Battery self-discharge detection method and device and vehicle

Abstract

The invention relates to a battery self-discharge detection method and device and a vehicle, and the method comprises the steps: building a relaxation model based on the open-circuit voltage of each battery unit in a relaxation process, and determining the balanced open-circuit voltage of each battery unit; determining a state of charge of the battery cell based on the equilibrium open circuit voltage of the battery cell and the temperature of the battery cell; and constructing a self-discharge evolution model based on the change quantity of the charge state of the battery unit corresponding to the multiple relaxation processes and the charge state of the normal battery unit, and determining the self-discharge current and the current change rate of the battery unit. According to the invention, the equilibrium open-circuit voltage can be fitted based on a small amount of relaxation process data, the range of self-discharge detection is widened, early detection of the battery unit with fast self-discharge current speed increase is realized, and the credibility and robustness of indexes can be improved to obtain more accurate evaluation of the self-discharge level of the battery.

Description

Technical Field

[0001] The present disclosure relates to the field of vehicle technology, and in particular to a battery self-discharge detection method, device and vehicle. Background Art

[0002] Battery self-discharge refers to the phenomenon that the stored energy in the battery is consumed spontaneously when the battery is not connected to any external load or circuit. Self-discharge will shorten the battery life and affect the overall performance of the battery pack. In some cases, it may even cause the battery to overheat, swell and explode, posing a threat to the safety of users' lives and property. Therefore, it is very necessary to monitor the battery self-discharge to improve battery utilization efficiency and reduce battery safety risks.

[0003] The currently commonly used self-discharge detection method needs to remove the influence of the relaxation process on the voltage when detecting whether the battery is self-discharging, otherwise it will cause the measured K value (the rate of decrease of the open circuit voltage of the battery during the static period) to be biased. However, the relaxation process lasts for a long time, and in the actual use scenario of the vehicle, due to the vehicle-side battery management system (BMS) strategy and on-board electrical appliances, the battery static data that can be obtained from the Internet of Vehicles database is short, and it is difficult to obtain the open circuit voltage at the end of the battery relaxation process.

[0004] Due to errors in the data itself and the calculation process, the results based on only one calculation are easily affected by accidental factors, and the credibility of the results is poor. At the same time, the results based on a data segment cannot reflect the changing trend of the battery over a longer period of time. If the self-discharge rate of a battery is fast, even if its current self-discharge current is small, it should be considered to have a greater safety risk. Therefore, it is inaccurate to evaluate the self-discharge level of the battery based on the current detection method, and the credibility and comprehensiveness of the detection method need to be improved. Summary of the invention

[0005] In order to solve the above technical problems, the present disclosure provides a battery self-discharge detection method, device and vehicle.

[0006] In a first aspect, the present disclosure provides a method for detecting battery self-discharge, comprising:

[0007] Obtaining the open circuit voltage of each battery cell of the battery pack and the temperature of each battery cell during the relaxation process;

[0008] Constructing a relaxation model based on the open circuit voltage of each battery cell during the relaxation process to determine the equilibrium open circuit voltage of the battery cell;

[0009] Determining a state of charge of the battery cell based on an equilibrium open circuit voltage of the battery cell and a temperature of the battery cell;

[0010] Based on the change in the state of charge of the battery cell corresponding to multiple relaxation processes and the state of charge of a normal battery cell, a self-discharge evolution model is constructed, and a self-discharge current and a current change rate of the battery cell are determined;

[0011] The state of charge of the normal battery cell is determined according to the state of charge of each of the battery cells.

[0012] In some embodiments, constructing a relaxation model based on the open circuit voltage of each battery cell of the battery pack during the relaxation process to determine the equilibrium open circuit voltage of the battery cell includes:

[0013] A relaxation process model is constructed based on the open circuit voltage and relaxation time of each battery cell during the relaxation process to obtain the equilibrium open circuit voltage of the battery cell.

[0014] In some embodiments, obtaining the open circuit voltage of each battery cell of the battery pack and the temperature of each battery cell during the relaxation process includes:

[0015] The open circuit voltage of each battery cell of the battery pack and the temperature of each battery cell in the relaxation process after charging are completed are obtained.

[0016] In some embodiments, obtaining the temperature of each battery cell includes:

[0017] The battery temperature detected by the temperature sensor closest to the battery cell is used as the temperature of the battery cell.

[0018] In some embodiments, the self-discharge evolution model is constructed based on the change in the state of charge of the battery cell corresponding to multiple relaxation processes and the state of charge of a normal battery cell, and the self-discharge current and current change rate of the battery cell are determined, including:

[0019] Determine the middle value of the state of charge of each battery cell of the battery pack as the state of charge of the normal battery cell;

[0020] Based on the change in the charge state of the battery cell corresponding to multiple relaxation processes and the charge state of a normal battery cell, as well as the interval time of the relaxation process, a self-discharge evolution model is fitted and constructed to determine the self-discharge current and current change rate of the battery cell.

