Intelligent power converter system based on adaptive load regulation and control method thereof

Abstract

The invention relates to the technical field of power conversion, and discloses an intelligent power converter system based on adaptive load regulation and a control method thereof. Comprising a power converter body, a plurality of sockets of different types are arranged on the power converter body, and a load sensing sensor, a micro-control unit, a step-down circuit and a bridge circuit are arranged in the power converter body; the load sensing sensor is electrically connected with the micro-control unit and is used for monitoring the power requirement of equipment connected with each socket in real time and transmitting a corresponding monitoring signal to the micro-control unit; the micro-control unit is electrically connected with the step-down circuit and the bridge circuit, and is used for controlling the step-down circuit and the bridge circuit to adjust output voltage and current according to a monitoring signal transmitted by the load sensing sensor; the micro-control unit controls the step-down circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding jacks according to the equipment power requirement monitored by the load sensing sensor, so as to realize the self-adaptive load adjustment of each jack.

Description

Technical Field

[0001] The present application relates to the field of power conversion technology, and in particular to an intelligent power converter system based on adaptive load regulation and a control method thereof. Background Art

[0002] In traditional power conversion devices, power converters typically use a fixed voltage output mode. For example, common power strips and chargers can only provide a single or preset voltage / current specification and cannot dynamically adjust output parameters based on the actual power requirements of the connected device. Specific shortcomings are as follows: 1. Lack of intelligent load identification capabilities: Existing equipment cannot monitor the power requirements of connected devices in real time. For different types of power-consuming devices (such as mobile phones, laptops, small household appliances, etc.), they all output a fixed voltage. This leads to "overvoltage power supply" problems when low-power devices are connected, resulting in energy waste and increased risk of equipment aging.

[0003] 2. Insufficient voltage conversion flexibility: When the input mains voltage does not match the voltage required by the device (for example, a 110V device connected to a 220V mains or vice versa), traditional converters rely on external transformers or fixed step-down modules. They cannot achieve dynamic voltage conversion through built-in circuits and do not support independent adjustment of multiple sockets, limiting their applicability.

[0004] 3. Single energy efficiency optimization method: Existing solutions only improve energy efficiency through fixed-efficiency circuit design and lack dynamic adjustment strategies based on real-time load data. Especially under low-load conditions, the proportion of circuit losses increases, and the overall power conversion efficiency is low, which does not meet the needs of green energy development.

[0005] 4. Lagging safety protection mechanisms: Traditional devices rely on hardware threshold triggers for overvoltage / overcurrent protection, which cannot be predicted based on device type and real-time power requirements. This can lead to device damage due to voltage fluctuations or parameter mismatches, resulting in insufficient safety.

[0006] Therefore, there is an urgent need for an intelligent power converter system based on adaptive load regulation to solve at least one of the above problems. Summary of the Invention

[0007] The present application provides an intelligent power converter system based on adaptive load regulation and its control method, aiming to solve the problem that in traditional power conversion devices, power converters generally adopt a fixed voltage output mode. For example, common power strips and chargers can only provide a single or preset voltage / current specification and cannot dynamically adjust the output parameters according to the actual power requirements of the connected device.

[0008] In a first aspect, the present application provides an intelligent power converter system based on adaptive load regulation, comprising: A power converter body, the power converter body being provided with a plurality of different types of sockets, and the power converter body being equipped with a load sensing sensor, a microcontroller unit, a step-down circuit, and a bridge circuit; the load sensing sensor being electrically connected to the microcontroller unit for real-time monitoring of the power demand of the device connected to each socket and transmitting a corresponding monitoring signal to the microcontroller unit; the microcontroller unit being electrically connected to the step-down circuit and the bridge circuit, respectively, for controlling the step-down circuit and the bridge circuit to adjust the output voltage and current according to the monitoring signal transmitted by the load sensing sensor; When the device connected to the socket requires low-voltage DC power supply, the microcontroller controls the step-down circuit to reduce the input voltage to the voltage required by the device and adjust the output current; when the socket is connected to different mains voltage inputs, the microcontroller controls the bridge circuit to convert the input mains voltage into a target voltage suitable for the socket; the microcontroller controls the step-down circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding socket according to the power demand of the device monitored by the load sensing sensor, so as to achieve adaptive load regulation for each socket.

