; and calculating the terminal remaining energy prediction value based on the terminal energy prediction value and the energy change value between the calibration start time and the current time when the terminal calibration condition is met.

[0018] In the method of the first aspect of the present invention, the remaining ampere-hour value at the current moment is obtained based on the ampere-hour change value to obtain the current estimated value of the state of charge, including: calculating the remaining ampere-hour value of the battery pack at the current moment based on the ampere-hour change value from the start time of charging and discharging of the battery pack to the current moment and the initial ampere-hour value at the start time; and obtaining the current estimated value of the state of charge based on the ampere-hour remaining value and the complete available ampere-hour value of the battery pack.

[0019] In the method of the first aspect of the present invention, the current calibration step length is obtained based on the terminal remaining energy prediction value, the current charging and discharging power, the current estimated value of the state of charge, and the preset value of the state of charge, including: obtaining the expected end duration based on the terminal remaining energy prediction value and the current charging and discharging power; obtaining the state of charge difference based on the preset value of the state of charge and the current estimated value of the state of charge; and obtaining the current calibration step length based on the state of charge difference, the expected end duration, and a scaling factor.

[0020] To achieve the above object, the second aspect of the present invention proposes a SOC calibration system combining full-range rated ampere-hour calibration with terminal power calibration, comprising:

[0021] The energy storage converter is used to monitor the current and voltage of the battery pack from the beginning of charging and discharging of the battery pack to obtain the ampere-hour change value and energy change value of each cycle, and send them to the battery management system;

[0022] A battery management system, for obtaining the ampere-hour change value and energy change value of the battery pack in each cycle; obtaining the remaining ampere-hour value at the current moment based on the ampere-hour change value to obtain the current estimated value of the state of charge; judging whether the battery pack reaches the terminal calibration condition, and if so, obtaining the terminal remaining energy prediction value based on the trained prediction model, the energy change value, and the terminal operating temperature at the current moment; obtaining the current calibration step length based on the terminal remaining energy prediction value, the current charging and discharging power, the current estimated value of the state of charge, and the preset value of the state of charge; and calibrating the current estimated value of the state of charge based on the current calibration step length until the current estimated value of the state of charge reaches the preset value of the state of charge, thereby completing the calibration.

[0023] To achieve the above-mentioned purpose, the third aspect of the present invention proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method proposed in the first aspect of the present invention.

[0024] To achieve the above-mentioned purpose, the fourth aspect of the present invention proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the method proposed in the first aspect of the present invention.

[0025] The SOC calibration method, system, electronic device and storage medium provided by the present invention combine full-range rated ampere-hour calibration with terminal power calibration, obtain the ampere-hour change value and energy change value of the battery pack in each cycle since the battery pack starts to charge and discharge; obtain the remaining ampere-hour value at the current moment based on the ampere-hour change value to obtain the current estimated value of the state of charge; judge whether the battery pack reaches the terminal calibration condition, and if so, obtain the terminal remaining energy prediction value based on the trained prediction model, the energy change value, and the terminal operating temperature at the current moment; obtain the current calibration step length based on the terminal remaining energy prediction value, the current charging and discharging power, the current estimated value of the state of charge, and the preset value of the state of charge; calibrate the current estimated value of the state of charge based on the current calibration step length until the current estimated value of the state of charge reaches the preset value of the state of charge, thereby completing the calibration. In this case, the full-range rated ampere-hour calibration method is used to obtain the current estimated state of charge based on the ampere-hour change value, and then when the terminal calibration condition is reached, the current calibration step is obtained based on the output result of the trained prediction model, combined with the current charging and discharging power, the current estimated state of charge, and the preset state of charge value to calibrate the current SOC estimated by the full-range rated ampere-hour calibration method, so that the current SOC estimated at the end of charging or discharging reaches the preset state of charge value, which solves the problem of the estimated SOC value seriously deviating from the actual value at the end of charging and discharging, especially at the end, caused by the traditional ampere-hour integration method, and makes the SOC value calculated at the end of charging and discharging, especially at the end, more accurate.

