Power battery state monitoring method and related equipment

Abstract

The invention discloses a power battery state monitoring method and related equipment, and relates to the field of power batteries, the method comprises the following steps: if it is detected that a target vehicle enters a dormant state, carrying out at least one battery state monitoring operation on the target vehicle; wherein the battery state monitoring operation comprises the steps that the dormancy duration of a battery management system of the target vehicle is obtained, and the battery management system is awakened under the condition that the dormancy duration is longer than the awakening period corresponding to the current battery state monitoring operation; and obtaining the charge state of each battery cell of the power battery through the battery management system.

Description

Technical Field

[0001] This specification relates to the field of power batteries, and more specifically, the present application relates to a power battery status monitoring method and related equipment. Background Art

[0002] In the related technology, the abnormal monitoring of the power battery of electric vehicles is usually carried out through two main channels, one is monitoring through the big data background, and the other is monitoring through the battery management system (BMS).

[0003] However, when electric vehicles are parked for a long time and the vehicle is dormant, the power battery information on the vehicle cannot be output to the big data background, and because the BMS is dormant, the battery status cannot be effectively monitored. When the battery is abnormal, it cannot be detected in time, causing damage to the vehicle.

[0004] Therefore, it is necessary to propose a power battery status monitoring method and related equipment to at least solve some of the above problems. Summary of the invention

[0005] A series of simplified concepts are introduced in the Summary of the Invention section, which will be further described in detail in the Detailed Description of the Invention section. The Summary of the Invention section of this application does not mean to attempt to define the key features and essential technical features of the claimed technical solution, nor does it mean to attempt to determine the scope of protection of the claimed technical solution.

[0006] In a first aspect, the present application proposes a power battery status monitoring method, comprising:

[0007] If it is detected that the target vehicle enters a dormant state, performing at least one battery status monitoring operation on the target vehicle;

[0008] Among them, the battery status monitoring operation includes:

[0009] Obtaining the sleep duration of the battery management system of the target vehicle, and waking up the battery management system when the sleep duration is greater than the wake-up cycle corresponding to the current battery status monitoring operation;

[0010] The charge state of each cell of the power battery is obtained through the battery management system.

[0011] In a feasible implementation manner, the wake-up period corresponding to the first battery status monitoring operation is a preset period, and the method further includes:

[0012] Determining a self-discharge rate of each battery cell based on the state of charge of each battery cell;

[0013] In the case that the self-discharge rate of any of the battery cells is abnormal, the wake-up period is updated according to the abnormal self-discharge rate of the battery cell, and the updated wake-up period is used as the wake-up period corresponding to the next battery status monitoring operation.

[0014] In a feasible implementation manner, the specific steps of obtaining the self-discharge rate of the battery cell include:

[0015] Acquire a first cell voltage of a target battery cell when the target vehicle is dormant or after the battery management system is dormant and a first time corresponding to the first cell voltage;

[0016] Acquire a second cell voltage of the target battery cell after the battery management system wakes up and a second time corresponding to the second cell voltage;

[0017] According to the first cell voltage and the corresponding relationship between the SOC value and the voltage, a first SOC value is obtained;

[0018] Obtaining a second SOC value according to the second cell voltage and the corresponding relationship between the SOC value and the voltage;

[0019] The self-discharge rate of the target battery cell is determined based on the first SOC value, the second SOC value, the first time, and the second time.

[0020] In a feasible implementation, it also includes:

[0021] Obtain the number of abnormal cells with abnormal self-discharge rate;

[0022] In the case where the number of the abnormal cells is less than or equal to the preset number, determining the modified wake-up period based on the larger value of the self-discharge rate of the abnormal cells;

[0023] When the number of the abnormal cells is greater than the preset number, the modified wake-up period is determined based on the self-discharge rates of all the abnormal cells.

[0024] In a feasible implementation manner, the above-mentioned determination of the modified wake-up period based on the larger value of the self-discharge rate of the abnormal battery cell includes:

[0025] According to the larger value of the self-discharge rate, the abnormal degree interval is determined;

[0026] Determine the wake-up period corresponding to the above abnormality level interval according to the above abnormality level interval;

[0027] The wake-up period corresponding to the above abnormality level interval is determined as the modified wake-up period.

[0028] In a feasible implementation manner, the above-mentioned determination of the modified wake-up period based on the self-discharge rate of all abnormal battery cells includes:

[0029] Obtaining relative position information of each abnormal battery cell in the target power battery;

[0030] Determine the position weight information of each abnormal battery cell according to the relative position information of each abnormal battery cell;

[0031] Determine an abnormality coefficient according to the self-discharge rates of all the abnormal cells and the corresponding position weight information of the abnormal cells;

[0032] The modified wake-up period is determined according to the abnormal coefficient.

[0033] In a feasible implementation, it also includes:

[0034] When the self-discharge rate of any of the above-mentioned battery cells exceeds the warning threshold, the battery management system is continuously awakened to continuously monitor the above-mentioned power battery;

[0035] The current status information of the power battery is sent to the management terminal and the customer mobile terminal.

[0036] In a second aspect, the present application proposes a power battery status monitoring device, comprising:

[0037] A battery status monitoring unit, configured to perform at least one battery status monitoring operation on the target vehicle if it is detected that the target vehicle enters a dormant state;

[0038] Wherein, the battery status monitoring unit includes a first acquisition component and a second acquisition component;

[0039] The first acquisition component is used to acquire the sleep duration of the battery management system of the target vehicle, and wake up the battery management system when the sleep duration is greater than the wake-up cycle corresponding to the current battery status monitoring operation;

[0040] The second acquisition component is used to acquire the charge state of each cell of the power battery through the battery management system.

