Electrical adaptive control method, control system and conversion socket

Abstract

The present invention relates to the field of electronic equipment technology, and specifically to an electrical adaptive control method, a control system, and a conversion socket. The steps of the control method include: detecting the action of plug replacement, obtaining the physical connection status of the plug through a sensor module, and recording the time and frequency of plug replacement; identifying the type of plug, using the built-in plug specification database and plug identification unit of the charging head to identify the specification characteristics of the plug, the specification characteristics include rated voltage, rated frequency, maximum load current, and physical structural characteristics of the plug. The present invention solves the problem in the prior art that the charging head cannot effectively adjust electrical parameters and protect equipment after the plug is replaced through an electrical adaptive control method and a control system, thereby improving the adaptability and safety of the charging head.

Description

Technical Field

[0001] The invention relates to the technical field of electronic equipment, and in particular to an electrical adaptive control method, a control system and a conversion socket. Background Art

[0002] In order to adapt to power sockets of different standards, some charging heads that support plug replacement have appeared on the market, but these charging heads have the following shortcomings in electrical parameter adjustment and adaptive control: most charging heads can only adjust the output voltage and frequency within a fixed range, and cannot be dynamically adjusted according to different plug types and electrical environment parameters, resulting in difficulty in ensuring the stability and safety of the output power supply. Summary of the invention

[0003] The present invention provides an electrical adaptive control method, a control system and a conversion socket to solve the technical problem that the charging head cannot effectively adjust the electrical parameters and protect the equipment after the plug is replaced.

[0004] The technical solution of the present invention to solve the above technical problems is as follows:

[0005] Provided is an electrical adaptive control method, a control system and a conversion socket, which are applied to a charging head with a replaceable plug. The control method comprises the following steps:

[0006] Detect the action of plug replacement, obtain the physical connection status of the plug through the sensor module, and record the time and frequency of plug replacement;

[0007] Identify the plug type, using the plug specification database and plug identification unit built into the charging head to identify the specification characteristics of the plug, wherein the specification characteristics include rated voltage, rated frequency, maximum carrying current and physical structure characteristics of the plug;

[0008] Acquire current electrical environment parameters, acquire the voltage and frequency of the input power supply in real time through the voltage detection module and frequency detection module built into the charging head, and evaluate the waveform quality of the input power supply through the power quality analysis module;

[0009] According to the recognition result and the current electrical environment parameters, the adaptive algorithm module is called to dynamically adjust the circuit parameters inside the charging head to ensure the stability of the output power;

[0010] Monitor the changes of the electrical environment parameters in real time, determine whether the electrical equipment will overheat or overload during use through the contact point temperature monitoring module and the current monitoring module, and predict the change trend of the electrical environment parameters through the fuzzy logic algorithm;

[0011] Send a prompt message, prompt the plug replacement status and current working status through the prompt module, and optimize the accuracy of the prompt message through the machine learning model.

[0012] On the other hand, an electrical adaptive control system is provided, which is applied to a charging head with a replaceable plug, and the control system includes:

[0013] A sensor module for detecting the physical connection status of the plug;

[0014] A plug specification database and a plug identification unit, used to identify specification features of the plug;

[0015] The voltage detection module and the frequency detection module are used to obtain the voltage and frequency of the input power supply in real time and perform Fourier transform and wavelet transform;

[0016] Power quality analysis module, used to evaluate the waveform quality and stability of the input power, including total harmonic distortion (THD) and voltage sag (Sag) parameters;

[0017] Adaptive algorithm module, including nonlinear optimization algorithm, particle swarm optimization (PSO) algorithm and simulated annealing algorithm, is used to dynamically adjust the parameters of the internal circuit according to the recognition results and the current electrical environment parameters to ensure the stability of the output power supply;

[0018] The contact point temperature monitoring module is used to monitor the temperature of the contact points between the plug and the charging head in real time and to model them using the finite element analysis (FEA) method;

[0019] The current monitoring module is used to monitor the input current and output current of the socket in real time and evaluate them using the statistical method of sliding window mean and standard deviation;

[0020] Prompt system, including LED indicator light, buzzer, voice prompt module and multi-modal perception module, used to send prompt information and operation guide to users;

[0021] A voltage conversion circuit, used to convert the input voltage into a desired target voltage, including linear conversion and nonlinear conversion;

[0022] A frequency conversion circuit, used for converting an input frequency into a desired target frequency, including synchronous conversion and asynchronous conversion;

[0023] A power factor correction circuit is used to correct the power factor of the input power supply, including phase correction and reactive power compensation;

[0024] Overload protection circuit, used to cut off the power supply when the current exceeds the threshold and dynamically adjust the trigger threshold;

[0025] Overheat protection circuit, used to cut off the power supply when the contact point temperature exceeds the threshold and dynamically adjust the trigger threshold;

[0026] The data storage module is used to store the system's operation logs and user feedback data to support subsequent data analysis and optimization.

[0027] In another aspect, an electrical adaptive control conversion socket is provided, the conversion socket comprising the electrical adaptive control system described above, and further comprising:

[0028] The charging head body is provided with L-level, N-level and ground-level contact plugs;

[0029] The replaceable plug component is fixed in the charging head body by an elastic plastic structure. The plug component includes plugs of various standard specifications to adapt to power sockets in different countries and regions. The elastic plastic structure is used to ensure the stability and easy replaceability of the connection between the plug component and the charging head body.

[0030] Furthermore, the elastic plastic structure includes:

[0031] An unlocking button movably mounted on one side of the charging head body, used to unlock the plug component;

[0032] A locking frame movably mounted in the charging head body, used for clamping and locking the plug component;

[0033] A bracket fixed in the charging head body, one end of the locking frame being fixed on the bracket;

[0034] A return spring is installed between the unlocking button and the locking frame, the locking frame is provided with a first inclined surface or an arc surface structure, and the action end of the unlocking button is provided with a second inclined surface or an arc surface structure;

[0035] When the unlocking button is pressed, the second inclined surface or arc surface structure is in contact with and presses the first inclined surface or arc surface structure, and the locking frame releases the plug component.

