Charging protection method, device and equipment based on intelligent fuse and storage medium

Abstract

The invention provides a charging protection method and device based on an intelligent fuse, equipment and a storage medium. The method comprises the following steps: receiving first data of a charging pile collected by a first intelligent fuse, second data of a vehicle-mounted battery module collected by a second intelligent fuse, and third data of the vehicle-mounted battery module collected by a voltage detection circuit; preprocessing the first data, the second data and the third data; obtaining a current deviation rate and a temperature deviation rate according to the first data, the second data and the third data after preprocessing, and a preset current prediction model and a temperature prediction model; if it is determined that the current and temperature of the charging system are abnormal according to the current deviation rate and the temperature deviation rate, and the abnormal time point of the temperature is earlier than the abnormal time point of the current, a target adjustment scheme is determined according to the current deviation rate and the temperature deviation rate; and adjusting the charging system according to the target adjustment scheme. The charging system can be adjusted in time, and the safety of the charging system is improved.

Description

Technical Field

[0001] This application relates to the technical field of emergency protection devices, and particularly to a charging protection method, device, equipment, and storage medium based on an intelligent fuse. Background Art

[0002] In the new energy field, the charging requirements of different electric vehicles are different, and the current fluctuates greatly during the charging process. At present, in the charging system of new energy electric vehicles, a fuse with fixed protection parameters is generally used to fuse and protect the overcurrent state of the charging circuit in the charging system. For the vehicle-end power management system, some charging branches, especially the added circuits, are in a monitoring blind area state. The anomalies in these monitoring blind areas will cause charging anomalies, which will in turn cause the vehicle-end power management system to malfunction or the protection to be untimely. Summary of the Invention

[0003] This application provides a charging protection method, device, equipment, and storage medium based on an intelligent fuse, which can timely monitor anomalies to adjust the charging system, thereby improving the safety of the charging system during the charging process.

[0004] In a first aspect, an embodiment of this application provides a charging protection method based on an intelligent fuse, which is applied to a control module of a charging system. The charging system includes the control module, a vehicle-mounted battery module connected to the control module, and a charging pile. The charging pile is provided with a target added circuit module. The method includes: Receiving first data of the charging pile collected by a first intelligent fuse, second data of the vehicle-mounted battery module collected by a second intelligent fuse, and third data of the vehicle-mounted battery module collected by a voltage detection circuit. The first data includes a first current, a first voltage, and a first temperature. The second data includes a second current and a second temperature. The third data includes a second voltage and the state of charge of the real-time battery pack; Preprocessing the first data, the second data, and the third data to obtain preprocessed first data, second data, and third data; Obtaining a current deviation rate and a temperature deviation rate according to a preset current prediction model, a temperature prediction model, the preprocessed first data, second data, and third data; If it is determined that the current and temperature of the charging system are abnormal according to the current deviation rate and the temperature deviation rate, and the abnormal time point of the temperature precedes the abnormal time point of the current, then determining a target adjustment plan according to the current deviation rate and the temperature deviation rate; Adjusting the charging system according to the target adjustment plan.

[0005] Second aspect, an embodiment of the present application provides a charging protection device based on an intelligent fuse, which is applied to a control module of a charging system. The charging system includes the control module, an in-vehicle battery module and a charging pile connected to the control module. The charging pile is provided with a target additional circuit module. The device includes: A receiving unit, configured to receive first data of the charging pile collected by a first intelligent fuse, second data of the in-vehicle battery module collected by a second intelligent fuse, and third data of the in-vehicle battery module collected by a voltage detection circuit. The first data includes a first current, a first voltage and a first temperature. The second data includes a second current and a second temperature. The third data includes a second voltage and the state of charge of the real-time battery pack. A processing unit, configured to preprocess the first data, the second data and the third data to obtain preprocessed first data, second data and third data. An obtaining unit, configured to obtain a current deviation rate and a temperature deviation rate according to a preset current prediction model, a temperature prediction model, and the preprocessed first data, second data and third data. A determining unit, configured to, if it is determined that the current and temperature of the charging system are abnormal according to the current deviation rate and the temperature deviation rate, and the abnormal time point of the temperature precedes the abnormal time point of the current, determine a target adjustment scheme according to the current deviation rate and the temperature deviation rate. An adjusting unit, configured to adjust the charging system according to the target adjustment scheme.

[0006] Third aspect, an embodiment of the present application provides a terminal device. The terminal device includes at least one processor, a communication interface and a memory. The communication interface is configured to send and / or receive data. The memory is configured to store a computer program. The at least one processor is configured to call the computer program stored in the memory to implement any method in the first aspect of the present application.

[0007] Fourth aspect, an embodiment of the present application provides an electronic device, including a processor and a memory. The memory is configured to store computer program code. The computer program code includes computer instructions. When the processor executes the computer instructions, the electronic device executes the instructions of any method in the first aspect of the present application.

[0008] Fifth aspect, an embodiment of the present application provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. The computer program includes program instructions. When the program instructions are executed by a processor, the processor is caused to execute some or all of the steps described in any method in the first aspect of the embodiments of the present application.

[0009] Sixth aspect, the present application provides a computer program, wherein the computer program is operable to cause a computer to execute some or all of the steps described in any method of the first aspect of the embodiments of the present application. The computer program may be a software installation package.

