Battery charging abnormality detection method and device

Abstract

The present invention relates to the field of battery detection technology, and discloses a method and device for detecting abnormal battery charging. The method comprises: obtaining outdoor temperature and battery temperature at multiple times; determining the battery temperature rising speed according to the outdoor temperature, battery temperature at multiple times, a preset standard temperature and a target temperature coefficient; detecting whether the battery temperature rising speed is within a preset temperature range; wherein, if the battery temperature rising speed is not within the preset temperature range, it is determined that the battery charging is abnormal.

Description

Technical Field

[0001] The present invention relates to the technical field of battery detection, and in particular to a method and device for detecting abnormal battery charging. Background Art

[0002] The Battery Management System (BMS) is one of the key technologies to ensure efficient, safe and reliable operation of the power system. BMS is responsible for monitoring the status of the battery pack, including key parameters such as battery voltage, current, temperature, etc., optimizing the charging and discharging strategy to improve battery efficiency, extend battery life, and ensure safe operation of the battery under various operating conditions.

[0003] At present, existing BMS systems are usually equipped with temperature sensors and temperature detection modules, which can monitor the temperature changes of the battery in real time and monitor the temperature rise rate during charging to ensure that it does not exceed the preset safety threshold.

[0004] However, relying solely on the response speed and accuracy of the temperature sensor may not meet the needs of high-precision monitoring, resulting in errors in the assessment of the temperature rise rate of the battery.

[0005] Therefore, how to improve the evaluation accuracy of the battery's temperature rise rate becomes a problem that needs to be solved. Summary of the invention

[0006] In view of this, the present invention provides a method and device for detecting abnormal battery charging.

[0007] In a first aspect, the present invention provides a method for detecting abnormal battery charging, the method comprising: obtaining outdoor temperature and battery temperature at multiple times; determining a battery temperature rise rate based on the outdoor temperature, the battery temperature at multiple times, a preset standard temperature and a target temperature coefficient; detecting whether the battery temperature rise rate is within a preset temperature range; wherein, if the battery temperature rise rate is not within the preset temperature range, it is determined that abnormal battery charging has occurred.

[0008] The battery charging abnormality detection method provided in this embodiment can more accurately depict the trend of battery temperature change by combining the battery temperature at multiple moments with the outdoor temperature, thereby calculating a more accurate temperature rise rate. This is more reliable than relying solely on battery temperature data detected by a temperature sensor, and reduces misjudgments caused by instantaneous fluctuations.

[0009] At the same time, when the battery temperature rise rate exceeds the preset temperature range, it can immediately identify potential charging anomalies, such as battery overheating, cooling system failure or improper charging strategy, so as to timely discover and solve the problem and prevent battery damage or safety accidents.

[0010] In one possible implementation, the battery temperature rise rate is determined based on the outdoor temperature, the battery temperature at multiple moments, a preset standard temperature and a target temperature coefficient, including: determining a reference temperature rise rate based on the outdoor temperature, the preset standard temperature and the target temperature coefficient; determining an actual temperature rise rate based on the battery temperature at a current moment and the battery temperature at a moment before the current moment; determining the battery temperature rise rate based on a first difference between the actual temperature rise rate and the parameter temperature rise rate.

[0011] The battery charging abnormality detection method provided in this embodiment can dynamically calculate the reference temperature rise rate of the battery by acquiring the outdoor temperature in real time and combining the battery temperature at two adjacent moments, the preset standard temperature and the target temperature coefficient. This dynamic adjustment method makes the battery temperature control more accurate and can adapt to the needs of different environments and working conditions.

[0012] In addition, by monitoring the battery temperature rise rate in real time and comparing it with the reference temperature rise rate, abnormal battery temperature rise can be detected in time. This helps prevent battery overheating, avoid serious accidents such as thermal runaway, fire or explosion, and improve the safety of the battery system.