[0041] In a third aspect, an electronic device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is used to implement the steps of the power battery status monitoring method of any one of the first aspects described above when executing the computer program stored in the memory.

[0042] In a fourth aspect, the present application further proposes a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the power battery status monitoring method of any one of the first aspects is implemented.

[0043] In summary, in the related art, during the vehicle's dormancy period, the big data background cannot obtain the vehicle status, and the BMS is also in low power consumption mode, and it is impossible to collect and monitor battery data in real time. Power battery abnormalities (such as excessive self-discharge of battery cells, battery cell imbalance, etc.) may occur during dormancy and cannot be perceived in time, resulting in safety hazards. This application dynamically determines whether the BMS needs to be woken up by monitoring the duration of vehicle dormancy, thereby realizing intermittent monitoring of the battery status in the dormant state. After waking up, the BMS collects SOC data for each battery cell in the battery pack one by one to ensure a comprehensive understanding of the battery status and avoid monitoring blind spots. In dormancy mode, the monitoring frequency can be dynamically adjusted to ensure timely capture of abnormal states of the power battery (such as abnormal SOC fluctuations). In the related art, if a fixed cycle or continuous wake-up monitoring method is adopted, although the battery abnormality can be detected in time, a large amount of power will be consumed, resulting in increased energy consumption of the power battery, especially when parked for a long time, which may cause over-discharge of the battery. This application designs a dynamic wake-up strategy based on the comparison of "sleep duration" and "wake-up cycle", which triggers the wake-up operation only when the sleep duration is greater than the preset wake-up cycle. When the sleep time is short or the battery status is normal, keep the BMS in sleep mode to avoid unnecessary energy consumption. The wake-up cycle can be dynamically adjusted according to the self-discharge rate or other parameters of the battery to balance monitoring needs and energy-saving goals. It can significantly reduce the battery energy consumption during vehicle sleep, extend the maintenance time of the remaining battery power, and improve the battery safety in long-term parking scenarios. In the related art, the BMS cannot collect the status of the single cells in the battery pack after sleep, which may cause the abnormalities of some cells (such as SOC imbalance or voltage abnormality) not to be discovered in time. These abnormalities may accumulate and eventually cause serious damage to the entire power battery pack. After waking up the BMS by the method adopted in this application, the SOC data of all cells in the power battery pack are collected one by one to ensure that the status of each cell is fully monitored. Through SOC data analysis, the abnormality of the single cell (such as excessive self-discharge or SOC significantly lower than other cells) can be discovered in time, and corresponding measures can be taken to avoid the impact of the abnormality of a single cell on the performance and safety of the entire battery pack, and realize refined cell status monitoring. In the related technology, when parked for a long time, battery abnormalities (such as internal short circuit, excessive self-discharge, etc.) may cause serious accidents such as thermal runaway, capacity loss, and even fire. Existing monitoring solutions cannot achieve continuous monitoring in the dormant state, posing a potential threat to user and vehicle safety. This method can respond quickly when abnormal battery conditions (such as a significant drop in SOC or an abnormally high self-discharge rate) occur through intelligent wake-up and high-frequency data acquisition. Once an abnormality is detected, the battery status information can be sent to the big data background and user terminal through the real-time communication module to ensure that managers and car owners are aware of the risks in a timely manner and take countermeasures. Significantly improve the reliability of battery monitoring and vehicle safety, and reduce the risk of accidents caused by battery abnormalities. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present specification. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0045] Figure 1 A schematic diagram of a power battery status monitoring method provided in an embodiment of the present application;

[0046] Figure 2 A schematic diagram of the structure of a power battery status monitoring device provided in an embodiment of the present application;

[0047] Figure 3 A schematic diagram of the structure of a power battery status monitoring electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The technical solutions 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 only part of the embodiments of the present application, rather than all of the embodiments.

[0049] Figure 1 A schematic diagram of a power battery status monitoring method provided in an embodiment of the present application, the method may specifically include:

[0050] S110, if it is detected that the target vehicle enters a dormant state, performing at least one battery status monitoring operation on the target vehicle;

[0051] Among them, the battery status monitoring operation includes:

[0052] S1101, obtaining the sleep duration of the battery management system of the target vehicle, and waking up the battery management system when the sleep duration is greater than the wake-up cycle corresponding to the current battery status monitoring operation;

[0053] S1102: Obtain the state of charge of each cell of the power battery through the battery management system.

[0054] For example, when the target vehicle is detected to be in a dormant state, the monitoring operation of the battery state of the target vehicle is started. The dormant state generally refers to the vehicle being in a non-operating state, that is, the vehicle is not driving or charging, and the battery management system (BMS) will enter a low-power dormant mode most of the time.

[0055] The sleep duration refers to the time interval from when the BMS enters sleep mode to the current moment. The wake-up cycle is a preset time interval used to determine the frequency of battery status monitoring operations. The monitoring system records the sleep duration of the vehicle's BMS and compares it with the wake-up cycle of the current monitoring cycle. If the sleep duration is longer than the wake-up cycle, the wake-up operation is triggered; otherwise, the BMS remains in sleep mode to save energy.

[0056] The process of waking up the BMS can be triggered by hardware control or signals to switch the BMS from sleep mode to working mode for subsequent monitoring. After waking up, the BMS begins to collect the state of charge (SOC) data of each cell in the power battery. SOC is an important parameter for measuring the remaining capacity of the battery and can reflect the current power level of the battery. Power batteries are usually composed of multiple series-parallel cells. Obtain the SOC of each cell one by one to ensure a comprehensive understanding of the battery status and avoid the abnormality of a single cell being ignored.

