Battery state of charge calibration method and related device

Abstract

The embodiment of the invention provides a battery charge state calibration method and a related device, and relates to the technical field of batteries, and the method comprises the steps: obtaining a capacity increment change curve of a battery in the charging process of the battery; and calibrating the state of charge of the battery according to the capacity increment change curve and a preset mapping relation between the capacity increment and the state of charge. Based on the method, the accuracy of SOC calibration can be effectively improved.

Description

Technical Field

[0001] The present application relates to the field of battery technology, and in particular to a battery state of charge calibration method and related devices. Background Art

[0002] The state of charge (SOC) of a battery may refer to the ratio of the remaining capacity of the battery to its capacity in a fully charged state, and may reflect the actual charge state of the battery at present.

[0003] In the related art, the ampere-hour integration method can be used to estimate the SOC of the battery. However, the ampere-hour integration method applied to the entire life cycle of the battery has accumulated errors due to factors such as current sensor sampling error and current available capacity error, resulting in the estimated SOC deviating seriously from the actual value over time. How to calibrate the SOC of the battery has become a problem that technicians in this field need to solve urgently. Summary of the invention

[0004] The embodiments of the present application provide a battery state of charge calibration method and related devices, which can effectively improve the accuracy of SOC calibration.

[0005] In a first aspect, an embodiment of the present application provides a battery state of charge calibration method, comprising:

[0006] During the battery charging process, obtaining a capacity increment change curve of the battery;

[0007] The state of charge of the battery is calibrated according to the capacity increment variation curve and a preset mapping relationship between the capacity increment and the state of charge.

[0008] In some embodiments, calibrating the state of charge of the battery according to the capacity increment change curve and a preset mapping relationship between the capacity increment and the state of charge includes:

[0009] Obtaining a target trough point in the capacity increment change curve;

[0010] The state of charge of the battery is calibrated according to the capacity increment corresponding to the target valley point and a preset mapping relationship between the capacity increment and the state of charge.

[0011] In some embodiments, obtaining a target trough point in the capacity increment change curve includes:

[0012] Obtaining a peak point in the capacity increment change curve;

[0013] Searching backward from the peak point, if the subsequent capacity increment data of a certain trough point are all greater than the capacity increment data corresponding to the trough point, and the differences are all greater than the first threshold, and the ratio of the difference between the capacity increment data corresponding to the trough point and the maximum value to the maximum value is greater than the second threshold, then the trough point is determined to be the target trough point.

[0014] In some embodiments, obtaining the capacity increment change curve of the battery includes:

[0015] Obtaining the charging voltage and charging current of the battery;

[0016] For any sampling node, according to the time interval between the previous sampling node and the charging current corresponding to the sampling node, the change amount of the battery capacity corresponding to the sampling node is obtained, and the change amount of the voltage between the previous sampling node and the previous sampling node is obtained;

[0017] According to the change amount of the battery capacity and the change amount of the voltage at each sampling node, obtaining the capacity increment data of each sampling node;

[0018] The capacity increment curve is determined according to the capacity increment data of each sampling node.

[0019] In some embodiments, the method further comprises:

[0020] During the battery charging process, if there is a sudden change in current, voltage compensation is performed on the charging voltage collected by the target sampling node; the target sampling node includes the sampling node corresponding to the sudden change in current and the sampling node within a preset time after the sudden change in current.

[0021] In some embodiments, if the target sampling node is a sampling node corresponding to a current mutation, performing voltage compensation on the charging voltage collected by the target sampling node includes:

[0022] Obtaining a voltage compensation value according to the charging voltage and charging current before the current mutation, and the charging voltage and charging current after the current mutation;

[0023] The charging voltage collected by the corresponding sampling node when the current suddenly changes is compensated according to the voltage compensation value.

[0024] In some embodiments, if the target sampling node is a sampling node within a preset time after the current mutation, the voltage compensation of the charging voltage collected by the target sampling node includes:

[0025] Obtaining the voltage difference between the charging voltage collected by the last sampling node before the charging current suddenly changes and the charging voltage collected by the first sampling node after a preset time;

[0026] The charging voltage collected by each sampling node within the preset time period is compensated according to the voltage difference.

[0027] In some embodiments, the method further comprises:

[0028] For any sampling node, if the voltage change amount between the sampling node and the previous sampling node is greater than or equal to the preset change amount, the capacity increment data of the sampling node is obtained according to the change amount of the battery capacity and the voltage change amount of the sampling node;

[0029] If the voltage change amount between the previous sampling node and the previous sampling node is less than the preset change amount, the capacity increment data of the previous sampling node is used as the capacity increment data corresponding to the current sampling node.