[0010] It can be seen that in the examples of the present application, a charging protection method based on an intelligent fuse is applied to a control module of a charging system. The charging system includes a control module, a vehicle-mounted battery module connected to the control module, and a charging pile. The charging pile is provided with a target additional circuit module. The method includes: receiving first data of the charging pile collected by a first intelligent fuse, second data of the vehicle-mounted battery module collected by a second intelligent fuse, and third data of the vehicle-mounted battery module collected by a voltage detection circuit. The first data includes a first current, a first voltage, and a first temperature. The second data includes a second current and a second temperature. The third data includes a second voltage and the state of charge of the real-time battery pack. The data of the charging state and the vehicle-mounted battery module are collected in real time through the intelligent fuse, improving the timeliness of monitoring. Preprocessing the first data, the second data, and the third data to obtain the preprocessed first data, second data, and third data; obtaining a current deviation rate and a temperature deviation rate according to a preset current prediction model, a temperature prediction model, the preprocessed first data, second data, and third data; if it is determined that the current and temperature of the charging system are abnormal according to the current deviation rate and the temperature deviation rate, and the abnormal time point of the temperature precedes the abnormal time point of the current, then determining a target adjustment scheme according to the current deviation rate and the temperature deviation rate; adjusting the charging system according to the target adjustment scheme. In the present application, it is determined whether the charging system is abnormal based on the real-time data of the intelligent fuse combined with an algorithm, improving the timeliness of monitoring and making timely adjustments, further improving the system safety. Description of the Drawings

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0012] Figure 1 It is a schematic structural diagram of a charging system provided by an embodiment of the present application; Figure 2 It is a schematic flowchart of a charging protection method based on an intelligent fuse provided by an embodiment of the present application; Figure 3 It is a schematic diagram of a display interface of a display device provided by an embodiment of the present application; Figure 4It is a block diagram of the functional units of a charging protection device based on an intelligent fuse provided by an embodiment of the present application; Figure 5 It is a schematic structural diagram of a control module provided by an embodiment of the present application. Specific embodiments

[0013] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present application.

[0014] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0015] Referring to "embodiment" herein means that a specific feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The phrase appears in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0016] Please refer to Figure 1 , Figure 1 It is a schematic structural diagram of a charging system provided by an embodiment of the present application. As Figure 1 shown, the charging system includes a control module, a charging pile, and an in-vehicle battery module. Among them, the control module is connected to the in-vehicle battery module and the charging pile.

[0017] Specifically, a target additional circuit module is provided inside the charging pile. A first intelligent fuse is also provided inside the charging pile. The first data inside the charging pile is collected through the first intelligent fuse. The vehicle where the control module is located is equipped with a second intelligent fuse, and the second data of the in-vehicle battery module is collected through the second intelligent fuse. The intelligent fuse in this application can collect the current and voltage on the charging pile side through a current sensor and / or a voltage sensor. Specifically, the current sensor and / or the voltage sensor are integrally arranged in the detection circuit of the intelligent fuse. The current sensor can be a Hall effect current sensor or a resistive current sensor. In addition, an operational amplifier and a filter are also provided in the detection circuit of the intelligent fuse. After the sensor outputs a signal, the signal is amplified, filtered, etc. through the operational amplifier and the filter, so that the microcontrollers of the first intelligent fuse and the second intelligent fuse can accurately collect the current and voltage, thereby improving the accuracy of the collected data.

[0018] Among them, the control module can be a vehicle-side power management system (Battery Management System, BMS), which is an electronic system used to manage, monitor, and control the in-vehicle battery module. In this application, the control module is arranged inside the vehicle. The control module can communicate with the first intelligent fuse inside the charging pile and the second intelligent fuse arranged inside the vehicle to exchange data. Specifically, on the vehicle side, the passive fuses of the total positive branch, the total negative branch, the battery pack heating circuit, etc. inside the in-vehicle battery module are replaced with the second intelligent fuse, and the second intelligent fuse communicates and reports the vehicle-side information of each branch to the control module. On the charging pile side, the fuse on the charging pile side is updated to the first intelligent fuse, and communicates with the control module to report the information of each branch on the charging pile side. The microcontroller on the charging pile side sends information to the vehicle-side control module through the signal line of the charging cable.

[0019] In the embodiment of this application, the additional circuit module is a circuit module reinstalled by the user. For example, it can be a charging cable adapter installed by the user. Since the vehicle has different requirements for the charging power, for the convenience of charging, the user will be equipped with a charging cable adapter, which is mainly used to convert the power into a current and voltage suitable for vehicle charging.

[0020] The following will be combined with Figure 2 , and the method in the embodiment of this application will be introduced in detail: In a possible example, please refer to Figure 2 , Figure 2 is a schematic flowchart of a charging protection method based on an intelligent fuse provided by the embodiment of this application. As shown in Figure 2As shown in the figure, a charging protection method based on an intelligent fuse is applied to a control module of a charging system. The charging system includes the control module, a vehicle-mounted battery module connected to the control module, and a charging pile. The charging pile is provided with a target additional circuit module. The method includes: S201, receiving first data of the charging pile collected by a first intelligent fuse, second data of the vehicle-mounted battery module collected by a second intelligent fuse, and third data of the vehicle-mounted battery module collected by a voltage detection circuit.

[0021] Among them, the first data includes a first current, a first voltage, and a first temperature. The second data includes a second current and a second temperature. The third data includes a second voltage and the state of charge of the real-time battery pack.

[0022] Specifically, the first intelligent fuse collects the first data of the charging pile, the second intelligent fuse collects the second data of the vehicle-mounted battery module, and the third data of the vehicle-mounted battery module is collected by the voltage detection circuit. The third data of the vehicle battery module is collected by the voltage detection circuit, reducing the data acquisition pressure of the second intelligent fuse and rationally using the facilities at the vehicle end. The data of the first intelligent fuse, the second intelligent fuse, and the voltage detection circuit provides data support for subsequent data processing.

[0023] S202, preprocessing the first data, the second data, and the third data to obtain preprocessed first data, second data, and third data.

[0024] Among them, after the first data, the second data, and the third data are collected, the first current, the first voltage, and the first temperature in the first data, the second current and the second temperature in the second data, and the second voltage and the state of charge of the real-time battery pack in the third data are respectively preprocessed to obtain preprocessed first data, second data, and third data. Specifically, a combination of median filtering and moving average filtering can be used to remove pulse noise and random fluctuations in the data, improving the smoothness and accuracy of the data.

[0025] S203, obtaining a current deviation rate and a temperature deviation rate according to a preset current prediction model, a temperature prediction model, the preprocessed first data, second data, and third data.

[0026] Among them, a current deviation rate and a temperature deviation rate are obtained according to a preset current prediction model, a temperature prediction model, and the preprocessed first data, second data, and third data. Combining the models improves the rationality of the determined current deviation rate and temperature deviation rate, and further improves the timeliness of monitoring abnormal conditions of the charging system.

