Self-adaptive temperature control adjustment and overload protection method for discharge gun

Abstract

The invention relates to the field of discharge gun temperature control adjustment, and discloses a self-adaptive temperature control adjustment and overload protection method for a discharge gun, which comprises the following steps of: collecting relevant parameters of the discharge gun and performing data preprocessing to construct a discharge gun temperature prediction model, and combining the discharge gun temperature prediction model to obtain a discharge gun temperature prediction model; and performing overload prediction judgment on the target discharge gun, performing fuzzy PID temperature control adjustment on the overloaded target discharge gun, and finally performing adaptive temperature control adjustment in combination with an adaptive optimization module. Extreme risks such as fire, electric shock and battery explosion can be avoided, the service life of the discharge gun and the battery is prolonged, and equipment shutdown caused by overheating or protection outage is avoided.

Description

Technical Field

[0001] The present invention relates to the field of temperature control regulation of a discharge gun, and particularly to an adaptive temperature control regulation and overload protection method for a discharge gun. Background Art

[0002] The discharge gun is a key component of an electric vehicle, which supports the reverse output of the electrical energy of the on-vehicle power battery to external devices or the power grid. Its function is opposite to that of the charging gun, realizing the function of "vehicle-to-grid discharging". The core working principle is that through the on-vehicle bidirectional charger (OBC), the direct current (DC) of the battery is converted into alternating current (AC) (such as 220V / 50Hz) for external devices to use, and the output voltage and current are dynamically adjusted according to the load demand to be compatible with different devices. The actual application scenarios of the discharge gun include providing emergency power for families and medical devices during power outages; driving induction cookers, lighting devices, etc. during camping; reverse power transmission to the power grid during peak power grid load periods to participate in power peak regulation; and performing temporary power replenishment for other power-deficient electric vehicles.

[0003] When the discharge gun generates electricity with a large current, heat will be generated due to the wire resistance. At the same time, the switching loss of power semiconductor devices and the influence of the ambient temperature will also generate heat. The high-temperature discharge gun will accelerate the aging of insulating materials, leading to the risk of electric leakage, and will reduce the battery life and cause thermal runaway. At the same time, when the actual output current of the discharge gun exceeds the rated value, and when the total power of the load device exceeds the maximum allowable discharge power of the vehicle, an overload phenomenon will occur. If the discharge gun is overloaded, the gun body plug / socket may melt and deform, the power device may break down, the battery capacity may have irreversible attenuation, etc., and it will even cause the carbonization of the line insulation layer, leading to electric leakage or short-circuit fire. To avoid the above situations, an adaptive temperature control regulation and overload protection method for a discharge gun is proposed. Summary of the Invention

[0004] The present invention overcomes the deficiencies of the prior art and provides an adaptive temperature control regulation and overload protection method for a discharge gun.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows: The first aspect of the present invention provides an adaptive temperature control regulation and overload protection method for a discharge gun, including the following steps: Collect the associated parameters of the discharge gun, and perform data preprocessing on the associated parameters of the discharge gun to obtain the preprocessed associated parameters of the discharge gun; Combine the preprocessed associated parameters of the discharge gun and the LSTM algorithm model to construct a target discharge gun temperature prediction model; Combine the target discharge gun temperature prediction model to perform overload prediction determination on the target discharge gun, and perform fuzzy PID temperature control regulation on the overloaded target discharge gun; In the target discharge gun, an adaptive temperature control adjustment of the target discharge gun is performed through an adaptive optimization module in combination with a fuzzy PID module.