[0021] In some embodiments, the self-discharge evolution model is constructed based on the change in the state of charge of the battery cell corresponding to multiple relaxation processes and the state of charge of a normal battery cell, and the self-discharge current and current change rate of the battery cell are determined, including:

[0022] Based on the charge state change data corresponding to multiple relaxation processes and the charge state of normal battery cells whose change is greater than a difference threshold, a self-discharge evolution model is constructed, and the self-discharge current and current change rate of the battery cell are determined.

[0023] In some embodiments, before determining the self-discharge current and the current change rate of the battery cell, the method further includes:

[0024] It is determined that the goodness of fit of the self-discharge evolution model is greater than a goodness of fit threshold.

[0025] In some embodiments, after determining the self-discharge current and the current change rate of the battery cell, the method further includes:

[0026] Based on the self-discharge current being greater than a current threshold, and / or the current change rate being greater than a current change rate threshold, it is determined that the battery cell is a self-discharge risk battery cell.

[0027] In a second aspect, the present disclosure further provides a battery self-discharge detection device, comprising:

[0028] An electrical parameter acquisition module, used to acquire the open circuit voltage of each battery cell of the battery pack and the temperature of each battery cell during the relaxation process;

[0029] An equilibrium open circuit voltage determination module, used to construct a relaxation model based on the open circuit voltage of each battery cell during the relaxation process, and determine the equilibrium open circuit voltage of the battery cell;

[0030] a state of charge determination module, configured to determine the state of charge of the battery cell based on an equilibrium open circuit voltage of the battery cell and a temperature of the battery cell;

[0031] A data determination module, configured to construct a self-discharge evolution model based on the change in the state of charge of the battery cell corresponding to multiple relaxation processes and the state of charge of a normal battery cell, and determine the self-discharge current and current change rate of the battery cell;

[0032] The state of charge of the normal battery cell is determined according to the state of charge of each of the battery cells.

[0033] In a third aspect, the present disclosure further provides a vehicle, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any of the battery self-discharge detection methods provided in the first aspect are implemented.

[0034] Compared with the prior art, the technical solution provided by the present invention has the following advantages:

[0035] The battery self-discharge detection method provided by the present disclosure constructs a relaxation model by acquiring the open circuit voltage of each battery cell during the relaxation process, and determines the equilibrium open circuit voltage of the battery cell using the data during the relaxation process, thereby solving the problem of inaccurate equilibrium open circuit voltage caused by insufficient relaxation time. The state of charge of the battery cell can be determined by using the corresponding relationship between the equilibrium open circuit voltage of the battery cell and the state of charge of the battery cell, and in combination with the temperature influence. The state of charge of each battery cell obtained is compared with the state of charge of the normal battery cell to determine the change amount, and the above test is repeated for many times, and a self-discharge evolution model is constructed according to the obtained change amount. Based on the self-discharge evolution model, the self-discharge current and current change rate of the battery cell can be determined, and the self-discharge current and current change rate of the battery cell can reflect the degree of self-discharge risk of the battery cell. Therefore, the present disclosure can fit the equilibrium open circuit voltage based on a small amount of relaxation process data, and broaden the scope of self-discharge detection, realize early detection of battery cells with a faster self-discharge current growth rate, and can also improve the credibility and robustness of the indicator to obtain a more accurate evaluation of the battery self-discharge level. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0038] Figure 1 A corresponding relationship between an open circuit voltage and a state of charge of a battery provided in an embodiment of the present disclosure;

[0039] Figure 2 A flowchart of a method for detecting battery self-discharge provided in an embodiment of the present disclosure;

[0040] Figure 3 A schematic diagram of a curve showing a change in the state of charge of a battery cell and a normal state of charge of a battery cell over time provided by an embodiment of the present disclosure;

[0041] Figure 4 A structural block diagram of a battery self-discharge detection device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0042] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0043] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0044] Battery self-discharge can be divided into physical self-discharge and chemical self-discharge according to the reaction type: physical self-discharge is caused by physical factors (current collector burrs, metal foreign matter and diaphragm defects, etc.) causing internal short circuits in the battery; chemical self-discharge is caused by internal chemical reactions in the battery (electrolyte side reactions, battery material corrosion, etc.). Chemical self-discharge usually occurs significantly at high temperatures, and physical self-discharge is the main cause of battery self-discharge abnormalities at room temperature.

[0045] The commonly used self-discharge detection method at present is the voltage drop method, which is to charge the battery to a specific state of charge (State of Charge, SOC) and then let it stand for a period of time, and measure the decrease in the open circuit voltage (Open Circuit Voltage, OCV) of the battery during the static period. The rate of decrease can be described by the K value, the unit is mV / d (millivolts / day) or mV / h (millivolts / hour), which represents the decrease in the open circuit voltage of the battery per unit time. The internal electrochemical reaction of lithium-ion batteries is incomplete at the end of charging and discharging, and it takes a long time to allow the internal chemical substances to continue to self-react to tend to stability. The external manifestation is that the battery voltage tends to stabilize. This process is called the relaxation process of the battery. The voltage drop method needs to remove the influence of the relaxation process on the voltage, otherwise it will cause deviations in the measured K value. Alternatively, using the open circuit voltage method, the self-discharge of the battery will cause the battery storage capacity to decrease, so the degree of self-discharge can also be judged based on the reduction in the capacity of the static device. Since there is a corresponding relationship between the open circuit voltage of the battery and the state of charge of the battery (SOC-OCV curve), Figure 1 The corresponding relationship between the open circuit voltage and the state of charge of a battery provided in an embodiment of the present disclosure is shown in FIG. Figure 1 It can be seen that at different temperatures, there is a corresponding relationship between the open circuit voltage and the state of charge. However, similar to the voltage drop method, the open circuit voltage method also requires obtaining the accurate equilibrium open circuit voltage after the battery relaxation is completed. Long-term static conditions in laboratory scenarios are easy to achieve, but in actual vehicle use scenarios, vehicle static conditions usually correspond to the engine off state. After the engine is turned off, the vehicle will only send data to the cloud for a few minutes or not send data at all. It is difficult to obtain complete long-term static vehicle network data. Therefore, it is also difficult to obtain the accurate equilibrium open circuit voltage after the battery relaxation is completed.