[0027] S204. If it is determined that the current and temperature of the charging system are abnormal based on the current deviation rate and the temperature deviation rate, and the abnormal time point of the temperature precedes the abnormal time point of the current, then determine a target adjustment scheme based on the current deviation rate and the temperature deviation rate.

[0028] Among them, when it is determined that the current and temperature of the charging system are abnormal based on the current deviation rate and the temperature deviation rate, and the abnormal time point of the temperature precedes the abnormal time point of the current, determine a target adjustment scheme based on the current deviation rate and the temperature deviation rate to determine a reasonable adjustment scheme, thereby improving the accuracy of the charging system.

[0029] In a possible example, the charging system may further include a display device. Please combine Figure 3 , Figure 3 This is a schematic diagram of a display interface of a display device provided in an embodiment of the present application. As Figure 3 shown, after determining the adjustment scheme, the control module generates a prompt message, which is used to prompt the user whether to use the adjustment scheme to adjust the charging system. The prompt message includes the adjustment scheme and the voice or text of the request indication. After receiving the prompt message, the user's display device generates a display interface to timely remind the user. For example Figure 3 shown, the display interface includes a first information prompt area 301, a second information prompt area 302, and a control button 303. The first information prompt area 301 is used to generate corresponding prompt information based on the prompt message to inform the user of the event that occurred. For example: It is detected that the target additional circuit module is abnormal. Whether to execute the target adjustment scheme. And generate the specific content of the target adjustment scheme in the second information prompt area 302 for the user to check. At the same time, the control button 303 includes options of "Yes" and "No" for the user to make an indication in a timely manner after confirmation. When the display device detects that the user selects the "Yes" indication button, it feeds back the feedback information for execution to the control module. When the display device detects that the user selects the "No" indication button, it feeds back the feedback information for prohibiting execution to the control module, facilitating the user to know the status of the charging system in real time and make a process, improving the user experience. It can be understood that the display device can be a smart phone, a tablet computer, a notebook computer, a desktop computer, a wearable device, a head-mounted device, a vehicle-mounted terminal and other devices. The specific types of the display device are not limited here, and the interface layout and specific generated content of the display device can be set according to actual needs and are not limited here.

[0030] Among them, if the adjustment scheme is to cut off the charging circuit of the charging system, then give priority to cutting off the charging circuit and generating a corresponding open circuit prompt to send to the user's display device, including the charging system in a timely manner, improving safety.

[0031] S205, adjust the charging system according to the target adjustment scheme.

[0032] After determining the corresponding target adjustment scheme, adjust the charging system according to the target adjustment scheme.

[0033] It can be seen that in this example, based on the intelligent fuse to collect data of the charging pile and the in-vehicle battery module, the timeliness and accuracy of the collected data are improved. Combining with the model to determine the current deviation rate and the temperature deviation rate, and then determine whether the charging system is abnormal for timely adjustment, thereby improving the safety of the charging system.

[0034] In a possible example, the preprocessing of the first data, the second data, and the third data to obtain the preprocessed first data, second data, and third data includes: performing median filtering and moving average filtering on the first data, the second data, and the third data to obtain the filtered first data, second data, and third data; performing normalization processing on the filtered first data, second data, and third data to obtain the preprocessed first data, second data, and third data.

[0035] In a specific example, median filtering and moving average filtering are performed on the first data, the second data, and the third data. Among them, median filtering replaces the value of a point in a digital sequence with the median of the values of each point in a neighborhood of this point to achieve the effects of denoising and smoothing. Moving average filtering can effectively smooth these fluctuations, reduce the influence of noise, and improve the stability and reliability of the data by averaging adjacent data points. Then, normalization operations are performed on the filtered first data, second data, and third data to unify data of different types and ranges within the first data, second data, and third data into the [0, 1] interval, which is convenient for subsequent calculations and comparisons.

[0036] It can be seen that in this example, preprocessing different types of data within the obtained first data, second data, and third data makes the preprocessed first data, second data, and third data convenient for subsequent calculations and improves the processing efficiency.

[0037] In a possible example, obtaining the current deviation rate and the temperature deviation rate according to the preset current prediction model, temperature prediction model, the preprocessed first data, second data, and third data includes: inputting the preprocessed first data, second data, and third data into the current prediction model to obtain the predicted current of the charging system; obtaining the operation duration of the charging system and the operation environment data, where the operation duration represents the duration from the starting operation time point of the charging system to the acquisition time point corresponding to the first data, the second data, and the third data; obtaining the predicted temperature of the charging system according to the predicted current, the temperature prediction model, the operation duration, the operation environment data, and the state of charge of the real-time battery pack; calculating the current deviation rate according to the predicted current, the first current, and the second current; and calculating the temperature deviation rate according to the predicted temperature, the first temperature, and the second temperature.

[0038] In a specific example, input the preprocessed first data, second data, and third data into the current prediction model to obtain the predicted current of the charging system, and the predicted current represents the current of the predicted charging system under normal conditions. Then determine the duration from the starting operation time point of the charging system to the acquisition time point corresponding to the first data, the second data, and the third data, so as to determine the operation duration of the charging system according to the starting operation time point and the acquisition time point. And obtain the operation environment data of the charging system. The operation environment data includes the temperature data of the charging pile operation environment. After obtaining the operation duration and the operation environment data, obtain the predicted temperature of the charging system according to the predicted current, the temperature prediction model, the operation duration, the operation environment data, and the state of charge of the real-time battery pack, and the predicted temperature represents the temperature of the predicted charging system under normal conditions.

[0039] Calculate the current deviation rate according to the predicted current, the first current, and the second current. The specific formula for calculating the current deviation rate is as follows: ; where is the current deviation rate, I3 is the predicted current, and I4 is the sum of the first current and the second current.

[0040] Calculate the temperature deviation rate according to the predicted temperature, the first temperature, and the second temperature. The specific formula for calculating the temperature deviation rate is as follows: ; where is the temperature deviation rate, T5 is the predicted temperature, and T6 is the sum of the first temperature and the second temperature.