[0006] Further, in a preferred embodiment of the present invention, the associated parameters of the discharge gun are collected, and data preprocessing is performed on the associated parameters of the discharge gun to obtain preprocessed associated parameters of the discharge gun, specifically: Determine the discharge gun, label it as the target discharge gun, obtain the operation manual of the target discharge gun, and based on the operation manual of the target discharge gun, determine the threshold values of the associated parameters of the target discharge gun; Among them, the threshold values of the associated parameters of the target discharge gun include the standard discharge current threshold value, the standard discharge voltage threshold value, the qualified threshold value of the working temperature of the discharge gun, and the standard coolant flow threshold value; Determine the discharge object of the discharge gun, label it as the device to be charged, connect the target discharge gun to the device to be charged for charging, and simultaneously preset the frequency of collecting associated parameters; Control the target discharge gun to perform a discharge process on the device to be charged, and during the discharge process, in combination with the frequency of collecting associated parameters, perform real-time collection and processing of the associated parameters of the target discharge gun to obtain the real-time associated parameters of the target discharge gun; Introduce a moving average filtering algorithm, and based on the moving average filtering algorithm, construct a moving average filtering window. Traverse and slide the real-time associated parameters of the target discharge gun through the moving average filtering window, and during the traversal and sliding process, calculate the average value of the real-time associated parameters of the target discharge gun within the moving average filtering window, so as to obtain the filtered real-time associated parameters of the target discharge gun, labeled as preprocessed associated parameters of the discharge gun.

[0007] Further, in a preferred embodiment of the present invention, the target discharge gun temperature prediction model is constructed by combining the preprocessed associated parameters of the discharge gun and the LSTM algorithm model, specifically: Introduce the LSTM algorithm model, and input the preprocessed associated parameters of the discharge gun into the LSTM algorithm model for storage; Determine the time window for analyzing the preprocessed associated parameters of the discharge gun in the LSTM algorithm model, and combine the time window to perform parameter segmentation on the preprocessed associated parameters of the discharge gun to obtain the preprocessed associated parameters of the discharge gun within the time window, labeled as a type of associated parameters of the discharge gun; Divide the type of associated parameters of the discharge gun into a training set and a validation set, and build the model architecture of the LSTM algorithm model. Among them, the method for building the model architecture of the LSTM algorithm model is to obtain the historical data network, and retrieve and output the model architecture of the LSTM algorithm model with the highest usage rate when performing LSTM analysis on the target discharge gun in the historical data network; Determine the loss function in the LSTM algorithm model after the model architecture is built, calibrate it as the target loss function, and perform training processing on the training set based on the target loss function. At the same time, analyze the loss curve in combination with the validation set during the training process; If the coincidence rate of the loss curves obtained from the training set and the validation set is less than the preset value, then perform hyperparameter tuning during the training process until the coincidence rate of the loss curves obtained from the training set and the validation set is not less than the preset value, and obtain the target discharge gun temperature prediction model.

[0008] Furthermore, in a preferred embodiment of the present invention, the target discharge gun temperature prediction model is combined to perform overload prediction determination on the target discharge gun, and fuzzy PID temperature control adjustment is performed on the overloaded target discharge gun. Specifically: Preset the operating time of the target discharge gun, predict the working temperature of the target discharge gun within the operating time of the target discharge gun through the target discharge gun temperature prediction model, and construct a working temperature change curve graph; Perform analysis on the change of the working temperature of the working temperature change curve graph, and calculate the dynamic current value of the target discharge gun during the change of the operating time and the change of the working temperature, which is calibrated as the dynamic current value to be analyzed; Based on the associated parameter threshold of the target discharge gun, perform overload analysis on the target discharge gun. If the dynamic current value to be analyzed does not remain within the standard discharge current threshold, it is determined that the target discharge gun has an overload phenomenon; At the same time, if the working temperature of the target discharge gun within the operating time of the target discharge gun does not remain within the qualified threshold of the discharge gun working temperature, it is also determined that the target discharge gun has an overload phenomenon; If the target discharge gun has an overload phenomenon, then combine the fuzzy PID temperature control device to perform fuzzy PID temperature control adjustment on the target discharge gun.