[0057] In summary, in the related art, during the vehicle's dormancy period, the big data background cannot obtain the vehicle status, and the BMS is also in low power consumption mode, and it is impossible to collect and monitor battery data in real time. Power battery abnormalities (such as excessive self-discharge of battery cells, battery cell imbalance, etc.) may occur during dormancy and cannot be perceived in time, resulting in safety hazards. This application dynamically determines whether the BMS needs to be woken up by monitoring the duration of vehicle dormancy, thereby realizing intermittent monitoring of the battery status in the dormant state. After waking up, the BMS collects SOC data for each battery cell in the battery pack one by one to ensure a comprehensive understanding of the battery status and avoid monitoring blind spots. In dormancy mode, the monitoring frequency can be dynamically adjusted to ensure timely capture of abnormal states of the power battery (such as abnormal SOC fluctuations). In the related art, if a fixed cycle or continuous wake-up monitoring method is adopted, although the battery abnormality can be detected in time, a large amount of power will be consumed, resulting in increased energy consumption of the power battery, especially when parked for a long time, which may cause over-discharge of the battery. This application designs a dynamic wake-up strategy based on the comparison of "sleep duration" and "wake-up cycle", which triggers the wake-up operation only when the sleep duration is greater than the preset wake-up cycle. When the sleep time is short or the battery status is normal, keep the BMS in sleep mode to avoid unnecessary energy consumption. The wake-up cycle can be dynamically adjusted according to the self-discharge rate or other parameters of the battery to balance monitoring needs and energy-saving goals. It can significantly reduce the battery energy consumption during vehicle sleep, extend the maintenance time of the remaining battery power, and improve the battery safety in long-term parking scenarios. In the related art, the BMS cannot collect the status of the single cells in the battery pack after sleep, which may cause the abnormalities of some cells (such as SOC imbalance or voltage abnormality) not to be discovered in time. These abnormalities may accumulate and eventually cause serious damage to the entire power battery pack. After waking up the BMS by the method adopted in this application, the SOC data of all cells in the power battery pack are collected one by one to ensure that the status of each cell is fully monitored. Through SOC data analysis, the abnormality of the single cell (such as excessive self-discharge or SOC significantly lower than other cells) can be discovered in time, and corresponding measures can be taken to avoid the impact of the abnormality of a single cell on the performance and safety of the entire battery pack, and realize refined cell status monitoring. In the related technology, when parked for a long time, battery abnormalities (such as internal short circuit, excessive self-discharge, etc.) may cause serious accidents such as thermal runaway, capacity loss, and even fire. Existing monitoring solutions cannot achieve continuous monitoring in the dormant state, posing a potential threat to user and vehicle safety. This method can respond quickly when abnormal battery conditions (such as a significant drop in SOC or an abnormally high self-discharge rate) occur through intelligent wake-up and high-frequency data acquisition. Once an abnormality is detected, the battery status information can be sent to the big data background and user terminal through the real-time communication module to ensure that managers and car owners are aware of the risks in a timely manner and take countermeasures. Significantly improve the reliability of battery monitoring and vehicle safety, and reduce the risk of accidents caused by battery abnormalities.

[0058] In a feasible implementation manner, the wake-up period corresponding to the first battery status monitoring operation is a preset period, and the method further includes:

[0059] S210, determining the self-discharge rate of each battery cell based on the state of charge of each battery cell;

[0060] S220: When the self-discharge rate of any of the battery cells is abnormal, update the wake-up period according to the abnormal self-discharge rate of the battery cell, and use the updated wake-up period as the wake-up period corresponding to the next battery status monitoring operation.

[0061] Exemplarily, the first battery status monitoring operation uses a preset fixed wake-up cycle. For example, it can be set to 20 minutes or other suitable time lengths. This wake-up cycle is used to start the monitoring operation, collect the battery cell SOC, and provide basic data for subsequent adjustments.

[0062] The self-discharge rate indicates the rate at which the SOC of a battery decreases when it is not in operation (such as in sleep mode).

[0063] The self-discharge rate can be calculated using the following formula:

[0064]

[0065] η is the self-discharge rate, ΔSOC is the change in SOC between two monitoring cycles, and Δt is the time interval between two monitoring cycles.

[0066] The SOC data of all cells is obtained through the BMS, and the self-discharge rate of each cell is calculated to identify potential abnormal cells. A reasonable threshold can be set (for example, the normal self-discharge rate should be less than 1% / hour). If the self-discharge rate of a cell exceeds the threshold, it is judged as abnormal.

[0067] If an abnormal cell is found, the wake-up cycle should be shortened to increase the monitoring frequency and obtain battery status data more timely. For example: if the threshold self-discharge rate is 0.5% / hour, the actual self-discharge rate is 1% / hour, and the current wake-up cycle is 2 hours, the new wake-up cycle is adjusted to 1 hour. If the self-discharge rates of all cells are normal, maintain the original wake-up cycle or extend it appropriately to reduce the number of wake-ups and save energy.

