A method, system and electronic device for vehicle charging warning

Abstract

The present application belongs to the field of vehicle charging, and discloses a vehicle charging early warning method, system and electronic equipment. The method comprises the following steps: receiving temperature information and state information uploaded by a vehicle; when a vehicle-mounted charger is in an operating state, outputting a predicted temperature sequence by using a prediction model; determining a real-time temperature sequence based on first temperature information; and when the residual error between the real-time temperature sequence and the predicted temperature sequence continuously increases and exceeds a first threshold value, sending first early warning information. In the present application, the first temperature information contains real-time temperature information of multiple key devices, so that the system can comprehensively master the heat distribution inside the vehicle-mounted charger. When the residual error between the real-time temperature sequence and the predicted temperature sequence continuously increases and exceeds the first threshold value, the first early warning information is sent, so that the system can identify an abnormal temperature rising trend, can send the first early warning information when the temperature has not reached a dangerous level, and early trend abnormal early warning in the charging process is realized.

Description

Technical Field

[0001] This invention relates to the field of vehicle charging, and more specifically, to a method, system, electronic device, and computer-readable storage medium for vehicle charging early warning. Background Technology

[0002] The widespread adoption of electric vehicles has made AC charging one of the most common ways for users to replenish their energy. As the core component of AC charging, the on-board charger generates heat during the conversion of AC to DC power, through its internal power devices and magnetic components. Poor heat dissipation or other malfunctions leading to thermal runaway can easily cause abnormal localized temperatures and rapid temperature rises at the vehicle end, posing a potential risk of malfunction and thermal runaway.

[0003] In related technologies, charging safety monitoring systems typically employ fixed threshold alarm mechanisms, making simple judgments based on data collected by temperature sensors. However, this approach cannot identify gradual temperature rise trends below the safety threshold, resulting in delayed early warning responses and difficulty in timely intervention before thermal runaway occurs.

[0004] Therefore, how to achieve early warning of abnormal trends during the charging process is a technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0005] To address the problem of delayed response to vehicle charging warnings in existing technologies, this invention provides a method, system, electronic device, and computer-readable storage medium for vehicle charging warnings.

[0006] A method for vehicle charging warning, applied to a cloud service platform, the method comprising: Receive temperature and status information uploaded by the vehicle; the temperature information includes first temperature information; the first temperature information is the real-time temperature information of each key component in the vehicle's on-board charger; Based on the status information, determine whether the on-board charger is in operation; If so, the first temperature information and the state information are input into the prediction model to obtain the predicted temperature sequence output by the prediction model; Based on the first temperature information, a real-time temperature sequence is determined. When the residual between the real-time temperature sequence and the predicted temperature sequence continues to increase and exceeds a first threshold, a first warning message is sent. The first warning message is used to indicate an abnormal temperature rise trend.

[0007] Optionally, before receiving the temperature and status information uploaded by the vehicle, the method further includes: Acquire historical charging condition data; the historical charging condition data includes the historical power of the on-board charger and the historical temperature information of each of the key components. Based on the historical charging condition data, the historical power of the on-board charger, the historical temperature rise rate of each key component, and the historical temperature difference between each key component are determined. The historical power, the historical temperature rise rate, and the historical temperature difference are combined to form a historical multidimensional feature set; Using the historical multidimensional feature set as input, a corresponding prediction model is established for the temperature sequence of each key device using a long short-term memory network or a temporal convolutional network.

[0008] Optionally, the step of inputting the first temperature information and the state information into the prediction model to obtain the predicted temperature sequence output by the prediction model includes: For each of the key components, the real-time temperature rise rate of the key component and the real-time temperature difference between the key component and other key components are determined based on the first temperature information. The real-time power of the on-board charger is determined based on the aforementioned status information; The real-time power, the real-time temperature rise rate, and the real-time temperature difference are integrated to form a real-time multidimensional feature set; The predicted temperature sequence of the key device is predicted based on the real-time multidimensional feature set using the prediction model corresponding to the key device.

[0009] Optionally, after determining whether the on-board charger is in operation based on the status information, the method further includes: When the on-board charger is in operation, historical charging condition data is acquired. For each of the key components, the real-time temperature rise rate of each key component and the real-time temperature difference between the key component and other key components are determined based on the first temperature information. The real-time temperature rise rate and the real-time temperature difference are combined to form a temperature rise feature vector, and cluster analysis is performed on the temperature rise feature vector based on historical charging condition data. When the distance between the temperature rise feature vector and the cluster center exceeds the second threshold, a second warning message is sent; the second warning message is used to indicate an abnormal temperature imbalance.