[0013] In one possible implementation, the process of determining the target temperature coefficient includes: determining the state of the preset temperature coefficient according to the outdoor temperature and the preset standard temperature; and processing the preset temperature coefficient according to the state of the preset temperature coefficient to determine the target temperature coefficient.

[0014] The battery charging abnormality detection method provided in this embodiment can dynamically adjust the state of the preset temperature coefficient by considering the change of outdoor temperature, thereby realizing flexible adjustment of the target temperature coefficient, so as to better adapt to the requirements under different outdoor temperatures and improve the accuracy and effectiveness of temperature control.

[0015] At the same time, by reasonably setting the preset temperature coefficient and processing it, a more stable target temperature coefficient can be determined. This helps to reduce the temperature fluctuation of the system during actual operation and improve the stability and reliability of the system.

[0016] In one possible implementation, the state of the preset temperature coefficient is determined based on the outdoor temperature and the preset standard temperature, including: determining a second difference between the outdoor temperature and the preset standard temperature; detecting whether the second difference is less than a preset value; if the second difference is less than the preset value, determining that the state of the preset temperature coefficient is a negative state; if the second difference is not less than the preset value, determining that the state of the preset temperature coefficient is a positive state.

[0017] The battery charging abnormality detection method provided in this embodiment can achieve more refined temperature control by calculating the second difference between the outdoor temperature and the preset standard temperature and judging the state of the preset temperature coefficient according to the difference. Thus, the temperature coefficient can be adjusted more accurately according to the requirements under different ambient temperatures, thereby improving the accuracy of temperature control.

[0018] In one possible implementation, the method also includes: if the battery temperature rise rate is not within the preset temperature range, detecting whether the battery temperature rise rate is less than the minimum value of the preset temperature range; if the battery temperature rise rate is less than the minimum value of the preset temperature range, determining a first fault result; if the battery temperature rise rate is not less than the minimum value of the preset temperature range, determining a second fault result.

[0019] The method for detecting abnormal battery charging provided in this embodiment can accurately judge the abnormal battery temperature rise rate by setting a clear preset temperature range and the corresponding fault judgment standard (i.e., the comparison between the battery temperature rise rate and the minimum value of the preset temperature range). This accuracy helps to timely discover potential battery fault problems and avoid further deterioration of the fault. In addition, once the abnormal battery temperature rise rate is detected, the system can quickly take corresponding treatment measures according to the judgment result (the first fault result or the second fault result). This rapid response capability helps to eliminate potential faults in a timely manner and prevent the fault from causing greater damage to the system.

[0020] In a possible implementation, the method further includes: prompting the first fault result or the second fault result through voice or text.

[0021] The battery charging abnormality detection method provided in this embodiment can directly and clearly convey the fault information through voice and text prompts when a fault occurs, avoiding delays caused by poor information transmission or misunderstanding. In addition, the voice and text prompts are not only direct feedback on the fault, but also serve as reminders, enhancing the attention of relevant personnel to system security.

[0022] In a second aspect, the present invention provides a device for detecting abnormal battery charging, the device comprising: an acquisition module for acquiring outdoor temperature and battery temperature at multiple times; a determination module for determining the battery temperature rise rate based on the outdoor temperature, the battery temperature at multiple times, a preset standard temperature and a target temperature coefficient; a first detection module for detecting whether the battery temperature rise rate is within a preset temperature range; wherein, if the battery temperature rise rate is not within the preset temperature range, it is determined that the battery charging is abnormal.

[0023] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the battery charging abnormality detection method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0024] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for detecting abnormal battery charging according to the first aspect or any corresponding embodiment thereof.

[0025] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the method for detecting abnormal battery charging according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 is a schematic diagram of a battery charging abnormality detection system according to an embodiment of the present invention;

[0028] Figure 2 is a flow chart of a method for detecting abnormal battery charging according to an embodiment of the present invention;

[0029] Figure 3 is a structural block diagram of a device for detecting abnormal battery charging according to an embodiment of the present invention;

[0030] Figure 4 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0032] Based on relevant technologies, the Battery Management System (BMS) is one of the key technologies to ensure efficient, safe and reliable operation of the power system. BMS is responsible for monitoring the status of the battery pack, including key parameters such as battery voltage, current, temperature, etc., optimizing the charging and discharging strategy to improve battery efficiency, extend battery life, and ensure safe operation of the battery under various working conditions.