[0068] In a feasible implementation manner, the specific steps of obtaining the self-discharge rate of the battery cell include:

[0069] S310, obtaining a first cell voltage of a target battery cell when the target vehicle is in sleep mode or after the battery management system is in sleep mode and a first time corresponding to the first cell voltage;

[0070] S320, obtaining a second cell voltage of the target cell after the battery management system wakes up and a second time corresponding to the second cell voltage;

[0071] S330, obtaining a first SOC value according to the first cell voltage and the corresponding relationship between the SOC value and the voltage;

[0072] S340, obtaining a second SOC value according to the second cell voltage and the corresponding relationship between the SOC value and the voltage;

[0073] S350: Determine the self-discharge rate of the target battery cell based on the first SOC value, the second SOC value, the first time, and the second time.

[0074] Exemplarily, the first cell voltage is the target cell voltage value recorded when the target vehicle or battery management system (BMS) enters a dormant state. The first cell voltage can be measured by a voltage acquisition module of the BMS. The first time is the time point corresponding to recording the first cell voltage, which can be marked as the first time (t 1 ).

[0075] The second cell voltage is the cell voltage value of the target cell measured again after the battery management system wakes up from sleep mode. The second cell voltage reflects the voltage drop caused by self-discharge of the cell during sleep. The second time is the time point corresponding to the recording of the second cell voltage, which can be marked as the second time (t 2 ).

[0076] The SOC and voltage correspondence includes a mapping curve or a mapping table of the power battery's single cell voltage and SOC. The SOC mapping curve or mapping table is obtained by the battery manufacturer or experimental testing, and is usually stored in the battery characteristic database of the BMS.

[0077] According to the first cell voltage, by looking up the corresponding relationship between the SOC value and the voltage, the first SOC value at the first moment is obtained, which is marked as SOC 1 .

[0078] Similarly, according to the second cell voltage, by looking up the corresponding relationship between the SOC value and the voltage, the SOC value at the second moment is obtained and marked as SOC 2 .

[0079] By combining the nonlinear relationship between SOC and voltage, the SOC value can be calculated more accurately, improving the accuracy of self-discharge rate calculation. After each BMS wakeup, the self-discharge rate of the battery cell is updated in real time, which helps to identify potential anomalies. Using data during vehicle sleep and BMS sleep, continuous high-frequency measurement of the battery cell is avoided, thereby reducing energy consumption.

[0080] In a feasible implementation, it also includes:

[0081] S410, obtaining the number of abnormal cells with abnormal self-discharge rates;

[0082] S420, when the number of the abnormal cells is less than or equal to the preset number, determining the modified wake-up period based on the larger value of the self-discharge rate of the abnormal cells;

[0083] S430: When the number of the abnormal cells is greater than the preset number, determine the modified wake-up period based on the self-discharge rates of all the abnormal cells.

[0084] For example, an abnormal cell refers to a cell whose self-discharge rate exceeds a set threshold (e.g., 2% / hour). In each monitoring, the number of cells in the battery pack that meet the abnormal condition is counted and can be marked as N. 异常

[0085] For example, suppose the battery pack contains 10 cells, of which the self-discharge rates of 3 cells are 2.5%, 3.0%, and 3.2%, respectively, exceeding the threshold. Then the number of abnormal cells N 异常 =3.

[0086] The preset number is a threshold used to distinguish between a minor abnormality and a serious abnormality of the number of abnormal cells, marked as N. 预设 .

[0087] If N 异常 ≤N 预设 , it is considered that the number of abnormal cells is small, and the wake-up cycle can be adjusted based on individual abnormal cells.

[0088] As N 异常 >N 预设 , it is considered that the number of abnormal cells is large, and the wake-up cycle can be adjusted by comprehensively considering all abnormal cells.

[0089] The method proposed in this embodiment can distinguish between minor and serious abnormalities according to the number of abnormal cells, and adopt different processing strategies to balance monitoring accuracy and energy consumption. When there are a small number of abnormal cells, focus on the single most serious cell, and when there are more abnormal cells, consider the overall situation to optimize monitoring efficiency. Dynamically adjust the wake-up cycle to avoid too frequent monitoring operations and reduce energy consumption.

[0090] In a feasible implementation manner, the above step S420 specifically includes:

[0091] S4201, determining an abnormality degree interval according to the above-mentioned larger value of the self-discharge rate;

[0092] S4202, determining a wake-up period corresponding to the abnormality level interval according to the abnormality level interval;

[0093] S4203: Determine the wake-up period corresponding to the above abnormality level interval as the modified wake-up period.

[0094] For example, the abnormality degree interval is determined according to the larger value of the self-discharge rate, and the maximum value of the self-discharge rate of the abnormal battery cell (marked as η max ) is the core parameter for judging the degree of abnormality, and this value reflects the discharge rate of the most seriously abnormal battery cell.

[0095] According to battery design and safety specifications, the self-discharge rate is divided into several abnormal degree intervals, such as:

[0096] η<η s0 It is within the normal range, with no obvious abnormality. s0 ≤η<η s1 It is a mild abnormality. s1 ≤η<η s2 Moderate abnormality. s2 This is a severe abnormality and requires emergency treatment.

[0097] Assume that the threshold is defined as: η s0 =2%,η s1 =5%,η s2＝ 10%.

[0098] If the maximum self-discharge rate is 6% / hour, then η max =6% belongs to the moderate abnormal range.

[0099] Set the corresponding wake-up period T for each interval 1 , T 2 , T 3 , ensure that the monitoring frequency matches the degree of abnormality:

[0100] Normal range sets a longer wake-up cycle (such as T1 = 4 hours). Mild abnormality shortens the wake-up cycle (such as T2 = 2 hours). Moderate abnormality further shortens the wake-up cycle (such as T3 = 1 hour). Severe abnormality BMS continues to work and no longer enters sleep state.