[0026] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0028] Figure 1 A flow chart of a SOC calibration method combining full-range rated ampere-hour calibration with terminal power calibration provided by an embodiment of the present invention;

[0029] Figure 2 A schematic diagram of the interaction between the energy storage converter and the battery management system provided in an embodiment of the present invention;

[0030] Figure 3 A block diagram of a battery management system provided by an embodiment of the present invention;

[0031] Figure 4 A schematic diagram of a portion of the process of the SOC calibration method combining full-range rated ampere-hour calibration with terminal power calibration provided by an embodiment of the present invention;

[0032] Figure 5A block diagram of a SOC calibration system that combines full-range rated ampere-hour calibration with terminal electrical quantity calibration provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0033] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0034] The following describes the SOC calibration method and system combining full-range rated ampere-hour calibration with terminal power calibration according to an embodiment of the present invention with reference to the accompanying drawings.

[0035] The embodiment of the present invention provides an SOC calibration method that combines full-range rated ampere-hour calibration with terminal power calibration, so that the SOC value calculated when reaching the end of charging and discharging is more accurate.

[0036] Figure 1 A flow chart of a SOC calibration method combining full-range rated ampere-hour calibration with terminal power calibration provided in an embodiment of the present invention. Figure 2 A schematic diagram of the interaction between the energy storage converter and the battery management system provided in an embodiment of the present invention.

[0037] like Figure 1 As shown, the SOC calibration method combining the full-range rated ampere-hour calibration with the terminal power calibration includes the following steps:

[0038] Step S101, from the start of charging and discharging of the battery pack, obtaining the ampere-hour change value and energy change value of the battery pack in each cycle.

[0039] In step S101, the ampere-hour change value and energy change value of the battery pack in each cycle are obtained using a PCS (Power Conversion System, energy storage converter). Specifically, the PCS is connected to the positive and negative electrodes of the battery pack, and the battery pack includes a plurality of battery cells (see Figure 2 ), PCS includes a precise and high-speed current and voltage acquisition module, which is used to collect the voltage and current of the battery pack in real time since the battery pack starts to charge and discharge. PCS uses the voltage and current collected by the current and voltage acquisition module to accurately integrate the ampere-hour value and energy value within the cycle, thereby obtaining the ampere-hour change value ΔAh and energy change value ΔE of each cycle since the battery pack starts to charge and discharge. PCS sends the calculated ampere-hour change value and energy change value of the battery pack in each cycle to BMS (Battery Management System) through 485 communication or CAN communication.

[0040] Step S102, obtaining the remaining ampere-hour value at the current moment based on the ampere-hour change value to obtain a current estimated value of the state of charge.

[0041] In step S102, the current estimated value of the state of charge is calculated by the BMS. Specifically, the BMS periodically reads the data of the periodic ampere-hour change value ΔAh and the energy change value ΔE with the PCS system through a high-precision timer through a reliable communication method such as 485 or high-speed CAN. The BMS system obtains the remaining ampere-hour value at the current moment based on the ampere-hour change value to obtain the current estimated value of the state of charge, including: the ampere-hour remaining value of the battery pack at the current moment is calculated based on the ampere-hour change value from the start time of charging and discharging of the battery pack to the current moment and the ampere-hour initial value at the start time; the current estimated value of the state of charge is obtained based on the ampere-hour remaining value and the complete available ampere-hour value of the battery pack.

[0042] Among them, the ampere-hour residual value satisfies:

[0043]

[0044] In the formula, Ah Remai n is the current remaining ampere-hour value of the battery pack, Ah0 is the initial ampere-hour value at the start time, t0 is the start time, t NOW is the current moment, ΔAh t It is the ampere-hour change value of each cycle from the start time to the current time. In addition, BMS can also obtain the energy remaining value. The energy remaining value satisfies: E0 is the initial energy value at the start time, ΔE t It is the energy change value of each cycle from the start time to the current time.