[0033] At present, existing BMS systems are usually equipped with temperature sensors and temperature detection modules, which can monitor the temperature changes of the battery in real time and monitor the temperature rise rate during charging to ensure that it does not exceed the preset safety threshold.

[0034] However, relying solely on the response speed and accuracy of the temperature sensor may not meet the needs of high-precision monitoring, resulting in errors in the assessment of the temperature rise rate of the battery.

[0035] Based on this, the present invention provides a method for detecting battery charging anomalies. By combining the battery temperature at multiple moments with the outdoor temperature, the trend of battery temperature changes can be more accurately depicted, thereby calculating a more accurate temperature rise rate. This is more reliable than relying solely on battery temperature data detected by temperature sensors, and reduces misjudgments caused by instantaneous fluctuations. At the same time, when the battery temperature rise rate exceeds the preset temperature range, the system can immediately identify potential charging anomalies, such as battery overheating, cooling system failure, or improper charging strategy. This sensitive anomaly detection mechanism helps to detect and solve problems in a timely manner, preventing battery damage or safety accidents.

[0036] Please refer to Figure 1 , Figure 1 is a schematic diagram of a battery charging abnormality detection system provided according to an embodiment of the present invention.

[0037] The battery charging abnormality detection system includes: a battery temperature monitoring module, a temperature change analysis unit, a fault diagnosis module, and a charge and discharge control module.

[0038] Among them, the battery temperature monitoring module is used to monitor the battery temperature parameters in real time and collect temperature data of various parts of the battery, including the surface temperature of the battery cell, the internal temperature of the battery pack and the outdoor temperature, etc. It can respond quickly to temperature changes and transmit the detected temperature data to the temperature change analysis unit in real time.

[0039] The temperature change analysis unit is used to obtain and analyze the real-time detected temperature parameters, and comprehensively analyze the outdoor temperature and the battery temperature. Taking the outdoor temperature into consideration, it is comprehensively determined whether the temperature rise rate is normal, and the analysis results are sent to the fault diagnosis module.

[0040] The fault diagnosis module determines the specific faults that exist based on the analysis results of the temperature change analysis unit, issues an alarm in a timely manner, and sends it to the central control system.

[0041] The charge and discharge control module controls the charge and discharge process of the battery according to the instructions issued by the central control system to ensure safe and efficient charge and discharge.

[0042] According to an embodiment of the present invention, an embodiment of a method for detecting abnormal battery charging is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0043] In this embodiment, a method for detecting abnormal battery charging is provided, which can be used in the above-mentioned abnormal battery charging detection system. Figure 2 is a flow chart of a method for detecting abnormal battery charging according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0044] Step S201, obtaining the outdoor temperature and the battery temperature at multiple times.

[0045] The outdoor temperature may be the outdoor temperature when the battery is being charged. The outdoor temperature may be T1 or T2. The battery temperature may be composed of the temperatures of various parts of the battery. The battery temperature may include the surface temperature of the battery cell and the internal temperature of the battery pack.

[0046] The battery temperature at multiple moments may be the battery temperature of the battery during the charging process. Specifically, both the outdoor temperature and the battery temperature may be detected by a battery temperature monitoring module, or may be detected by other modules, which are not specifically limited here.

[0047] As an example, the battery temperature monitoring module may include multiple temperature sensors. Among them, one temperature sensor may intermittently collect the temperature data T of each part of the battery. t , where t=(1, 2, 3...n), t represents different time, and n represents the number of interval time. The outdoor temperature can be collected by another temperature sensor.