[0101] The corresponding wake-up period is directly used as the modified value according to the abnormality degree interval to ensure that the system adopts the period in the next monitoring operation.

[0102] If the system determines that it is a severe abnormality (ηmax≥η s2 ), the following emergency measures can be initiated: The MS remains awake and monitors the battery status in real time. Sends alarm information to the cloud big data platform. Notification mechanism: Notify after-sales service personnel and car owners to carry out emergency repairs or further testing.

[0103] The method proposed in the embodiment of the present application adjusts the monitoring frequency based on different abnormality levels to avoid overly frequent or insufficient wake-up operations. In severe abnormal situations, the continuous monitoring mode is quickly entered to prevent the expansion of potential risks. In mild abnormalities and normal states, the wake-up cycle is extended to reduce unnecessary energy consumption. Through this solution, accurate identification and classification of abnormal states of battery cells can be achieved to ensure safe and stable operation of the battery system, while improving operation and maintenance efficiency.

[0104] In a feasible implementation manner, the above step S430 specifically includes:

[0105] S4301, obtaining the relative position information of each abnormal battery cell in the target power battery;

[0106] S4302, determining the position weight information of each abnormal battery cell according to the relative position information of each abnormal battery cell;

[0107] S4303, determining an abnormality coefficient according to the self-discharge rates of all the abnormal cells and the corresponding position weight information of the abnormal cells;

[0108] S4304. Determine the modified wake-up period according to the abnormal coefficient.

[0109] Exemplarily, a power battery is composed of a plurality of battery cells, and the relative position information of the battery cells refers to their arrangement positions in the battery pack, such as the module number, series / parallel sequence or physical position (such as center battery cell, edge battery cell) of the battery cells.

[0110] The relative position information can be determined by recording the position number of the abnormal cell in the BMS. The position information is usually provided by the cell monitoring unit of the hardware circuit, and the data includes the cell serial number or the physical position within the module.

[0111] Assume that the power battery pack consists of 10 cells: Abnormal cell 1: position number is 3. Abnormal cell 2: position number is 7. Abnormal cell 3: position number is 10.

[0112] Cells in different locations may have different effects on the power battery pack. For example, edge cells may be more prone to abnormalities due to poor heat dissipation, so they have a higher weight. Locations where high current flows through cells with large loads may be given priority and have a higher weight. Center cells generally have better heat dissipation or lower loads, so they may have a lower weight.

[0113] Position weight w i It is a value associated with the relative position information of each battery cell. The specific allocation rule can be determined according to factors such as heat dissipation characteristics, module design, current distribution, etc. For example, suppose the weight allocation rule is: the weight of the battery cell at the center is w = 1.0. The weight of the battery cell at the edge is w = 1.5.

[0114] The weights of abnormal cells are as follows:

[0115] Abnormal cell 1 (position 3, central cell): weight w3 = 1.0.

[0116] Abnormal cell 2 (position 7, middle position): weight w7=1.2.

[0117] Abnormal cell 3 (position 10, edge cell): weight w10=1.5.

[0118] Abnormal coefficient (C 异常 ) is the self-discharge rate η of all abnormal cells i and its position weight w i The calculation result is used to quantify the overall degree of abnormality.

[0119]

[0120] N 异常：异常电芯数量。

[0121] η i is the self-discharge rate of the ith abnormal cell. i is the position weight of the i-th abnormal cell.

[0122] Assume that the self-discharge rate of abnormal cells is as follows: Abnormal cell 1: η 3 =2.5%. Abnormal cell 2: η 7 =3.0%. Abnormal cell 3: η 10 =3.5%.

[0123] The position weight is: w 3 =1.0,w 7 =1.2,w 10 =1.5.

[0124] Calculate the anomaly coefficient:

[0125] C 异常 =(2.5×1.0)+(3.0×1.2)+(3.5×1.5)

[0126] C 异常 =2.5+3.6+5.25=11.35

[0127] According to the design requirements of the power battery, set the corresponding wake-up cycle for different ranges of abnormal coefficients. For example:

[0128] C 异常 <5: Wake-up period T = 4 hours (normal).

[0129] 5≤C 异常<10: wake-up period T = 2 hours (mild abnormality).

[0130] 10≤C 异常 <15: wake-up period T = 1 hour (moderate abnormality).

[0131] C 异常 ≥15: BMS continues to work (severe abnormality).

[0132] The embodiment of the present application introduces position weights to focus on cells that have a greater impact on battery performance, thereby improving monitoring effects. Dynamically adjust the wake-up cycle to avoid excessive or insufficient monitoring operations. Extend the wake-up cycle in normal or slightly abnormal situations to reduce energy consumption.

[0133] In a feasible implementation, it also includes:

[0134] When the self-discharge rate of any of the above-mentioned battery cells exceeds the warning threshold, the battery management system is continuously awakened to continuously monitor the above-mentioned power battery;

[0135] The current status information of the power battery is sent to the management terminal and the customer mobile terminal.

[0136] Exemplarily, the warning threshold is a self-discharge rate critical value used to identify the severity of the abnormality. 预警 = 10%. When the self-discharge rate of any battery cell exceeds this threshold, it indicates that the battery cell may have serious problems, such as internal short circuit, excessive aging or extreme environmental impact.

[0137] The self-discharge rate η of any battery cell is detected i >η 预警 , the BMS switches from sleep mode to continuous working mode, collecting power battery status data at a high frequency, such as the voltage, SOC, temperature, etc. of each battery cell. Continuous wake-up can ensure real-time monitoring of the power battery under abnormal conditions to avoid further expansion of potential risks.