[0036] The beneficial effects of the present invention are:

[0037] The present invention solves the problem that the charging head in the prior art cannot effectively adjust the electrical parameters and protect the device after the plug is replaced by an electrical adaptive control method and control system, thereby improving the adaptive ability and safety of the charging head. The sensor module is used to detect the plug replacement action in real time, obtain the physical connection status of the plug, and record the time and frequency of the replacement. This function ensures the accuracy of the plug replacement and avoids electrical failures caused by improper replacement. Through the built-in plug specification database and plug identification unit, the present invention can accurately identify the specification characteristics of the plug, provide parameters for subsequent dynamic adjustment, ensure that the charging head can adjust the corresponding electrical parameters according to different plug types and specifications, and improve the applicability of the device. According to the plug identification result and the current electrical environment parameters, the present invention calls the adaptive algorithm module to dynamically adjust the circuit parameters inside the charging head to ensure the stability of the output power supply. Through the contact point temperature monitoring module and the current monitoring module, the changes in the electrical environment parameters are monitored in real time to determine whether the electrical equipment will overheat or overload during use. This protection mechanism ensures the safety of the equipment and avoids electrical failures caused by overload or overheating. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A flowchart of an electrical adaptive control method according to an embodiment of the present invention;

[0039] Figure 2 This is a diagram of power quality assessment results in one embodiment of the present invention;

[0040] Figure 3 A current and voltage waveform diagram in one embodiment of the present invention;

[0041] Figure 4 This is a diagram showing the effects of overheat protection and overload protection in one embodiment of the present invention;

[0042] Figure 5 This is a temperature field distribution diagram of the contact point in one embodiment of the present invention;

[0043] Figure 6 A temperature distribution diagram predicted by finite element analysis in one embodiment of the present invention;

[0044] Figure 7 A heat dissipation path diagram in one embodiment of the present invention;

[0045] Figure 8 This is a diagram showing the effect of power factor correction in one embodiment of the present invention;

[0046] Fig. 9 This is a schematic diagram of the structure of an electrical adaptive control conversion socket in one embodiment of the present invention;

[0047] Fig.10 A side view of an electrical adaptive control conversion socket in one embodiment of the present invention;

[0048] Fig.11 for Fig.10 Sectional view at "AA" in the figure;

[0049] Fig.12 The local structure of the electrical adaptive control conversion socket in one embodiment of the present invention Figure 1 ;

[0050] Fig.13 The local structure of the electrical adaptive control conversion socket in one embodiment of the present invention Figure 2 ;

[0051] In the accompanying drawings, the components represented by the reference numerals are as follows:

[0052] 1. Charging head body; 2. Contact plug; 3. Plug parts;

[0053] 4. Elastic plastic structure; 41. Unlock button; 411. Second inclined surface or arc surface structure; 42. Locking frame; 421. First inclined surface or arc surface structure; 43. Bracket; 44. Return spring. DETAILED DESCRIPTION

[0054] The present invention provides the following preferred embodiments:

[0055] Embodiment 1

[0056] In order to solve the problem in the prior art that the charging head cannot effectively adjust the electrical parameters and protect the device after the plug is replaced, this embodiment proposes an electrical adaptive control method. Figure 1 As shown, the steps of the electrical adaptive control method include:

[0057] S100, detecting the action of plug replacement, obtaining the physical connection status of the plug through the sensor module, and recording the time and frequency of plug replacement.

[0058] S200, identifying the type of the plug, using the built-in plug specification database and plug identification unit of the charging head to identify the specification characteristics of the plug, wherein the specification characteristics include rated voltage, rated frequency, maximum load current and physical structure characteristics of the plug.

[0059] S300, obtaining current electrical environment parameters, obtaining the voltage and frequency of the input power supply in real time through the voltage detection module and frequency detection module built into the charging head, and evaluating the waveform quality of the input power supply through the power quality analysis module.

[0060] S400: Based on the recognition result and the current electrical environment parameters, an adaptive algorithm module is called to dynamically adjust the circuit parameters inside the charging head to ensure the stability of the output power.

[0061] S500, monitor the changes of the electrical environment parameters in real time, determine whether the electrical equipment will overheat or overload during use through the contact point temperature monitoring module and the current monitoring module, and predict the change trend of the electrical environment parameters through the fuzzy logic algorithm.

[0062] S600: Send a prompt message, prompt the plug replacement status and the current working status through the prompt module, and optimize the accuracy of the prompt message through a machine learning model.

[0063] In this embodiment, the sensor module uses highly sensitive mechanical sensors and photoelectric sensors, which can quickly detect changes in the physical connection state of the plug when it is inserted or unplugged. These sensors are installed at the plug interface of the charging head body, and determine whether the plug has been replaced by detecting changes in the contact point between the plug and the charging head body. It should be understood that the sensor module can not only detect the insertion and removal of the plug, but also record the time and frequency of plug replacement, providing data support for subsequent dynamic adjustments.

[0064] Furthermore, the plug identification unit uses the built-in plug specification database, combined with image recognition algorithms and signal processing technology, to perform high-precision identification of the specification characteristics of the plug. The plug specification database stores the specification information of a variety of standard plugs, including rated voltage, rated frequency, maximum load current and physical structure characteristics. When the plug is replaced, the plug identification unit obtains the plug image through a photoelectric sensor and uses a convolutional neural network (CNN) algorithm to identify the physical structure characteristics of the plug. At the same time, through signal processing technology, the electrical signal at the contact point between the plug and the charging head body is analyzed to further verify the specification characteristics of the plug. It can be understood that this multi-dimensional identification method ensures the accuracy and reliability of plug type identification.

[0065] Furthermore, the voltage detection module and the frequency detection module are integrated at the input end of the charger, and can obtain the voltage and frequency parameters of the input power in real time. These two modules use high-performance analog front end (AFE) and digital signal processing (DSP) technology to ensure high accuracy and real-time detection. The power quality analysis module evaluates the waveform quality of the input power through Fourier transform and wavelet transform, and calculates parameters such as total harmonic distortion (THD) and voltage sag (Sag), providing a basis for subsequent dynamic adjustments, such as Figures 2 to 3 It is important to understand that the high-precision detection and evaluation capabilities of these modules are the basis for ensuring the stability of the output power supply.

[0066] Furthermore, the adaptive algorithm module dynamically adjusts the circuit parameters inside the charger according to the plug recognition results and the current electrical environment parameters. The voltage parameters and frequency parameters are adjusted through the nonlinear optimization algorithm to ensure the dynamic response of the output power. It should be understood that the use of the nonlinear optimization algorithm can effectively cope with the rapid changes in the input power parameters and ensure the stability and accuracy of the output power.

[0067] Furthermore, this embodiment monitors the changes of electrical environment parameters in real time through the contact point temperature monitoring module and the current monitoring module, such as Figure 4 As shown. The contact point temperature monitoring module arranges multiple temperature sensors near the contact points between the plug and the charging head body to monitor the temperature distribution of the contact points in real time. The current monitoring module monitors the input current and output current in real time through a current sensor with a high sampling rate. These modules use the statistical method of sliding window mean and standard deviation to evaluate the stability of the current. At the same time, the fuzzy logic algorithm is used to predict the changing trend of electrical environmental parameters and dynamically adjust the trigger thresholds of the overload protection and overheating protection mechanisms. It can be understood that this real-time monitoring and prediction mechanism can effectively prevent the equipment from overheating or overloading due to changes in electrical parameters during use, thereby improving the safety of the equipment.