[0009] In some embodiments, when the device connected to the socket requires low-voltage DC power supply, the microcontroller unit controls the step-down circuit to reduce the input voltage to the voltage required by the device and adjust the output current, including: when the device is plugged into the socket, the load sensing sensor obtains the rated voltage parameters of the device in real time, and the microcontroller unit controls the step-down circuit to gradually reduce the input AC voltage to the DC voltage required by the device according to the rated voltage parameters, and dynamically adjusts the current according to the corresponding real-time power demand of the device, so that the output voltage fluctuation range is within the preset fluctuation range of the rated voltage.

[0010] In some embodiments, when the socket is connected to different mains voltage inputs, the microcontroller unit controls the bridge circuit to convert the input mains voltage into a target voltage suitable for the socket, including: when the socket is connected to the mains as input, the bridge circuit converts the mains power corresponding to the mains into a target voltage suitable for the socket according to the socket specification parameters, and during the conversion process, the frequency and phase of the output voltage are monitored in real time by the microcontroller unit to ensure that the distortion of the converted voltage waveform is less than the preset distortion, and the on-off frequency of the switching tube of the bridge circuit is adjusted to achieve voltage level matching and two-way transmission of electric energy between different sockets.

[0011] In some embodiments, the step-down circuit and the bridge circuit are controlled to automatically adjust the output voltage and current of the corresponding socket according to the power demand of the device monitored by the load sensing sensor to achieve adaptive load regulation for each socket, including: when the load sensing sensor detects that the power of the device connected to the socket is less than a preset threshold, the microcontroller unit adjusts the output voltage to the minimum effective voltage actually required by the device, and reduces the output current according to the adjustment ratio corresponding to the minimum effective voltage, so that the device can reduce the energy loss caused by the internal resistance of the circuit while meeting normal operation.

[0012] In some embodiments, the microcontroller unit is also used to automatically identify the device type based on the device startup current waveform and continuous power data collected by the load sensing sensor, and match the optimal voltage regulation strategy according to a preset device type database, wherein the preset device type database includes voltage-power matching parameters of multiple electrical devices.

[0013] Exemplarily, the microcontroller unit stores power regulation data of historically connected devices, and dynamically optimizes the response speed and accuracy of voltage regulation by analyzing the voltage adaptation process when the device is repeatedly connected, thereby shortening the voltage adjustment time when the same type of device is connected again.

[0014] In some embodiments, the load sensing sensor includes a current transformer and a voltage sensor, which are integrated into the power supply circuit of each socket to respectively collect the input current and port voltage of the device in real time. The microcontroller unit calculates the real-time power based on the collected data and performs abnormality detection. When it is detected that the power mutation exceeds the preset mutation range of the rated value, the overvoltage protection or overcurrent protection mechanism is triggered to cut off the power supply of the corresponding socket.

[0015] In some embodiments, an independent power management module is provided inside the power converter body, and the power management module includes a filtering circuit and an energy storage capacitor. The filtering circuit is used to filter out the high-frequency noise generated when the step-down circuit and the bridge circuit are working, and the energy storage capacitor maintains stable power supply when the input voltage fluctuates instantaneously to ensure the continuous monitoring function of the micro control unit and the load sensing sensor.

[0016] In some embodiments, a human-computer interaction interface is provided on the surface of the power converter body, and the human-computer interaction interface includes a status indicator light and a parameter adjustment button, through which the voltage upper limit and current protection threshold of any socket can be set.

[0017] In a second aspect, the present application provides a control method for an intelligent power converter system based on adaptive load regulation, which is applied to the intelligent power converter system based on adaptive load regulation provided in any embodiment of the present application; the method comprises: When the device connected to the socket requires low-voltage DC power supply, the step-down circuit is controlled to reduce the input voltage to the voltage required by the device and adjust the output current; When the socket is connected to a different mains voltage input, the control bridge circuit converts the input mains voltage into a target voltage suitable for the socket; According to the power demand of the equipment monitored by the load sensing sensor, the buck circuit and the bridge circuit are controlled to automatically adjust the output voltage and current of the corresponding socket to achieve adaptive load regulation for each socket.