[0010] Optionally, the temperature information may also include second temperature information of the charging socket and third temperature information of the vehicle's high-voltage components; After determining whether the on-board charger is in operation based on the status information, the method further includes: When the on-board charger is not in operation, the first temperature information, the second temperature information and the third temperature information are monitored. If both the first temperature information and the second temperature information are higher than the third threshold, and the third temperature information is within a preset range, then the standby parameters of the on-board charger are obtained. Determine whether the standby parameters are normal; If so, a third warning message is issued; the third warning message is used to indicate that the on-board charger temperature is abnormal. If not, a fourth warning message is issued; the fourth warning message is used to indicate that the on-board charger is in standby abnormality.

[0011] Optionally, after monitoring the first temperature information, the second temperature information, and the third temperature information, the method further includes: If the first temperature information or the second temperature information is higher than the third threshold, and the third temperature information is within a preset range, then a fifth warning message is issued; the fifth warning message is used to indicate that the temperature control status of the on-board charger is abnormal. If a third temperature information is found that is outside the normal range, and the first temperature information and the second temperature information are higher than the third temperature information that is outside the preset range, a sixth warning information is issued; the sixth warning information is used to indicate that the local temperature of the vehicle is abnormal.

[0012] Optionally, the key components include at least one of the following: power factor correction circuit switching transistor, power factor correction circuit inductor, main transformer, dual active bridge converter switching transistor, heat dissipation substrate, and water-cooled channel heat sink.

[0013] A vehicle charging warning system, applied to a cloud service platform, the system comprising: The information receiving module is used to receive temperature information and status information uploaded by the vehicle; the temperature information includes first temperature information; the first temperature information is the real-time temperature information of each key component in the vehicle's on-board charger. A status determination module is used to determine whether the on-board charger is in operation based on the status information. The temperature prediction module is used to input the first temperature information and the status information into the prediction model when the on-board charger is in operation, so as to obtain the predicted temperature sequence output by the prediction model. The first early warning module is used to determine a real-time temperature sequence based on the first temperature information. When the residual between the real-time temperature sequence and the predicted temperature sequence continues to increase and exceeds a first threshold, a first early warning message is sent. The first early warning message is used to indicate an abnormal temperature rise trend.

[0014] An electronic device, comprising: A processor and a memory, the memory being used to store at least one instruction, which, when loaded and executed by the processor, implements the vehicle charging warning method as described in any of the preceding embodiments.

[0015] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a vehicle charging warning method as described in any of the preceding claims.

[0016] The vehicle charging early warning method provided in this invention is applied to a cloud service platform. It receives temperature and status information uploaded by the vehicle; determines whether the on-board charger is in operation based on the status information; if so, it inputs the first temperature information and status information into a prediction model to obtain a predicted temperature sequence output by the model; and sends a first early warning message when the residual between the first temperature information and the predicted temperature sequence is greater than a first threshold. In this invention, the first temperature information includes real-time temperature information of multiple key components inside the on-board charger, enabling the system to comprehensively understand the internal heat distribution of the on-board charger. When it is confirmed that the on-board charger is in operation, the prediction model predicts a predicted temperature sequence for a future period, and sends a first early warning message when the residual between the first temperature information and the predicted temperature sequence is greater than a first threshold. This allows the system to identify abnormal temperature rise trends and send the first early warning message before the temperature reaches a dangerous level, providing maintenance personnel with a longer time window to take measures before the problem worsens, effectively preventing safety accidents such as thermal runaway, and reducing maintenance costs caused by the escalation of the fault. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating a vehicle charging early warning method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a key internal component of an on-board charger provided in an embodiment of the present invention; Figure 3 A flowchart illustrating another vehicle charging warning method provided in an embodiment of the present invention; Figure 4 for Figure 1 A flowchart illustrating an actual manifestation of S03 in a provided vehicle charging warning method; Figure 5A flowchart illustrating another method for vehicle charging warning provided in an embodiment of the present invention; Figure 6 A flowchart illustrating yet another vehicle charging warning method provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of a vehicle high-voltage component provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of a vehicle charging early warning system provided in an embodiment of the present invention. Detailed Implementation

[0019] To better understand the technical solution of the present invention, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0020] It should be understood that the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0021] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0022] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0023] The widespread adoption of electric vehicles has made AC charging one of the most common ways for users to replenish their energy. As the core component of AC charging, the on-board charger generates heat during the conversion of AC to DC power, through its internal power devices and magnetic components. Poor heat dissipation or other malfunctions leading to thermal runaway can easily cause abnormal localized temperatures and rapid temperature rises at the vehicle end, posing a potential risk of malfunction and thermal runaway.

[0024] In related technologies, charging safety monitoring systems typically employ fixed threshold alarm mechanisms, making simple judgments based on data collected by temperature sensors. However, this approach cannot identify gradual temperature rise trends below the safety threshold, resulting in delayed early warning responses and difficulty in timely intervention before thermal runaway occurs.

[0025] Therefore, the present invention provides a method for vehicle charging warning to solve the above problems.