[0045] The current estimated state of charge satisfies:

[0046] SOC 估算 =(Ah Remain / Ah Real )*100%

[0047] In the formula, SOC 估算 is the current estimated value of the state of charge, Ah Re al is the full available ampere-hour value of the battery pack.

[0048] Among them, the complete available ampere-hour value of the battery pack is Ah Re al is obtained based on the data of a test battery pack of the same model as the battery pack. The test battery pack in the embodiment of the present invention refers to the battery pack used in the actual project. Data collection for the battery pack used in the actual project can ensure that the collected battery data is adjusted and calibrated in real time according to the actual working conditions and life attenuation of the project, so that the subsequent parameter calculation is more accurate.

[0049] Specifically, for the test battery pack of the same model, the BMS obtains the complete ampere-hour value of the test battery pack during multiple charging or discharging processes (i.e., the ampere-hour change value of the battery from being fully charged when empty or being fully discharged when empty) Ah Total The complete available ampere-hour value Ah of the battery pack of the present invention in the current life state is obtained based on the average value of the complete ampere-hour value of multiple charging or discharging processes. Re al. BMS can also obtain the complete energy value E of the test battery pack during multiple charging or discharging processes Total The complete available energy value E of the battery pack of the present invention at the current life state is obtained based on the average value of the complete energy values ​​of multiple charging or discharging processes. Real .

[0050] Step S103, determining whether the battery pack has reached the terminal calibration condition, and if so, obtaining the terminal remaining energy prediction value based on the trained prediction model, energy change value, and the terminal operating temperature at the current moment.

[0051] In step S103 , the battery pack reaching the terminal calibration condition means that the voltage of the battery cells in the battery pack reaches the calibration voltage.

[0052] Specifically, Figure 2 As shown, the battery pack includes M battery cells, namely battery cell a1, battery cell a2, ..., battery cell a M The BMS monitors the battery pack status, including the voltage of each battery cell, the operating temperature of the battery pack, and the charge and discharge power. If it is detected that the voltage of at least one battery cell reaches the calibration voltage, it can be determined that the battery pack has reached the terminal calibration condition. The time when the terminal calibration condition is reached is the calibration start time t 校准开始 .

[0053] In step S103, if the battery pack does not reach the terminal calibration condition, the current estimated value of the state of charge obtained in step S102 does not need to be calibrated.

[0054] In step S103, if the battery pack reaches the terminal calibration condition, the calibration step is entered to calibrate the current estimated value of the state of charge. The calibration step requires the use of a trained prediction model. The prediction model is trained using a training data set to obtain a trained prediction model, and the training data set is obtained based on multiple sets of battery data; for a charging or discharging process, a corresponding set of battery data is obtained based on the complete ampere-hour value and complete energy value of the charging or discharging process, the terminal ampere-hour value and terminal energy value of the charging or discharging process, and the terminal operating temperature and terminal operating power of the charging or discharging process.

[0055] The following first explains the prediction model and the training of the prediction model.

[0056] The prediction model can adopt a linear fitting algorithm or a nonlinear fitting algorithm. Among them, the linear fitting algorithm can select the ordinary least squares method. The nonlinear fitting algorithm can be selected from Kalman filtering, polynomial regression, support vector machine or neural network, etc.

[0057] Taking the prediction model using ordinary least squares as an example, Figure 3 A block diagram of a battery management system provided by an embodiment of the present invention. Figure 4 This is a partial process diagram of the SOC calibration method combining full-range rated ampere-hour calibration with terminal power calibration provided by an embodiment of the present invention. Figure 3 and Figure 4 As shown, the training process of the prediction model of the present invention includes:

[0058] 1) Perform multiple complete charge and discharge operations on the test battery pack to obtain multiple sets of battery data. Each set of battery data corresponds to a complete charge and discharge operation. Each set of battery data includes the complete ampere-hour value Ah of the corresponding charge or discharge process. Tot al and the complete energy value E Total , corresponding to the terminal ampere-hour value of the charging or discharging process Ah End and the terminal energy value E End , corresponding to the terminal operating temperature T of the charging or discharging process AVG and terminal operating power P AVG Among them, the terminal ampere-hour value is Ah End satisfy: Terminal energy value E End satisfy: Among them, the voltage meets the terminal calibration condition means that the voltage of at least one battery cell in the test battery pack reaches the calibration voltage, and the voltage meets the cut-off condition means that the voltage of at least one battery cell in the test battery pack reaches the cut-off voltage. The terminal ampere-hour value Ah End The sum of the ampere-hour change values ​​ΔAh of all cycles between the calibration start time corresponding to when the voltage of at least one battery cell in the test battery pack reaches the calibration voltage and the cut-off time corresponding to when the voltage of at least one battery cell reaches the cut-off voltage, and the terminal energy value E End The sum of the energy change values ​​ΔE of all cycles between the calibration start time corresponding to when the voltage of at least one battery cell in the test battery pack reaches the calibration voltage and the cut-off time corresponding to when the voltage of at least one battery cell reaches the cut-off voltage, and the terminal operating temperature T AVG is the operating temperature of the battery pack from the start time to the end time of calibration, and the terminal operating power P AVGThe operating power of the battery pack from the start time to the end time of calibration. For each data in this step, the BMS periodically obtains the ampere-hour change value ΔAh and energy change value ΔE of the test battery pack through the timer, and calculates the complete ampere-hour value Ah through the energy statistics module in the SOC calculation module. Total , complete energy value E Total , Terminal ampere-hour value Ah End and the terminal energy value E End , monitor the terminal operating temperature T through the battery cell monitoring module AVG and terminal operating power P AVG After obtaining a set of battery data corresponding to a complete charge and discharge, the data is cleaned first, and the data that does not meet the requirements is removed and stored in the data storage module. A total of N sets of battery data are stored.

[0059] 2) Collecting sample data: Collecting sample data from N groups of battery data stored in the data storage module. The sample data, for example, includes N groups of samples, each group of samples includes a terminal energy value E End and terminal operating temperature T AVG .

[0060] 3) Constructing mathematical model: Using ordinary least squares method, the mathematical model is E End =β*T AVG +ε.

[0061] 4) BMS updates model parameters: BMS first cleans the data of N groups of samples, and then uses ordinary least squares method to perform regression fitting analysis on the terminal energy value and terminal operating temperature. This method is relatively simple and has low requirements and can be used on embedded devices. The error function E under this mathematical model is expressed as Among them, E Endi represents the terminal energy value in the i-th group of samples, T AVGi represents the terminal operating temperature in the i-th group of samples. β and ε are model parameters. The partial derivatives of β and ε are calculated on both sides, and the point where the derivative is 0 is found to obtain the values ​​of β and ε in the model, thus completing the training of the prediction model. That is:

[0062]

[0063] In step S103, the calibration step includes obtaining a terminal residual energy prediction value based on a trained prediction model, an energy change value, and a terminal operating temperature at a current moment.

[0064] Among them, the terminal remaining energy prediction value is obtained based on the trained prediction model, the energy change value, and the terminal operating temperature at the current moment, including: inputting the terminal operating temperature at the current moment into the trained prediction model to obtain the terminal energy prediction value; the terminal remaining energy prediction value is calculated based on the terminal energy prediction value and the energy change value between the calibration start time and the current time when the terminal calibration conditions are met.

[0065] Specifically, Figure 4 As shown, the regression parameters of the trained prediction model are output to the terminal calibration module. After the battery pack reaches the terminal calibration condition, the terminal operating temperature at the current moment is obtained. The terminal operating temperature at the current moment in the terminal calibration module is input into the trained prediction model to obtain the terminal energy prediction value E 预测 , and then calculate the terminal remaining energy prediction value E 末端预测 . Represents the sum of the energy change values ​​of all cycles between the start time of calibration and the current time.