[0009] Furthermore, in a preferred embodiment of the present invention, the step of if the target discharge gun has an overload phenomenon, then combine the fuzzy PID temperature control device to perform fuzzy PID temperature control adjustment on the target discharge gun is specifically: For the discharge gun with an overload phenomenon, if through the target discharge gun temperature prediction model, it is predicted that the working temperature of the target discharge gun within the operating time of the target discharge gun does not remain within the qualified threshold of the discharge gun working temperature, or it is predicted that the dynamic current value to be analyzed does not remain within the standard discharge current threshold, it is determined that the target discharge gun is in predicted overload; If during the process of real-time acquisition and processing of the associated parameters of the target discharge gun, there is a situation where the working temperature of the target discharge gun does not remain within the qualified threshold of the discharge gun working temperature, or the real-time acquisition current of the target discharge gun does not remain within the standard discharge current threshold, it is determined that the target discharge gun is in real-time overload; Integrate the fuzzy PID module into the target discharge gun. If the target discharge gun is predicted to be overloaded, based on the fuzzy PID module, perform predictive overload protection on the target discharge gun; Among them, the predictive overload protection is to limit the discharge current output of the target discharge gun, and regulate the coolant flow rate of the target discharge gun through the fuzzy PID module to ensure that the coolant flow rate of the target discharge gun always remains within the coolant standard flow rate threshold; If the target discharge gun is in real-time overload, based on the fuzzy PID module, perform real-time overload protection on the target discharge gun; Among them, the real-time overload protection is to immediately cut off the power supply of the target discharge gun through the fuzzy PID module.

[0010] Furthermore, in a preferred embodiment of the present invention, the adaptive temperature control adjustment of the target discharge gun is performed by combining the adaptive optimization module and the fuzzy PID module in the target discharge gun, specifically as follows: In the target discharge gun, connect the adaptive optimization module, where the adaptive optimization module is used to perform adaptive temperature control adjustment on the target discharge gun; Based on the adaptive optimization module, record and store the surrounding environment parameters and historical operation records each time the target discharge gun is in an overloaded situation, and construct a dynamic adjustment fuzzy rule table according to all the recorded and stored data; Among them, all the working temperatures and discharge currents that the target discharge gun will output corresponding to different surrounding environment parameters and operation records are recorded in the dynamic adjustment fuzzy rule table; Update the dynamic adjustment fuzzy rule table in real-time, and introduce the dynamic adjustment fuzzy rule table into the fuzzy PID module for adaptive temperature control adjustment of the target discharge gun.

[0011] The second aspect of the present invention also provides an adaptive temperature control adjustment and overload protection system for a discharge gun. The adaptive temperature control adjustment and overload protection system includes a memory and a processor. The memory stores the adaptive temperature control adjustment and overload protection method. When the adaptive temperature control adjustment and overload protection method is executed by the processor, the following steps are implemented: Collect the associated parameters of the discharge gun, and perform data preprocessing on the associated parameters of the discharge gun to obtain the preprocessed associated parameters of the discharge gun; Combine the preprocessed associated parameters of the discharge gun and the LSTM algorithm model to construct a target discharge gun temperature prediction model; Combine the target discharge gun temperature prediction model to perform overload prediction determination on the target discharge gun, and perform fuzzy PID temperature control adjustment on the overloaded target discharge gun; In the target discharge gun, perform adaptive temperature control adjustment on the target discharge gun by combining the adaptive optimization module and the fuzzy PID module.

[0012] The technical defects existing in the background art solved by the present invention, the present invention has the following beneficial effects: collecting the associated parameters of the discharge gun and performing data preprocessing, for constructing a discharge gun temperature prediction model, combining the discharge gun temperature prediction model, performing an overload prediction determination on the target discharge gun, and performing a fuzzy PID temperature control adjustment on the overloaded target discharge gun, and finally performing an adaptive temperature control adjustment in combination with an adaptive optimization module. The present invention can avoid extreme risks such as fire, electric shock, battery explosion, etc., extend the service life of the discharge gun and the battery, and avoid equipment shutdown caused by overheating or protection power-off. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present invention 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 invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to these drawings.