[0026] Please refer to Figure 1 The flowchart below shows a method for vehicle charging warning provided in an embodiment of the present invention, applied to a cloud service platform, and includes the following steps: Step S01: Receive temperature and status information uploaded by the vehicle.

[0027] The temperature information includes first temperature information, which is the real-time temperature information of each key component in the vehicle's on-board charger.

[0028] In this embodiment, the on-board charger, as a key component for vehicle charging, is responsible for converting alternating current (AC) to direct current (DC). During this process, its internal critical components generate heat. Real-time temperature information of these critical components is crucial for monitoring charging safety and serves as the foundational data for the system to determine whether any abnormalities exist in the charging process.

[0029] Receiving temperature and status information is crucial for a comprehensive understanding of the on-board charger's operational status. Relying solely on information from a single temperature point is insufficient to accurately determine the overall thermal condition of the on-board charger. Therefore, this embodiment utilizes multi-point temperature information to provide the system with a complete picture of the on-board charger's thermal distribution. Simultaneously, status information helps the system determine whether the on-board charger is truly operational.

[0030] Please refer to Figure 2 This is a schematic diagram of the structure of a key internal component of an on-board charger provided in an embodiment of the present invention.

[0031] like Figure 2 As shown, in some embodiments, key components of the on-board charger may include at least one of the following: a power factor correction circuit switch, a power factor correction circuit inductor, a main transformer, a dual active bridge converter switch, a heat sink, and a water-cooled channel radiator.

[0032] Based on this, the first temperature information can be obtained by multiple temperature sensors pre-installed inside the on-board charger. The first temperature information may include the temperature of the power factor correction circuit switch transistor T_switch (PFC), the temperature of the power factor correction circuit inductor T_inductor, the temperature of the main transformer T_transformer, the temperature of the primary side of the dual active bridge converter switch transistor T_switch (DAB)1, the temperature of the secondary side of the dual active bridge converter switch transistor T_switch (DAB)2, the temperature of the heat sink substrate T_sink, the temperature of the water-cooled channel radiator inlet T_water channel1, and the temperature of the water-cooled channel radiator outlet T_water channel2, etc.

[0033] Step S02: Determine whether the on-board charger is in operation based on the status information.

[0034] If so, proceed to step S03.

[0035] In this embodiment, the status information describes the operating status of the on-board charger. By analyzing the status information, the system can confirm whether the on-board charger is actually running, and thus decide which strategy to use for charging warning. When the on-board charger is running, the system executes step S03, inputting the first temperature information and status information into the prediction model to obtain the predicted temperature sequence output by the prediction model, and decides whether to issue a warning based on the predicted temperature sequence.

[0036] In some embodiments, when the on-board charger is not in operation, steps S31 to S34 and steps S41 to S47 can also be executed, which will not be described in detail here.

[0037] Step S03: Input the first temperature information and state information into the prediction model to obtain the predicted temperature sequence output by the prediction model.

[0038] In this embodiment, the initial temperature and status information obtained from the vehicle are fed into the prediction model as input parameters. After receiving this data, the prediction model generates a sequence reflecting future temperature change trends, i.e., a predicted temperature sequence, based on its internal algorithm. This sequence is used for subsequent comparison with the actual temperature to determine if any anomalies exist. The predicted temperature sequence reflects the expected temperature change pattern of the on-board charger under the current operating conditions and is the basis for the system's anomaly detection.

[0039] The specific implementation of step S03 can be referred to the embodiments shown in subsequent steps S21 to S24, which will not be repeated here.

[0040] Step S04: Determine the real-time temperature sequence based on the first temperature information. When the residual between the real-time temperature sequence and the predicted temperature sequence continues to increase and exceeds the first threshold, send the first warning information.

[0041] The first warning message is used to indicate an abnormal upward trend in temperature.

[0042] In this embodiment, the first temperature information is converted into a real-time temperature sequence, which is then compared with a predicted temperature sequence. When the residual between the real-time temperature sequence and the predicted temperature sequence continues to increase and exceeds a set first threshold, the system generates a first warning message. This process is a crucial step in the system's judgment of abnormal temperature rise trends, enabling the identification of anomalies in temperature change trends and providing accurate basis for subsequent warnings.

[0043] Traditional fixed-threshold alarm mechanisms cannot adapt to temperature variation patterns under different charging scenarios. Therefore, this embodiment can more accurately identify abnormal trends by judging based on the continuous increase of residuals. When the residuals continue to increase and exceed the first threshold, it indicates that the temperature change trend has significantly deviated from the normal range, suggesting a potential risk. At this time, the system will generate the first warning message. This mechanism can provide early warning before the problem worsens, buying more time to take preventive measures and effectively avoiding the occurrence of safety hazards.