[0068] Furthermore, the prompt module includes an LED indicator, a buzzer and a voice prompt unit, which can send the plug replacement status and current working status information to the user. When the plug replacement succeeds or fails, the prompt module sends a corresponding prompt signal through the LED indicator and the buzzer to ensure that the user can understand the replacement status in time. At the same time, the prompt module displays the current working status, including the operating voltage, operating frequency and current limit value, and optimizes the accuracy of the prompt information through the machine learning model. It can be understood that this multimodal prompt system not only improves the user's operating convenience, but also enhances the reliability of the system.

[0069] The benefit of this embodiment is that the reliability of plug replacement and high-precision identification of plug types are ensured through the highly sensitive sensor module and the multi-dimensional plug identification method. The high-precision detection capabilities of the voltage detection module, the frequency detection module and the power quality analysis module provide accurate input data for adaptive adjustment. The dynamically adjusted adaptive algorithm module and the real-time monitoring and prediction protection mechanism effectively ensure the stability of the output power supply and the safety of the equipment. Through the multi-modal prompt system, users can easily understand the working status of the equipment, ensuring reliability during use.

[0070] Embodiment 2

[0071] In order to solve the problem that the electrical parameters of the charging head cannot be effectively adjusted after the plug is replaced, this embodiment further optimizes the method of dynamically adjusting the internal circuit parameters of the charging head to ensure the stability and purity of the output power.

[0072] In this embodiment, when the plug replacement action is detected, the sensor module obtains the physical connection status of the plug and records the time and frequency of the plug replacement. The plug identification unit uses the built-in plug specification database and plug identification algorithm to identify the specification characteristics of the plug, including the rated voltage V target and rated frequency f target Next, the voltage detection module and the frequency detection module obtain the voltage V of the input power supply in real time. input and frequency f input , and use these data to calculate the voltage conversion factor K v And the frequency conversion factor K f :

[0073] , , where V target and f target is the target voltage and target frequency preset according to the plug specification database, V input and f input It is the voltage and frequency of the input power actually detected.

[0074] Furthermore, the voltage parameters and frequency parameters are adjusted by a nonlinear optimization algorithm to ensure the dynamic response of the output power supply. Specifically, the error function J is:

[0075] , where J is the error function, V output,i and f output,j are the output voltage at the i-th sampling point and the output frequency at the j-th sampling point, respectively. N is the total number of sampling points for the output voltage, and M is the total number of sampling points for the output frequency. It should be understood that by minimizing the error function J, the nonlinear optimization algorithm can dynamically adjust the circuit parameters inside the charger to ensure that the output voltage and frequency have the minimum deviation from the target value.

[0076] Furthermore, in order to ensure the accuracy and stability of the adjustment, this embodiment adopts a feedback control mechanism. During the adjustment process, the changes in the output voltage and frequency are monitored in real time through the contact point temperature monitoring module and the current monitoring module to evaluate their dynamic response. The feedback control mechanism dynamically adjusts the parameters of the voltage conversion circuit and the frequency conversion circuit according to the monitoring results to ensure the accuracy of the output voltage and frequency. It can be understood that this real-time monitoring and feedback adjustment mechanism can effectively cope with the rapid changes in electrical environment parameters and maintain the stability of the output power supply.

[0077] Furthermore, in order to eliminate the harmonic interference of the input power supply, this embodiment uses an adaptive filter to process the voltage and frequency of the input power supply. The adaptive filter can dynamically adjust the filter parameters according to the spectrum components of the input power supply, thereby effectively filtering out the harmonic interference and ensuring the purity of the output power supply. It should be understood that the use of the adaptive filter not only improves the quality of the output power supply, but also enhances the anti-interference ability of the system.

[0078] The benefit of this embodiment is that, through the nonlinear optimization algorithm and feedback control mechanism, the dynamic adjustment of the charging head after the plug is replaced is realized, ensuring the stability and accuracy of the output power. The introduction of the adaptive filter further eliminates the harmonic interference of the input power and improves the purity of the output power.

[0079] Embodiment 3

[0080] In order to solve the problem of inaccurate assessment of the input power waveform quality of the charging head after the plug is replaced, this embodiment further optimizes the function of the power quality analysis module to ensure that the system can accurately assess the waveform quality of the input power and take protective measures in time.

[0081] like Figure 3 As shown, in this embodiment, the voltage detection module obtains the instantaneous voltage waveform V of the input power supply. input (t), and perform Fourier transform on it to obtain the spectral component V^ of the voltage input (f). Fourier transform can convert time domain signals into frequency domain signals, so as to conveniently analyze the spectral components of voltage, including the amplitude and frequency of fundamental wave and each harmonic. Furthermore, the frequency detection module obtains the instantaneous frequency waveform f of the input power supply. input (t), and perform wavelet transform on it to obtain the time-frequency distribution diagram W of the frequency f (t,f). Wavelet transform can provide detailed information about the frequency variation over time, which is helpful for evaluating the frequency stability of the input power supply.

[0082] Furthermore, this embodiment uses the Kalman filter algorithm to smooth the acquired voltage and frequency parameters, eliminate noise interference, and obtain a stable state estimation value V^ input and f^ input The Kalman filter algorithm effectively reduces the impact of measurement noise through a recursive estimation and update process, making the evaluation results more accurate. It should be understood that this smoothing method not only improves the accuracy of waveform quality evaluation, but also enhances the reliability of the system.

[0083] Furthermore, the power quality analysis module is based on the smoothed voltage and frequency parameters, such as Figure 2As shown in the figure, the waveform quality of the input power is evaluated, including total harmonic distortion (THD) and voltage sag (Sag) parameters, and the evaluation results are stored in the system log. During the evaluation process, the input power is comprehensively evaluated using the preset power quality standards. It can be understood that this evaluation method can fully reflect the waveform quality of the input power and help the system to detect potential electrical problems in a timely manner.

[0084] Furthermore, if the evaluation result does not meet the preset safety standards, the system will automatically trigger an alarm mechanism and send the alarm information to the user's smart terminal through a wireless communication module or a connecting cable. The wireless communication module can use wireless transmission technologies such as Bluetooth, Wi-Fi or Zigbee, and the connecting cable can use a wired transmission method such as USB or Ethernet cable. It should be understood that this alarm mechanism can remind users in time to ensure that the device operates in a safe electrical environment.

[0085] The benefit of this embodiment is that, through Fourier transform and wavelet transform, a high-precision evaluation of the quality of the input power waveform is achieved. The introduction of the Kalman filter algorithm effectively eliminates noise interference and improves the stability of the evaluation results. The automatic triggering and information transmission of the alarm mechanism ensures that the user can understand the working status of the equipment in a timely manner, avoids potential electrical failures, and improves the safety of the system.