[0048] As an example, the battery temperature monitoring module may include multiple temperature sensors. The multiple sensors may intermittently collect temperature data T of various parts of the battery. t , where t=(1, 2, 3...n), t represents different time, and n represents the number of interval time. That is, each sensor detects a part of the battery.

[0049] Step S202 , determining the battery temperature rising speed according to the outdoor temperature, the battery temperatures at multiple times, the preset standard temperature and the target temperature coefficient.

[0050] The preset standard temperature can be set manually according to the battery's use environment, type, performance, etc. The target temperature coefficient can represent the temperature coefficient that is adjusted according to the outdoor temperature and can affect the battery's rising speed.

[0051] After determining the outdoor temperature, the battery temperature at multiple times, the preset standard temperature and the target temperature coefficient, the battery temperature rise rate can be determined by data fitting methods, by thermal models, or by machine learning methods.

[0052] As an example, when using the data fitting method, the battery temperature is recorded at different time points to form time series data, and the battery temperature data is cleaned to remove outliers or noise. The data can also be smoothed to reduce fluctuations. Use mathematical models (such as linear regression, polynomial regression, exponential regression, etc.) to fit the battery temperature time series data. Consider the outdoor temperature as one of the input variables of the model to reflect its impact on the battery temperature. According to the fitted model, calculate the rate of change of the battery temperature over time, that is, the temperature rise rate. The temperature rise rate can be approximated using derivative or difference methods. According to the preset target temperature coefficient, the calculated temperature rise rate is appropriately adjusted. Specifically, it may involve multiplying the temperature rise rate by the target temperature coefficient, or correcting the model according to the target temperature coefficient.

[0053] As an example, when using the thermal model method, a thermal model of the battery is established based on the physical characteristics of the battery and the principle of heat conduction. The thermal model can describe the relationship between the battery temperature and factors such as the outdoor temperature, charging rate, and heat dissipation conditions. The outdoor temperature, the battery temperature at multiple times, the preset standard temperature, and the target temperature coefficient are used as input parameters of the thermal model. Use the thermal model to perform simulation calculations to obtain a curve of the battery temperature changing over time. During the simulation process, the parameters of the thermal model can be adjusted as needed to improve the accuracy of the simulation. According to the simulated battery temperature curve, the temperature rise rate is calculated. This can be achieved by deriving or differentiating the temperature curve.

[0054] As an example, when using a machine learning-based method, a large amount of data such as outdoor temperature, battery temperature, charging rate, heat dissipation conditions, etc. is collected to form a training data set. Preprocess the data, including data cleaning and normalization. Select a suitable machine learning algorithm (such as support vector machine, neural network, random forest, etc.), and use the training data set for model training. During the training process, outdoor temperature, battery temperature, etc. are used as input features, and the temperature rise rate is used as the output target. Use the trained model to make predictions, input new outdoor temperature, battery temperature and other data, and obtain the predicted temperature rise rate. According to the preset target temperature coefficient, make appropriate adjustments to the predicted temperature rise rate.

[0055] Step S203, detecting whether the battery temperature rise rate is within a preset temperature range; if the battery temperature rise rate is not within the preset temperature range, it is determined that the battery charging is abnormal.

[0056] The preset temperature range can indicate that the battery temperature rise rate is within a normal temperature range. The preset temperature range can be set according to the characteristics of the battery, etc., and is not specifically limited here, and can be implemented by those skilled in the art.

[0057] After determining the battery temperature rise rate, it is necessary to detect whether the battery temperature rise rate is within a preset temperature range. If the battery temperature rise rate is not within the preset temperature range, it is determined that the battery charging is abnormal. That is, if the battery temperature rise rate is less than the minimum value of the preset temperature range or greater than the maximum value of the preset temperature range, it is determined that the battery charging is abnormal.

[0058] The battery charging anomaly detection method provided in this embodiment can more accurately depict the trend of battery temperature changes by combining the battery temperature at multiple moments with the outdoor temperature, thereby calculating a more accurate temperature rise rate. This is more reliable than relying solely on battery temperature data detected by temperature sensors, and reduces misjudgments caused by instantaneous fluctuations. At the same time, when the battery temperature rise rate exceeds the preset temperature range, potential charging anomalies can be immediately identified, such as battery overheating, cooling system failure, or improper charging strategy, so as to promptly discover and solve problems and prevent battery damage or safety accidents.