[0046] Existing methods usually construct indicators based on the analysis results of a certain data segment to reflect the self-discharge level of the battery at that time. Due to errors in the data itself and the calculation process, the results based on only one calculation are easily affected by accidental factors, and the credibility of the results is poor. At the same time, the results obtained based on a data segment cannot reflect the changing trend of the battery over a longer period of time. If the self-discharge growth rate of a battery is fast, even if its current self-discharge current is small, it should be considered that there is a greater safety risk. Therefore, it is inaccurate to evaluate the self-discharge level of the battery based on the current detection method, and the credibility and comprehensiveness of the detection method need to be improved.

[0047] Based on this, the present disclosure provides a method for detecting battery self-discharge. Figure 2 The present invention provides a flow chart of a method for detecting battery self-discharge according to an embodiment of the present invention. The method can be performed by a battery self-discharge detection device, which can be arranged in a vehicle, such as Figure 2 As shown, the battery self-discharge detection method includes S110 to S140:

[0048] S110, obtaining the open circuit voltage of each battery cell of the battery pack and the temperature of each battery cell during the relaxation process.

[0049] For example, taking the battery pack of a vehicle as an example, the battery pack is composed of multiple battery cells. The Internet of Vehicles data can only obtain the state of charge of the entire battery pack, and cannot obtain the state of charge of a single battery cell, so it is necessary to use the open circuit voltage and temperature of each battery cell to determine the state of charge of each battery cell, so as to judge the self-discharge of each single battery later. The open circuit voltage of different battery cells may be different during the relaxation process, so the open circuit voltage of each battery cell of the battery pack during the relaxation process can be obtained. For example, the Internet of Vehicles data can directly obtain the open circuit voltage of each battery cell of the battery pack during the relaxation process, and the temperature of each battery cell can be obtained by a temperature sensor. In some optional embodiments, the open circuit voltage of each battery cell can also be obtained by the control module of the vehicle. The embodiment of the present disclosure does not specifically limit how to obtain the open circuit voltage and temperature of the battery cell.

[0050] S120: construct a relaxation model based on the open circuit voltage of each battery cell during the relaxation process, and determine the equilibrium open circuit voltage of the battery cell.

[0051] When using the open circuit voltage method to obtain the state of charge of a battery cell, the open circuit voltage when the battery cell reaches equilibrium is required. However, the BMS strategy will cause the vehicle to only send data for a few minutes to tens of minutes after powering off. The use of on-board electrical appliances will cause the battery cell to break the relaxation process. Therefore, the static data of the battery cell stored in the Internet of Vehicles data is relatively small, and it is difficult to directly obtain the equilibrium open circuit voltage by long-term static state, and it is also impossible to obtain the accurate equilibrium open circuit voltage.

[0052] Therefore, in step S110, the open circuit voltage of each battery cell of the battery pack is obtained during the relaxation process, and a relaxation model is constructed using the open circuit voltage to obtain the equilibrium open circuit voltage of each battery cell, so as to solve the problem of inaccurate equilibrium open circuit voltage caused by insufficient relaxation time.

[0053] In addition, in terms of the construction of the relaxation model, by constructing a mathematical model instead of a machine learning model to fit the voltage response of the relaxation process, the accuracy of the machine learning model can be effectively solved due to changes in data distribution. At the same time, the relaxation process is optimized to reduce the interference of related factors on the relaxation process, effectively improving the fitting accuracy.

[0054] S130 : Determine the state of charge of the battery cell based on the equilibrium open circuit voltage of the battery cell and the temperature of the battery cell.

[0055] At different temperatures, there are different corresponding relationships between the equilibrium open circuit voltage of the battery cell and the state of charge of the battery cell (SOC-OCV). For example, you can refer to Figure 1 The corresponding relationship diagram provided in the figure uses a two-dimensional linear interpolation method to obtain the state of charge of the battery cell, such as SOC=interp2d(Vb, Tb), where SOC represents the state of charge of the battery cell, Vb represents the equilibrium open circuit voltage of the battery cell, and Tb represents the temperature of the battery cell. Therefore, if it is necessary to obtain the state of charge of the battery cell, it is first necessary to obtain the equilibrium open circuit voltage and temperature of each battery cell. Based on the temperature of the battery cell obtained in step S110 and the equilibrium open circuit voltage of the battery cell obtained in step S120, the state of charge of the battery cell can be obtained using a two-dimensional linear interpolation method.