[0066] Step S104, obtaining a current calibration step length based on the terminal remaining energy prediction value, the current charging and discharging power, the current estimated value of the state of charge, and the preset value of the state of charge.

[0067] In step S104, the calibration step further includes obtaining a current calibration step length based on the terminal remaining energy prediction value, the current charging and discharging power, the current estimated value of the state of charge, and the preset value of the state of charge.

[0068] The current calibration step length is obtained based on the terminal remaining energy prediction value, the current charge and discharge power, the current estimated value of the state of charge, and the preset value of the state of charge, including: obtaining the expected end time based on the terminal remaining energy prediction value and the current charge and discharge power; obtaining the state of charge difference based on the preset value of the state of charge and the current estimated value of the state of charge; and obtaining the current calibration step length based on the state of charge difference, the expected end time, and the scaling factor. The current calibration step length satisfies:

[0069] ΔSOC=(SCC 预设 -SOC 估算 ) / ((E 末端测 / P NOw )*x)

[0070] Where ΔSOC is the current calibration step size, SOC 预设 The preset value of the state of charge at the cut-off time, SOC 估算 is the current estimated value of the state of charge, P NOWIn the embodiment of the present invention, the expected end time is calculated using the terminal remaining energy prediction value and the current charge and discharge power, and multiplied by a certain scaling factor x, and then the state of charge difference between the state of charge preset value at the cut-off time and the current estimated state of charge value is combined to obtain the current calibration step.

[0071] Step S105 , calibrating the current estimated value of the state of charge based on the current calibration step length until the current estimated value of the state of charge reaches the preset value of the state of charge, thereby completing the calibration.

[0072] In step S105, the calibration step further includes calibrating the current estimated value of the state of charge based on the current calibration step length to obtain a current calibrated value of the state of charge SOC 校准 , i.e. SOC 校准 =SOC 估算 +ΔSOC. If the current calibration value of the state of charge SOC 校准 Equal to SOC 预设 , then stop the calibration. If the current calibration value SOC 校准 Not equal to SOC 预设 , then the current calibration value of the state of charge SOC 校准 As the current estimated value of the state of charge at the new current moment, the terminal remaining energy prediction value corresponding to the new current moment is recalculated, and combined with the new current charge and discharge power, the new current calibration step length corresponding to the new current moment is obtained, and the current estimated value of the state of charge at the corresponding moment is calibrated using the new current calibration step length until the current estimated value of the state of charge reaches the preset value of the state of charge. Thus, the current estimated value of the state of charge is controlled to approach the preset value of the state of charge through the step length of each approximation (i.e., the current calibration step length calculated each time), and at the preset cut-off time, the current estimated value of the state of charge is exactly equal to the preset value of the state of charge, ensuring that the current estimated value of the state of charge at the cut-off time is an accurate state of charge value.

[0073] In this embodiment, the prediction model can be updated regularly. Specifically, when formulating the model update strategy, the gradual characteristics of the physical state of the battery cell should be fully considered. Given that the battery cell state will not change significantly and drastically in the short term, an optimized update strategy can be set: for example, whenever the number of accumulated new battery data groups reaches a preset number and the device is in an idle state, a regression analysis is performed again to update the model. This ensures a balance between model adjustment and device performance.

[0074] In this embodiment, the SOC calibration method also includes an early warning step. Specifically, considering that the parameters of the prediction model in the method of the present invention are highly dependent on the data collected from the local device, the model parameters regressed on different terminal devices are different, so it is necessary to establish a monitoring and alarm mechanism. After each operation, the device will report the prediction result (i.e., the terminal energy prediction value E 预测 ) and the actual value of the current operating data (i.e. the terminal energy value E End ) is used for comparison. When the error between the predicted result and the true value exceeds the preset threshold, the alarm mechanism is triggered. When the error exceeds the preset threshold for the first time, the device automatically performs the re-regression fitting process and adjusts the model parameters based on the latest data. If the prediction error still exceeds the threshold after the parameters are re-estimated, the cloud alarm system will be activated. The operation and maintenance or R&D personnel will be notified to intervene and the model will be prohibited from being used again until the processing is completed.