[0059] In a possible implementation, the above step S202 includes:

[0060] Step a1, determining a reference temperature rising speed according to the outdoor temperature, a preset standard temperature and a target temperature coefficient.

[0061] The reference temperature rising speed can characterize the error speed caused by the influence of the outdoor temperature. Specifically, the reference temperature rising speed can be determined according to the outdoor temperature, the preset standard temperature and the target temperature coefficient by a thermal model method, a machine learning method, etc. This is not specifically limited here and can be implemented by those skilled in the art.

[0062] Step a2, determining the actual temperature rising speed according to the battery temperature at the current moment and the battery temperature at the moment before the current moment.

[0063] The actual temperature rise rate can represent the ideal temperature rise rate of the battery during the charging process. During the battery charging process, the temperature difference between adjacent moments can indicate the temperature rise rate in this time period. Then, for each time period, it is determined whether the temperature rise rate in this time period is abnormal.

[0064] Step a3, determining the battery temperature rising rate according to a first difference between the actual temperature rising rate and the parameter temperature rising rate.

[0065] After the actual temperature rising speed and the parameter temperature rising speed are determined, the battery temperature rising speed may be determined according to a first difference between the actual temperature rising speed and the parameter temperature rising speed.

[0066] From the above, it can be seen that the reference temperature rise rate can characterize the error rate caused by the influence of outdoor temperature; the actual temperature rise rate can characterize the ideal rise rate of the battery during the charging process; then through the first difference between the actual temperature rise rate and the parameter temperature rise rate, the battery temperature rise rate in the time period between the battery temperature at the current moment and the moment before the current moment can be obtained.

[0067] As an example, according to the outdoor temperature, the battery temperature at multiple times, the preset standard temperature and the target temperature coefficient, the process of determining the battery temperature rise rate may be:

[0068] S1. Use temperature sensors to collect the temperature data T of each part of the battery at intervals t , where t = (1, 2, 3...n), t represents different time, n represents the number of interval time, and the interval time is set to △t; at the same time, another temperature sensor is used to collect the outdoor temperature as Toutdoor;

[0069] The specific method for the temperature change analysis unit to determine the temperature rise rate is as follows:

[0070] P1. Set the actual battery temperature rise rate to Vactual, that is

[0071] P2. Set the battery temperature rise rate during charging to K, the target temperature coefficient to q, and set the preset standard temperature to Tstandard.

[0072] The steps for determining the battery temperature rise rate K can be determined by the following formula:

[0073] K=V 实际 -(T 室外 -T 标准 )*q.

[0074] Substituting the formula of actual battery temperature rise rate Vactual into the above formula, we get the following formula:

[0075]

[0076] The battery charging abnormality detection method provided in this embodiment can dynamically calculate the reference temperature rise rate of the battery by acquiring the outdoor temperature in real time and combining the battery temperature at two adjacent moments, the preset standard temperature and the target temperature coefficient. This dynamic adjustment method makes the battery temperature control more accurate and can adapt to the needs of different environments and working conditions.

[0077] In addition, by monitoring the battery temperature rise rate in real time and comparing it with the reference temperature rise rate, abnormal battery temperature rise can be detected in time. This helps prevent battery overheating, avoid serious accidents such as thermal runaway, fire or explosion, and improve the safety of the battery system.

[0078] In a possible implementation, the process of determining the target temperature coefficient includes:

[0079] Step b1, determining the state of the preset temperature coefficient according to the outdoor temperature and the preset standard temperature.

[0080] Specifically, the above step b1 includes:

[0081] Step b11, determining a second difference between the outdoor temperature and a preset standard temperature.

[0082] Step b12, detecting whether the second difference is smaller than a preset value.