[0056] S140, constructing a self-discharge evolution model based on the charge state of the battery cell corresponding to multiple relaxation processes and the change amount of the charge state of the normal battery cell, and determining the self-discharge current and current change rate of the battery cell;

[0057] The state of charge of the normal battery cell is determined according to the state of charge of each battery cell.

[0058] Exemplarily, the state of charge of each battery cell obtained is compared with the state of charge of a normal battery cell to obtain the change in the state of charge. Based on the change in the state of charge, the self-discharge risk of the battery cell can be preliminarily judged. Among them, the state of charge of the normal battery cell is determined according to the state of charge of each battery cell in the battery pack. The battery pack includes multiple battery cells, such as normal battery cells and abnormal battery cells. According to the state of charge of each battery cell, the state of charge of the normal battery cell can be determined, which will be explained in the subsequent embodiments. The above detection is performed on each battery cell in the battery pack for multiple consecutive times and the change in the state of charge is obtained. Based on the state of charge of the battery cell corresponding to multiple relaxation processes and the change in the state of charge of the normal battery cell, a self-discharge evolution model is constructed. The self-discharge evolution model can reflect the self-discharge current and current change rate of the battery cell. The self-discharge current and current change rate can reflect the self-discharge of the battery cell to a certain extent. For example, if the self-discharge current of the battery cell is small, but its current change rate increases rapidly, that is, the current growth rate is large, then the battery cell also has a self-discharge risk.

[0059] After constructing the self-discharge evolution model, the robustness of the results can be guaranteed by simulating the goodness of fit. The self-discharge current change rate obtained according to the model fitting can reflect the self-discharge current growth rate and expand the detection range of self-discharge anomalies. Evaluation indicators such as the self-discharge current obtained based on multiple relaxation processes are more credible.

[0060] The battery self-discharge detection method provided by the present disclosure constructs a relaxation model by acquiring the open circuit voltage of each battery cell during the relaxation process, and determines the equilibrium open circuit voltage of the battery cell using the data during the relaxation process, thereby solving the problem of inaccurate equilibrium open circuit voltage caused by insufficient relaxation time. The state of charge of the battery cell can be determined by using the corresponding relationship between the equilibrium open circuit voltage of the battery cell and the state of charge of the battery cell, and in combination with the temperature influence. The state of charge of each battery cell obtained is compared with the state of charge of the normal battery cell to determine the change amount, and the above test is repeated for many times, and a self-discharge evolution model is constructed according to the obtained change amount. Based on the self-discharge evolution model, the self-discharge current and current change rate of the battery cell can be determined, and the self-discharge current and current change rate of the battery cell can reflect the degree of self-discharge risk of the battery cell. Therefore, the present disclosure can fit the equilibrium open circuit voltage based on a small amount of relaxation process data, and broaden the scope of self-discharge detection, realize early detection of battery cells with a faster self-discharge current growth rate, and can also improve the credibility and robustness of the indicator to obtain a more accurate evaluation of the battery self-discharge level.

[0061] Optionally, before executing step S140, it is also necessary to determine whether all battery cells in the battery pack have been traversed, that is, data is acquired for each battery cell in the battery pack. After the acquisition is completed, step S140 is executed, otherwise, the required data continues to be acquired.

[0062] In some embodiments, a relaxation model is constructed based on the open circuit voltage of each battery cell of the battery pack during the relaxation process to determine the equilibrium open circuit voltage of the battery cell, including:

[0063] A relaxation process model is constructed based on the open circuit voltage and relaxation time of each battery cell during the relaxation process to obtain the equilibrium open circuit voltage of the battery cell.

[0064] Exemplarily, to construct a relaxation process model, the open circuit voltage of each battery cell during the relaxation process and the relaxation time corresponding to the open circuit voltage are required. The relaxation time here refers to the time from the start of the relaxation process to the acquisition of the open circuit voltage.

[0065] According to the corresponding relationship between the open circuit voltage Vt and the relaxation time tr of each battery cell during the relaxation process:

[0066] Vt=f(Vb,τ,tr); (1)

[0067] Wherein, Vb is the equilibrium open circuit voltage of the battery cell; τ is the relaxation time constant, that is, the time required for the battery to return to the equilibrium state from the polarization state; tr is the relaxation time, that is, the time from the start of the relaxation process to the acquisition of the open circuit voltage; f(~) is the constructed relaxation model. The specifically constructed relaxation model can be constructed by various types of functions such as exponential functions, power functions or logarithmic functions. The embodiments of the present disclosure do not limit this and can be selected according to actual needs. Based on this relaxation model, the equilibrium open circuit voltage of each battery cell can be obtained.

[0068] In some embodiments, obtaining the open circuit voltage of each battery cell of the battery pack and the temperature of each battery cell during the relaxation process includes:

[0069] The open circuit voltage of each battery cell of the battery pack and the temperature of each battery cell in the relaxation process after charging are completed are obtained.