[0086] Embodiment 4

[0087] In order to solve the optimization efficiency problem of adjusting the voltage and frequency parameters of the charging head after the plug is replaced, this embodiment further optimizes the nonlinear optimization algorithm and adopts a variety of optimization techniques to ensure the accuracy and stability of the output voltage and frequency.

[0088] In this embodiment, a nonlinear model of voltage and frequency is constructed:

[0089] ,

[0090] , where g1 and g2 are nonlinear functions, T(t) is the temperature time series, and ϵ1(t) and ϵ2(t) are random errors. It should be understood that these nonlinear models can more accurately describe the variation of voltage and frequency parameters, providing a more reliable basis for the optimization algorithm.

[0091] Furthermore, the voltage and frequency parameters are optimized using the gradient descent method and the Hessian matrix. Specifically, the optimization variable vector x is updated by the following formula:

[0092] , where x is the optimization variable vector, α and β are step size parameters, ∇J is the gradient vector, and H(J) is the Hessian matrix. It should be understood that through the gradient descent method and the Hessian matrix, the voltage and frequency parameters can be effectively optimized to ensure the dynamic response and stability of the output power supply.

[0093] Furthermore, in order to improve the efficiency of optimization, this embodiment adjusts the convergence speed of the parameters through affine transformation and S-shaped function. Specifically, the parameter adjustment formula is:

[0094] , where σ is the S-shaped function, and A and b are the affine transformation parameters. Through the affine transformation and the S-shaped function, the convergence speed of the parameters can be effectively controlled and the convergence performance of the optimization algorithm can be improved. It can be understood that this parameter adjustment method not only speeds up the optimization process, but also ensures the reliability of the optimization results.

[0095] Furthermore, this embodiment uses a particle swarm optimization algorithm to further optimize the voltage and frequency parameters to ensure that the optimal solution is found in the multi-objective optimization. The particle swarm optimization algorithm updates the speed and position of the particles through the following formula:

[0096] ,

[0097] , where v i is the velocity of the ith particle, x i is the position of the ith particle, ω is the inertia weight, c1 and c2 are acceleration coefficients, r1 and r2 are random numbers, p i is the historical optimal position of the i-th particle, P global It is the global optimal position. It should be understood that the particle swarm optimization algorithm can find the global optimal solution in multi-objective optimization through group intelligence, further improving the adaptive performance of the charging head.

[0098] Furthermore, in order to improve the global search capability of the particle swarm optimization algorithm, this embodiment introduces a simulated annealing algorithm. The simulated annealing algorithm avoids the particle swarm optimization algorithm from falling into a local optimal solution through a random search and annealing process. Specifically, the simulated annealing algorithm updates the optimization parameters through the following formula:

[0099] , Δx is the random step size, and T is the annealing temperature. It should be understood that the simulated annealing algorithm gradually reduces the influence of the random step size by gradually reducing the annealing temperature, so that the optimization process can gradually converge from the global search to the local optimum.

[0100] The benefit of this embodiment is that by constructing a nonlinear model and a variety of optimization techniques, efficient optimization of voltage and frequency parameters is achieved. The use of gradient descent method and Hessian matrix ensures the accuracy and stability of the optimization process. The introduction of affine transformation and S-shaped function improves the convergence speed of parameters and speeds up the optimization process. The combination of particle swarm optimization algorithm and simulated annealing algorithm ensures that the global optimal solution is found in multi-objective optimization, further improving the adaptive performance of the charging head.

[0101] Embodiment 5

[0102] According to the electrical adaptive control method described in the aforementioned embodiment, this embodiment further optimizes the process of real-time monitoring of changes in electrical environmental parameters to ensure that the charging head can effectively prevent electrical equipment from overheating or overloading during use.

[0103] In this embodiment, the input current I of the socket is monitored in real time by a current sensor with a high sampling rate. input (t) and output current I output (t). The current sensor uses a high-performance Hall effect sensor, which can achieve high-speed sampling and high-precision measurement. It should be understood that the high-sampling-rate current sensor can obtain detailed information about current changes in real time, providing accurate data support for subsequent current stability evaluation.

[0104] Furthermore, this embodiment uses a statistical method of sliding window mean and standard deviation to evaluate the input current I input (t) and output current I output (t). Specifically, the size of the sliding window is N, and the current mean value μ at the current time point t is I (t) and standard deviation σ I (t) is calculated by the following formula:

[0105] ,

[0106] ,It needs to be understood that the sliding window mean and ,standard deviation can evaluate the current fluctuation in real time and provide accurate ,input data for the overload protection mechanism.

[0107] Furthermore, in order to improve the accuracy of current monitoring, this embodiment uses a Kalman filter to monitor the input current I input (t) and output current I output (t) is smoothed. The Kalman filter effectively reduces the influence of measurement noise through the recursive estimation and update process, making the current monitoring result more stable. It can be understood that the introduction of the Kalman filter not only improves the accuracy of current monitoring, but also enhances the anti-interference ability of the system.

[0108] Furthermore, in order to evaluate the harmonic distortion of the current, the present embodiment uses the variational mode decomposition (VMD) method to separate the input current I input (t) and output current I output (t). The VMD method can separate the current signal into multiple modal components through multi-scale decomposition, and each component corresponds to a current component of a different frequency. The harmonic distortion parameters can be calculated based on the separated modal components to further evaluate the quality of the current. It should be understood that the VMD method can effectively separate the different frequency components in the current, providing reliable data support for harmonic distortion evaluation.

[0109] Furthermore, according to the current monitoring result, this embodiment dynamically adjusts the triggering threshold of the overload protection mechanism. I (t) exceeds the preset high threshold, or standard deviation σ I When (t) is too large, the overload protection mechanism will be automatically triggered to cut off the power output to prevent the electrical equipment from overloading. At the same time, according to the evaluation results of the harmonic distortion parameters, the sensitivity of the overload protection mechanism is adjusted to ensure that protective measures can be taken more promptly when the current quality is poor. It can be understood that this dynamic adjustment mechanism can effectively respond to changes in electrical environment parameters and improve the safety and reliability of the system.

[0110] Embodiment 6

[0111] According to the electrical adaptive control method described in the above-mentioned embodiment, this embodiment further optimizes the step of determining whether the electrical equipment will be overheated or overloaded during use by using the contact point temperature monitoring module and the current monitoring module.

[0112] In this embodiment, in order to ensure that the charging head does not overheat or overload due to poor contact during use, a variety of temperature monitoring technologies and current evaluation methods are used. First, multiple temperature sensors are arranged near the contact point between the charging head and the plug to monitor the temperature distribution of the contact point in real time. These temperature sensors can be thermocouples, thermistors or integrated temperature sensors to form temperature field data T(x, y, z, t). It should be understood that through multi-point temperature monitoring, the temperature changes of the contact points can be comprehensively evaluated, providing detailed data support for subsequent thermal distribution modeling.