[0030] In some embodiments, the method further comprises:

[0031] When the battery is fully charged, the available capacity of the battery is updated according to the state of charge corresponding to the target valley.

[0032] In a second aspect, the present application provides an electronic device, including: a memory and a processor;

[0033] The memory is used to store computer instructions; the processor is used to execute the computer instructions stored in the memory to implement any method in the first aspect.

[0034] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and the computer program is executed by a processor to implement any one of the methods in the first aspect.

[0035] In a fourth aspect, the present application provides a computer program product, comprising a computer program, which implements any one of the methods in the first aspect when executed by a processor.

[0036] A fifth method, an embodiment of the present application provides a vehicle, in which the electronic device as described in the second aspect is disposed.

[0037] The battery state of charge calibration method and related device provided in the embodiment of the present application obtain the capacity increment change curve of the battery during the battery charging process; and calibrate the battery state of charge according to the capacity increment change curve and the mapping relationship between the preset capacity increment and the state of charge. Based on the above method, the accuracy of SOC calibration can be effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a schematic diagram of a SOC voltage curve;

[0039] Figure 2 is a schematic diagram of a DQ / DV-V curve;

[0040] Figure 3 is a schematic diagram of a DQ / DV-SOC curve;

[0041] Figure 4 A schematic diagram of the structure of a calibration device provided in an embodiment of the present application;

[0042] Figure 5 A flow chart of a battery state of charge calibration method provided in an embodiment of the present application Figure 1 ;

[0043] Figure 6 A flow chart of a battery state of charge calibration method provided in an embodiment of the present application Figure 2 ;

[0044] Figure 7 A schematic diagram of voltage correction provided in an embodiment of the present application;

[0045] Figure 8 A schematic diagram of SOC correction provided in an embodiment of the present application;

[0046] Fig. 9 A schematic diagram of the structure of a battery state of charge calibration device provided in an embodiment of the present application;

[0047] Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0049] In the embodiments of the present application, words such as "first" and "second" are used to distinguish the same or similar items with substantially the same functions and effects, and do not limit their order. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit them to be different.

[0050] It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0051] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0052] Lithium iron phosphate||graphite batteries have become the choice of many users due to their low cost and high safety. However, accurate calibration of the SOC of lithium iron phosphate||graphite batteries during use is still a difficult problem. The reasons are: (1) The ampere-hour integration method used in the entire life cycle of the battery has accumulated errors due to factors such as current sensor sampling error and current available capacity error, resulting in the estimated SOC of this method deviating seriously from the actual accumulation over time; (2) The accumulated error of ampere-hour integration is large, and it needs to be calibrated in time in combination with other strategies, such as Figure 1 As shown, however, because the voltage of lithium iron phosphate||graphite battery is long and flat, the current strategy is limited to closed circuit voltage calibration (CCV) when SOC is above 90%, full charge end (SOC=100%) calibration (HLV), open circuit voltage (OCV) and Kalman filter (EKF) calibration when SOC is below 20%, and full discharge end calibration (SOC=0%) (HLV).

[0053] However, during use, the battery mostly operates in the 20%-90% platform area, resulting in a large deviation in the above calibration method.

[0054] Incremental Capacity Analysis (ICA) can effectively solve the above problems. It is an in-situ non-invasive lithium battery performance analysis method that can quantitatively analyze the internal state of the battery without disassembling or damaging the battery.

[0055] There are two directions of analysis based on ICA: (1) Studying the relationship between capacity increment and voltage under constant current state, that is, DQ / DV-V curve, such as Figure 2As shown in the figure, the peak (peak intensity, peak area and peak axis) and trough (trough axis) of the curve show obvious gradual changes with rate, temperature and aging, which can reflect the electrochemical evolution mechanism inside the battery. This method is often used to analyze the available capacity of the battery in the current state to evaluate the aging state of the battery. (2) Under constant current state, ICA is combined with SOC, and the characteristics of the DQ / DV-SOC curve (IC-SOC, referred to as IC curve) are summarized through big data statistics, such as Figure 3 As shown in the figure, some studies have found that there are three characteristic points in the peak and valley values ​​of DQ / DV (peaks ①, ②, and valley Ⅱ) that have a relatively accurate correspondence with SOC (all within the range of 30-80% SOC), and online SOC calibration can be performed based on this correspondence.

[0056] However, in the above scheme, the current requirement is extremely strict during SOC calibration, and almost an absolute constant current is required. In actual application, it is unable to cope with various operating conditions of the battery, resulting in poor accuracy of SOC calibration.

[0057] In view of this, an embodiment of the present application provides a battery state of charge calibration method and related devices. During the battery charging process, by compensating the voltage under the non-constant current state, an equivalent IC curve is simulated, which can cover the application scenarios of almost all charging conditions and effectively improve the accuracy of SOC calibration.