[0070] For example, since the open circuit voltage of each battery cell in the battery pack during the relaxation process is affected by the current size, current fluctuation and charge state of the battery cell, large current fluctuations may cause the lithium ion insertion / deinsertion process in each battery cell to become unstable and reflected in the voltage change during the relaxation process.

[0071] The discharge condition of a vehicle in actual use mainly corresponds to the vehicle driving state. Due to the influence of factors such as complex road conditions, variable driving behaviors and kinetic energy recovery, the current fluctuations during driving are large and the battery's state of charge is difficult to control, which is not conducive to the subsequent construction of a stable relaxation model. During the charging process, although there are differences in the current size, the current is relatively stable over a period of time, and the state of charge of each battery cell after charging is mostly distributed in a higher range. Compared with the discharge condition, the relaxation process under the charging condition is more stable, and the constructed relaxation model can obtain higher fitting accuracy.

[0072] Therefore, the open circuit voltage of each battery cell of the battery pack and the temperature corresponding to each battery cell during the relaxation process after charging are completed can be obtained, so as to construct a relaxation model with higher goodness of fit.

[0073] In some embodiments, obtaining the temperature of each battery cell includes:

[0074] The battery temperature detected by the temperature sensor closest to the battery cell is regarded as the temperature of the battery cell.

[0075] Exemplarily, when obtaining the temperature of each battery cell, a temperature sensor can be used for detection. Taking a vehicle as an example, the battery of the vehicle has multiple battery packs, each battery pack includes multiple battery cells and temperature sensors, and the temperature sensors do not correspond one to one to the battery cells. In some scenarios, the number of temperature sensors is less than the number of battery cells, and the surface temperature of a specific battery cell cannot be directly obtained through a certain temperature sensor. The battery temperature detected by the temperature sensor closest to the battery cell is closer to the surface temperature of the battery cell. Therefore, using the battery temperature detected by the temperature sensor closest to the battery cell as the temperature of the battery cell can improve the accuracy of temperature detection and further improve the reliability of the acquired state of charge of the battery cell.

[0076] Specifically, first determine the battery cell and position whose temperature needs to be acquired, then determine multiple temperature sensors and positions in the same battery pack as the battery cell, calculate the distance between the battery cell and each temperature sensor, and use the temperature detected by the temperature sensor closest to the battery cell as the temperature of the battery cell.

[0077] For example, according to the arrangement of the battery pack, the positions of the battery and the temperature sensor are converted into coordinate points to calculate the Euclidean distance between the two points. The coordinates of the battery cell are (x1, y1), and the coordinates of the temperature sensor are (x2, y2). The formula is as follows:

[0078]

[0079] Wherein, Dist is the distance between the battery cell and the temperature sensor.

[0080] Multiple distances may be obtained by calculation, from which the temperature detected by the temperature sensor closest to the battery cell is selected as the temperature of the battery cell.

[0081] Optionally, if there are multiple temperature sensors that are at an equal and closest distance to a battery cell, the average temperature value of the multiple temperature sensors is used as the temperature of the battery cell. To avoid inaccurate detection by the temperature sensor, the average value can be used as the temperature of the battery cell. For example, if two temperature sensors are closest to a battery cell, the temperatures of the two temperature sensors are obtained and the average value is taken as the temperature of the battery. In other embodiments, the temperature range can also be pre-set to remove temperature sensors whose detected temperatures do not meet the requirements to improve accuracy. The temperature of the battery cell can be selected according to actual needs, and the embodiments of the present disclosure do not impose specific restrictions on this.

[0082] In some embodiments, based on the change in the state of charge of the battery cell corresponding to multiple relaxation processes and the state of charge of the normal battery cell, a self-discharge evolution model is constructed, and the self-discharge current and current change rate of the battery cell are determined, including:

[0083] The middle value of the state of charge of each battery cell of the battery pack is determined as the state of charge of the normal battery cell.

[0084] Exemplarily, the battery pack includes multiple battery cells. After fitting the relaxation model, the equilibrium open circuit voltage corresponding to each battery cell can be obtained. Combined with the corresponding relationship between the equilibrium open circuit voltage of the battery cell and the state of charge of the battery cell, the state of charge of each battery cell can be obtained. There are many battery cells, and there may be battery cells in different states, such as normal battery cells and abnormal battery cells. Abnormal battery cells may have a risk of self-discharge or other states. By comparing the state of charge of normal battery cells with the state of charge of abnormal battery cells, it is possible to detect whether there is a risk of self-discharge for the battery cells. Therefore, the normal battery cells and their state of charge should be determined first.

[0085] In the same battery pack, most of the battery cells are usually normal battery cells, and only a few battery cells may have the risk of self-discharge. Therefore, the middle value of the state of charge of each battery cell in the battery pack can be determined as the state of charge of the normal battery cell. The following formula:

[0086] SOCnm=median(SOC1,SOC2,...,SOCn); (3)

[0087] Wherein, SOCnm represents the middle value of the state of charge of each battery cell (the state of charge of a normal battery cell); and n represents the number of battery cells in the battery pack.

[0088] In other scenarios, other values ​​may also be selected as the state of charge of a normal battery cell, such as the average value of the state of charge of each battery cell in a battery pack, etc. The embodiments of the present disclosure do not specifically limit how to determine the state of charge of a normal battery cell.