[0014] Figure 1 Shows a flowchart of an adaptive temperature control adjustment and overload protection method for a discharge gun; Figure 2 Shows a method flowchart for performing an overload prediction determination on a target discharge gun and performing a fuzzy PID temperature control adjustment on the overloaded target discharge gun; Figure 3 Shows a program view of an adaptive temperature control adjustment and overload protection system for a discharge gun. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] In order to be able to more clearly understand the above objects, features and advantages of the present invention, the present invention will be further described in detail below in conjunction with the drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0016] Many specific details are set forth in the following description in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0017] Figure 1 Shows a flowchart of an adaptive temperature control adjustment and overload protection method for a discharge gun, including the following steps: S102: Collect the associated parameters of the discharge gun and perform data preprocessing on the associated parameters of the discharge gun to obtain preprocessed discharge gun associated parameters; S104: Combine the preprocessed discharge gun correlation parameters and the LSTM algorithm model to construct a target discharge gun temperature prediction model; S106: Combine the target discharge gun temperature prediction model to perform overloading prediction and determination on the target discharge gun, and perform fuzzy PID temperature control adjustment on the overloaded target discharge gun; S108: In the target discharge gun, combine the adaptive optimization module and the fuzzy PID module to perform adaptive temperature control adjustment on the target discharge gun.

[0018] Further, in a preferred embodiment of the present invention, the method for collecting the correlation parameters of the discharge gun and preprocessing the correlation parameters of the discharge gun to obtain the preprocessed discharge gun correlation parameters specifically includes: Determine the discharge gun, label it as the target discharge gun, obtain the operation manual of the target discharge gun, and based on the operation manual of the target discharge gun, determine the correlation parameter thresholds of the target discharge gun; Among them, the correlation parameter thresholds of the target discharge gun include the standard discharge current threshold, the standard discharge voltage threshold, the qualified threshold of the discharge gun operating temperature, and the standard coolant flow threshold; Determine the discharge object of the discharge gun, label it as the device to be charged, connect the target discharge gun to the device to be charged for charging, and simultaneously preset the correlation parameter collection frequency; Control the target discharge gun to perform discharge processing on the device to be charged, and during the discharge processing, combine the correlation parameter collection frequency to perform real-time collection and processing of the correlation parameters of the target discharge gun to obtain the real-time correlation parameters of the target discharge gun; Introduce a moving average filtering algorithm, and based on the moving average filtering algorithm, construct a moving average filtering window. Traverse and slide the moving average filtering window on the real-time correlation parameters of the target discharge gun, and during the traversal and sliding process, calculate the average value of the real-time correlation parameters of the target discharge gun within the moving average filtering window, so as to obtain the filtered real-time correlation parameters of the target discharge gun, which are labeled as the preprocessed discharge gun correlation parameters.

[0019] It should be noted that before the discharge gun performs adaptive temperature control adjustment and overload protection, it is necessary to determine the possible temperature and real-time current data generated during the operation of the discharge gun. Prediction can be carried out by constructing a model. Since constructing a model requires data conditions, it is necessary to collect the associated data during the operation of the discharge gun, that is, the standard discharge current threshold, the standard discharge voltage threshold, the qualified threshold of the discharge gun operating temperature, and the standard coolant flow threshold, which are used as the condition data for constructing the model and performing adaptive temperature control. After the data is collected, it is necessary to preprocess the data, including data filtering and noise reduction processing, because the collected data may have noise affecting the accuracy of the data. Therefore, combined with the moving average filtering algorithm, the associated data of the discharge gun collected is preprocessed.

[0020] Further, in a preferred embodiment of the present invention, the combined preprocessing of the discharge gun associated parameters and the LSTM algorithm model is used to construct a target discharge gun temperature prediction model, specifically as follows: Introduce the LSTM algorithm model and input the preprocessed discharge gun associated parameters into the LSTM algorithm model for storage; Determine the time window for analyzing the preprocessed discharge gun associated parameters in the LSTM algorithm model, and combine the time window to perform parameter segmentation on the preprocessed discharge gun associated parameters to obtain the preprocessed discharge gun associated parameters within the time window, which are labeled as a type of discharge gun associated parameters; Divide the type of discharge gun associated parameters into a training set and a validation set, and build the model architecture of the LSTM algorithm model. Among them, the method for building the model architecture of the LSTM algorithm model is to obtain the historical data network and retrieve and output the model architecture of the LSTM algorithm model with the highest usage rate when performing LSTM analysis on the target discharge gun in the historical data network; Determine the loss function in the LSTM algorithm model after the model architecture is built, which is labeled as the target loss function, and perform training processing on the training set based on the target loss function. At the same time, perform loss curve analysis in combination with the validation set during the training process; If the coincidence rate of the loss curves obtained from the training set and the validation set is less than the preset value, then perform hyperparameter tuning during the training process until the coincidence rate of the loss curves obtained from the training set and the validation set is not less than the preset value to obtain the target discharge gun temperature prediction model.