[0058] The following specific embodiments are used to describe in detail the technical solution of the present application and how the technical solution of the present application solves the above technical problems. The following specific embodiments can be implemented independently or in combination with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0059] Figure 4 This is a schematic diagram of an application scenario for calibrating the battery SOC according to an embodiment of the present application. Figure 4 As shown, including:

[0060] Current monitoring module, temperature monitoring module, IC calibration SOC module and non-volatile memory (NVM) storage module.

[0061] The current monitoring module is used to monitor the current during the operation of the battery, identify the charge and discharge mode of the battery, and identify the jump of the current.

[0062] The temperature monitoring module is used to monitor the temperature of the battery during operation and determine whether to calibrate the SOC of the battery.

[0063] The IC calibration SOC module is used to calibrate the SOC of the battery according to the collected voltage and current during the battery charging process.

[0064] The NVM storage module is used to store the calibrated SOC for subsequent use or use by other units.

[0065] Based on the above embodiments, the battery state of charge calibration method provided in the embodiments of the present application is described below.

[0066] Figure 5 A flow chart of a battery state of charge calibration method provided in an embodiment of the present application Figure 1 The execution subject of the embodiment of the present application may be a battery management system, such as Figure 5 As shown, the steps include:

[0067] S501. During the battery charging process, obtain a capacity increment change curve of the battery.

[0068] In some embodiments, the battery management system may determine the capacity increment change curve according to the capacity increment change data obtained during the battery charging process, and the capacity increment data during the battery charging process may refer to the ratio between the change in battery capacity (DQ) at each sampling node relative to the previous sampling node and the change in charging voltage (DV) during the battery charging process. That is, each sampling node corresponds to a capacity increment data (DQ / DV).

[0069] During the battery charging process, the battery management system may collect the corresponding voltage and current at each sampling node, and calculate the capacity increment data of each sampling node based on the voltage and current.

[0070] Exemplarily, the voltage and current of the battery during the charging process are obtained; for any sampling node, the change in battery capacity corresponding to the sampling node is obtained based on the time interval between the previous sampling node and the current corresponding to the sampling node, and the voltage change between the previous sampling node and the sampling node is obtained; based on the change in battery capacity and the voltage change at each sampling node, the capacity increment data of each sampling node is obtained, and based on the capacity increment data of each sampling node, the capacity increment curve is determined.

[0071] In some embodiments, the capacity increment data may satisfy the following formula:

[0072]

[0073] Wherein, I is the current, Δt is the time interval from the last sampling node, and ΔV is the voltage change (also called voltage difference) from the last sampling node.

[0074] When the battery management system obtains the voltage and current of each sampling node, the capacity increment data of each sampling node can be obtained according to the above method. When the capacity increment data of each sampling node is obtained, the capacity increment curve of the battery can be determined.

[0075] In some embodiments, during the charging process, the charging current may change multiple times (i.e., a current mutation occurs), causing the corresponding voltage to mutate, resulting in an abnormality in the capacity increment data determined based on the voltage mutation, thereby causing deviations in the subsequent SOC calibration based on the capacity increment data. Therefore, when it is determined that a current mutation occurs, the corresponding voltage can be compensated, thereby reducing the probability of an abnormality in the capacity increment data determined based on the voltage mutation.

[0076] In some embodiments, the battery management system can determine whether a current mutation occurs based on the acquired charging current. For example, if the difference between the charging current collected by the current sampling node and the charging current collected by the previous sampling node is less than or equal to a preset current threshold, the charging current can be considered to be in a constant current state (i.e., no current mutation occurs); if the difference is greater than the preset current threshold, it can be considered that a current mutation occurs.

[0077] In some embodiments, after the charging current mutates, the reasons for the voltage mutation include the voltage mutation caused by the ohmic internal resistance and the mutation caused by the battery being in a non-steady state due to the current fluctuation in a short period of time (that is, after the current mutates, the battery will enter a non-steady state, and after a period of time, the battery enters a steady state). Therefore, when compensating for the voltage, the voltage collected when the current mutates and when the battery is in a non-steady state can be compensated.

[0078] Exemplarily, during the battery charging process, if there is a sudden change in current, voltage compensation is performed on the voltage collected by the target sampling node; the target sampling node includes the sampling node corresponding to the sudden change in current and the sampling node within a preset time after the sudden change in current.

[0079] The preset time period after the current mutation may refer to the time period during which the battery is in a non-steady state after the current mutation.