[0089] Based on the change in the state of charge of the battery cell corresponding to multiple relaxation processes and the state of charge of the normal battery cell, as well as the interval time of the relaxation process, a self-discharge evolution model is fitted and constructed to determine the self-discharge current and current change rate of the battery cell.

[0090] The change can be calculated based on the charge state of each battery cell and the charge state of a normal battery cell, as shown in the following formula:

[0091] ΔSOCi=SOCnm-SOCi; (4)

[0092] Here, SOCi represents the state of charge of the i-th battery cell, and ΔSOC represents the difference between the state of charge of a normal battery cell and the state of charge of each battery cell.

[0093] After obtaining the ΔSOC data of multiple relaxation processes, combined with the interval time of the relaxation process, the self-discharge evolution model can be fitted and constructed to determine the self-discharge current and current change rate of the battery cell. The interval time of the relaxation process refers to the time taken for each relaxation process relative to the first relaxation process.

[0094] Optionally, when fitting and constructing the self-discharge evolution model, the least squares fitting formula can be combined. The purpose of using the least squares method is to make the value estimated by the self-discharge evolution model as close to the true value as possible, that is, to minimize the sum of squared errors. The formula for calculating the sum of squared errors is as follows:

[0095]

[0096] Among them, L represents the sum of squared errors, yi is the true value, g(x) is the fitted value, Σ represents the sum of all samples, and n is the number of samples.

[0097] The formula for the sum of squared errors represents the gap between the true value and the fitted value. The larger the gap, the larger the sum of squared errors; and the smaller the gap, the smaller the sum of squared errors, and the closer the true value is to the fitted value. Therefore, a more accurate self-discharge evolution model curve can be constructed in combination with the least squares method. It should be noted that the above content is only a partial formula corresponding to a feasible implementation method, which is only for example.

[0098] For example, Figure 3 A schematic diagram of a curve showing the change in the state of charge of a battery cell and the state of charge of a normal battery cell over time provided by an embodiment of the present disclosure, with reference to Figure 3, the relative time (day) on the horizontal axis represents the relaxation interval time, and the ΔSOC (%) on the vertical axis represents the change in the state of charge of the battery cell compared with the state of charge of the normal battery cell. The original data is the real ΔSOC data at different times calculated by the above steps, and the fitting curve is the self-discharge evolution model curve fitted based on the real data. For example, the self-discharge evolution model curve (the relationship model between ΔSOC and t) corresponds to the following formula:

[0099] ΔSOC=at 2 +bt+c; (6)

[0100] Among them, ΔSOC is a quadratic function of t, a can reflect the current change rate of self-discharge, b can reflect the self-discharge current size, and c can be understood as a constant. If the ΔSOC and t values ​​within a certain period of time are known, this model can be fitted, and the self-discharge current and current change rate within this period of time can be reflected based on a and b.

[0101] Optionally, the multiple relaxation process can be set to 7 times. If the number is not reached, return to step S110 to continue to obtain the required electrical parameters of each battery cell.

[0102] In some embodiments, based on the change in the state of charge of the battery cell corresponding to multiple relaxation processes and the state of charge of the normal battery cell, a self-discharge evolution model is constructed, and the self-discharge current and current change rate of the battery cell are determined, including:

[0103] Based on the state of charge change data of the battery cell corresponding to multiple relaxation processes and the state of charge of the normal battery cell whose change is greater than the difference threshold, a self-discharge evolution model is constructed, and the self-discharge current and current change rate of the battery cell are determined.

[0104] For example, the battery cell with self-discharge risk can be preliminarily determined based on the change in the charge state of the battery cell and the charge state of the normal battery cell. If the change in the charge state of the battery cell and the charge state of the normal battery cell is greater than the difference threshold, it is preliminarily determined that the current battery cell has a self-discharge risk. For example, if the difference threshold is 5%, when ΔSOC is greater than 5%, it is preliminarily determined that the battery cell has a self-discharge risk, and when the self-discharge evolution model is subsequently constructed, the data corresponding to the battery cell can be directly screened.

[0105] In the same battery pack, the capacity difference between the capacity of a battery cell with a self-discharge risk and the capacity of a normal battery cell can be approximated as the capacity inconsistency caused by abnormal self-discharge of the battery cell, so the following formula exists:

[0106]

[0107] Among them, ΔSOC represents the change in the state of charge of a normal battery cell and the state of charge of each battery cell; SOCnm represents the state of charge of a normal battery cell in a battery pack; SOCsd represents the state of charge of a battery cell with a risk of self-discharge; Cn is the rated capacity of such normal battery cell, and Csd is the capacity lost due to self-discharge of a battery cell with a risk of self-discharge.

[0108] The formula for calculating the capacity loss of a battery cell with self-discharge risk due to self-discharge is as follows:

[0109]

[0110] Wherein, t0 is the time when self-discharge starts; t1 is the time when self-discharge ends; Isd is the self-discharge current.