[0113] Furthermore, the finite element analysis (FEA) method is used to model the temperature field data and predict the heat distribution and heat dissipation path of the contact point, such as Figures 5 to 7As shown in the figure. The FEA method divides the contact point area into multiple tiny units, calculates the temperature change and heat transfer of each unit, and thus constructs a temperature distribution model of the entire contact point. It can be understood that this modeling method can accurately predict the thermal distribution of the contact point and provide a scientific basis for the design of the overheating protection mechanism.

[0114] Furthermore, in order to improve the accuracy and response speed of temperature monitoring, this embodiment uses a combination of thermocouples and thermistors. Thermocouples are used to monitor high temperature areas, while thermistors are used to monitor low temperature areas. The combination of thermocouples and thermistors can cover a wider temperature range and ensure the comprehensiveness and accuracy of temperature monitoring. It should be understood that this combination not only improves the accuracy of temperature monitoring, but also speeds up the response speed, which helps to detect and deal with overheating problems in a timely manner.

[0115] Furthermore, the fuzzy logic algorithm is used to evaluate the temperature anomaly of the contact point and determine the level of overheating risk. The fuzzy logic algorithm analyzes the data of the temperature sensor and divides the temperature change into multiple levels, such as low risk, medium risk and high risk. Specifically, the algorithm processes the temperature data according to the preset fuzzy rules and membership functions, and outputs the corresponding overheating risk level. It should be understood that the fuzzy logic algorithm can effectively handle the nonlinear characteristics of temperature changes and improve the accuracy of overheating assessment.

[0116] Furthermore, the trigger threshold of the overheat protection mechanism is dynamically adjusted according to the overheat risk level. When the evaluation results show that the contact point has a high overheat risk, the overheat protection mechanism will automatically lower the trigger threshold and cut off the power output in advance to prevent the overheating problem from further deteriorating. At the same time, when the evaluation results show that the contact point is in a low-risk state, the overheat protection mechanism will appropriately increase the trigger threshold to reduce the possibility of false alarms. It can be understood that this dynamic adjustment mechanism can flexibly adjust the protection threshold according to the actual temperature conditions to ensure the safety and reliability of the system.

[0117] Through this embodiment, comprehensive monitoring and accurate evaluation of the temperature of the charging head contact point is achieved. The combination of finite element analysis method and fuzzy logic algorithm not only improves the accuracy of temperature monitoring, but also enhances the adaptability of the system. The dynamically adjusted overheating protection mechanism ensures that electrical equipment can operate safely under different usage conditions.

[0118] Embodiment 7

[0119] According to the electrical adaptive control method described in the above embodiment, this embodiment further optimizes the step of dynamically adjusting the internal circuit parameters of the charger head, and uses a power factor correction algorithm to ensure the efficiency and quality of the output power. Figure 8 shown.

[0120] In this embodiment, in order to improve the energy efficiency of the charger, a power factor correction algorithm is used. First, the current and voltage waveforms of the input power supply are obtained in real time through the current detection module and the voltage detection module. input (t) and V input (t). The detection module uses high-performance Hall effect sensors and voltage sensors to ensure the accuracy and real-time nature of the data. It should be understood that accurate waveform data is the basis for power factor correction and can provide reliable support for subsequent calculations.

[0121] Furthermore, the phase angle φ(t) of the input current is calculated. The phase angle is calculated by the following formula:

[0122] , where Δt k is the time difference of the kth sampling point, I input,k and V input,k are the input current and voltage at the kth sampling point respectively. It can be understood that the calculation of the phase angle can reflect the phase difference between the input current and voltage, and provide a key parameter for power factor correction.

[0123] Furthermore, the current power factor PF is calculated input (t). The power factor is calculated by the following formula:

[0124]

[0125] The power factor calculation result is used to evaluate the power factor of the current input power supply. It should be understood that the power factor reflects the efficiency of electric energy utilization. Through real-time monitoring of the power factor, the deficiency of electric energy utilization can be discovered and corrected in time.

[0126] Furthermore, according to the preset target power factor PF target , calculate the required phase correction value Δϕ(t):

[0127]

[0128] After calculating the phase correction value, the Kalman filter is used to smooth the phase correction value to eliminate noise interference and obtain a stable state estimate Δϕ^(t):

[0129] , where K(t) is the Kalman gain, z(t) is the observation value, and H is the observation matrix. It can be understood that the use of the Kalman filter effectively reduces the fluctuation of the phase correction value and improves the stability of the power factor correction.

[0130] Furthermore, the phase of the input current is adjusted by the phase correction circuit so that the actual power factor P FactualClose to the target power factor PF target The phase correction circuit includes a phase corrector and a reactive power compensation module, which can dynamically adjust the phase and reactive power of the input current to improve the power factor of the system. It should be understood that the introduction of the phase correction circuit not only improves the power factor, but also optimizes the utilization efficiency of electric energy and reduces the waste of electric energy.

[0131] Furthermore, the power factor after phase correction is monitored in real time through a feedback mechanism to ensure that it remains at the target power factor PF. target If the monitored power factor deviates from the target value, the parameters of the phase correction circuit will be dynamically adjusted until the power factor returns to normal. It can be understood that this real-time feedback and adjustment mechanism can continuously optimize the power factor and ensure the stable operation of the system.

[0132] Furthermore, the adaptive control mechanism is used to dynamically adjust the parameters of the phase correction algorithm according to the change of the output load. The adaptive control mechanism automatically adjusts the parameters of the phase correction algorithm by analyzing the change of the load to adapt to the power factor correction requirements under different load conditions. It can be understood that this adaptive control mechanism enables the system to achieve efficient power factor correction under different load conditions, thereby improving the flexibility and adaptability of the system.

[0133] Through this embodiment, real-time monitoring and dynamic correction of the input power factor are achieved. The high-performance sensor module, accurate phase angle and power factor calculation method, Kalman filter and smoothing processing make the power factor correction more accurate and stable. The introduction of phase correction circuit and adaptive control mechanism optimizes the utilization efficiency of electric energy, reduces the waste of electric energy, and ensures the stable operation of the system under different load conditions.

[0134] Embodiment 8

[0135] According to the electrical adaptive control method described in the above embodiments, this embodiment proposes an electrical adaptive control system.

[0136] In this embodiment, a fully integrated electrical adaptive control system is designed for a charger with a replaceable plug. First, the sensor module includes a variety of high-precision sensors, such as Hall effect sensors, voltage sensors, current sensors, and temperature sensors, which are used to detect the physical connection status of the plug, the voltage and frequency of the input power supply, the input and output currents, and the temperature of the contact points in real time. It should be understood that the combination of multiple sensors can provide comprehensive electrical environment parameters to support the adaptive control of the system.