[0041] It can be seen that in this example, after calculating the predicted current and predicted temperature based on the current prediction model and temperature prediction model, the current deviation rate and temperature deviation rate are calculated, improving the accuracy of the calculation results.

[0042] In a possible example, the current prediction model is determined according to the following steps: Obtain a plurality of first historical data of the charging pile collected by the first intelligent fuse under various working conditions, a plurality of second historical data of the vehicle-mounted battery module collected by the second intelligent fuse, and a plurality of third historical data of the vehicle-mounted battery module collected by the voltage detection circuit. The various working conditions characterize the operating conditions of the charging pile with different additional circuit modules in various operating environments. The first historical data includes the first historical current, the first historical voltage, and the first historical temperature. The second historical data includes the second historical current and the second historical temperature. The third historical data includes the second historical voltage and the state of charge of the first battery pack; Based on the plurality of first historical data, the plurality of second historical data, and the plurality of third historical data, train a reference current change model to obtain the current change model, and the current change model is: I1 = a0 + a1×V1 + a2×V2 + a3×T1 + a4×T2 + a5×N; where, the I1 is the predicted current, the V1 is the first voltage, the V2 is the second voltage, the T1 is the first temperature, the T2 is the second temperature, the a0, the a1, the a2, the a3, the a4, and the a5 are constants, and the N is the state of charge of the real-time battery pack.

[0043] In a specific example, since the charging pile can be equipped with different additional circuit modules and operate in various operating environments, it is necessary to obtain a plurality of first historical data of the charging pile collected by the first intelligent fuse under various working conditions, a plurality of second historical data of the vehicle-mounted battery module collected by the second intelligent fuse, and a plurality of third historical data of the vehicle-mounted battery module collected by the voltage detection circuit. Among them, the collected first historical data, second historical data, and third historical data are the data when the charging system is operating normally. Obtain the reference current change model, and substitute the first historical data, second historical data, and third historical data into the reference current change model: I 11 = a0 + a1×V 11 + a2×V 12 + a3×T 11 + a4×T 12 + a5×N1; where, I 11 is the sum of the first historical current in the first historical data and the second historical current in the second historical data, V 11 is the first historical voltage, V12 is the second historical voltage, T 11 is the first historical temperature, T 12 is the second historical temperature, and N1 is the state of charge of the first historical battery pack.

[0044] Determine the values of a0, a1, a2, a3, a4, and a5 based on the reference current change model, the first historical data, the second historical data, and the third historical data. Substitute the determined a0, a1, a2, a3, a4, and a5 into the reference current change model to obtain the current change model: I1 = a0 + a1×V1 + a2×V2 + a3×T1 + a4×T2 + a5×N.

[0045] It can be seen that in this example, the reference current change model is trained based on historical data to obtain the current change model, improving the accuracy of the model output data.

[0046] In a possible example, obtain multiple fourth historical data of the charging pile collected by the first intelligent fuse under multiple working conditions, multiple fifth historical data of the vehicle-mounted battery module collected by the second intelligent fuse, the state of charge of multiple second historical battery packs collected by the voltage detection circuit, multiple historical operation durations, and multiple historical environmental data. The multiple working conditions characterize the operation of the charging pile with different additional circuit modules in multiple operating environments. The fourth historical data includes the fourth temperature and the fourth current, and the fifth historical data includes the fifth temperature and the fifth current; train the reference temperature change model based on the multiple fourth historical data, the multiple fifth historical data, the state of charge of the multiple second historical battery packs, the multiple historical operation durations, and the multiple historical environmental data to obtain the temperature change model, and the temperature change model is: T3 = b0 + b1t + b2I2 + b3T4 + b4M + b5t 2 + b6I2 2 + b7T4 2 + b8M 2 + b9tI2 + b 10 tT4 + b 11 tM + b 12 I2T4 + b 13 I2M + b 14 T4M; where, the T3 is the predicted temperature, the t is the operation duration, the I2 is the predicted normal current, the T4 is the temperature data in the operation environmental data, the M is the state of charge of the real-time battery pack, the b0, the b1, the b2, the b3, the b4, the b5, the b6, the b7, the b8, the b9, the b 10 、the b 11, the said b 12 , the said b 13 and the said b 14 are constants.

[0047] In a specific example, multiple fourth historical data of the charging pile collected by the first intelligent fuse, multiple fifth historical data of the in-vehicle battery module collected by the second intelligent fuse, and the state of charge of multiple second historical battery packs of the in-vehicle battery module collected by the voltage detection circuit are obtained, and multiple historical operation durations and multiple historical environmental data are obtained. The reference temperature change model is trained with the obtained data. The reference temperature change model can be a model generated by the polynomial fitting method. The reference temperature change model can be: T 23 =b0 + b1t2 + b2I 22 +b4T 24 +b4M2 + b5t2 2 +b6I 22 2 +b7T 24 2 +b8M2 2 +b9t2I 22 +b 10 t2T 24 +b 11 t2M2 + b 12 I 22 T 24 +b 13 I 22 M2 + b 14 T 24 M2, so as to calculate and obtain the values of b0, b1, b2, b3, b4, b5, b6, b7, b8, b9, b 10 , b 11 , b 12 , b 13 and b 14 The obtained values are substituted into the reference temperature change model to obtain the temperature change model. Among them, T 23 is the sum of the fourth historical temperature and the fifth historical temperature, t2 is the historical operation duration, I 22 is the sum of the fourth historical current and the fifth historical current, T 24 is the temperature data in the historical environmental data, and M2 is the state of charge of the second historical battery pack.

[0048] It can be seen that in this example, the reference temperature change model is trained based on historical data, so as to obtain the temperature change model and improve the accuracy of the model output data.

[0049] In a possible example, an current prediction model can also be determined based on a neural network algorithm, multiple first historical data of the charging pile collected by the first intelligent fuse under multiple working conditions, multiple second historical data of the vehicle-mounted battery module collected by the second intelligent fuse, and multiple third historical data of the vehicle-mounted battery module collected by the voltage detection circuit.