[0111] At room temperature, the factors that cause battery cells to self-discharge are mainly physical factors, including current collector burrs, metal foreign matter, and diaphragm defects. These factors will continue to deteriorate over time, such as the continuous deposition of metal impurities and the continuous expansion of diaphragm defects, so the self-discharge current will continue to increase. Assuming that the deterioration rate of the battery self-discharge factors is constant within a certain period of time, that is, the growth rate of the self-discharge current is constant within a certain period of time, it can be expressed as:

[0112] Isd=I0+kt; (9)

[0113] Wherein, Isd is the self-discharge current, I0 is the initial self-discharge current during this period, k is the self-discharge current growth rate (rate of change), and t is time. In addition, the self-discharge current Isd changes with time.

[0114] Considering formulas (7), (8), and (9) comprehensively, we can obtain the specific relationship model between ΔSOC and t:

[0115]

[0116] Therefore, formula (10) is a specific expansion form of formula (6). According to formula (10), the self-discharge current and the current change rate in this time period can be reflected.

[0117] In some embodiments, before determining the self-discharge current and the current change rate of the battery cell, the method further includes:

[0118] It is determined that the goodness of fit of the self-discharge evolution model is greater than the goodness of fit threshold.

[0119] For example, after fitting the self-discharge evolution model, its goodness of fit R can be directly obtained. 2Goodness of fit is an important indicator for evaluating the model fitting effect, and can be used to evaluate the explanatory and predictive abilities of the model. The goodness of fit can be calculated by comparing the regression sum of squares (SSR) and the total sum of squares (SST) of the self-discharge evolution model. The specific formula is as follows: R 2 =SSR / SST. SSR stands for the regression sum of squares, which is used to measure the strength of the linear relationship between the independent variable and the dependent variable; SST stands for the total sum of squares, which is used to measure the degree of variation of the dependent variable. Based on this, the goodness of fit R can be obtained. 2 . The greater the goodness of fit, the higher the model credibility. The maximum value of the goodness of fit is 1. The smaller the goodness of fit, the worse the model credibility. Therefore, a goodness of fit threshold can be set, such as 0.9, and the goodness of fit corresponding to the self-discharge evolution model is compared with the goodness of fit threshold. If it is determined that the goodness of fit of the self-discharge evolution model is greater than the goodness of fit threshold, it is determined that the self-discharge evolution model currently constructed by fitting has a higher credibility. This self-discharge evolution model can be used to determine whether there is a self-discharge risk in the battery cell. It should be noted that there is no restriction on the specific method of obtaining the regression sum of squares and the total sum of squares, and it can be calculated according to actual needs.

[0120] In some embodiments, after determining the self-discharge current and the current change rate of the battery cell, the method further includes:

[0121] Based on the self-discharge current being greater than a current threshold, and / or the current change rate being greater than a current change rate threshold, it is determined that the battery cell is a self-discharge risk battery cell.

[0122] According to the self-discharge evolution model constructed by fitting, the self-discharge current and current change rate of each battery cell can be obtained, and the current threshold and current change rate threshold are pre-set. The obtained parameters are compared with the pre-set thresholds to determine whether the battery cell is a self-discharge risk battery cell.

[0123] Exemplarily, the obtained self-discharge current of the battery cell is compared with the current threshold, and if the self-discharge current is greater than the current threshold, the battery cell is determined to be a self-discharge risk battery cell. Alternatively, the obtained current change rate of the battery cell is compared with the current change rate threshold, and if the current change rate is greater than the current change threshold, it means that the self-discharge current of the battery cell increases rapidly. Even if the current self-discharge current is small, but the increase rate is fast, it can be considered that there is a greater safety risk, and the battery cell can be determined to be a self-discharge risk battery cell.

[0124] Optionally, the self-discharge current is compared with the current threshold, and the current change rate is compared with the current change threshold. If the self-discharge current is greater than the current threshold, and the current change rate is greater than the current change rate threshold, the battery cell is determined to be a self-discharge risk battery cell. Whether the battery cell has a self-discharge risk is determined by jointly judging whether the battery cell has a self-discharge risk by the self-discharge current and the current change rate, which can improve the reliability of the judgment result.

[0125] The present disclosure also provides a battery self-discharge detection device, Figure 4 A structural block diagram of a battery self-discharge detection device provided in an embodiment of the present disclosure, referring to Figure 4 , including: an electrical parameter acquisition module 31 , an equilibrium open circuit voltage determination module 32 , a charge state determination module 33 and a data determination module 34 .

[0126] The electrical parameter acquisition module 31 is used to obtain the open circuit voltage of each battery cell of the battery pack and the temperature of each battery cell during the relaxation process. The equilibrium open circuit voltage determination module 32 is used to construct a relaxation model based on the open circuit voltage of each battery cell during the relaxation process, and determine the equilibrium open circuit voltage of the battery cell. The state of charge determination module 33 is used to determine the state of charge of the battery cell based on the equilibrium open circuit voltage of the battery cell and the temperature of the battery cell. The data determination module 34 is used to construct a self-discharge evolution model based on the change in the state of charge of the battery cell corresponding to multiple relaxation processes and the state of charge of the normal battery cell, and determine the self-discharge current and current change rate of the battery cell; wherein the state of charge of the normal battery cell is determined according to the state of charge of each battery cell.

[0127] The embodiments of the present disclosure further provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the battery self-discharge detection method described in any of the above embodiments are implemented.