[0021] It should be noted that based on the LSTM model to predict the future temperature change of the discharge gun, it is necessary to construct an LSTM model and combine the data of the discharge gun for model training. First, construct an LSTM algorithm model and build its architecture. The purpose of using the model architecture of the LSTM algorithm model with the highest usage rate when performing LSTM analysis on the target discharge gun is that the LSTM algorithm model needs to build an architecture, such as determining the number of input layer features, the number of neurons in the LSTM layer, etc. The purpose of parameter segmentation of the preprocessed discharge gun correlation parameters in combination with the time window is to obtain time window data, so as to have a definite time for time step prediction and realize the construction of the model. The time window is usually the past sixty seconds and the future thirty seconds. The purposes of obtaining the training set and the validation set are to train the model parameters and tune the hyperparameters respectively to prevent overfitting. The loss function is to calculate the mean square error of the data during the training process. Combining the validation set for loss curve analysis is to compare the coincidence rate between the predicted value and the true value. If the coincidence rate is large, it is judged that the predicted value output by the model is close to the true value and can be directly output for use, and the temperature prediction model of the target discharge gun is obtained.

[0022] Further, in a preferred embodiment of the present invention, in the target discharge gun, the adaptive optimization module is combined with the fuzzy PID module to perform adaptive temperature control adjustment on the target discharge gun, specifically as follows: In the target discharge gun, connect the adaptive optimization module, where the adaptive optimization module is used to perform adaptive temperature control adjustment on the target discharge gun; Based on the adaptive optimization module, record and store the surrounding environment parameters and historical operation records each time the target discharge gun is in an overload situation, and construct a dynamic adjustment fuzzy rule table according to all the recorded and stored data; Among them, all the working temperatures and discharge currents that the target discharge gun will output corresponding to different surrounding environment parameters and operation records are recorded in the dynamic adjustment fuzzy rule table; The dynamic adjustment fuzzy rule table is updated in real time, and the dynamic adjustment fuzzy rule table is introduced into the fuzzy PID module to perform adaptive temperature control adjustment on the target discharge gun.

[0023] It should be noted that the adaptive optimization module can perform intelligent learning of the discharge gun in combination with the fuzzy PID module, that is, perform adaptive temperature control adjustment of the discharge gun. Recording and storing the surrounding environment parameters and historical operation records each time the target discharge gun is in an overload situation can judge the influence on the discharge gun under different combinations of surrounding environment parameters and operation records. For example, when the environmental temperature is high and the operation of the discharge gun is improper, it may all lead to temperature rise. Therefore, after generating the dynamic adjustment fuzzy rule table, when the discharge gun has corresponding situations, it can be adaptively adjusted in combination with the fuzzy PID module, such as power off and other processing, to achieve adaptive temperature control adjustment.

[0024] Figure 2 A method flow chart for performing overload prediction determination on a target discharge gun and performing fuzzy PID temperature control adjustment on the overloaded target discharge gun is shown, including the following steps: S202: Combine the target discharge gun temperature prediction model to perform overload prediction determination on the target discharge gun, and perform fuzzy PID temperature control adjustment on the overloaded target discharge gun; S204: If there is an overload phenomenon in the target discharge gun, combine the fuzzy PID temperature control device to perform fuzzy PID temperature control adjustment on the target discharge gun.