[0050] In a possible example, multiple first historical data of the charging pile, multiple second historical data of the vehicle-mounted battery module, and multiple third historical data of the vehicle-mounted battery module under different working conditions can be obtained. A reference current change model is trained based on the data corresponding to each working condition to obtain different current change models corresponding to different working conditions. Similarly, multiple fourth historical currents of the charging pile, multiple fifth historical currents, state of charge of multiple second historical battery packs, multiple historical operation durations, and multiple historical environmental data under different working conditions are obtained to train a reference temperature change model, and different temperature change models corresponding to different working conditions are obtained. Before receiving the first data of the charging pile collected by the first intelligent fuse, the second data of the vehicle-mounted battery module collected by the second intelligent fuse, and the third data of the vehicle-mounted battery module collected by the voltage detection circuit, a current change model and a temperature change model are matched from different current change models and different temperature change models based on the basic information of the target installation circuit module and the real-time operating environment data. The current deviation rate and the temperature deviation rate are calculated based on the matched current change model and temperature change model to further improve the accuracy of the data determined based on the model. Among them, the basic information includes information such as the installation circuit module identifier and the charging power.

[0051] In a possible example, if it is determined that the current and temperature of the charging system are abnormal according to the current deviation rate and the temperature deviation rate, and the abnormal time point of the temperature precedes the abnormal time point of the current, then a target adjustment scheme is determined according to the current deviation rate and the temperature deviation rate, including: obtaining a normal current deviation rate range and a normal temperature deviation rate range; if the current deviation rate exceeds the normal current deviation rate range and the temperature deviation rate exceeds the normal temperature deviation rate range, then obtain the abnormal time point of the temperature and the abnormal time point of the current; if the abnormal time point of the temperature precedes the abnormal time point of the current, then determine that the charging system is abnormal; determine the target current abnormal deviation range to which it belongs from multiple current abnormal deviation ranges according to the current deviation rate; and determine the target temperature abnormal deviation range to which it belongs from multiple temperature abnormal deviation ranges according to the temperature deviation rate; search for the target adjustment scheme in a preset database according to the target current abnormal deviation range and the target temperature abnormal deviation range, and the preset database includes the corresponding relationship between different current abnormal deviation ranges, different temperature abnormal deviation ranges, and different adjustment schemes.

[0052] In a specific example, after obtaining the current deviation rate and the temperature deviation rate, the normal current deviation rate range and the normal temperature deviation rate range are obtained. It is determined whether the current deviation rate is within the normal current deviation rate range and whether the temperature deviation rate is within the normal temperature deviation rate range. If the current deviation rate exceeds the normal current deviation rate range and the temperature deviation rate exceeds the normal temperature deviation rate range, then the abnormal time point of the temperature and the abnormal time point of the current are further obtained. The sequence of the abnormal time point of the temperature and the abnormal time point of the current is compared. If the abnormal time point of the temperature precedes the abnormal time point of the current, it is determined that the charging system is abnormal. For example, if the target additional circuit module is an adapter, its resistance increases due to temperature rise, resulting in an abnormal decrease in the charging current, so it is determined that the charging system is abnormal.

[0053] After determining the abnormalities of the temperature and the current, further, the change rules of the temperature and the current within a preset time period can be combined to determine whether the abnormal result is accurate. That is, if the first temperature and the second temperature continuously increase within the preset time period, and the first current and the second current continuously decrease, it is determined that the charging system is abnormal, avoiding the influence of temporary power fluctuations on the judgment result and improving the accuracy of the determination result.

[0054] After determining that the charging system is abnormal, the target current abnormal deviation range to which it belongs is determined from multiple current abnormal deviation ranges according to the current deviation rate, and the target temperature abnormal deviation range to which it belongs is determined from multiple temperature abnormal deviation ranges according to the temperature deviation rate. The multiple current abnormal deviation ranges and the multiple temperature abnormal deviation ranges are preset deviation ranges. The target adjustment scheme is searched from the preset database according to the target current abnormal deviation range and the target temperature abnormal deviation range. The preset database includes the corresponding relationships between different current abnormal deviation ranges, different temperature abnormal deviation ranges, and different adjustment schemes.

[0055] For example, the multiple current abnormal deviation ranges include a first current abnormal deviation range and a second current abnormal deviation range, where the first current deviation range is greater than 5% and less than or equal to 8%, and the second current abnormal deviation range is greater than 8% and less than or equal to 12%. The multiple temperature abnormal deviation ranges include a first temperature abnormal deviation range and a second temperature abnormal deviation range. The first temperature deviation range is greater than 5% and less than or equal to 8%, and the second temperature abnormal deviation range is greater than 8% and less than or equal to 12%.

[0056] If it is determined that the current deviation rate is within the first current deviation range and the temperature deviation rate is within the first temperature deviation range, the adjustment scheme corresponding to the first current deviation range and the first temperature deviation range is searched from the preset database, and this adjustment scheme is the target adjustment scheme.

[0057] Among them, different current abnormal deviation ranges and different temperature abnormal deviation ranges correspond to different adjustment schemes. Specifically, the larger the current deviation rate and the temperature deviation rate are, the higher the warning level is. For example, the adjustment scheme corresponding to the first current deviation range and the first temperature deviation range can be: reminding the user to pay attention to observing the charging situation, and at the same time reducing the charging power of the charging system by 10% - 20%. The adjustment scheme corresponding to the first current deviation range and the second temperature deviation range, or the second current deviation range and the first temperature deviation range can be: reducing the charging power to 50% - 70%, and suggesting that the user stop charging as soon as possible and check the adapter. The adjustment scheme corresponding to the second current deviation range and the second temperature deviation range can be: immediately stopping charging, cutting off the charging circuit, preventing the fault from deteriorating further, and notifying professional maintenance personnel for inspection and repair.

[0058] It can be seen that in this example, it is determined whether the charging system is abnormal based on the current deviation rate and the temperature deviation rate, and the corresponding adjustment scheme is determined by combining the deviation degrees of the current deviation rate and the temperature deviation rate, which improves the rationality of the adjustment and the safety of the charging system.