[0075] In order to implement the above-mentioned embodiment, the present invention further proposes a SOC calibration system which combines full-range rated ampere-hour calibration with terminal electrical quantity calibration.

[0076] Figure 5 A block diagram of a SOC calibration system that combines full-range rated ampere-hour calibration with terminal electrical quantity calibration provided by an embodiment of the present invention.

[0077] like Figure 5 As shown, the SOC calibration system combining the full-range rated ampere-hour calibration with the terminal power calibration includes an energy storage converter 11 and a battery management system 12, wherein:

[0078] The energy storage converter 11 is used to monitor the current and voltage of the battery pack from the start of charging and discharging of the battery pack to obtain the ampere-hour change value and energy change value of each cycle, and send them to the battery management system;

[0079] The battery management system 12 is used to obtain the ampere-hour change value and energy change value of the battery pack in each cycle; obtain the remaining ampere-hour value at the current moment based on the ampere-hour change value to obtain the current estimated value of the state of charge; determine whether the battery pack reaches the terminal calibration condition, and if so, obtain the terminal remaining energy prediction value based on the trained prediction model, the energy change value, and the terminal operating temperature at the current moment; obtain the current calibration step length based on the terminal remaining energy prediction value, the current charging and discharging power, the current estimated value of the state of charge, and the preset value of the state of charge; calibrate the current estimated value of the state of charge based on the current calibration step length until the current estimated value of the state of charge reaches the preset value of the state of charge, thereby completing the calibration.

[0080] Furthermore, in a possible implementation of the embodiment of the present invention, in the battery management system 12, the battery pack reaching the terminal calibration condition means that the voltage of the battery cells in the battery pack reaches the calibration voltage.

[0081] Furthermore, in a possible implementation of an embodiment of the present invention, in the battery management system 12, a training data set is used to train a prediction model to obtain a trained prediction model, and the training data set is obtained based on multiple groups of battery data; wherein, for a charging or discharging process, a corresponding group of battery data is obtained based on the complete ampere-hour value and complete energy value of the charging or discharging process, the terminal ampere-hour value and terminal energy value of the charging or discharging process, and the terminal operating temperature and terminal operating power of the charging or discharging process.

[0082] Furthermore, in a possible implementation of the embodiment of the present invention, in the battery management system 12, the prediction model adopts a linear fitting algorithm or a nonlinear fitting algorithm.

[0083] Furthermore, in a possible implementation of an embodiment of the present invention, in the battery management system 12, a terminal remaining energy prediction value is obtained based on a trained prediction model, an energy change value, and a terminal operating temperature at a current moment, including: inputting the terminal operating temperature at a current moment into a trained prediction model to obtain a terminal energy prediction value; and calculating the terminal remaining energy prediction value based on the terminal energy prediction value and the energy change value between the calibration start time and the current time when the terminal calibration condition is met.

[0084] Furthermore, in a possible implementation of an embodiment of the present invention, in the battery management system 12, the remaining ampere-hour value at the current moment is obtained based on the ampere-hour change value to obtain the current estimated value of the state of charge, including: obtaining the ampere-hour remaining value of the battery pack at the current moment based on the ampere-hour change value from the start time of charging and discharging of the battery pack to the current moment and the ampere-hour initial value at the start time; and obtaining the current estimated value of the state of charge based on the ampere-hour remaining value and the complete available ampere-hour value of the battery pack.

[0085] Furthermore, in a possible implementation of an embodiment of the present invention, in the battery management system 12, a current calibration step is obtained based on the terminal remaining energy prediction value, the current charging and discharging power, the current estimated value of the state of charge, and the preset value of the state of charge, including: obtaining an expected end duration based on the terminal remaining energy prediction value and the current charging and discharging power; obtaining a state of charge difference based on the preset value of the state of charge and the current estimated value of the state of charge; and obtaining the current calibration step based on the state of charge difference, the expected end duration, and a scaling factor.