[0080] In some embodiments, the causes of the current mutation may include the switching of different current multiples during the charging process, local short-term fluctuations, etc. Different causes have corresponding time to enter the steady state (preset duration), which can be predefined in the battery management system. The battery management system determines the corresponding preset duration according to the causes of the current mutation, and performs voltage compensation on the voltage collected within the preset duration.

[0081] In some embodiments, for the charging voltage of the battery collected at the moment of current mutation, a voltage compensation value can be obtained based on the charging voltage and charging current before the current mutation, and the charging voltage and charging current after the current mutation; and the charging voltage collected by the corresponding sampling node when the current mutation occurs is compensated based on the voltage compensation value.

[0082] Exemplarily, the battery management system may use a preset fitting algorithm to fit the current and voltage collected before and after the current mutation moment to obtain the voltage compensation value, and subtract the voltage compensation value from the voltage collected at the current mutation moment to obtain the compensated voltage.

[0083] The battery management system can also obtain the internal resistance of the battery, obtain the compensation voltage based on the internal resistance and the current collected at the moment of the current mutation, and compensate the voltage collected at the moment of the current mutation based on the compensation voltage.

[0084] In some embodiments, when the battery is in a non-steady state, the voltage difference between the charging voltage collected by the last sampling node before the charging current suddenly changes and the charging voltage collected by the first sampling node after a preset time period can be obtained; and the charging voltage collected by each sampling node within the preset time period is compensated according to the voltage difference.

[0085] Exemplarily, for sampling node A, it is the last sampling node before the charging current suddenly changes, and the collected charging voltage is UA. At the first sampling node B after the preset time, the collected charging voltage is UB. The voltage difference between the above two sampling nodes is UA-UB.

[0086] For each sampling node included in the preset time length, the voltage difference may be subtracted from the charging voltage collected by each sampling node to complete compensation for the charging voltage collected by each sampling node within the preset time length.

[0087] S502: Calibrate the state of charge of the battery according to the capacity increment variation curve and a preset mapping relationship between the capacity increment and the state of charge.

[0088] The state of charge of the battery before calibration may refer to a state of charge determined based on a current estimation strategy (eg, an ampere-hour integration method).

[0089] In some embodiments, when the battery management system obtains the capacity increment change curve, it can use a pre-trained recognition model to obtain the target capacity increment in the capacity increment curve, and calibrate the battery's state of charge based on the mapping relationship between the target capacity and the preset capacity increment and the state of charge.

[0090] In some embodiments, when the battery management system obtains the capacity increment change curve, it can obtain the target trough point in the capacity increment change curve; and calibrate the state of charge of the battery according to the capacity increment corresponding to the target trough point and the mapping relationship between the preset capacity increment and the state of charge.

[0091] The target trough point may refer to a point in the capacity increment change curve obtained based on the capacity increment data that is consistent with the following: Figure 3 A similar trough point II is shown.

[0092] When the battery management system obtains the target capacity increment or the capacity increment corresponding to the trough point No. II, it can obtain the state of charge corresponding to the target capacity increment or the capacity increment corresponding to the trough point No. II through the mapping relationship between the preset capacity increment and the state of charge, and use the obtained state of charge as the actual state of charge of the battery at the moment when the target capacity increment or the capacity increment corresponding to the trough point No. II is located.

[0093] The mapping relationship between the preset capacity increment and the state of charge may be a mapping relationship obtained based on a large number of actual tests. For example, different batches of cells under the same material and process conditions are selected to perform DQ / DV-SOC curve tests at different rates (such as 0.1C to 1C), different temperatures (such as -10°C to 40°C) and different aging (such as 80 to 100%), and the stability of different feature points and the changes under rate, temperature and aging are statistically analyzed to obtain the mapping relationship.

[0094] The battery state of charge prediction method provided in the embodiment of the present application obtains the capacity increment change curve of the battery during the battery charging process; and calibrates the battery state of charge according to the capacity increment change curve and the mapping relationship between the preset capacity increment and the state of charge.

[0095] Combine the following Figure 6 , the battery state of charge calibration method provided in the embodiment of the present application is further explained.

[0096] Figure 6 A flow chart of a battery state of charge calibration method provided in an embodiment of the present application Figure 2 ,like Figure 6 As shown, the following steps are included:

[0097] S601 . During battery operation, monitor the current and temperature of the battery to determine whether to perform SOC calibration.

[0098] In some embodiments, the battery management system can confirm the charge and discharge status of the battery according to the direction of the current (e.g., negative for charging and positive for discharging), and determine to calibrate the SOC of the battery when the battery is charged.

[0099] In some embodiments, to improve the accuracy of battery SOC calibration, during the charging process, the battery management system can calibrate the battery SOC when the battery is within a preset temperature range according to the temperature. The battery SOC calibration can be called turning on the IC strategy total enable IC_Enable of the battery management system.