[0138] The current status information of the power battery includes but is not limited to the number of abnormal cells, self-discharge rate, voltage, SOC, temperature, total voltage of the battery pack, total SOC, temperature distribution, and severity analysis of abnormal cells (such as mild, moderate, and severe abnormalities). It can also include suggestions for managers and customers, such as "repair as soon as possible" or "stop using".

[0139] The manager is usually an after-sales service team or a battery operation management platform. The BMS collects and packages the current data, which is uploaded to the cloud through the vehicle communication module (such as 4G / 5G), and the cloud platform pushes the status information to the manager's terminal.

[0140] The manager terminal may be a monitoring system or a professional application that displays detailed battery status data and abnormality reports.

[0141] The customer is usually the owner or user of the vehicle. The data collected by the BMS is processed by the cloud platform and sent to the customer's mobile terminal (such as a mobile phone app). The message content can be presented in a simple and easy-to-understand way, focusing on risks and necessary actions. The display format can include prompt notifications and status information. Prompt notifications include "Battery abnormality, please go to the service center for inspection as soon as possible." Status information includes "Battery cell 3 is abnormal, the discharge rate exceeds the standard, and the battery health risk is high."

[0142] The method proposed in the embodiment of the present application enables the BMS to monitor the battery status in real time to avoid the spread of risks after the abnormal battery cell exceeds the warning threshold. The status information is sent to the management personnel and the customer terminal synchronously to ensure that all parties are informed. Continuous monitoring and timely notification can minimize the risk of safety accidents caused by abnormal battery cells. Customers can quickly understand the battery status of the vehicle through the mobile terminal and take necessary measures.

[0143] In summary, in the related art, during the vehicle's dormancy period, the big data background cannot obtain the vehicle status, and the BMS is also in low power consumption mode, and it is impossible to collect and monitor battery data in real time. Power battery abnormalities (such as excessive self-discharge of battery cells, battery cell imbalance, etc.) may occur during dormancy and cannot be perceived in time, resulting in safety hazards. This application dynamically determines whether the BMS needs to be woken up by monitoring the duration of vehicle dormancy, thereby realizing intermittent monitoring of the battery status in the dormant state. After waking up, the BMS collects SOC data for each battery cell in the battery pack one by one to ensure a comprehensive understanding of the battery status and avoid monitoring blind spots. In dormancy mode, the monitoring frequency can be dynamically adjusted to ensure timely capture of abnormal states of the power battery (such as abnormal SOC fluctuations). In the related art, if a fixed cycle or continuous wake-up monitoring method is adopted, although the battery abnormality can be detected in time, a large amount of power will be consumed, resulting in increased energy consumption of the power battery, especially when parked for a long time, which may cause over-discharge of the battery. This application designs a dynamic wake-up strategy based on the comparison of "sleep duration" and "wake-up cycle", which triggers the wake-up operation only when the sleep duration is greater than the preset wake-up cycle. When the sleep time is short or the battery status is normal, keep the BMS in sleep mode to avoid unnecessary energy consumption. The wake-up cycle can be dynamically adjusted according to the self-discharge rate or other parameters of the battery to balance monitoring needs and energy-saving goals. It can significantly reduce the battery energy consumption during vehicle sleep, extend the maintenance time of the remaining battery power, and improve the battery safety in long-term parking scenarios. In the related art, the BMS cannot collect the status of the single cells in the battery pack after sleep, which may cause the abnormalities of some cells (such as SOC imbalance or voltage abnormality) not to be discovered in time. These abnormalities may accumulate and eventually cause serious damage to the entire power battery pack. After waking up the BMS by the method adopted in this application, the SOC data of all cells in the power battery pack are collected one by one to ensure that the status of each cell is fully monitored. Through SOC data analysis, the abnormality of the single cell (such as excessive self-discharge or SOC significantly lower than other cells) can be discovered in time, and corresponding measures can be taken to avoid the impact of the abnormality of a single cell on the performance and safety of the entire battery pack, and realize refined cell status monitoring. In the related technology, when parked for a long time, battery abnormalities (such as internal short circuit, excessive self-discharge, etc.) may cause serious accidents such as thermal runaway, capacity loss, and even fire. Existing monitoring solutions cannot achieve continuous monitoring in the dormant state, posing a potential threat to user and vehicle safety. This method can respond quickly when abnormal battery conditions (such as a significant drop in SOC or an abnormally high self-discharge rate) occur through intelligent wake-up and high-frequency data acquisition. Once an abnormality is detected, the battery status information can be sent to the big data background and user terminal through the real-time communication module to ensure that managers and car owners are aware of the risks in a timely manner and take countermeasures. Significantly improve the reliability of battery monitoring and vehicle safety, and reduce the risk of accidents caused by battery abnormalities.

[0144] like Figure 2 As shown, the present application proposes a power battery status monitoring device, comprising:

[0145] A battery status monitoring unit 21 is used to perform at least one battery status monitoring operation on the target vehicle if it is detected that the target vehicle enters a dormant state;

[0146] The battery status monitoring unit 21 includes a first acquisition component 210 and a second acquisition component 220;

[0147] The first acquisition component 210 is used to acquire the sleep duration of the battery management system of the target vehicle, and wake up the battery management system when the sleep duration is greater than the wake-up cycle corresponding to the current battery status monitoring operation;

[0148] The second acquisition component 220 is used to acquire the state of charge of each cell of the power battery through the battery management system.