[0083] Step b13: if the second difference is less than the preset value, determine that the state of the preset temperature coefficient is a negative state.

[0084] Step b14: if the second difference is not less than the preset value, determine that the state of the preset temperature coefficient is a positive state.

[0085] The current outdoor temperature can be compared with the preset standard temperature, and the current state of the preset temperature coefficient can be determined based on the comparison result. For example, if the outdoor temperature is higher than the preset standard temperature, the preset temperature coefficient may be in a "high temperature state"; if the outdoor temperature is lower than the standard temperature, it may be in a "low temperature state"; if the two are similar, it may be in a "normal state". That is, if the outdoor temperature is higher than the preset standard temperature, the state of the preset temperature coefficient is determined to be a negative state. If the outdoor temperature is lower than the standard temperature, the state of the preset temperature coefficient is determined to be a positive state.

[0086] Step b2, processing the preset temperature coefficient according to the state of the preset temperature coefficient to determine the target temperature coefficient.

[0087] Depending on the state of the preset temperature coefficient, different processing logic is applied. If the preset temperature coefficient is in a "high temperature state", the target temperature coefficient may be changed to a positive value. If the preset temperature coefficient is in a "low temperature state", the target temperature coefficient may be changed to a negative value to maintain the normal operating temperature range of the battery. If the preset temperature coefficient is in a "normal state", the target temperature coefficient may remain unchanged.

[0088] As an example, when the outdoor temperature is higher than the preset standard temperature, the target temperature coefficient is a positive number. At this time, as the outdoor temperature rises, the battery temperature rise rate will accelerate; when the outdoor temperature is lower than the preset standard temperature, the target temperature coefficient is a negative number. At this time, as the outdoor temperature decreases, the battery temperature rise rate may slow down.

[0089] The battery charging abnormality detection method provided in this embodiment can dynamically adjust the state of the preset temperature coefficient by considering the change of outdoor temperature, thereby realizing flexible adjustment of the target temperature coefficient, so as to better adapt to the requirements under different outdoor temperatures and improve the accuracy and effectiveness of temperature control.

[0090] At the same time, by reasonably setting the preset temperature coefficient and processing it, a more stable target temperature coefficient can be determined. This helps to reduce the temperature fluctuation of the system during actual operation and improve the stability and reliability of the system.

[0091] In addition, by calculating the second difference between the outdoor temperature and the preset standard temperature, and judging the state of the preset temperature coefficient according to the size of the difference, more refined temperature control can be achieved, so that the temperature coefficient can be adjusted more accurately according to the requirements under different ambient temperatures, thereby improving the accuracy of temperature control.

[0092] In a possible implementation, the method further includes:

[0093] Step c1: if the battery temperature rise rate is not within the preset temperature range, detecting whether the battery temperature rise rate is less than a minimum value of the preset temperature range.

[0094] If the battery temperature rise rate is not within the preset temperature range, it is determined that the battery charging is abnormal, and it is necessary to detect whether the battery temperature rise rate is less than the minimum value of the preset temperature range.

[0095] Step c2: if the battery temperature rise rate is less than the minimum value of the preset temperature range, determine the first fault result.

[0096] The battery temperature rise rate is lower than the minimum value of the preset temperature range, and the first fault result may be determined as a problem of low charging efficiency or even no charging.

[0097] Step c3: if the battery temperature rising speed is not less than the minimum value of the preset temperature range, determine the second fault result.

[0098] If the battery temperature rise rate is not less than the minimum value of the preset temperature range, and the battery temperature rise rate is not within the preset temperature range, that is, the battery temperature rise rate is greater than the maximum value of the preset temperature range, then the second fault result may be problems such as excessive output voltage, excessive current, poor charging and heat dissipation, and line aging.