[0086] It should be noted that the aforementioned explanation of the SOC calibration method embodiment combining full-range rated ampere-hour calibration with terminal electrical quantity calibration is also applicable to the SOC calibration system combining full-range rated ampere-hour calibration with terminal electrical quantity calibration of this embodiment, and will not be repeated here.

[0087] In an embodiment of the present invention, the ampere-hour change value and energy change value of the battery pack in each cycle are obtained since the battery pack starts to charge and discharge; the remaining ampere-hour value at the current moment is obtained based on the ampere-hour change value to obtain the current estimated value of the state of charge; it is determined whether the battery pack reaches the terminal calibration condition, and if so, the terminal remaining energy prediction value is obtained based on the trained prediction model, the energy change value, and the terminal operating temperature at the current moment; the current calibration step length is obtained based on the terminal remaining energy prediction value, the current charging and discharging power, the current estimated value of the state of charge, and the preset value of the state of charge; the current estimated value of the state of charge is calibrated based on the current calibration step length until the current estimated value of the state of charge reaches the preset value of the state of charge, thereby completing the calibration. In this case, the full-range rated ampere-hour calibration method is used to obtain the current estimated state of charge based on the ampere-hour change value, and then when the terminal calibration condition is reached, the current calibration step is obtained based on the output result of the trained prediction model, combined with the current charging and discharging power, the current estimated state of charge, and the preset state of charge value to calibrate the current SOC estimated by the full-range rated ampere-hour calibration method, so that the current SOC estimated at the end of charging or discharging reaches the preset state of charge value, which solves the problem of the estimated SOC value seriously deviating from the actual value at the end of charging and discharging, especially at the end, caused by the traditional ampere-hour integration method, and makes the SOC value calculated at the end of charging and discharging, especially at the end, more accurate.

[0088] In the method and system of the present invention, the BMS synchronizes the energy changes within the cycle with the PCS through high-speed communication, monitors the state of the battery, and collects a large number of data sets. Then a reasonable mathematical model is constructed, and the model parameters are obtained by analysis after the data set is input. The key point is that the BMS uses the full-range rated ampere-hour calibration method to estimate the current SOC in the early stage of charging and discharging, and calibrates the SOC estimated by the full-range rated ampere-hour calibration method according to the model output results at the end of charging and discharging. Among them, the prediction module uses the classic linear relationship model as an example. The characteristics of the actual data set are far more complex than the model in the example. Different mathematical models can be constructed according to the characteristics between the data and the project requirements to more accurately describe the data set. Once the model training is completed and verified to be effective, the model parameters or the entire model structure can be deployed on the embedded terminal device, thereby realizing real-time data prediction. The method and system of the present invention eliminate the SOC offset problem caused by the cumulative error and the inaccurate initial SOC at the end of the battery charging and discharging, and can more truly reflect the current state of charge of the battery, thereby improving the robustness of the system and customer satisfaction.

[0089] In order to implement the above embodiments, the present invention also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided by the above embodiments.

[0090] In order to implement the above embodiments, the present invention further proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0091] In order to implement the above embodiments, the present invention further provides a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0092] In the description of the aforementioned embodiments, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0093] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0094] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0095] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0096] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0097] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0098] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0099] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A SOC calibration method combining full-range rated ampere-hour calibration with terminal power calibration, characterized in that: include: Since the battery pack starts to charge and discharge, obtaining the ampere-hour change value and energy change value of the battery pack in each cycle; Obtaining a remaining ampere-hour value at a current moment based on the ampere-hour change value to obtain a current estimated value of the state of charge; Determine whether the battery pack reaches the terminal calibration condition, and if so, obtain the terminal remaining energy prediction value based on the trained prediction model, the energy change value, and the terminal operating temperature at the current moment; Obtaining a current calibration step length based on the terminal remaining energy prediction value, the current charging and discharging power, the current estimated value of the state of charge, and the preset value of the state of charge; The current estimated value of the state of charge is calibrated based on the current calibration step until the current estimated value of the state of charge reaches the preset value of the state of charge, thereby completing the calibration.