[0149] The above power battery status monitoring device can also perform the following steps:

[0150] In a feasible implementation manner, the wake-up period corresponding to the first battery status monitoring operation is a preset period, and further includes:

[0151] Determining a self-discharge rate of each battery cell based on the state of charge of each battery cell;

[0152] In the case that the self-discharge rate of any of the battery cells is abnormal, the wake-up period is updated according to the abnormal self-discharge rate of the battery cell, and the updated wake-up period is used as the wake-up period corresponding to the next battery status monitoring operation.

[0153] In a feasible implementation manner, the specific steps of obtaining the self-discharge rate of the battery cell include:

[0154] Acquire a first cell voltage of a target battery cell when the target vehicle is dormant or after the battery management system is dormant and a first time corresponding to the first cell voltage;

[0155] Acquire a second cell voltage of the target battery cell after the battery management system wakes up and a second time corresponding to the second cell voltage;

[0156] According to the first cell voltage and the corresponding relationship between the SOC value and the voltage, a first SOC value is obtained;

[0157] Obtaining a second SOC value according to the second cell voltage and the corresponding relationship between the SOC value and the voltage;

[0158] The self-discharge rate of the target battery cell is determined based on the first SOC value, the second SOC value, the first time, and the second time.

[0159] In a feasible implementation, it also includes:

[0160] Obtain the number of abnormal cells with abnormal self-discharge rate;

[0161] In the case where the number of the abnormal cells is less than or equal to the preset number, determining the modified wake-up period based on the larger value of the self-discharge rate of the abnormal cells;

[0162] When the number of the abnormal cells is greater than the preset number, the modified wake-up period is determined based on the self-discharge rates of all the abnormal cells.

[0163] In a feasible implementation manner, the above-mentioned determination of the modified wake-up period based on the larger value of the self-discharge rate of the abnormal battery cell includes:

[0164] According to the larger value of the self-discharge rate, the abnormal degree interval is determined;

[0165] Determine the wake-up period corresponding to the above abnormality level interval according to the above abnormality level interval;

[0166] The wake-up period corresponding to the above abnormality level interval is determined as the modified wake-up period.

[0167] In a feasible implementation manner, the above-mentioned determination of the modified wake-up period based on the self-discharge rate of all abnormal battery cells includes:

[0168] Obtaining relative position information of each abnormal battery cell in the target power battery;

[0169] Determine the position weight information of each abnormal battery cell according to the relative position information of each abnormal battery cell;

[0170] Determine an abnormality coefficient according to the self-discharge rates of all the abnormal cells and the corresponding position weight information of the abnormal cells;

[0171] The modified wake-up period is determined according to the abnormal coefficient.

[0172] In a feasible implementation, it also includes:

[0173] When the self-discharge rate of any of the above-mentioned battery cells exceeds the warning threshold, the battery management system is continuously awakened to continuously monitor the above-mentioned power battery;

[0174] The current status information of the power battery is sent to the management terminal and the customer mobile terminal.

[0175] In summary, in the related art, during the vehicle's dormancy period, the big data background cannot obtain the vehicle status, and the BMS is also in low power consumption mode, and it is impossible to collect and monitor battery data in real time. Power battery abnormalities (such as excessive self-discharge of battery cells, battery cell imbalance, etc.) may occur during dormancy and cannot be perceived in time, resulting in safety hazards. This application dynamically determines whether the BMS needs to be woken up by monitoring the duration of vehicle dormancy, thereby realizing intermittent monitoring of the battery status in the dormant state. After waking up, the BMS collects SOC data for each battery cell in the battery pack one by one to ensure a comprehensive understanding of the battery status and avoid monitoring blind spots. In dormancy mode, the monitoring frequency can be dynamically adjusted to ensure timely capture of abnormal states of the power battery (such as abnormal SOC fluctuations). In the related art, if a fixed cycle or continuous wake-up monitoring method is adopted, although the battery abnormality can be detected in time, a large amount of power will be consumed, resulting in increased energy consumption of the power battery, especially when parked for a long time, which may cause over-discharge of the battery. This application designs a dynamic wake-up strategy based on the comparison of "sleep duration" and "wake-up cycle", which triggers the wake-up operation only when the sleep duration is greater than the preset wake-up cycle. When the sleep time is short or the battery status is normal, keep the BMS in sleep mode to avoid unnecessary energy consumption. The wake-up cycle can be dynamically adjusted according to the self-discharge rate or other parameters of the battery to balance monitoring needs and energy-saving goals. It can significantly reduce the battery energy consumption during vehicle sleep, extend the maintenance time of the remaining battery power, and improve the battery safety in long-term parking scenarios. In the related art, the BMS cannot collect the status of the single cells in the battery pack after sleep, which may cause the abnormalities of some cells (such as SOC imbalance or voltage abnormality) not to be discovered in time. These abnormalities may accumulate and eventually cause serious damage to the entire power battery pack. After the device used in this application wakes up the BMS, it collects the SOC data of all cells in the power battery pack one by one to ensure that the status of each cell is fully monitored. Through SOC data analysis, it is possible to detect the abnormality of the single cell in time (such as excessive self-discharge or SOC significantly lower than other cells), and take corresponding measures to avoid the impact of the abnormality of a single cell on the performance and safety of the entire battery pack, and realize refined cell status monitoring. In related technologies, when parked for a long time, battery abnormalities (such as internal short circuit, excessive self-discharge, etc.) may cause serious accidents such as thermal runaway, capacity loss, and even fire. Existing monitoring solutions cannot achieve continuous monitoring in the dormant state, posing a potential threat to user and vehicle safety. Through intelligent wake-up and high-frequency data acquisition, this device can respond quickly when abnormal battery conditions (such as a significant drop in SOC or an abnormally high self-discharge rate) occur. Once an abnormality is detected, the battery status information can be sent to the big data background and user terminal through the real-time communication module to ensure that managers and car owners are aware of the risks in a timely manner and take countermeasures. Significantly improve the reliability of battery monitoring and vehicle safety, and reduce the risk of accidents caused by battery abnormalities.