[0099] As an example, when the fault diagnosis module determines a specific fault, the battery temperature rise rate is K, and the preset temperature range can be (K1, K2). When K<K1, it means that the battery temperature rises too slowly, which means that there may be problems with low charging efficiency or even no charging. An alarm is issued in time to notify the charging abnormality, that is, a voice prompt of "the charging interface may be bad" is played through voice, prompting the owner to check the charging interface; when K>K2, it means that the battery temperature rises too fast, which means that the output voltage is too high, the current is too large, the charging heat dissipation is poor, the line is aging, and other problems may occur. A danger alarm is sent in time and sent to the central control system at the same time. After receiving the alarm signal, the central control system sends a command to the charge and discharge control module. The charge and discharge control module controls the charging controller to cut off the power, that is, cut the charging circuit, and issue an alarm.

[0100] The method for detecting abnormal battery charging provided in this embodiment can accurately judge the abnormal battery temperature rise rate by setting a clear preset temperature range and the corresponding fault judgment standard (i.e., the comparison between the battery temperature rise rate and the minimum value of the preset temperature range). This accuracy helps to timely discover potential battery fault problems and avoid further deterioration of the fault. In addition, once the abnormal battery temperature rise rate is detected, the system can quickly take corresponding treatment measures according to the judgment result (the first fault result or the second fault result). This rapid response capability helps to eliminate potential faults in a timely manner and prevent the fault from causing greater damage to the system.

[0101] In a possible implementation, the method further includes: prompting the first fault result or the second fault result via voice or text.

[0102] As can be seen from the above content, when K<K1, it means that the battery temperature rises too slowly, which means that there may be problems with low charging efficiency or even failure to charge. You can use voice "Warning, battery charging is abnormal. The current charging efficiency is low and may not be charged normally. Please check the charging device connection and battery status immediately." You can also use text "

Battery charging abnormality warning

[0103] In a possible implementation, when prompting via text, the alarm level of the first fault result or the second fault result is determined, and then the alarm level is sent to the user's terminal.

[0104] The battery charging abnormality detection method provided in this embodiment can directly and clearly convey the fault information through voice and text prompts when a fault occurs, avoiding delays caused by poor information transmission or misunderstanding. In addition, the voice and text prompts are not only direct feedback on the fault, but also serve as reminders, enhancing the attention of relevant personnel to system security.

[0105] In this embodiment, a device for detecting abnormal battery charging is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0106] This embodiment provides a device for detecting abnormal battery charging. Figure 3As shown, it includes: an acquisition module 301, used to obtain the outdoor temperature and the battery temperature at multiple times; a determination module 302, used to determine the battery temperature rising speed according to the outdoor temperature, the battery temperature at multiple times, the preset standard temperature and the target temperature coefficient; a first detection module 303, used to detect whether the battery temperature rising speed is within the preset temperature range; wherein, if the battery temperature rising speed is not within the preset temperature range, it is determined that the battery charging is abnormal.

[0107] In one possible implementation, the determination module 302 includes: a first determination unit, used to determine a reference temperature rise rate based on the outdoor temperature, a preset standard temperature and a target temperature coefficient; a second determination unit, used to determine the actual temperature rise rate based on the battery temperature at the current moment and the battery temperature at the previous moment; and a third determination unit, used to determine the battery temperature rise rate based on a first difference between the actual temperature rise rate and the parameter temperature rise rate.

[0108] In one possible implementation, the device further includes: a state determination module, used to determine the state of a preset temperature coefficient according to the outdoor temperature and a preset standard temperature; and a coefficient determination module, used to process the preset temperature coefficient according to the state of the preset temperature coefficient to determine the target temperature coefficient.

[0109] In one possible implementation, the state determination module includes: a fourth determination unit, used to determine the second difference between the outdoor temperature and the preset standard temperature; a detection unit, used to detect whether the second difference is less than the preset value; a fifth determination unit, used to determine that the state of the preset temperature coefficient is a negative state if the second difference is less than the preset value; and a sixth determination unit, used to determine that the state of the preset temperature coefficient is a positive state if the second difference is not less than the preset value.