[0044] Based on the above technical solution, the vehicle charging early warning method provided in this embodiment of the invention receives temperature and status information uploaded by the vehicle; determines whether the on-board charger is in operation based on the status information; if so, inputs the first temperature information and status information into a prediction model to obtain a predicted temperature sequence output by the prediction model; determines a real-time temperature sequence based on the first temperature information; and sends a first early warning message when the residual between the real-time temperature sequence and the predicted temperature sequence continues to increase and exceeds a first threshold. In this invention, the first temperature information includes real-time temperature information of multiple key components inside the on-board charger, enabling the system to comprehensively understand the internal heat distribution of the on-board charger. When it is confirmed that the on-board charger is in operation, the prediction model is used to predict the predicted temperature sequence for a future period. Determining the real-time temperature sequence based on the first temperature information and sending a first early warning message when the residual between the real-time temperature sequence and the predicted temperature sequence continues to increase and exceeds a first threshold allows the system to identify abnormal temperature rise trends and send the first early warning message before the temperature reaches a dangerous level. This provides maintenance personnel with a more sufficient time window to take measures before the problem worsens, effectively preventing safety accidents such as thermal runaway, and also reducing maintenance costs caused by the expansion of the fault.

[0045] Please refer to Figure 3 The flowchart below shows another method for vehicle charging warning provided in an embodiment of the present invention.

[0046] In some embodiments, to enable the prediction model to adapt to the characteristics of different charging scenarios and reduce false alarms caused by environmental differences, the following can also be performed before executing step S01: Figure 3 The steps shown are as follows: Step S11: Obtain historical charging condition data.

[0047] The historical charging data includes the historical power of the on-board charger and the historical temperature information of each key component.

[0048] In this embodiment, historical charging condition data includes the historical power output of the on-board charger during previous charging sessions and the historical temperature information of each key component. This historical charging condition data provides foundational information for subsequent model training, helping the system more accurately determine whether temperature changes during the current charging process are normal.

[0049] In some embodiments, historical charging condition data may include extreme charging condition data from actual user scenarios, typical charging condition data for ambient temperatures at various temperature ranges, and historical charging data for similar vehicles under the same environmental conditions, as shown in the table below:

[0050] Step S12: Determine the historical power of the on-board charger, the historical temperature rise rate of each key component, and the historical temperature difference between each key component based on historical charging condition data.

[0051] In this embodiment, historical charging data is used to determine the historical power of the on-board charger during past charging processes, as well as the historical temperature rise rate of each key component and the historical temperature difference between different components. Historical power reflects the energy conversion during charging, historical temperature rise rate shows the temperature change trend over time, and historical temperature difference reveals the thermal distribution characteristics between different components. These parameters comprehensively reflect the thermal behavior patterns of the on-board charger under various operating conditions. By analyzing these parameters, the system can better understand the temperature change patterns during normal charging, providing a basis for subsequent identification of abnormal situations. This multi-dimensional parameter-based analysis method is more comprehensive and accurate than a single indicator.

[0052] In some embodiments, the system can extract power and temperature data points for each charging cycle from historical charging condition data. For historical power, the power value of the on-board charger can be directly read from the data. For historical temperature rise rate, the temperature difference of each key component at adjacent time points is calculated and divided by the time interval. For historical temperature difference, the temperature difference between different key components at the same moment is calculated.

[0053] Step S13: Integrate historical power, historical temperature rise rate and historical temperature difference to form a historical multidimensional feature set.

[0054] In this embodiment, the historical power of the on-board charger, the historical temperature rise rate of each key component, and the historical temperature difference between each key component are integrated into a unified data structure, which constitutes a historical multi-dimensional feature set describing the thermal behavior during the charging process. This set can comprehensively reflect the temperature change pattern of the on-board charger during the charging process and provide basic data for the subsequent establishment of a prediction model.

[0055] Step S14: Using historical multidimensional feature sets as input, a corresponding prediction model is established for the temperature sequence of each key device using a long short-term memory network or a temporal convolutional network.

[0056] In this embodiment, a historical multidimensional feature set is used as input, and a dedicated prediction model is built for each key component using either a Long Short-Term Memory (LSTM) network or a Temporal Convolutional Network (TCNN). LSM networks excel at handling long-term dependent time-series data, while TCNNs effectively capture local temporal patterns. In this way, the system can establish a dedicated temperature change prediction model for each key component inside the on-board charger, enabling the model to learn the normal temperature change patterns of the component under different charging conditions, providing a foundation for subsequent real-time temperature prediction.

[0057] Different key components possess different thermal characteristics, and individual modeling can more accurately reflect their respective variation patterns. Traditional single models struggle to adapt to the diverse characteristics of all components, while prediction models trained separately for each component can better capture its specific temperature change trends. This approach improves prediction accuracy, enabling the system to identify abnormal upward trends before temperatures reach dangerous levels, providing a more reliable basis for safety warnings.

[0058] Please refer to Figure 4 ,for Figure 1 A flowchart illustrating an actual manifestation of S03 in a provided vehicle charging warning method.