[0100] S602: When it is determined to perform SOC calibration, obtain the charging current and charging voltage of the battery at each sampling node.

[0101] The battery is connected to a sensor for measuring the current and voltage of the battery, and the battery management system can read the charging current and charging voltage of the battery from the sensor at each sampling node.

[0102] S603, acquiring the charging current according to each sampling node, and determining whether the charging current has a sudden change, if so, executing step S604, if not, executing step S605.

[0103] S604, performing voltage compensation on the charging voltage corresponding to the period of time when the current mutation occurs.

[0104] Optionally, performing voltage compensation on the charging voltage corresponding to the period of current mutation may also be referred to as starting the modification enable IC_VoltModEnable of the battery management system.

[0105] like Figure 7 As shown, by correcting the voltage, the abnormal fluctuation of the voltage curve caused by the abnormal voltage can be reduced. Among them, the black curve is the voltage after correction, and the gray curve is the voltage before correction.

[0106] S605: Acquire the capacity increment data according to the charging voltage and the charging current, and determine the capacity increment curve according to the capacity increment data.

[0107] In the embodiment of the present application, the specific implementation of steps S604 and S605 can refer to Figure 5 The specific implementation method shown in S501 in the illustrated embodiment will not be repeated here.

[0108] In some embodiments, to improve the efficiency of acquiring capacity increment data, the capacity increment data may be calculated once when a significant change occurs in the charging voltage.

[0109] Exemplarily, for any sampling node, if the voltage change between the sampling node and the previous sampling node is greater than or equal to a preset change, the capacity increment data of the sampling node is obtained based on the change in the battery capacity and the voltage change of the sampling node; if the voltage change between the sampling node and the previous sampling node is less than the preset change, the capacity increment data of the previous sampling node is used as the capacity increment data corresponding to the current sampling node.

[0110] For example, for sampling node A and its previous sampling node B, if the voltage change (UA-UB, also called voltage difference) between the voltage UA collected by sampling node A and the voltage UB collected by sampling node B is greater than or equal to a preset change (for example, 3 mV), then the capacity increment data corresponding to the sampling node A is calculated based on the voltage change between the voltage UA collected by sampling node A and the voltage collected by sampling node B and the corresponding capacity change.

[0111] For sampling node A and its previous sampling node B, if the voltage change (UA-UB, also called voltage difference) between the voltage UA collected by sampling node A and the voltage UB collected by sampling node B is less than a preset change (for example, 3 millivolts), the capacity increment data corresponding to the sampling node B can be used as the capacity increment data of node A. By using the capacity increment data of the previous node at a node with a smaller voltage change, the efficiency of acquiring the capacity increment data is improved.

[0112] S606: Obtain a target trough point in the capacity increment curve.

[0113] In some embodiments, when the capacity increment curve is obtained, a valley search may be performed in the curve to determine the target valley point.

[0114] Exemplarily, a peak point in the capacity increment change curve is obtained; searching backward from the peak point, if the subsequent capacity increment data of a certain trough point are all greater than the capacity increment data corresponding to the trough point, and the differences are all greater than a first threshold, and the difference between the capacity increment data corresponding to the trough point and the maximum value, and the ratio of the difference to the maximum value is greater than a second threshold, then the trough point is determined to be the target trough point.

[0115] During the valley search process, the battery management system can find the maximum value (DQ / DVmax, i.e., the peak value) in the capacity increment data, and use this as a benchmark to gradually search for the lowest point. The trough point (DQ / DVmin) is determined as follows: when the subsequent DQ / DV are greater than the DQ / DV corresponding to the trough point, and the difference is greater than a certain threshold A, and the (DQ / DVmax-DQ / DVmin) / DQDVmax of the trough point is greater than a certain threshold B (such as 0.8), then the trough point is considered to be the target trough point.

[0116] In some embodiments, based on prior knowledge, it is known that the target valley point usually occurs when the battery power is in the middle stage (e.g., 30%-80%). Therefore, during the charging process, when it is determined according to the ampere-hour integration method that the current charging power is greater than the lower limit value of the middle stage (e.g., 30%), online valley search begins.

[0117] It should be understood that online valley finding is a continuous process based on the charging process. In the process of continuously acquiring the capacity change data, as the collected capacity change data continues to increase (that is, the capacity change curve continues to change with the increase of capacity data), the battery management system may repeat the above-mentioned determination process multiple times until the target valley point is found. When the battery management system finds the target valley point, it can stop acquiring the capacity increment data.

[0118] S607: Calibrate the SOC of the battery according to the target valley point.