[0128] It should be noted that examples of readable storage media include, but are not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or components, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device or component.

[0129] The storage medium provided in the above-mentioned embodiment of the present disclosure and the battery self-discharge detection method provided in the embodiment of the present disclosure are based on the same inventive concept, and have the same beneficial effects as the methods adopted, run or implemented by the application programs or instructions stored therein.

[0130] The present disclosure also provides a vehicle, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the battery self-discharge detection method described in any of the above embodiments are implemented. The present disclosure can fit the equilibrium open circuit voltage based on a small amount of relaxation process data, and broaden the scope of self-discharge detection, realize early detection of battery cells with a faster self-discharge current growth rate, and can also improve the credibility and robustness of the indicator to obtain a more accurate evaluation of the battery self-discharge level.

[0131] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0132] The above description is only a specific embodiment of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting battery self-discharge, characterized in that: include: Obtaining the open circuit voltage of each battery cell of the battery pack and the temperature of each battery cell during the relaxation process; Constructing a relaxation model based on the open circuit voltage of each battery cell during the relaxation process to determine the equilibrium open circuit voltage of the battery cell; Determining a state of charge of the battery cell based on an equilibrium open circuit voltage of the battery cell and a temperature of the battery cell; Based on the change in the state of charge of the battery cell corresponding to multiple relaxation processes and the state of charge of a normal battery cell, a self-discharge evolution model is constructed, and a self-discharge current and a current change rate of the battery cell are determined; The state of charge of the normal battery cell is determined according to the state of charge of each of the battery cells.

2. The method for detecting battery self-discharge according to claim 1, characterized in that: The step of constructing a relaxation model based on the open circuit voltage of each battery cell of the battery pack during the relaxation process to determine the equilibrium open circuit voltage of the battery cell includes: A relaxation process model is constructed based on the open circuit voltage and relaxation time of each battery cell during the relaxation process to obtain the equilibrium open circuit voltage of the battery cell.

3. The method for detecting battery self-discharge according to claim 1, characterized in that: The obtaining of the open circuit voltage of each battery cell of the battery pack and the temperature of each battery cell during the relaxation process includes: The open circuit voltage of each battery cell of the battery pack and the temperature of each battery cell in the relaxation process after charging are completed are obtained.

4. The method for detecting battery self-discharge according to any one of claims 1 to 3, characterized in that: The obtaining of the temperature of each battery cell includes: The battery temperature detected by the temperature sensor closest to the battery cell is used as the temperature of the battery cell.

5. The method for detecting battery self-discharge according to claim 1, characterized in that: The self-discharge evolution model is constructed based on the change in the state of charge of the battery cell corresponding to multiple relaxation processes and the state of charge of a normal battery cell, and the self-discharge current and current change rate of the battery cell are determined, including: Determine the middle value of the state of charge of each battery cell of the battery pack as the state of charge of the normal battery cell; Based on the change in the charge state of the battery cell corresponding to multiple relaxation processes and the charge state of a normal battery cell, as well as the interval time of the relaxation process, a self-discharge evolution model is fitted and constructed to determine the self-discharge current and current change rate of the battery cell.

6. The method for detecting battery self-discharge according to claim 1, characterized in that: The self-discharge evolution model is constructed based on the change in the state of charge of the battery cell corresponding to multiple relaxation processes and the state of charge of a normal battery cell, and the self-discharge current and current change rate of the battery cell are determined, including: Based on the charge state change data corresponding to multiple relaxation processes and the charge state of normal battery cells whose change is greater than a difference threshold, a self-discharge evolution model is constructed, and the self-discharge current and current change rate of the battery cell are determined.

7. The method for detecting battery self-discharge according to any one of claims 1 to 3, characterized in that: Before determining the self-discharge current and the current change rate of the battery cell, the method further includes: It is determined that the goodness of fit of the self-discharge evolution model is greater than a goodness of fit threshold.

8. The method for detecting battery self-discharge according to any one of claims 1 to 3, characterized in that: After determining the self-discharge current and the current change rate of the battery cell, the method further includes: Based on the self-discharge current being greater than a current threshold, and / or the current change rate being greater than a current change rate threshold, it is determined that the battery cell is a self-discharge risk battery cell.

9. A battery self-discharge detection device, characterized in that: include: An electrical parameter acquisition module, used to acquire the open circuit voltage of each battery cell of the battery pack and the temperature of each battery cell during the relaxation process; An equilibrium open circuit voltage determination module, used to construct a relaxation model based on the open circuit voltage of each battery cell during the relaxation process, and determine the equilibrium open circuit voltage of the battery cell; a state of charge determination module, configured to determine the state of charge of the battery cell based on an equilibrium open circuit voltage of the battery cell and a temperature of the battery cell; A data determination module, configured to construct a self-discharge evolution model based on the change in the state of charge of the battery cell corresponding to multiple relaxation processes and the state of charge of a normal battery cell, and determine the self-discharge current and current change rate of the battery cell; The state of charge of the normal battery cell is determined according to the state of charge of each of the battery cells.

10. A vehicle, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the battery self-discharge detection method according to any one of claims 1 to 8 when executing the computer program.

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