[0059] In a possible example, before receiving the first data of the charging pile collected by the first intelligent fuse, the second data of the vehicle-mounted battery module collected by the second intelligent fuse, and the third data of the vehicle-mounted battery module collected by the voltage detection circuit, it further includes: collecting the charging power of the target additional circuit module; adjusting the first fusing current of the first intelligent fuse and the second fusing current of the second intelligent fuse according to the charging power.

[0060] In a specific example, before receiving the first data of the charging pile collected by the first intelligent fuse, the second data of the vehicle-mounted battery module collected by the second intelligent fuse, and the third data of the vehicle-mounted battery module collected by the voltage detection circuit, the control module collects the charging power of the target additional circuit module, and adjusts the first fusing current of the first intelligent fuse and the second fusing current of the second intelligent fuse according to the charging power, so that the intelligent fuse can respond in time when the charging system with different additional circuit modules installed is abnormal, and improve the safety of the charging system.

[0061] The above mainly introduced the solution of the embodiments of the present application from the perspective of the execution process of the method side. It can be understood that in order for the electronic device to implement the above functions, it includes the corresponding hardware structure and / or software module for executing each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments provided herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the form of hardware or computer software driving the hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0062] The embodiments of the present application can divide the functional units of the electronic device according to the above method examples. For example, each functional unit can be divided corresponding to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. It should be noted that the division of units in the embodiments of the present application is illustrative, only a logical functional division, and there can be other division methods in actual implementation.

[0063] In the case of dividing each functional module corresponding to each function, the following will be combined with Figure 4 to illustrate a charging protection device based on an intelligent fuse in the embodiments of the present application. Figure 4 It is a functional unit composition block diagram of a charging protection device based on an intelligent fuse provided by the embodiments of the present application.

[0064] A charging protection device based on an intelligent fuse is applied to the control module of a charging system. The charging system includes the control module, a vehicle-mounted battery module and a charging pile connected to the control module. The charging pile is provided with a target additional circuit module. The device includes: A receiving unit 401, configured to receive the first data of the charging pile collected by the first intelligent fuse, the second data of the vehicle-mounted battery module collected by the second intelligent fuse, and the third data of the vehicle-mounted battery module collected by a voltage detection circuit. The first data includes a first current, a first voltage and a first temperature. The second data includes a second current and a second temperature. The third data includes a second voltage and the state of charge of the real-time battery pack; A processing unit 402, configured to preprocess the first data, the second data and the third data to obtain the preprocessed first data, second data and third data; An acquisition unit 403, configured to obtain a current deviation rate and a temperature deviation rate according to a preset current prediction model, temperature prediction model, the preprocessed first data, second data, and third data; A determination unit 404, configured to, if it is determined that the current and temperature of the charging system are abnormal according to the current deviation rate and the temperature deviation rate, and the abnormal time point of the temperature precedes the abnormal time point of the current, determine a target adjustment scheme according to the current deviation rate and the temperature deviation rate; An adjustment unit 405, configured to adjust the charging system according to the target adjustment scheme.

[0065] In a possible example, the processing unit 402 is further configured to: perform median filtering and moving average filtering on the first data, the second data, and the third data to obtain filtered first data, second data, and third data; and perform normalization processing on the filtered first data, second data, and third data to obtain the preprocessed first data, second data, and third data.

[0066] In a possible example, the acquisition unit 403 is further configured to: input the preprocessed first data, second data, and third data into the current prediction model to obtain the predicted current of the charging system; and obtain the running duration and running environment data of the charging system, where the running duration represents the duration from the start time point of the charging system operation to the acquisition time point corresponding to the first data, the second data, and the third data; and obtain the predicted temperature of the charging system according to the predicted current, the temperature prediction model, the running duration, the running environment data, and the state of charge of the real-time battery pack; and calculate the current deviation rate according to the predicted current, the first current, and the second current; and calculate the temperature deviation rate according to the predicted temperature, the first temperature, and the second temperature.

[0067] In a possible example, the current prediction model is determined according to the following steps: obtaining a plurality of first historical data of the charging pile collected by the first intelligent fuse under various working conditions, a plurality of second historical data of the in-vehicle battery module collected by the second intelligent fuse, and a plurality of third historical data of the in-vehicle battery module collected by the voltage detection circuit, where the various working conditions characterize the operating conditions of the charging pile with different additional circuit modules in various operating environments, the first historical data includes first historical current, first historical voltage, and first historical temperature, the second historical data includes second historical current and second historical temperature, and the third historical data includes second historical voltage and the state of charge of the first historical battery pack; and training a reference current change model based on the plurality of first historical data, the plurality of second historical data, and the plurality of third historical data to obtain the current change model, and the current change model is: I1 = a0 + a1×V1 + a2×V2 + a3×T1 + a4×T2 + a5×N; Wherein, I1 is the predicted current, V1 is the first voltage, V2 is the second voltage, T1 is the first temperature, T2 is the second temperature, a0, a1, a2, a3, a4, and a5 are constants, and N is the state of charge of the real-time battery pack.

[0068] In a possible example, the temperature prediction model is determined according to the following steps: obtaining a plurality of fourth historical data of the charging pile collected by the first intelligent fuse under various working conditions, a plurality of fifth historical data of the in-vehicle battery module collected by the second intelligent fuse, the state of charge of a plurality of second historical battery packs of the in-vehicle battery module collected by the voltage detection circuit, a plurality of historical operation durations, and a plurality of historical environmental data, where the various working conditions characterize the operating conditions of the charging pile with different additional circuit modules in various operating environments, the fourth historical data includes fourth temperature and fourth current, and the fifth historical data includes fifth temperature and fifth current; and training a reference temperature change model based on the plurality of fourth historical data, the plurality of fifth historical data, the state of charge of the plurality of second historical battery packs, the plurality of historical operation durations, and the plurality of historical environmental data to obtain the temperature change model, and the temperature change model is: T3 = b0 + b1t + b2I2 + b3T4 + b4M + b5t 2 + b6I2 2 + b7T4 2 + b8M 2 + b9tI2 + b 10 tT4 + b 11 tM + b12 I2T4 + b 13 I2M + b 14 T4M; Wherein, T3 is the predicted temperature, t is the running duration, I2 is the predicted current, T4 is the temperature data in the operating environment data, M is the state of charge of the real-time battery pack, and b0, b1, b2, b3, b4, b5, b6, b7, b8, b9, b 10 、the b 11 、the b 12 、the b 13 and the b 14 are constants.