[0119] When the battery management system finds the target valley point, it can obtain the true SOC value of the battery according to the capacity increment data corresponding to the target valley point and the mapping relationship. Figure 8 As shown, the mapping relationship may be a DQ / DV-SOC curve.

[0120] Exemplarily, when the target valley point is obtained, the corresponding SOC true value is searched in the DQ / DV-SOC curve according to the DQ / DV data corresponding to the target valley point. For example, if the SOC true value found in the DQ / DV-SOC curve according to the DQ / DV data corresponding to the target valley point is 60%, and the SOC determined based on the ampere-hour integration method at the target valley point is 70%, then the SOC of the battery can be calibrated to 60%. Optionally, the SOC change in the subsequent charging process can also be synchronously calibrated based on the current calibration relationship.

[0121] S608: When the battery is fully charged, update the available capacity of the battery according to the state of charge corresponding to the target valley.

[0122] In some embodiments, the battery management system may also update the available capacity of the battery based on the state of charge corresponding to the target valley when the battery is fully charged, so as to calibrate the available capacity of the battery.

[0123] Exemplarily, updating the available capacity of the battery may satisfy the following formula:

[0124] Cn=(Q÷(1-M))×100

[0125] Among them, Cn is the available capacity of the battery after updating, M is the state of charge corresponding to the target valley (for example, 60%), and Q is the capacity from the target valley point to full charge, which can be determined by the ampere-hour integration method.

[0126] S609: Update the available capacity of the battery into the target memory.

[0127] The battery management system can update the updated available capacity of the battery to a preset target memory for use by other devices.

[0128] In summary, the battery state of charge calibration method provided in the embodiment of the present application can cover the application scenarios of almost all power vehicle charging conditions and even penetrate into the energy storage field, effectively improving the accuracy of SOC, and can also update the available capacity of the battery, thereby improving the accuracy of battery state estimation.

[0129] Based on the above embodiments, the embodiments of the present application also provide a battery state of charge calibration device.

[0130] Fig. 9 A schematic diagram of the structure of a battery state of charge calibration device 90 provided in an embodiment of the present application is shown in FIG. Fig. 9 As shown, including:

[0131] The acquisition module 901 is used to acquire the capacity increment change curve of the battery during the battery charging process.

[0132] The calibration module 902 is used for calibrating the state of charge of the battery according to the capacity increment change curve and the preset mapping relationship between the capacity increment and the state of charge.

[0133] In some embodiments, the acquisition module 901 is further used to acquire a target trough point in the capacity increment change curve.

[0134] In some embodiments, the calibration module 902 is further used to calibrate the state of charge of the battery according to the capacity increment corresponding to the target valley point and a preset mapping relationship between the capacity increment and the state of charge.

[0135] In some embodiments, the acquisition module 901 is also used to obtain the peak point in the capacity increment change curve; starting from the peak point and searching backward, if the subsequent capacity increment data of a certain trough point are all greater than the capacity increment data corresponding to the trough point, and the differences are all greater than a first threshold, and the difference between the capacity increment data corresponding to the trough point and the maximum value, and the ratio of the difference to the maximum value is greater than a second threshold, then the trough point is determined to be the target trough point.

[0136] In some embodiments, the acquisition module 901 is also used to acquire the battery charging voltage and charging current; for any sampling node, the change in battery capacity corresponding to the sampling node is obtained according to the time interval between the previous sampling node and the charging current corresponding to the sampling node, and the voltage change between the previous sampling node and the sampling node is obtained; the capacity increment data of each sampling node is obtained according to the battery capacity change and the voltage change of each sampling node; the capacity increment curve is determined according to the capacity increment data of each sampling node.

[0137] In some embodiments, the calibration module 902 is also used to perform voltage compensation on the charging voltage collected by the target sampling node if there is a current mutation during the battery charging process; the target sampling node includes the sampling node corresponding to the current mutation, and the sampling node within a preset time after the current mutation.

[0138] In some embodiments, the calibration module 902 is also used to obtain a voltage compensation value based on the charging voltage and charging current before the current mutation, and the charging voltage and charging current after the current mutation; and compensate the charging voltage collected by the corresponding sampling node when the current mutation occurs according to the voltage compensation value.

[0139] In some embodiments, the calibration module 902 is further used to obtain the voltage difference between the charging voltage collected by the last sampling node before the charging current suddenly changes and the charging voltage collected by the first sampling node after a preset time period; and compensate the charging voltage collected by each sampling node within the preset time period according to the voltage difference.