[0137] Furthermore, the plug specification database and the plug identification unit are used to identify the specification characteristics of the plug. The plug identification unit automatically identifies the type of the plug, including the rated voltage and frequency, by analyzing the physical connection status of the plug and the information in the specification database. It can be understood that the accuracy of plug identification is the basis for ensuring the adaptive control of the system, and the use of the plug specification database provides rich data support for identification.

[0138] Furthermore, the voltage detection module and the frequency detection module obtain the voltage and frequency of the input power supply in real time, and perform Fourier transform and wavelet transform. Fourier transform is used to analyze the spectral components of the voltage, and wavelet transform is used to analyze the time-frequency distribution of the frequency. Based on these transformation results, the power quality analysis module evaluates the waveform quality and stability of the input power supply, including total harmonic distortion (THD) and voltage sag (Sag) parameters. It should be understood that high-precision power quality assessment can promptly detect and handle abnormal conditions of the input power supply to ensure the quality of the output power supply.

[0139] Furthermore, the adaptive algorithm module includes a nonlinear optimization algorithm, a particle swarm optimization (PSO) algorithm, and a simulated annealing algorithm. These algorithms are used to dynamically adjust the parameters of the internal circuit according to the identification results and the current electrical environment parameters to ensure the stability of the output power supply. The nonlinear optimization algorithm ensures that the deviation between the output parameter and the target value is minimized by minimizing the error function J. The particle swarm optimization algorithm and the simulated annealing algorithm are used for multi-objective optimization to find the global optimal solution. It should be understood that the combined use of multiple optimization algorithms enables the system to cope with complex electrical environments more flexibly and optimize the performance of the output power supply.

[0140] Furthermore, the contact point temperature monitoring module monitors the temperature of the contact points of the plug and the charging head in real time, and uses the finite element analysis (FEA) method to model and predict the heat distribution and heat dissipation path of the contact points. The temperature monitoring module obtains the temperature field data of the contact points through multi-point temperature sensors to provide detailed data for heat distribution modeling. It can be understood that the combination of temperature monitoring and modeling methods can effectively prevent overheating problems and avoid equipment damage.

[0141] Furthermore, the current monitoring module monitors the input current and output current of the socket in real time, and uses the statistical methods of sliding window mean and standard deviation to evaluate. These methods can evaluate the current fluctuation in real time and provide accurate input data for the overload protection mechanism. It can be understood that the accuracy and real-time nature of current monitoring are important factors in ensuring the effectiveness of overload protection.

[0142] Furthermore, the prompt system includes an LED indicator, a buzzer, a voice prompt module and a multimodal perception module, which are used to send prompt information and operation guides to the user. The LED indicator is used to display the working status of the system, the buzzer is used to sound an alarm, and the voice prompt module is used to provide detailed voice operation guides. The multimodal perception module further optimizes the performance of the prompt system through user feedback data. It should be understood that the combination of multiple prompt methods can notify users more comprehensively and improve their safety awareness and user experience.

[0143] Furthermore, the voltage conversion circuit is used to convert the input voltage to the required target voltage, including linear conversion and nonlinear conversion. The linear conversion circuit is suitable for a small range of voltage adjustment, while the nonlinear conversion circuit can handle a large range of voltage changes. The frequency conversion circuit is used to convert the input frequency to the required target frequency, including synchronous conversion and asynchronous conversion. Synchronous conversion ensures the synchronization of the output frequency with the input frequency, and asynchronous conversion is used to handle situations where the frequency changes are large. It should be understood that the combination of multiple conversion methods enables the system to cope with different types of voltage and frequency changes, ensuring the stability and quality of the output power supply.

[0144] Furthermore, the power factor correction circuit is used to correct the power factor of the input power supply, including phase correction and reactive power compensation. The phase correction circuit improves the power factor by adjusting the phase of the input current; the reactive power compensation module further optimizes the utilization efficiency of electric energy by compensating for reactive power. It can be understood that power factor correction not only improves the utilization rate of electric energy, but also reduces the reactive power in the power grid and optimizes the overall performance of the system.

[0145] Furthermore, the overload protection circuit is used to cut off the power supply when the current exceeds the threshold and dynamically adjust the trigger threshold. The overload protection mechanism automatically adjusts the trigger threshold by monitoring the current changes in real time to ensure that the device can be effectively protected under different load conditions. It can be understood that the dynamic adjustment mechanism of overload protection can respond to current changes more flexibly and improve the reliability and safety of the system.

[0146] Furthermore, the overheat protection circuit is used to cut off the power supply when the contact point temperature exceeds the threshold value, and dynamically adjust the trigger threshold value. The overheat protection mechanism automatically adjusts the trigger threshold value by real-time monitoring of the temperature field data to ensure that the contact point will not be damaged due to excessive temperature. It can be understood that the dynamic adjustment mechanism of overheat protection can detect and handle temperature anomalies more promptly, thereby improving the safety and reliability of the system.

[0147] Furthermore, the data storage module is used to store the system's operation logs and user feedback data to support subsequent data analysis and optimization. The data storage module includes internal memory and external memory, which can record the system's operating status and user operation records. Through data analysis, the system's adaptive control algorithm can be further optimized and the system's performance can be improved. It should be understood that the support of data storage and analysis enables the system to be continuously improved and optimized.

[0148] Through this embodiment, comprehensive optimization and integration of the electrical adaptive control system is achieved. The use of multiple sensors and monitoring modules ensures that the system can comprehensively and accurately obtain electrical environment parameters. The multiple optimization algorithms of the adaptive algorithm module enable the system to flexibly respond to complex electrical environments. The combination of multiple protection mechanisms and prompt systems improves the security of the system and the user's safety awareness. The benefit of this embodiment is that through the comprehensive optimization and integration of the system, efficient, stable and safe operation of the charging head under different conditions of use is achieved, thereby improving the overall performance of the system.

[0149] Embodiment 9

[0150] According to the electrical adaptive control system described in the above embodiments, Figures 9 to 13 As shown, this embodiment proposes a structure and function of an electrical adaptive control conversion socket to ensure the stability and easy replacement of the plug component 3.

[0151] In this embodiment, an electrical adaptive control conversion socket is designed, including a charging head body 1 and a replaceable plug component 3. The charging head body 1 is provided with L-level, N-level and ground-level contact plugs 2, which are used to connect the live wire, the neutral wire and the ground wire respectively. It should be understood that this multi-level contact design can ensure a stable connection between the charging head and the socket, and improve the reliability of the system.