[0025] Furthermore, in a preferred embodiment of the present invention, the combining the target discharge gun temperature prediction model to perform overload prediction determination on the target discharge gun and performing fuzzy PID temperature control adjustment on the overloaded target discharge gun is specifically as follows: Preset the operating time of the target discharge gun, predict the working temperature of the target discharge gun during the operating time of the target discharge gun through the target discharge gun temperature prediction model, and construct a working temperature change curve graph; Perform working temperature change analysis on the working temperature change curve graph, and calculate the dynamic current value of the target discharge gun during the change of the operating time and the change of the working temperature, and calibrate it as the dynamic current value to be analyzed; Based on the associated parameter threshold of the target discharge gun, perform overload analysis on the target discharge gun. If the dynamic current value to be analyzed does not remain within the standard discharge current threshold, it is determined that the target discharge gun has an overload phenomenon; At the same time, if the working temperature of the target discharge gun during the operating time of the target discharge gun does not remain within the qualified threshold of the discharge gun working temperature, it is also determined that the target discharge gun has an overload phenomenon; If the target discharge gun has an overload phenomenon, combine the fuzzy PID temperature control device to perform fuzzy PID temperature control adjustment on the target discharge gun.

[0026] It should be noted that by predicting the working temperature of the discharge gun during the target operating time and constructing a working temperature change curve graph, the change of the temperature can be known more clearly and intuitively. Combining the change of the working temperature and calculating the dynamic current value to be analyzed is for the purpose of judging whether the discharge gun has an overload. The calculation formula is: ; Wherein, is the rated maximum current, α is the attenuation coefficient, is the safety temperature threshold, is the critical temperature threshold. The above data can be obtained from the working temperature change curve graph for analysis, so as to calculate the dynamic current value to be analyzed. If the current is too large, it will directly cause overload, and if the temperature is too high, it will also cause an overload phenomenon.

[0027] Further, in a preferred embodiment of the present invention, if there is an overload phenomenon in the target discharge gun, the fuzzy PID temperature control device is combined to perform fuzzy PID temperature control adjustment on the target discharge gun, specifically as follows: For a discharge gun with an overload phenomenon, if it is predicted by the target discharge gun temperature prediction model that the operating temperature of the target discharge gun during the operating time of the target discharge gun does not remain within the qualified threshold of the discharge gun operating temperature, or it is predicted that the dynamic current value to be analyzed does not remain within the standard discharge current threshold, then it is determined that the target discharge gun is in predicted overload; If during the real-time acquisition and processing of the associated parameters of the target discharge gun, there is a situation where the operating temperature of the target discharge gun does not remain within the qualified threshold of the discharge gun operating temperature, or the real-time acquired current of the target discharge gun does not remain within the standard discharge current threshold, then it is determined that the target discharge gun is in real-time overload; Integrate the fuzzy PID module for the target discharge gun. If the target discharge gun is in predicted overload, then based on the fuzzy PID module, perform predicted overload protection on the target discharge gun; Among them, the predicted overload protection is to limit the discharge current output of the target discharge gun, and regulate the coolant flow rate of the target discharge gun through the fuzzy PID module to ensure that the coolant flow rate of the target discharge gun always remains within the standard coolant flow threshold; If the target discharge gun is in real-time overload, then based on the fuzzy PID module, perform real-time overload protection on the target discharge gun; Among them, the real-time overload protection is to immediately cut off the power of the target discharge gun through the fuzzy PID module.

[0028] It should be noted that the overload of the discharge gun includes predicted overload and real-time overload. By obtaining the predicted operation temperature data through the model and combining the calculated current value to determine whether there is an overload situation, it is predicted overload. And by real-time monitoring the operating temperature and current value of the discharge gun to determine real-time overload. Predicted overload needs to be prevented, including limiting power operation. Limiting the current to a small probability and ensuring the full power operation of the cooling system. While real-time overload requires direct power-off to prevent harm caused by overload.