[0069] In a possible example, the determining unit 404 is further configured to: obtain a normal current deviation rate range and a normal temperature deviation rate range; and if the current deviation rate exceeds the normal current deviation rate range and the temperature deviation rate exceeds the normal temperature deviation rate range, obtain the abnormal time point of the temperature and the abnormal time point of the current; and if the abnormal time point of the temperature precedes the abnormal time point of the current, determine that the charging system is abnormal; and determine the target current abnormal deviation range to which it belongs from multiple current abnormal deviation ranges according to the current deviation rate; and determine the target temperature abnormal deviation range to which it belongs from multiple temperature abnormal deviation ranges according to the temperature deviation rate; and look up the target adjustment scheme in a preset database according to the target current abnormal deviation range and the target temperature abnormal deviation range, where the preset database includes the corresponding relationships between different current abnormal deviation ranges, different temperature abnormal deviation ranges, and different adjustment schemes.

[0070] In a possible example, the device further includes a collection unit, configured to: collect the charging power of the target additional circuit module; and adjust the first fusing current of the first intelligent fuse and the second fusing current of the second intelligent fuse according to the charging power.

[0071] Please combine Figure 5 , Figure 5 This is a schematic structural diagram of a control module provided by an embodiment of the present application. As Figure 5 shown, the control module includes a processor 501, a communication module 502, a memory 503, and a program 504. The number of the processors 501 can be set according to actual needs, and the processor 501 is communicatively connected to the memory 503 and the communication module 502 through an internal communication bus.

[0072] Among them, the program 504 is stored in the above-mentioned memory 503 and is configured to be executed by the above-mentioned processor 501. The program 504 includes instructions for executing any step in the above-mentioned method embodiments. It can be understood that the number of programs 504 can be set according to actual needs, and specific details are not limited here.

[0073] Among them, the processor 501 can be, for example, a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logical blocks, units, and circuits described in connection with the disclosure of the present application. The processor 501 can also be a combination that realizes computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and so on. The communication unit can be a communication module 502, a transceiver, a transceiver circuit, etc., and the storage unit can be a memory 503.

[0074] The memory 503 can be a volatile memory, a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM).

[0075] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired or wireless manner. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains one or more collections of available media. The available media can be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0076] An embodiment of the present application further provides a computer storage medium. The computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute some or all of the steps of any of the methods described in the foregoing method embodiments. The computer includes an electronic device.

[0077] An embodiment of the present application further provides a computer program product. The computer program product includes a computer program, and the computer program is operable to enable a computer to execute some or all of the steps of any of the methods described in the foregoing method embodiments.

[0078] The computer program product can be a software installation package, and the computer includes an electronic device.

[0079] It should be understood that in various embodiments of the present application, the magnitudes of the serial numbers of the foregoing processes do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0080] In several embodiments provided by the present application, it should be understood that the disclosed methods, devices, and systems can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation; for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, and the indirect coupling or communication connection of the device or unit may be in electrical, mechanical or other forms.

[0081] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0082] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can be physically included separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware, or in the form of hardware plus software functional units.

[0083] The integrated unit implemented in the form of software functional units can be stored in a computer-readable storage medium. The above-mentioned software functional units are stored in a storage medium and include a number of instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute some steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs that can store program codes.

[0084] Although the present invention is disclosed as above, the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions without departing from the spirit and scope of the present invention, and can make various changes and modifications, including combinations of the above different functions and implementation steps, including software and hardware implementation manners, which are all within the protection scope of the present invention.

Claims

1. A charging protection method based on an intelligent fuse, characterized in that, A control module applied to a charging system, the charging system including the control module, a vehicle-mounted battery module and a charging pile connected to the control module, the charging pile being provided with a target additional circuit module, the method comprising: Receiving first data of the charging pile collected by a first intelligent fuse, second data of the vehicle-mounted battery module collected by a second intelligent fuse, and third data of the vehicle-mounted battery module collected by a voltage detection circuit, the first data including a first current, a first voltage and a first temperature, the second data including a second current and a second temperature, and the third data including a second voltage and the state of charge of the real-time battery pack; Performing preprocessing on the first data, the second data and the third data to obtain preprocessed first data, second data and third data; Obtaining a current deviation rate and a temperature deviation rate according to a preset current prediction model, temperature prediction model, the preprocessed first data, second data and third data; If it is determined that the current and temperature of the charging system are abnormal according to the current deviation rate and the temperature deviation rate, and the abnormal time point of the temperature precedes the abnormal time point of the current, then determining a target adjustment scheme according to the current deviation rate and the temperature deviation rate; Adjusting the charging system according to the target adjustment scheme.

2. The method according to claim 1, characterized in that, The performing preprocessing on the first data, the second data and the third data to obtain preprocessed first data, second data and third data includes: Performing median filtering and moving average filtering on the first data, the second data and the third data to obtain filtered first data, second data and third data; Performing normalization processing on the filtered first data, second data and third data to obtain the preprocessed first data, second data and third data.

3. The method according to claim 1, wherein The obtaining a current deviation rate and a temperature deviation rate according to a preset current prediction model, temperature prediction model, the preprocessed first data, second data and third data includes: Inputting the preprocessed first data, second data and third data into the current prediction model to obtain a predicted current of the charging system; Obtaining the operation duration and operation environment data of the charging system, the operation duration representing the duration from the starting operation time point of the charging system to the acquisition time point corresponding to the first data, the second data and the third data; Obtaining a predicted temperature of the charging system according to the predicted current, the temperature prediction model, the operation duration, the operation environment data and the state of charge of the real-time battery pack; Calculating the current deviation rate according to the predicted current, the first current and the second current; Calculating the temperature deviation rate according to the predicted temperature, the first temperature and the second temperature.