[0059] Based on the above embodiments, in some embodiments, step S03 may include the following steps: Step S21: For each of all key components, determine the real-time temperature rise rate of the key component and the real-time temperature difference between the key component and other key components based on the first temperature information.

[0060] In this embodiment, the system uses the first temperature information to calculate the rate of temperature change of each key component over time, i.e., the real-time temperature rise rate. Simultaneously, the system also calculates the temperature difference between different key components at the same moment, referred to as the real-time temperature difference. The real-time temperature rise rate and real-time temperature difference reflect the thermal state and interrelationships of each key component under the current charging state, providing fundamental information for subsequent temperature prediction and anomaly detection.

[0061] Step S22: Determine the real-time power of the on-board charger based on the status information.

[0062] In this embodiment, the system utilizes the vehicle's uploaded status information to calculate or obtain the current real-time power of the on-board charger, providing input for the prediction model. The magnitude of the real-time power directly affects the heat generation of the internal components of the on-board charger, with different temperature change patterns at different power levels. Relying solely on temperature data cannot fully reflect the charging status, while combining it with power data can more accurately identify normal fluctuations and abnormal temperature rises.

[0063] Step S23: Integrate real-time power, real-time temperature rise rate, and real-time temperature difference to form a real-time multidimensional feature set.

[0064] Because using any single parameter—real-time power, real-time temperature rise rate, or real-time temperature difference—cannot fully reflect the thermal behavior during charging, this embodiment fuses real-time power, real-time temperature rise rate, and real-time temperature difference to form a real-time multi-dimensional feature set. Combining these three parameters provides more complete input data for the prediction model, thereby accurately identifying normal fluctuations and abnormal temperature rises. This method reduces the false alarm rate, improves the reliability of the early warning system, and enables the system to detect potential risks before the temperature reaches dangerous levels.

[0065] Step S24: Using the prediction model corresponding to the key components, predict the predicted temperature sequence of the key components based on the real-time multidimensional feature set.

[0066] In this embodiment, a prediction model specifically trained for each key component is used as input to calculate the expected temperature change trend of the key component over a future period. This process generates a predicted temperature sequence representing the temperature change trend of each key component inside the on-board charger, reflecting the normal temperature change pattern of each key component under current operating conditions.

[0067] Please refer to Figure 5 This is a flowchart of another vehicle charging warning method provided in an embodiment of the present invention.

[0068] In some embodiments, to enable the prediction model to adapt to the characteristics of different charging scenarios and reduce false alarms caused by environmental differences, after performing step S02, the following can also be performed: Figure 5 The steps shown are as follows: Step S31: When the on-board charger is in operation, acquire historical charging condition data.

[0069] In this embodiment, when the on-board charger is in operation, the system acquires historical charging condition data to provide a basis for subsequent temperature analysis.

[0070] Step S32: For each of all key components, determine the real-time temperature rise rate of each key component and the real-time temperature difference between the key component and other key components based on the first temperature information.

[0071] The specific implementation process of this step is the same as that of step S21, and will not be repeated here.

[0072] Step S33: The real-time temperature rise rate and real-time temperature difference are fused to form a temperature rise feature vector, and cluster analysis is performed on the temperature rise feature vector based on historical charging condition data.

[0073] In this embodiment, the system integrates the hourly temperature rise rate and real-time temperature difference of each key component inside the on-board charger into a structured temperature rise feature vector. Then, based on historical charging data, cluster analysis is performed on the temperature rise feature vector. Using data from past charging processes as a reference, the current temperature rise feature vector is compared with historical data to identify similar patterns or anomalies.

[0074] In some embodiments, the system can extract similar temperature rise feature vectors from historical charging condition data as a reference for cluster analysis. Then, a clustering algorithm is used to group the current temperature rise feature vector with historical data to determine its category. If the distance between the current temperature rise feature vector and a cluster center exceeds a set threshold, it is considered an anomaly.

[0075] Step S34: When the distance between the temperature rise feature vector and the cluster center exceeds the second threshold, send the second warning information.

[0076] The second warning message is used to indicate abnormal temperature imbalances.

[0077] In this embodiment, the cluster centers formed by cluster analysis of historical charging data represent the temperature distribution pattern under normal charging conditions. Checking whether the distance between the temperature rise feature vector and the cluster center exceeds a second threshold is to promptly detect abnormal temperature imbalances. If the current temperature rise feature vector exceeds the second threshold, it indicates that the current temperature distribution of the on-board charger differs significantly from the normal pattern, potentially indicating overheating or underheating of certain critical components. In this case, a second warning message is promptly sent to allow relevant personnel to take preventative measures, avoid further deterioration of the problem, improve charging safety, and reduce the risk of safety accidents caused by temperature imbalances.

[0078] Please refer to Figure 6 This is a flowchart of another vehicle charging warning method provided in an embodiment of the present invention.

[0079] In some embodiments, the temperature information may further include second temperature information of the charging socket and third temperature information of the vehicle's high-voltage components.