[0018] This application provides a method and system for adaptive frequency adjustment and muscle relaxation intensity control for a fascia massage gun. This approach aims to address the existing lack of a power converter system that integrates a load-sensing sensor, a microcontroller unit (MCU), a buck circuit, and a bridge circuit, and uses an intelligent algorithm to achieve independent adaptive adjustment for multiple outlets. The core flaw of existing solutions lies in their passive fixed output, rather than active sensing and dynamic adaptation. This application uses a load-sensing sensor to monitor the power requirements of each outlet in real time. Combined with the dynamic control strategy of the MCU, this method automatically identifies the voltage and current requirements of different devices, such as mobile phones and small household appliances. This enables intelligent conversion from 110V / 220V mains power to low-voltage DC (DC) such as 5V and 9V, or between different mains voltages, supporting a wide range of device types and application scenarios. It automatically reduces the output voltage and current for low-power devices, avoiding the excess energy consumption associated with traditional fixed high-voltage power supplies. This improves power conversion efficiency, significantly reduces energy waste, and meets energy conservation and emission reduction requirements. Through the coordinated control of the buck circuit (BUCK circuit) and the H-Bridge circuit (H-Bridge circuit), damage to devices caused by voltage anomalies is effectively prevented, improving power supply reliability. By integrating load monitoring, parameter adjustment, and protection mechanisms into the same control system, the system responds to device power changes in real time and quickly triggers overvoltage / overcurrent protection when a sudden power change is detected. Compared to traditional hysteresis protection mechanisms, this reduces response time to less than 200 milliseconds, comprehensively improving system safety. Through a built-in power classification algorithm and adaptive learning module (as expanded by the dependent claims), the system automatically matches the optimal voltage strategy and optimizes regulation accuracy, eliminating the need for manual user configuration. This delivers a "plug-and-play" intelligent power supply experience, significantly different from traditional power conversion devices that require manual intervention or fixed parameters.

[0019] In summary, the present invention solves the problems of poor adaptability, low energy efficiency and insufficient safety in the existing technology through the core architecture of "load sensing-intelligent decision-making-dynamic adjustment", provides a new technical path for the intelligent and efficient development of power conversion equipment, and has significant creativity and practical value.

[0020] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0022] Figure 1 This is a schematic block diagram of the structure of an intelligent power converter system based on adaptive load regulation provided by an embodiment of the present application; Figure 2 This is a schematic structural diagram of a power converter body provided by an embodiment of the present application; Figure 3 This is a flowchart illustrating the steps of a control method for an intelligent power converter system based on adaptive load regulation provided by an embodiment of the present application; Figure 4 This is a schematic block diagram of the structure of a micro control unit provided in one embodiment of the present application.

[0023] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0025] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined, or partially merged, so the actual execution order may vary depending on the actual situation.

[0026] It should be understood that, in order to clearly describe the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, terms such as "first" and "second" are used to distinguish between identical or similar items having substantially the same functions and effects. Those skilled in the art will understand that terms such as "first" and "second" do not limit the quantity or order of execution, and that terms such as "first" and "second" do not necessarily define differences.

[0027] It should be understood that the terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0028] It will also be understood that the term "and / or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0029] The following describes some embodiments of the present application in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features therein may be combined with each other.

[0030] In traditional power conversion devices, power converters typically use a fixed voltage output mode. For example, common power strips and chargers can only provide a single or preset voltage / current specification and cannot dynamically adjust output parameters based on the actual power requirements of the connected device. Specific shortcomings are as follows: 1. Lack of intelligent load identification capabilities: Existing equipment cannot monitor the power requirements of connected devices in real time. For different types of power-consuming devices (such as mobile phones, laptops, small household appliances, etc.), they all output a fixed voltage. This leads to "overvoltage power supply" problems when low-power devices are connected, resulting in energy waste and increased risk of equipment aging.

[0031] 2. Insufficient voltage conversion flexibility: When the input mains voltage does not match the voltage required by the device (for example, a 110V device connected to a 220V mains or vice versa), traditional converters rely on external transformers or fixed step-down modules. They cannot achieve dynamic voltage conversion through built-in circuits and do not support independent adjustment of multiple sockets, limiting their applicability.

[0032] 3. Single energy efficiency optimization method: Existing solutions only improve energy efficiency through fixed-efficiency circuit design and lack dynamic adjustment strategies based on real-time load data. Especially under low-load conditions, the proportion of circuit losses increases, and the overall power conversion efficiency is low, which does not meet the needs of green energy development.

[0033] 4. Lagging safety protection mechanisms: Traditional devices rely on hardware threshold triggers for overvoltage / overcurrent protection, which cannot be predicted based on device type and real-time power requirements. This can lead to device damage due to voltage fluctuations or parameter mismatches, resulting in insufficient safety.

[0034] Therefore, there is an urgent need for an intelligent power converter system based on adaptive load regulation to solve at least one of the above problems.