[0110] In one possible implementation, the above-mentioned device also includes: a second detection module, which is used to detect whether the battery temperature rise rate is less than the minimum value of the preset temperature range if the battery temperature rise rate is not within the preset temperature range; a first fault result determination module, which is used to determine the first fault result if the battery temperature rise rate is less than the minimum value of the preset temperature range; and a second fault result determination module, which is used to determine the second fault result if the battery temperature rise rate is not less than the minimum value of the preset temperature range.

[0111] In a possible implementation, the device further includes: a prompt module, configured to prompt the first fault result or the second fault result through voice or text.

[0112] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0113] The battery charging abnormality detection device in this embodiment is presented in the form of a functional unit, where the functional unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0114] The embodiment of the present invention also provides a computer device having the above Figure 3 A battery charging abnormality detection device is shown.

[0115] See also Figure 4 , Figure 4 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 4 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 4 A processor 10 is taken as an example.

[0116] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0117] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0118] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0119] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0120] The computer device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means.

[0121] The input device 30 can receive input digital or character information, and generate key signal input related to the user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0122] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0123] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0124] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for detecting abnormal battery charging, characterized in that: The method comprises: Get the outdoor temperature and battery temperature at multiple times; determining a battery temperature rising rate according to the outdoor temperature, battery temperatures at multiple times, a preset standard temperature and a target temperature coefficient; Detecting whether the battery temperature rise rate is within a preset temperature range; wherein, if the battery temperature rise rate is not within the preset temperature range, determining that the battery charging is abnormal.

2. The method for detecting abnormal battery charging according to claim 1, characterized in that: The determining the battery temperature rising speed according to the outdoor temperature, the battery temperature at multiple times, the preset standard temperature and the target temperature coefficient includes: Determine a reference temperature rising speed according to the outdoor temperature, the preset standard temperature and the target temperature coefficient; Determine the actual temperature rise rate according to the battery temperature at the current moment and the battery temperature at the moment before the current moment; The battery temperature rising rate is determined according to a first difference between the actual temperature rising rate and the parameter temperature rising rate.

3. The method for detecting abnormal battery charging according to claim 2, characterized in that: The process of determining the target temperature coefficient includes: Determine a state of a preset temperature coefficient according to the outdoor temperature and the preset standard temperature; According to the state of the preset temperature coefficient, the preset temperature coefficient is processed to determine the target temperature coefficient.

4. The method for detecting abnormal battery charging according to claim 3, characterized in that: The state of determining the preset temperature coefficient according to the outdoor temperature and the preset standard temperature includes: Determining a second difference between the outdoor temperature and the preset standard temperature; Detecting whether the second difference is less than a preset value; If the second difference is less than the preset value, determining that the state of the preset temperature coefficient is a negative state; If the second difference is not less than the preset value, it is determined that the state of the preset temperature coefficient is a positive state.

5. The method for detecting abnormal battery charging according to any one of claims 1 to 4, characterized in that: The method further comprises: If the battery temperature rise rate is not within the preset temperature range, detecting whether the battery temperature rise rate is less than a minimum value of the preset temperature range; If the battery temperature rise rate is less than a minimum value of a preset temperature range, determining a first fault result; If the battery temperature rising speed is not less than a minimum value of a preset temperature range, a second fault result is determined.

6. The method for detecting abnormal battery charging according to claim 5, characterized in that: The method further comprises: The first fault result or the second fault result is prompted by voice or text.

7. A battery charging abnormality detection device, characterized in that: The device comprises: An acquisition module is used to obtain outdoor temperature and battery temperature at multiple times; A determination module, used to determine the battery temperature rise rate according to the outdoor temperature, the battery temperature at multiple times, a preset standard temperature and a target temperature coefficient; The first detection module is used to detect whether the battery temperature rise rate is within a preset temperature range; if the battery temperature rise rate is not within the preset temperature range, it is determined that the battery charging is abnormal.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for detecting abnormal battery charging according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for detecting battery charging abnormality according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the method for detecting abnormal battery charging according to any one of claims 1 to 6.

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