[0029] As Figure 3 shown, in the second aspect of the present invention, an adaptive temperature control adjustment and overload protection system for a discharge gun is also provided. The adaptive temperature control adjustment and overload protection system includes a memory 31 and a processor 32. The memory 31 stores an adaptive temperature control adjustment and overload protection method. When the adaptive temperature control adjustment and overload protection method is executed by the processor 32, the following steps are realized: Collect the associated parameters of the discharge gun, and perform data preprocessing on the associated parameters of the discharge gun to obtain the preprocessed associated parameters of the discharge gun; Combine the preprocessed associated parameters of the discharge gun and the LSTM algorithm model to construct a target discharge gun temperature prediction model; Combine the target discharge gun temperature prediction model to conduct overload prediction determination on the target discharge gun, and perform fuzzy PID temperature control adjustment on the overloaded target discharge gun; In the target discharge gun, through the adaptive optimization module combined with the fuzzy PID module, perform adaptive temperature control adjustment on the target discharge gun.

[0030] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for adaptive temperature control and overload protection of a discharge gun, characterized in that: The following steps are involved: Collecting the associated parameters of the discharge gun, and performing data preprocessing on the associated parameters of the discharge gun to obtain preprocessed associated parameters of the discharge gun; Combined with the pre-processed discharge gun related parameters and the LSTM algorithm model, a target discharge gun temperature prediction model is constructed; Combined with the target discharge gun temperature prediction model, the target discharge gun is predicted and judged for overload, and the overloaded target discharge gun is adjusted by fuzzy PID temperature control; In the target discharge gun, the adaptive optimization module is combined with the fuzzy PID module to perform adaptive temperature control on the target discharge gun.

2. The method for adaptive temperature control and overload protection of a discharge gun according to claim 1, characterized in that: The collecting of the associated parameters of the discharge gun and the preprocessing of the associated parameters of the discharge gun to obtain the preprocessed associated parameters of the discharge gun are specifically: Determine a discharge gun, calibrate it as a target discharge gun, obtain a working specification of the target discharge gun, and determine a threshold value of an associated parameter of the target discharge gun based on the working specification of the target discharge gun; The associated parameter thresholds of the target discharge gun include a standard discharge current threshold, a standard discharge voltage threshold, a discharge gun operating temperature qualified threshold, and a coolant standard flow threshold; Determine the discharge target of the discharge gun, mark it as the device to be charged, connect the target discharge gun to the device to be charged, and preset the frequency of collecting related parameters; Controlling the target discharge gun to perform discharge processing on the charging device, and during the discharge processing, combining the associated parameter collection frequency, performing real-time collection processing on the target discharge gun to obtain the real-time associated parameters of the target discharge gun; A sliding average filtering algorithm is introduced, and a sliding average filtering window is constructed based on the sliding average filtering algorithm. The sliding average filtering window is traversed and slid on the real-time associated parameters of the target discharge gun. During the traversal and sliding process, the real-time associated parameters of the target discharge gun in the sliding average filtering window are averaged to obtain the real-time associated parameters of the target discharge gun after filtering, which are calibrated as the preprocessed discharge gun associated parameters.

3. The method for adaptive temperature control and overload protection of a discharge gun according to claim 1, characterized in that: The target discharge gun temperature prediction model is constructed by combining the preprocessing discharge gun associated parameters and the LSTM algorithm model, specifically: Introducing an LSTM algorithm model, and inputting the pre-processing discharge gun associated parameters into the LSTM algorithm model for storage; Determine the time window for analyzing the pre-processing discharge gun associated parameters in the LSTM algorithm model, and perform parameter segmentation on the pre-processing discharge gun associated parameters in combination with the time window to obtain the pre-processing discharge gun associated parameters within the time window, and calibrate them as a type of discharge gun associated parameters; A type of discharge gun associated parameters is divided into a training set and a validation set, and a model architecture is constructed for an LSTM algorithm model, wherein the method for constructing the model architecture for the LSTM algorithm model is to obtain a historical data network, retrieve a model architecture of the LSTM algorithm model with the highest usage rate when performing LSTM analysis on a target discharge gun in the historical data network, and output the model architecture; After the model architecture is built, the loss function is determined in the LSTM algorithm model, calibrated as the target loss function, and the training set is trained based on the target loss function. At the same time, the loss curve analysis is performed on the validation set during the training process. If the overlap rate of the loss curves obtained from the training set and the validation set is less than a preset value, hyperparameter tuning is performed during the training process until the overlap rate of the loss curves obtained from the training set and the validation set is not less than the preset value, thereby obtaining a target discharge gun temperature prediction model.