2. The SOC calibration method combining full-range rated ampere-hour calibration and terminal power calibration according to claim 1, characterized in that: The battery pack reaching the terminal calibration condition means that the voltage of the battery cells in the battery pack reaches the calibration voltage.

3. The SOC calibration method combining full-range rated ampere-hour calibration and terminal power calibration according to claim 1, characterized in that: A prediction model is trained using a training data set to obtain a trained prediction model, wherein the training data set is obtained based on multiple groups of battery data; wherein, for a charging or discharging process, a corresponding group of battery data is obtained based on the complete ampere-hour value and complete energy value of the charging or discharging process, the terminal ampere-hour value and terminal energy value of the charging or discharging process, and the terminal operating temperature and terminal operating power of the charging or discharging process.

4. The SOC calibration method combining full-range rated ampere-hour calibration and terminal power calibration according to claim 1, characterized in that: The prediction model adopts a linear fitting algorithm or a nonlinear fitting algorithm.

5. The SOC calibration method combining full-range rated ampere-hour calibration with terminal power calibration according to claim 1, characterized in that: The obtaining of the terminal remaining energy prediction value based on the trained prediction model, the energy change value, and the terminal operating temperature at the current moment includes: Input the terminal operating temperature at the current moment into the trained prediction model to obtain the terminal energy prediction value; The terminal residual energy prediction value is calculated based on the terminal energy prediction value and the energy change value between the calibration start time and the current time when the terminal calibration condition is met.

6. The SOC calibration method combining full-range rated ampere-hour calibration and terminal power calibration according to claim 1, characterized in that: The obtaining the remaining ampere-hour value at the current moment based on the ampere-hour change value to obtain the current estimated value of the state of charge includes: The remaining ampere-hour value of the battery pack at the current moment is calculated based on the ampere-hour change value from the starting moment when the battery pack starts charging and discharging to the current moment and the ampere-hour initial value at the starting moment; A current estimated value of the state of charge is obtained based on the remaining ampere-hour value and the complete available ampere-hour value of the battery pack.

7. The SOC calibration method combining full-range rated ampere-hour calibration with terminal power calibration according to claim 1, characterized in that: The obtaining of the current calibration step length based on the terminal remaining energy prediction value, the current charging and discharging power, the current estimated value of the state of charge, and the preset value of the state of charge includes: Obtaining an expected end time based on the terminal remaining energy prediction value and the current charge and discharge power; Obtaining a state of charge difference based on the preset state of charge value and the current estimated state of charge value; A current calibration step size is obtained based on the state of charge difference, the expected end time, and a scaling factor.

8. A SOC calibration system combining full-range rated ampere-hour calibration with terminal power calibration, characterized in that: include: The energy storage converter is used to monitor the current and voltage of the battery pack from the beginning of charging and discharging of the battery pack to obtain the ampere-hour change value and energy change value of each cycle, and send them to the battery management system; A battery management system, used for obtaining the ampere-hour change value and energy change value of the battery pack in each cycle; Based on the ampere-hour change value, the remaining ampere-hour value at the current moment is obtained to obtain the current estimated value of the state of charge; judging whether the battery pack has reached the terminal calibration condition, and if so, obtaining the terminal remaining energy prediction value based on the trained prediction model, the energy change value, and the terminal operating temperature at the current moment; Obtaining a current calibration step length based on the terminal remaining energy prediction value, the current charging and discharging power, the current estimated value of the state of charge, and the preset value of the state of charge; The current estimated value of the state of charge is calibrated based on the current calibration step until the current estimated value of the state of charge reaches the preset value of the state of charge, thereby completing the calibration.

9. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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