[0080] Please refer to Figure 7 This is a schematic diagram of a vehicle high-voltage component provided in an embodiment of the present invention.

[0081] The powertrain includes a motor controller, a drive motor, a DC-DC converter, and a transmission. For example... Figure 7 As shown, the high-voltage components of the vehicle may include, but are not limited to, the power battery, motor controller, drive motor, DC-DC converter, transmission, PTC heater, and air conditioning compressor. The third temperature information can be collected by the temperature sensors built into each high-voltage component of the vehicle.

[0082] Furthermore, the second temperature information can be obtained through... Figure 7 The temperature is collected by the built-in temperature sensor in the charging socket.

[0083] Based on this, after executing step S02, the following can also be executed: Figure 6 The steps shown are as follows: Step S41: When the on-board charger is not in operation, monitor the first temperature information, the second temperature information, and the third temperature information.

[0084] In this embodiment, the system monitors first, second, and third temperature information when the on-board charger is not in operation. The first temperature information represents the real-time temperature of key components of the on-board charger, the second temperature information is the temperature of the charging socket, and the third temperature information refers to the temperature of the vehicle's high-voltage components. The system determines the type of warning message to issue by judging whether these temperature information meet specific conditions.

[0085] Step S42: If both the first temperature information and the second temperature information are higher than the third threshold, and the third temperature information is within a preset range, then the standby parameters of the on-board charger are obtained.

[0086] In this embodiment, if both the first and second temperature information are higher than the third threshold, and the third temperature information is within a preset range, it indicates that only the on-board charger and charging socket are hot while other high-voltage components are at normal temperatures. This suggests that the problem may lie with the on-board charger itself rather than the external environment. Obtaining the on-board charger's standby parameters at this time can help the system determine whether the issue is a hardware failure of the on-board charger or temperature fluctuations during normal standby.

[0087] In some embodiments, the standby parameters may include, but are not limited to, standby current, standby voltage, and internal circuit status. The system records the standby parameters and uses them for subsequent analysis to determine whether an early warning mechanism needs to be triggered.

[0088] Step S43: Determine if the standby parameters are normal.

[0089] If yes, proceed to step S44. If no, proceed to step S45.

[0090] Step S44: Issue the third warning message.

[0091] The third warning information is used to indicate abnormal temperature of the on-board charger.

[0092] Step S45: Issue the fourth warning message.

[0093] The fourth warning information is used to indicate abnormal standby status of the on-board charger.

[0094] In this embodiment, when both the first and second temperature information are higher than the third threshold, and the third temperature information is within a preset range, the system checks the standby parameters and sends different types of warning messages based on the results. By checking the standby parameters, the system can determine the root cause of the problem. When the standby parameters are normal, it proves that the on-board charger is only abnormal in temperature, and the system issues a third warning message to indicate that the on-board charger's temperature is abnormal. When the standby parameters are abnormal, it proves that both the temperature and standby status of the on-board charger are abnormal, and the system issues a fourth warning message to indicate that the on-board charger's standby is abnormal.

[0095] This process design ensures that the system can accurately distinguish between different types of faults, helping maintenance personnel quickly locate problems, reduce unnecessary inspections and repairs, and improve work efficiency. At the same time, accurate early warning information can help vehicle owners take timely and appropriate measures to prevent safety hazards from escalating.

[0096] In some embodiments, after performing step S41, the following steps may also be performed: Step S46: If the first temperature information or the second temperature information is higher than the third threshold, and the third temperature information is within the preset range, then a fifth warning information is issued.

[0097] The fifth warning message is used to indicate that the temperature control status of the on-board charger is abnormal.

[0098] In this embodiment, if the first temperature information or the second temperature information is higher than the third threshold, and the third temperature information is within the preset range, it indicates that only the charger or socket temperature is high, which proves that the on-board charger's own temperature control system may be faulty. At this time, a fifth warning message is sent to indicate that the temperature control status of the on-board charger is abnormal.

[0099] Step S47: If there is a third temperature information that is not within the normal range, and the first temperature information and the second temperature information are higher than the third temperature information that is not within the preset range, then a sixth warning information is issued.

[0100] The sixth warning message is used to indicate abnormal local temperatures in the vehicle.

[0101] In this embodiment, when a third temperature reading outside the normal range exists, and both the first and second temperature readings are higher than this third temperature reading, it indicates that the problem may be located closer to the charger or socket. At this point, a sixth warning message indicating a localized temperature anomaly in the vehicle is sent. Timely detection of localized temperature anomalies helps prevent safety accidents such as thermal runaway and ensures the safety of the charging process. Simultaneously, this targeted warning helps maintenance personnel quickly locate the problem, reducing troubleshooting time.