[0152] Furthermore, the plug component 3 is fixed in the charging head body 1 through an elastic plastic structure 4. The elastic plastic structure 4 includes an unlocking button 41 movably mounted on one side of the charging head body 1, which is used to unlock the plug component 3. The unlocking button 41 is made of a highly elastic material, such as polyurethane or polypropylene, to ensure that the user feels comfortable during pressing and releasing. It is understandable that the highly elastic unlocking button 41 can effectively reduce the user's operating force and improve the user experience.

[0153] Furthermore, a locking frame 42 is movably installed in the charging head body 1 for clamping and locking the plug component 3. One end of the locking frame 42 is fixed to a bracket 43 in the charging head body 1. The bracket 43 is made of high-strength, low-conductivity materials, such as polycarbonate, to ensure the strength and safety of the structure. It should be understood that the material selection of the bracket 43 affects the stability of the system. The polycarbonate bracket 43 can provide sufficient support while avoiding the risk of conductivity.

[0154] Furthermore, a reset spring 44 is installed between the unlocking button 41 and the locking frame 42. The reset spring 44 is a metal spring or an elastic rope to ensure that the unlocking button 41 can be quickly reset during the pressing and releasing process. The locking frame 42 is provided with a first inclined surface or curved surface structure 421, and the action end of the unlocking button 41 is provided with a second inclined surface or curved surface structure 411. When the user presses the unlocking button 41, the second inclined surface or curved surface structure 411 fits and squeezes the first inclined surface or curved surface structure 421, so that the locking frame 42 releases the plug component 3. It can be understood that the design of this inclined surface or curved surface can effectively increase the driving force of the unlocking button 41, ensuring that the plug component 3 can be smoothly unlocked during the pressing process.

[0155] Furthermore, the plug component 3 includes plugs of various standard specifications, such as EU standard plugs, US standard plugs and British standard plugs, which are suitable for power sockets in different countries and regions. The design of each plug specification takes into account its use requirements in different sockets, ensuring that various standard sockets can be seamlessly connected when the plug component 3 is replaced. It should be understood that the design of multi-specification plugs enables the conversion socket to be widely applicable to different electrical environments, significantly improving the versatility and convenience of the device.

[0156] Furthermore, the material selection of the elastic plastic structure 4 has also been optimized. The main part is made of polycarbonate PC material, which has high strength and good insulation performance, ensuring safety and durability in complex electrical environments. The elastic part is made of thermoplastic elastomer TPE material, which has good flexibility and resilience, and can ensure the smooth operation of the unlocking button 41 and the locking frame 42. It can be understood that the reasonable combination of materials not only improves the mechanical performance of the system, but also ensures electrical safety.

[0157] Through this embodiment, the optimized design and manufacture of the electrical adaptive control conversion socket are realized. The use of the elastic plastic structure 4 ensures the stability and easy replacement of the plug component 3. The selection of multiple materials and structures enables the system to remain stable and safe under different use conditions. The benefit of this embodiment is that through structural optimization and material selection, the overall performance of the conversion socket is improved, making it more suitable for the needs of modern electrical equipment.

[0158] The beneficial effects of the present invention are specifically embodied in that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An electrical adaptive control method, applied to a charging head with a replaceable plug, characterized in that: The steps of the control method include: Detect the action of plug replacement, obtain the physical connection status of the plug through the sensor module, and record the time and frequency of plug replacement; Identify the plug type, using the plug specification database and plug identification unit built into the charging head to identify the specification characteristics of the plug, wherein the specification characteristics include rated voltage, rated frequency, maximum carrying current and physical structure characteristics of the plug; Acquire current electrical environment parameters, acquire the voltage and frequency of the input power supply in real time through the voltage detection module and frequency detection module built into the charging head, and evaluate the waveform quality of the input power supply through the power quality analysis module; According to the recognition result and the current electrical environment parameters, the adaptive algorithm module is called to dynamically adjust the circuit parameters inside the charging head to ensure the stability of the output power; Monitor the changes of the electrical environment parameters in real time, determine whether the electrical equipment will overheat or overload during use through the contact point temperature monitoring module and the current monitoring module, and predict the change trend of the electrical environment parameters through the fuzzy logic algorithm; Sending prompt information, prompting the plug replacement status and current working status through the prompt module, and optimizing the accuracy of the prompt information through the machine learning model; The step of dynamically adjusting the circuit parameters inside the charging head includes: Calculate the voltage conversion factor K v And the frequency conversion factor K f : , , where V target and f target is the target voltage and target frequency preset according to the plug specification database, V input and f input The voltage and frequency of the input power actually detected; The voltage parameters and frequency parameters are adjusted by a nonlinear optimization algorithm to ensure the dynamic response of the output power supply. The expression of the nonlinear optimization algorithm is: , where J is the error function, V output,i and f output,j are the output voltage of the i-th sampling point and the output frequency of the j-th sampling point, N is the total number of sampling points of the output voltage, and M is the total number of sampling points of the output frequency; The dynamic response is monitored in real time using a feedback control mechanism, and parameters of the voltage conversion circuit and the frequency conversion circuit are dynamically adjusted according to the monitoring results to ensure the accuracy of the output voltage and the output frequency; During the adjustment process, an adaptive filter is used to eliminate harmonic interference of the input power supply to ensure the purity of the output voltage and output frequency.

2. The electrical adaptive control method according to claim 1, characterized in that: The step of evaluating the waveform quality of the input power supply by the power quality analysis module comprises: The instantaneous voltage waveform V of the input power supply is obtained through the voltage detection module input (t), and perform Fourier transform on it to obtain the spectral component V^ of the voltage input (f); The instantaneous frequency waveform f of the input power is obtained through the frequency detection module input (t), and perform wavelet transform on it to obtain the time-frequency distribution diagram W of the frequency f (t,f); The Kalman filter algorithm is used to smooth the voltage and frequency parameters, eliminate noise interference, and obtain a stable state estimation value V^ input and f^ input ; The power quality analysis module evaluates the waveform quality of the input power, including total harmonic distortion (THD) and voltage sag (Sag) parameters, and stores the evaluation results in the system log; If the evaluation result does not meet the preset safety standards, the system automatically triggers the alarm mechanism and sends the alarm information to the user's smart terminal through the wireless communication module or connecting cable.