4. The method for adaptive temperature control and overload protection of a discharge gun according to claim 1, characterized in that: The target discharge gun temperature prediction model is combined to perform overload prediction and judgment on the target discharge gun, and fuzzy PID temperature control is performed on the overloaded target discharge gun, specifically: Preset the target discharge gun operation time, predict the operating temperature of the target discharge gun during the target discharge gun operation time through the target discharge gun temperature prediction model, and construct an operating temperature change curve graph; Performing an operating temperature change analysis on the operating temperature change curve, and calculating a dynamic current value of a target discharge gun during a change in operating time and an operating temperature, and calibrating the dynamic current value to be analyzed; Based on the associated parameter threshold of the target discharge gun, an overload analysis is performed on the target discharge gun. If the dynamic current value to be analyzed is not maintained within the standard discharge current threshold, it is determined that the target discharge gun is overloaded. At the same time, if the operating temperature of the target discharge gun is not maintained within the discharge gun operating temperature qualified threshold during the target discharge gun operating time, it is also determined that the target discharge gun is overloaded; If the target discharge gun is overloaded, the fuzzy PID temperature control device is combined to perform fuzzy PID temperature control adjustment on the target discharge gun.

5. The method for adaptive temperature control and overload protection of a discharge gun according to claim 4, characterized in that: If the target discharge gun is overloaded, the fuzzy PID temperature control device is combined to perform fuzzy PID temperature control adjustment on the target discharge gun, specifically: For a discharge gun with an overload phenomenon, if the target discharge gun temperature prediction model predicts that the operating temperature of the target discharge gun during the target discharge gun operation time is not maintained within the discharge gun operating temperature qualified threshold, or the dynamic current value to be analyzed is predicted to be not maintained within the standard discharge current threshold, then the target discharge gun is judged to be in a predicted overload; If, during the real-time collection and processing of the associated parameters of the target discharge gun, the operating temperature of the target discharge gun is not maintained within the qualified threshold of the discharge gun operating temperature, or the real-time collected current of the target discharge gun is not maintained within the standard discharge current threshold, it is determined that the target discharge gun is in real-time overload; The fuzzy PID module is integrated with the target discharge gun. If the target discharge gun is in a predicted overload, the target discharge gun is protected against predicted overload based on the fuzzy PID module. The predicted overload protection is to limit the discharge current output of the target discharge gun, and to control the coolant flow of the target discharge gun through the fuzzy PID module to ensure that the coolant flow of the target discharge gun is always maintained within the coolant standard flow threshold; If the target discharge gun is in real-time overload, the target discharge gun is protected from overload in real time based on the fuzzy PID module; The real-time overload protection is to immediately cut off the power supply to the target discharge device through a fuzzy PID module.

6. The method for adaptive temperature control and overload protection of a discharge gun according to claim 1, characterized in that: The target discharge gun is subjected to adaptive temperature control adjustment by combining the adaptive optimization module with the fuzzy PID module, specifically: In the target discharge gun, an adaptive optimization module is connected, wherein the adaptive optimization module is used to perform adaptive temperature control on the target discharge gun; Based on the adaptive optimization module, the surrounding environment parameters and historical operation records are recorded and stored each time the target discharge gun is in an overload condition, and a dynamic adjustment fuzzy rule table is constructed according to all the recorded and stored data; The dynamic adjustment fuzzy rule table records all the operating temperatures and discharge currents that the target discharge gun will output under different ambient environment parameters and operation records; The dynamic adjustment fuzzy rule table is updated in real time, and the dynamic adjustment fuzzy rule table is introduced into the fuzzy PID module to perform adaptive temperature control of the target discharge gun.

7. An adaptive temperature control and overload protection system for a discharge gun, characterized in that: The adaptive temperature control regulation and overload protection system includes a memory and a processor, and the memory stores an adaptive temperature control regulation and overload protection method program. When the adaptive temperature control regulation and overload protection method program is executed by the processor, the adaptive temperature control regulation and overload protection method steps as described in any one of claims 1-6 are implemented.

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