[0102] Please refer to Figure 8 This is a schematic diagram of a vehicle charging early warning system provided in an embodiment of the present invention. Figure 8 As shown, when applied to a cloud service platform, the vehicle charging warning system may include: The information receiving module 100 is used to receive temperature information and status information uploaded by the vehicle; the temperature information includes first temperature information; the first temperature information is the real-time temperature information of each key component in the vehicle's on-board charger. The status determination module 200 is used to determine whether the on-board charger is in operation based on status information. The temperature prediction module 300 is used to input the first temperature information and status information into the prediction model when the on-board charger is in operation, and obtain the predicted temperature sequence output by the prediction model. The first early warning module 400 is used to determine the real-time temperature sequence based on the first temperature information. When the residual between the real-time temperature sequence and the predicted temperature sequence continues to increase and exceeds the first threshold, the first early warning information is sent. The first early warning information is used to indicate an abnormal temperature rise trend.

[0103] Based on the above embodiments, in some embodiments, the vehicle charging early warning system may further include a model building module, used for: Acquire historical charging condition data; historical charging condition data includes the historical power of the on-board charger and the historical temperature information of each key component. Based on historical charging condition data, determine the historical power of the on-board charger, the historical temperature rise rate of each key component, and the historical temperature difference between each key component. A multi-dimensional feature set of history is formed by integrating historical power, historical temperature rise rate, and historical temperature difference; Using historical multidimensional feature sets as input, a corresponding prediction model is established for the temperature sequence of each key component using a long short-term memory network or a temporal convolutional network.

[0104] Based on the above embodiments, in some embodiments, the temperature prediction module 300 can specifically be used for: For each of all key components, the real-time temperature rise rate of the key component and the real-time temperature difference between the key component and other key components are determined based on the first temperature information. The real-time power of the on-board charger is determined based on the status information; Real-time power, real-time temperature rise rate, and real-time temperature difference are integrated to form a real-time multi-dimensional feature set; The predicted temperature sequence of key components is predicted based on the prediction model corresponding to the key components and the real-time multidimensional feature set.

[0105] Based on the above embodiments, in some embodiments, the vehicle charging warning system may further include a second warning module, used for: When the on-board charger is in operation, acquire historical charging condition data; For each of all key components, the real-time temperature rise rate of each key component and the real-time temperature difference between the key component and other key components are determined based on the first temperature information. The temperature rise feature vector is formed by integrating the real-time temperature rise rate and the real-time temperature difference, and cluster analysis is performed on the temperature rise feature vector based on historical charging condition data. When the distance between the temperature rise feature vector and the cluster center exceeds the second threshold, a second warning message is sent; the second warning message is used to indicate abnormal temperature imbalance.

[0106] Based on the above embodiments, in some embodiments, the temperature prediction module 300 can specifically be used for: Based on the above embodiments, in some embodiments, the temperature information also includes second temperature information of the charging socket and third temperature information of the vehicle's high-voltage components; The vehicle charging warning system may also include a third warning module for: When the on-board charger is not in operation, the first temperature information, the second temperature information, and the third temperature information are monitored; If both the first and second temperature information are higher than the third threshold, and the third temperature information is within a preset range, then the standby parameters of the on-board charger are obtained. Check if the standby parameters are normal; If so, a third warning message will be issued; the third warning message is used to indicate that the on-board charger temperature is abnormal. If not, a fourth warning message will be issued; the fourth warning message is used to indicate that the on-board charger is in standby abnormality.

[0107] Based on the above embodiments, in some embodiments, the vehicle charging warning system may further include a fourth warning module, used for: If the first or second temperature information is higher than the third threshold, and the third temperature information is within the preset range, a fifth warning message will be issued; the fifth warning message is used to indicate that the temperature control status of the on-board charger is abnormal. If a third temperature information is found that is outside the normal range, and the first and second temperature information are higher than the third temperature information that is outside the preset range, a sixth warning information will be issued; the sixth warning information is used to indicate local temperature abnormalities in the vehicle.

[0108] Based on the above embodiments, in some embodiments, the key components include at least one of the following: power factor correction circuit switching transistor, power factor correction circuit inductor, main transformer, dual active bridge converter switching transistor, heat dissipation substrate, and water-cooled channel heat sink.

[0109] This embodiment provides an electronic device, including a processor and a memory. The memory is used to store at least one instruction. When the instruction is loaded and executed by the processor, it implements the above-mentioned vehicle charging warning method. Its execution method and beneficial effects are similar and will not be described again here.

[0110] This invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the above-mentioned vehicle charging warning method. The execution method and beneficial effects are similar and will not be described again here.

[0111] It should be noted that although the steps are described in a specific order above, it does not mean that the steps must be executed in the above specific order. In fact, some of these steps can be executed concurrently, or even in a different order, as long as the required function can be achieved.