3. The electrical adaptive control method according to claim 2, characterized in that: The step of adjusting the voltage parameters and the frequency parameters by the nonlinear optimization algorithm comprises: Construct a nonlinear model of voltage and frequency: , , where g1 and g2 are nonlinear functions, T(t) is the temperature time series, and is a random error; Optimize voltage and frequency parameters using gradient descent and Hessian matrix: , where x is the optimization variable vector, α and β are step size parameters, is the gradient vector, H(J) is the Hessian matrix; The convergence speed of parameters is adjusted through affine transformation and S-shaped function to improve the efficiency of optimization: , where x scaled represents the optimized variable vector after convergence, σ is the S-shaped function, A and b are the affine transformation parameters; The voltage and frequency parameters are further optimized using the particle swarm optimization algorithm to ensure that the optimal solution is found in the multi-objective optimization: , , where v i is the velocity of the ith particle, x i is the position of the ith particle, ω is the inertia weight, c1 and c2 are acceleration coefficients, r1 and r2 are random numbers, p i is the historical optimal position of the i-th particle, P global is the global optimal position; Using a feedback control mechanism to monitor the optimization results in real time, and dynamically adjusting the parameters of the particle swarm optimization algorithm according to the optimization results, so as to ensure the accuracy of the output voltage and the output frequency; The global search capability of the particle swarm optimization algorithm is improved by a simulated annealing algorithm to avoid falling into a local optimal solution.

4. The electrical adaptive control method according to claim 1, characterized in that: The step of real-time monitoring of changes in the electrical environment parameters comprises: The input current I of the socket is monitored in real time through the current sensor input (t) and output current I output (t); The input current I is evaluated using a sliding window mean and standard deviation statistical method. input (t) and output current I output Stability of (t): , ,in, is the size of the sliding window, μ I (t) and σ I (t) are the mean and standard deviation of the current at the current time point t; The input current I input (t) and output current I output (t) performing smoothing to improve the accuracy of current monitoring; The input current I is separated by using the variational mode decomposition (VMD) method. input (t) and output current I output (t) to evaluate the harmonic distortion of the current; According to the current monitoring results, the triggering threshold of the overload protection mechanism is dynamically adjusted.

5. The electrical adaptive control method according to claim 1, characterized in that: The step of determining whether the electrical equipment will not overheat or overload during use by using the contact point temperature monitoring module and the current monitoring module includes: Arrange a plurality of temperature sensors near the contact point between the plug and the charging head to monitor the temperature distribution of the contact point in real time to form temperature field data T (x, y, z, t); Use finite element analysis (FEA) to model temperature field data and predict heat distribution and heat dissipation paths at contact points; The combination of thermocouples and thermistors can improve the accuracy and response speed of temperature monitoring; Use fuzzy logic algorithms to evaluate temperature anomalies at contact points and determine the level of overheating risk; According to the overheating risk level, the triggering threshold of the overheating protection mechanism is dynamically adjusted.

6. The electrical adaptive control method according to claim 1, characterized in that: The dynamically adjusting the circuit parameters inside the charging head also includes using a power factor correction algorithm, and the steps of the power factor correction algorithm include: Detect the current and voltage waveform of the input power supply I input (t) and V input (t), and calculate the phase angle of the input current : , where Δt k is the time difference of the kth sampling point, I input,k and V input,k are the input current and voltage of the kth sampling point respectively; Calculate the current power factor PF input (t): ； According to the preset target power factor PF target , calculate the required phase correction value : ； The Kalman filter is used to smooth the phase correction value, eliminate noise interference, and obtain a stable state estimate. : , where K(t) is the Kalman gain, z(t) is the observation value, and H is the observation matrix; The phase correction circuit is used to adjust the phase of the input current so that the actual power factor PF actual Close to the target power factor PF target ; The power factor after phase correction is monitored in real time through the feedback mechanism to ensure that it remains at the target power factor PF target within the scope of If the monitored power factor deviates from the target power factor PF target , adjust the parameters of the phase correction circuit until the power factor returns to normal; Through the adaptive control mechanism, the parameters of the phase correction algorithm are dynamically adjusted according to the changes in the output load to ensure that the power factor can be corrected under different load conditions.

7. An electrical adaptive control system, used to execute the electrical adaptive control method according to any one of claims 1 to 6, applied to a charging head with a replaceable plug, characterized in that: The control system comprises: A sensor module for detecting the physical connection status of the plug; A plug specification database and a plug identification unit, used to identify specification features of the plug; The voltage detection module and the frequency detection module are used to obtain the voltage and frequency of the input power supply in real time and perform Fourier transform and wavelet transform; Power quality analysis module, used to evaluate the waveform quality and stability of the input power, including total harmonic distortion (THD) and voltage sag (Sag) parameters; Adaptive algorithm module, including nonlinear optimization algorithm, particle swarm optimization (PSO) algorithm and simulated annealing algorithm, is used to dynamically adjust the parameters of the internal circuit according to the recognition results and the current electrical environment parameters to ensure the stability of the output power supply; The contact point temperature monitoring module is used to monitor the temperature of the contact points between the plug and the charging head in real time and to model them using the finite element analysis (FEA) method; The current monitoring module is used to monitor the input current and output current of the socket in real time and evaluate them using the statistical method of sliding window mean and standard deviation; Prompt system, including LED indicator light, buzzer, voice prompt module and multi-modal perception module, used to send prompt information and operation guide to users; A voltage conversion circuit, used to convert the input voltage into a desired target voltage, including linear conversion and nonlinear conversion; A frequency conversion circuit, used for converting an input frequency into a desired target frequency, including synchronous conversion and asynchronous conversion; A power factor correction circuit is used to correct the power factor of the input power supply, including phase correction and reactive power compensation; Overload protection circuit, used to cut off the power supply when the current exceeds the threshold and dynamically adjust the trigger threshold; Overheat protection circuit, used to cut off the power supply when the contact point temperature exceeds the threshold and dynamically adjust the trigger threshold; The data storage module is used to store the system's operation logs and user feedback data to support subsequent data analysis and optimization.

8. An electrical adaptive control conversion socket, characterized in that: The conversion socket includes the electrical adaptive control system according to claim 7, and further includes: The charging head body (1) is provided with L-level, N-level and ground-level contact plugs (2); A replaceable plug component (3) is fixed in the charging head body (1) via an elastic plastic structure (4); the plug component (3) includes plugs of various standard specifications for adapting to different power sockets; the elastic plastic structure (4) is used to ensure the stability and ease of replacement of the connection between the plug component (3) and the charging head body (1); The elastic plastic structure (4) comprises: An unlocking button (41) movably mounted on one side of the charging head body (1) and used for unlocking the plug component (3); A locking frame (42) movably mounted in the charging head body (1) and used for clamping and locking the plug component (3); A bracket (43) fixed inside the charging head body (1), one end of the locking bracket (42) being fixed on the bracket (43); A return spring (44) is installed between the unlocking button (41) and the locking frame (42); a first inclined surface or curved surface structure (421) is provided on the locking frame (42); and a second inclined surface or curved surface structure (411) is provided at the action end of the unlocking button (41); When the unlocking button (41) is pressed, the second inclined surface or curved surface structure (411) fits against and presses the first inclined surface or curved surface structure (421), and the locking frame (42) releases the plug component (3).

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