[0140] In some embodiments, the calibration module 902 is also used to obtain the capacity increment data of any sampling node based on the change in the battery capacity and the voltage change of the sampling node if the voltage change between the sampling node and the previous sampling node is greater than or equal to a preset change; if the voltage change between the sampling node and the previous sampling node is less than the preset change, the capacity increment data of the previous sampling node is used as the capacity increment data corresponding to the current sampling node.

[0141] In some embodiments, the calibration module 902 is further configured to update the available capacity of the battery according to the state of charge corresponding to the target valley when the battery is fully charged.

[0142] The battery state of charge calibration device provided in the embodiment of the present application can execute the battery state of charge calibration method provided in any of the above embodiments, and its principles and technical effects are similar, which will not be repeated here.

[0143] Fig.10 A schematic diagram of the structure of an electronic device 100 provided in an embodiment of the present application is shown in FIG. Fig.10 As shown, it includes: a transceiver 1001, a processor 1002, and a memory 1003.

[0144] The processor 1002 executes the computer execution instructions stored in the memory, so that the processor 1002 executes the scheme in the above embodiment. The processor 1002 can be a general-purpose processor, including a central processing unit CPU, a network processor (network processor, NP), etc.; it can also be a digital signal processor DSP, an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0145] The memory 1003 is connected to the processor 1002 via a system bus and completes communication between them. The memory 1003 is used to store computer program instructions.

[0146] The transceiver 1001 can receive data and send control instructions.

[0147] Optionally, the electronic device 100 may further include a communication interface, so that it can communicate and interact with an external or internal device through the communication interface, and the external device may be, for example, a client (e.g., a mobile phone, a tablet). In a specific implementation, if the communication interface, the memory 1003, and the processor 1002 are implemented independently, the communication interface, the memory 1003, and the processor 1002 may be interconnected through a bus and communicate with each other.

[0148] The system bus can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The system bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. The transceiver is used to realize the communication between the database access device and other computers (such as clients, read-write libraries, and read-only libraries). The memory may include random access memory (RAM) and may also include non-volatile memory.

[0149] Optionally, in a specific implementation, if the communication interface, the memory 1003 and the processor 1002 are integrated on a chip, the communication interface, the memory 1003 and the processor 1002 can communicate through an internal interface.

[0150] The embodiment of the present application further provides a vehicle, wherein the electronic device described in any of the above embodiments is arranged in the vehicle.

[0151] A computer-readable storage medium is also provided in an embodiment of the present application, on which a computer program is stored. When the computer program is executed by a processor, the technical solution of the above-mentioned battery state of charge calibration method embodiment is implemented. The implementation principle and technical effect are similar and will not be repeated here.

[0152] In one possible implementation, a computer-readable medium may include a random access memory (RAM), a read-only memory (ROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, a magnetic disk storage or other magnetic storage device, or any other medium that is intended to carry or store the required program code in the form of instructions or data structures and can be accessed by a computer. Moreover, any connection is appropriately referred to as a computer-readable medium. For example, if the software is transmitted from a website, server or other remote source using a coaxial cable, a fiber optic cable, a twisted pair, a digital subscriber line (DSL) or wireless technologies such as infrared, radio and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL or wireless technologies such as infrared, radio and microwave are included in the definition of the medium. Disks and optical disks as used herein include optical disks, laser disks, optical disks, digital versatile disks (DVDs), floppy disks and Blu-ray disks, where disks usually reproduce data magnetically, while optical disks reproduce data optically using lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0153] A computer program product is also provided in an embodiment of the present application, including a computer program. When the computer program is executed by a processor, the technical solution of the above-mentioned battery state of charge calibration method embodiment is implemented. The implementation principle and technical effect are similar and will not be repeated here.

[0154] In the specific implementation of the above-mentioned terminal device or server, it should be understood that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. The general-purpose processor can be a microprocessor or the processor can be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor.

[0155] Those skilled in the art will appreciate that all or part of the steps of any of the above method embodiments may be completed by hardware associated with program instructions. The aforementioned program may be stored in a computer-readable storage medium, and when the program is executed, all or part of the steps of the above method embodiments are executed.

[0156] If the technical solution of the present application is implemented in the form of software and sold or used as a product, it can be stored in a computer-readable storage medium. Based on such an understanding, all or part of the technical solution of the present application can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a computer program or several instructions. The computer software product enables a computer device (which can be a personal computer, a server, a network device, or a similar electronic device) to perform all or part of the steps of the method described in the embodiment of the present application.

[0157] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0158] It should be further noted that, although the various steps in the flowchart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0159] It should be understood that the above-mentioned device embodiments are only illustrative, and the device of the present application can also be implemented in other ways. For example, the division of units / modules in the above-mentioned embodiments is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0160] In addition, unless otherwise specified, each functional unit / module in each embodiment of the present application may be integrated into one unit / module, each unit / module may exist physically separately, or two or more units / modules may be integrated together. The above-mentioned integrated unit / module may be implemented in the form of hardware or in the form of a software program module.