[0112] This is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method of vehicle charging warning, characterized in that, Applied to a cloud service platform, the method includes: Receive temperature and status information uploaded by the vehicle; the temperature information includes first temperature information; the first temperature information is the real-time temperature information of each key component in the vehicle's on-board charger; Based on the status information, determine whether the on-board charger is in operation; If so, the first temperature information and the state information are input into the prediction model to obtain the predicted temperature sequence output by the prediction model; Based on the first temperature information, a real-time temperature sequence is determined. When the residual between the real-time temperature sequence and the predicted temperature sequence continues to increase and exceeds a first threshold, a first warning message is sent. The first warning message is used to indicate an abnormal temperature rise trend.

2. The method according to claim 1, characterized in that, Before receiving the temperature and status information uploaded by the vehicle, the method further includes: Acquire historical charging condition data; the historical charging condition data includes the historical power of the on-board charger and the historical temperature information of each of the key components. Based on the historical charging condition data, the historical power of the on-board charger, the historical temperature rise rate of each key component, and the historical temperature difference between each key component are determined. The historical power, the historical temperature rise rate, and the historical temperature difference are combined to form a historical multidimensional feature set; Using the historical multidimensional feature set as input, a corresponding prediction model is established for the temperature sequence of each key device using a long short-term memory network or a temporal convolutional network.

3. The method according to claim 2, characterized in that, The step of inputting the first temperature information and the state information into the prediction model to obtain the predicted temperature sequence output by the prediction model includes: For each of the key components, the real-time temperature rise rate of the key component and the real-time temperature difference between the key component and other key components are determined based on the first temperature information. The real-time power of the on-board charger is determined based on the aforementioned status information; The real-time power, the real-time temperature rise rate, and the real-time temperature difference are integrated to form a real-time multidimensional feature set; The predicted temperature sequence of the key device is predicted based on the real-time multidimensional feature set using the prediction model corresponding to the key device.

4. The method according to claim 1, characterized in that, After determining whether the on-board charger is in operation based on the status information, the method further includes: When the on-board charger is in operation, historical charging condition data is acquired. For each of the key components, the real-time temperature rise rate of each key component and the real-time temperature difference between the key component and other key components are determined based on the first temperature information. The real-time temperature rise rate and the real-time temperature difference are combined to form a temperature rise feature vector, and cluster analysis is performed on the temperature rise feature vector based on historical charging condition data. When the distance between the temperature rise feature vector and the cluster center exceeds the second threshold, a second warning message is sent; the second warning message is used to indicate an abnormal temperature imbalance.

5. The method according to claim 1, characterized in that, The temperature information also includes second temperature information of the charging socket and third temperature information of the vehicle's high-voltage components. After determining whether the on-board charger is in operation based on the status information, the method further includes: When the on-board charger is not in operation, the first temperature information, the second temperature information and the third temperature information are monitored. If both the first temperature information and the second temperature information are higher than the third threshold, and the third temperature information is within a preset range, then the standby parameters of the on-board charger are obtained. Determine whether the standby parameters are normal; If so, a third warning message is issued; the third warning message is used to indicate that the on-board charger temperature is abnormal. If not, a fourth warning message is issued; the fourth warning message is used to indicate that the on-board charger is in standby abnormality.

6. The method according to claim 5, characterized in that, After monitoring the first temperature information, the second temperature information, and the third temperature information, the method further includes: If the first temperature information or the second temperature information is higher than the third threshold, and the third temperature information is within a preset range, then a fifth warning message is issued; the fifth warning message is used to indicate that the temperature control status of the on-board charger is abnormal. If a third temperature information is found that is outside the normal range, and the first temperature information and the second temperature information are higher than the third temperature information that is outside the preset range, a sixth warning information is issued; the sixth warning information is used to indicate that the local temperature of the vehicle is abnormal.

7. The method according to claim 1, characterized in that, The key components include at least one of the following: power factor correction circuit switching transistor, power factor correction circuit inductor, main transformer, dual active bridge converter switching transistor, heat dissipation substrate, and water-cooled channel radiator.

8. A vehicle charging warning system, characterized in that, The system is applied to a cloud service platform and includes: The information receiving module is used to receive temperature information and status information uploaded by the vehicle; the temperature information includes first temperature information; the first temperature information is the real-time temperature information of each key component in the vehicle's on-board charger. A status determination module is used to determine whether the on-board charger is in operation based on the status information. The temperature prediction module is used to input the first temperature information and the status information into the prediction model when the on-board charger is in operation, so as to obtain the predicted temperature sequence output by the prediction model. The first early warning module is used to determine a real-time temperature sequence based on the first temperature information. When the residual between the real-time temperature sequence and the predicted temperature sequence continues to increase and exceeds a first threshold, a first early warning message is sent. The first early warning message is used to indicate an abnormal temperature rise trend.

9. An electronic device, characterized in that, include: A processor and a memory, the memory being used to store at least one instruction, which, when loaded and executed by the processor, implements the vehicle charging warning method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the vehicle charging warning method as described in any one of claims 1-7.

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