4. The method according to claim 3, characterized in that, The current prediction model is determined according to the following steps: Obtain multiple first historical data of the charging pile collected by the first intelligent fuse under multiple working conditions, multiple second historical data of the vehicle-mounted battery module collected by the second intelligent fuse, and multiple third historical data of the vehicle-mounted battery module collected by the voltage detection circuit. The multiple working conditions characterize the operating conditions of the charging pile with different additional circuit modules under multiple operating environments. The first historical data includes the first historical current, the first historical voltage, and the first historical temperature. The second historical data includes the second historical current and the second historical temperature. The third historical data includes the second historical voltage and the state of charge of the first historical battery pack; Train a reference current change model based on the multiple first historical data, the multiple second historical data, and the multiple third historical data to obtain the current change model. The current change model is: I1 = a0 + a1×V1 + a2×V2 + a3×T1 + a4×T2 + a5×N; Wherein, I1 is the predicted current, V1 is the first voltage, V2 is the second voltage, T1 is the first temperature, T2 is the second temperature, a0, a1, a2, a3, a4, and a5 are constants, and N is the state of charge of the real-time battery pack.

5. The method according to claim 3, wherein The temperature prediction model is determined according to the following steps: Obtain multiple fourth historical data of the charging pile collected by the first intelligent fuse under multiple working conditions, multiple fifth historical data of the vehicle-mounted battery module collected by the second intelligent fuse, the state of charge of multiple second historical battery packs collected by the voltage detection circuit, multiple historical operation durations, and multiple historical environment data. The multiple working conditions characterize the operating conditions of the charging pile with different additional circuit modules under multiple operating environments. The fourth historical data includes the fourth temperature and the fourth current. The fifth historical data includes the fifth temperature and the fifth current; Train a reference temperature change model based on the multiple fourth historical data, the multiple fifth historical data, the state of charge of the multiple second historical battery packs, the multiple historical operation durations, and the multiple historical environment data to obtain the temperature change model. The temperature change model is: T3 = b0 + b1t + b2I2 + b3T4 + b4M + b5t 2 + b6I2 2 + b7T4 2 + b8M 2 + b9tI2 + b 10 tT4 + b 11 tM + b 12 I2T4 + b 13 I2M + b 14 T4M; Wherein, T3 is the predicted temperature, t is the running duration, I2 is the predicted current, T4 is the temperature data in the operating environment data, M is the state of charge of the real-time battery pack, and b0, b1, b2, b3, b4, b5, b6, b7, b8, b9, b 10 , b 11 , b 12 , b 13 , and b 14 are constants.

6. The method according to any one of claims 1-5, characterized in that If it is determined that the current and temperature of the charging system are abnormal according to the current deviation rate and the temperature deviation rate, and the abnormal time point of the temperature precedes the abnormal time point of the current, then determine the target adjustment scheme according to the current deviation rate and the temperature deviation rate, including: Obtain the normal current deviation rate range and the normal temperature deviation rate range; If the current deviation rate exceeds the normal current deviation rate range and the temperature deviation rate exceeds the normal temperature deviation rate range, then obtain the abnormal time point of the temperature and the abnormal time point of the current; If the abnormal time point of the temperature precedes the abnormal time point of the current, then determine that the charging system is abnormal; Determine the target current abnormal deviation range to which it belongs from multiple current abnormal deviation ranges according to the current deviation rate; and Determine the target temperature abnormal deviation range to which it belongs from multiple temperature abnormal deviation ranges according to the temperature deviation rate; Look up the target adjustment scheme from a preset database according to the target current abnormal deviation range and the target temperature abnormal deviation range, where the preset database includes the correspondence between different current abnormal deviation ranges, different temperature abnormal deviation ranges, and different adjustment schemes.

7. The method according to any one of claims 1-5, characterized in that Before receiving the first data of the charging pile collected by the first intelligent fuse, the second data of the vehicle-mounted battery module collected by the second intelligent fuse, and the third data of the vehicle-mounted battery module collected by the voltage detection circuit, it further includes: Collect the charging power of the target additional circuit module; Adjust the first fusing current of the first intelligent fuse and the second fusing current of the second intelligent fuse according to the charging power.

8. A charging protection device based on an intelligent fuse, characterized in that, Applied to the control module of the charging system, the charging system includes the control module, a vehicle-mounted battery module and a charging pile connected to the control module, the charging pile is provided with a target additional circuit module, and the device includes: A receiving unit, configured to receive the first data of the charging pile collected by the first intelligent fuse, the second data of the vehicle-mounted battery module collected by the second intelligent fuse, and the third data of the vehicle-mounted battery module collected by the voltage detection circuit, where the first data includes a first current, a first voltage, and a first temperature, the second data includes a second current and a second temperature, and the third data includes a second voltage and the state of charge of the real-time battery pack; A processing unit, configured to preprocess the first data, the second data, and the third data to obtain the preprocessed first data, second data, and third data; An obtaining unit, configured to obtain a current deviation rate and a temperature deviation rate according to a preset current prediction model, temperature prediction model, the preprocessed first data, second data, and third data; A determining unit, configured to, if it is determined that the current and temperature of the charging system are abnormal according to the current deviation rate and the temperature deviation rate, and the abnormal time point of the temperature precedes the abnormal time point of the current, determine a target adjustment scheme according to the current deviation rate and the temperature deviation rate; An adjusting unit, configured to adjust the charging system according to the target adjustment scheme.

9. An electronic device, characterized in that, It includes: A processor and a memory, where the memory is used to store computer program code, the computer program code includes computer instructions, and when the processor executes the computer instructions, the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, A computer program is stored in the computer-readable storage medium, the computer program includes program instructions, and when the program instructions are executed by the processor, the processor is caused to execute the method according to any one of claims 1 to 7.

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