[0161] If the integrated unit / module is implemented in the form of hardware, the hardware may be a digital circuit, an analog circuit, etc. The physical implementation of the hardware structure includes but is not limited to transistors, memristors, etc. If not specifically stated, the processor may be any appropriate hardware processor, such as a CPU, a GPU, an FPGA, a DSP, an ASIC, etc. If not specifically stated, the storage unit may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random-Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high-bandwidth memory HBM (High-Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc.

[0162] If the integrated unit / module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0163] In the above embodiments, the description of each embodiment has its own emphasis. For the part not described in detail in a certain embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0164] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A battery state of charge calibration method, characterized in that: include: During the battery charging process, obtaining a capacity increment change curve of the battery; The state of charge of the battery is calibrated according to the capacity increment variation curve and a preset mapping relationship between the capacity increment and the state of charge.

2. The method according to claim 1, characterized in that: The step of calibrating the state of charge of the battery according to the capacity increment change curve and a preset mapping relationship between the capacity increment and the state of charge includes: Obtaining a target trough point in the capacity increment change curve; The state of charge of the battery is calibrated according to the capacity increment corresponding to the target valley point and a preset mapping relationship between the capacity increment and the state of charge.

3. The method according to claim 2, characterized in that The obtaining of a target trough point in the capacity increment change curve includes: Obtaining a peak point in the capacity increment change curve; Searching backward from the peak point, if the subsequent capacity increment data of a trough point are all greater than the capacity increment data corresponding to the trough point, and the differences are all greater than the first threshold, and the difference between the capacity increment data corresponding to the trough point and the capacity increment data corresponding to the peak point, and the ratio of the difference between the capacity increment data corresponding to the trough point and the capacity increment data corresponding to the peak point is greater than the second threshold, then the trough point is determined to be the target trough point.

4. The method according to claim 3, characterized in that The obtaining of the capacity increment change curve of the battery includes: Obtaining the charging voltage and charging current of the battery; For any sampling node, according to the time interval between the last sampling node and the charging current corresponding to the sampling node, the change amount of the battery capacity corresponding to the sampling node is obtained, and the change amount of the voltage between the last sampling node and the last sampling node is obtained; According to the change amount of the battery capacity and the change amount of the voltage at each sampling node, obtaining the capacity increment data of each sampling node; The capacity increment curve is determined according to the capacity increment data of each sampling node.

5. The method according to claim 3, characterized in that: The method further comprises: During the battery charging process, if there is a sudden change in current, voltage compensation is performed on the charging voltage collected by the target sampling node; the target sampling node includes the sampling node corresponding to the sudden change in current and the sampling node within a preset time after the sudden change in current.

6. The method according to claim 5, characterized in that If the target sampling node is a sampling node corresponding to a sudden change in current, performing voltage compensation on the charging voltage collected by the target sampling node includes: Obtaining a voltage compensation value according to the charging voltage and charging current before the current mutation, and the charging voltage and charging current after the current mutation; The charging voltage collected by the corresponding sampling node when the current suddenly changes is compensated according to the voltage compensation value.

7. The method according to claim 5, characterized in that If the target sampling node is a sampling node within a preset time after the current mutation, the voltage compensation for the charging voltage collected by the target sampling node includes: Obtaining the voltage difference between the charging voltage collected by the last sampling node before the charging current suddenly changes and the charging voltage collected by the first sampling node after a preset time; The charging voltage collected by each sampling node within the preset time period is compensated according to the voltage difference.

8. The method according to claim 3, characterized in that The method further comprises: For any sampling node, if the voltage change amount between the sampling node and the previous sampling node is greater than or equal to the preset change amount, the capacity increment data of the sampling node is obtained according to the change amount of the battery capacity and the voltage change amount of the sampling node; If the voltage change amount between the previous sampling node and the previous sampling node is less than the preset change amount, the capacity increment data of the previous sampling node is used as the capacity increment data corresponding to the current sampling node.

9. The method according to any one of claims 2 to 8, characterized in that: The method further comprises: When the battery is fully charged, the available capacity of the battery is updated according to the state of charge corresponding to the target valley.

10. An electronic device, characterized in that: The electronic device comprises: a processor, a transceiver, and a memory; the processor is communicatively connected with the transceiver and the memory respectively; The memory stores computer-executable instructions; The transceiver communicates and interacts with an external device; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 9.

11. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 9.

12. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 9 when being executed by a controller.

13. A vehicle, characterized in that: Comprising the electronic device as claimed in claim 10.

Images