[0176] like Figure 3 As shown, an embodiment of the present application also provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor, and when the processor 320 executes the computer program 311, the steps of any of the above-mentioned methods for monitoring the status of the power battery are implemented.

[0177] Since the electronic device introduced in this embodiment is a device used to implement a power battery status monitoring device in the embodiment of the present application, based on the method introduced in the embodiment of the present application, the technical personnel in this field can understand the specific implementation mode of the electronic device of the present embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present application is not introduced in detail here. As long as the equipment used by the technical personnel in this field to implement the method in the embodiment of the present application is within the scope of protection of this application.

[0178] During the specific implementation process, when the computer program 311 is executed by a processor, any implementation method in the embodiments corresponding to the first aspect can be implemented.

[0179] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0180] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0181] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0182] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0183] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0184] An embodiment of the present application further provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device executes the process of power battery status monitoring in the corresponding embodiment.

[0185] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or a data center that includes one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)), etc.

[0186] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0187] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0188] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0189] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0190] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially 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, and the computer software product is stored in a storage medium, including a number of instructions to enable 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 storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0191] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. 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 make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for monitoring the state of a power battery, characterized in that: include: If it is detected that the target vehicle enters a dormant state, performing at least one battery status monitoring operation on the target vehicle; Among them, the battery status monitoring operation includes: Acquire the sleep duration of the battery management system of the target vehicle, and wake up the battery management system when the sleep duration is greater than the wake-up cycle corresponding to the current battery status monitoring operation; The charge state of each cell of the power battery is acquired through the battery management system.

2. The power battery status monitoring method according to claim 1, characterized in that: The wake-up period corresponding to the first battery status monitoring operation is a preset period, and the method further includes: Determining a self-discharge rate of each battery cell based on the state of charge of each battery cell; When the self-discharge rate of any of the battery cells is abnormal, the wake-up period is updated according to the abnormal self-discharge rate of the battery cell, and the updated wake-up period is used as the wake-up period corresponding to the next battery status monitoring operation.

3. The power battery status monitoring method according to claim 2, characterized in that: The specific steps of obtaining the self-discharge rate of the battery cell include: Acquire a first cell voltage of a target battery cell when the target vehicle is dormant or after the battery management system is dormant and a first time corresponding to the first cell voltage; Acquire a second cell voltage of the target battery cell after the battery management system wakes up and a second time corresponding to the second cell voltage; Obtaining a first SOC value according to the first cell voltage and the corresponding relationship between the SOC value and the voltage; Obtaining a second SOC value according to the second cell voltage and the corresponding relationship between the SOC value and the voltage; The self-discharge rate of the target battery cell is determined based on the first SOC value, the second SOC value, the first time, and the second time.

4. The power battery status monitoring method according to claim 2, characterized in that: Also includes: Obtain the number of abnormal cells with abnormal self-discharge rate; When the number of abnormal cells is less than or equal to a preset number, determining the modified wake-up period based on a larger value of the self-discharge rate of the abnormal cells; When the number of the abnormal battery cells is greater than the preset number, the modified wake-up period is determined based on the self-discharge rates of all the abnormal battery cells.

5. The power battery status monitoring method according to claim 4, characterized in that: The determining the modified wake-up period based on the larger value of the self-discharge rate of the abnormal battery cell includes: Determining an abnormality degree interval according to the larger value of the self-discharge rate; Determine a wake-up period corresponding to the abnormality level interval according to the abnormality level interval; The wake-up period corresponding to the abnormality level interval is determined as the modified wake-up period.

6. The power battery status monitoring method according to claim 4, characterized in that: The step of determining the modified wake-up cycle based on the self-discharge rates of all abnormal cells includes: Obtaining relative position information of each abnormal battery cell in the target power battery; Determining position weight information of each abnormal battery cell according to the relative position information of each abnormal battery cell; Determine an abnormality coefficient according to the self-discharge rates of all the abnormal cells and the corresponding position weight information of the abnormal cells; The modified wake-up period is determined according to the abnormal coefficient.

7. The power battery status monitoring method according to any one of claims 3 to 6, characterized in that: Also includes: When the self-discharge rate of any of the battery cells exceeds the warning threshold, the battery management system is continuously awakened to continuously monitor the power battery; The current status information of the power battery is sent to the management terminal and the customer mobile terminal.

8. A power battery status monitoring device, characterized in that: include: A battery status monitoring unit, configured to perform at least one battery status monitoring operation on the target vehicle if it is detected that the target vehicle enters a dormant state; The battery status monitoring unit includes a first acquisition component and a second acquisition component: The first acquisition component is used to acquire the sleep duration of the battery management system of the target vehicle, and wake up the battery management system when the sleep duration is greater than the wake-up cycle corresponding to the current battery status monitoring operation; The second acquisition component is used to acquire the charge state of each cell of the power battery through the battery management system.

9. An electronic device, comprising: A memory and a processor, wherein the processor is used to implement the steps of the power battery status monitoring method as described in any one of claims 1 to 7 when executing a computer program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the power battery status monitoring method according to any one of claims 1 to 7 are implemented.

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