[0035] To solve the above problems, please refer to Figures 1 to 2The present application provides an intelligent power converter system based on adaptive load regulation, comprising: a power converter body, on which a plurality of different types of sockets are provided, the power converter body having a built-in load sensing sensor, a microcontroller unit, a step-down circuit, and a bridge circuit; the load sensing sensor is electrically connected to the microcontroller unit, and is used to monitor the power demand of the device connected to each socket in real time and transmit the corresponding monitoring signal to the microcontroller unit; the microcontroller unit is electrically connected to the step-down circuit and the bridge circuit, respectively, and is used to control the step-down circuit and the bridge circuit to adjust the output voltage and current according to the monitoring signal transmitted by the load sensing sensor; when the device connected to the socket requires low-voltage DC power supply, the microcontroller unit controls the step-down circuit to reduce the input voltage to the voltage required by the device and regulate the output current; when the socket is connected to a different mains voltage input, the microcontroller unit controls the bridge circuit to convert the input mains voltage to a target voltage suitable for the socket; the microcontroller unit controls the step-down circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding socket according to the power demand of the device monitored by the load sensing sensor, so as to achieve adaptive load regulation for each socket.

[0036] Specifically, this intelligent power converter system uses the power converter body as a carrier and integrates the following core functional modules to achieve adaptive adjustment of the load: Multi-type socket design: The body is equipped with multiple different types of sockets (such as USB-A, USB-C, AC jack, etc.), supporting the access of different devices such as mobile phones, laptops, small appliances, etc., and is compatible with various interface forms and power requirements. Figure 2As shown, the main body can also be integrated with modules such as a power input box, heat dissipation holes, a power button, and a display light. Load sensing sensor: Each socket has a built-in independent voltage / current sensor (or integrated power sensor) to monitor the real-time power (P=U×I), voltage, current and other parameters of the connected device in real time, and transmit the monitoring signal (analog or digital) to the microcontroller unit (MCU). Microcontroller unit (MCU): The core control module of the system, with built-in load identification algorithm and adjustment strategy. Its functions include: receiving load sensing sensor data, analyzing the power requirements of the device (such as identifying the mobile phone fast charging protocol, the rated voltage of home appliances, etc.); generating control instructions according to preset rules (such as the device type database, safety thresholds), driving the step-down circuit and the bridge circuit to dynamically adjust the output parameters; supporting independent control of multiple sockets to ensure that the outputs of each socket do not interfere with each other. The step-down circuit utilizes a DC-DC converter module (such as a buck circuit). When a device requires low-voltage DC power (e.g., charging a 5V / 9V / 12V mobile phone), the MCU controls the step-down circuit to reduce the rectified high-voltage DC voltage of the input mains (e.g., 220V AC) to the device's required voltage. The circuit then uses PWM (pulse width modulation) to adjust the output current to meet the power requirement. The bridge circuit, consisting of a full-bridge rectifier and an inverter unit, is designed to handle different mains voltage input scenarios (e.g., converting from 110V to 220V). If the input mains voltage does not match the device's rated voltage, the bridge circuit converts the input voltage to the target voltage (e.g., converting 220V input to 110V output, or vice versa) through rectification, inversion, or step-down / step-up conversion. This supports bidirectional voltage conversion.

[0037] The system achieves adaptive load regulation through a closed-loop "sensing-processing-regulation": Load sensing: Sensors collect voltage and current signals from each socket in real time, calculate instantaneous power, and identify device type (e.g., distinguishing between mobile phones and laptops by their characteristic current waveforms) or directly read device communication protocols (e.g., voltage requests in the PD fast charging protocol). Policy processing: The MCU compares real-time monitoring data with a preset device power database (which stores parameters such as the rated voltage, current, and safety thresholds of common devices) to determine whether output adjustment is necessary. For example, if a low-power device (such as a mobile phone) is connected and the actual required power is detected to be lower than the fixed output power, the step-down circuit is triggered to reduce the voltage to the device's rated value to avoid "overvoltage power supply." If a 110V device is connected to a 220V mains supply, the bridge circuit activates the inverter function, converting 220V AC to 110V AC, eliminating the need for an external transformer. Dynamic adjustment: For each socket, the MCU independently controls the operating parameters of the buck circuit or bridge circuit: DC output scenario: By adjusting the PWM duty cycle of the buck circuit, the output voltage (such as 5V, 9V, 12V) and current (such as 1A, 2.4A, 3A) are precisely controlled to match the real-time needs of the device; AC voltage conversion scenario: The bridge circuit converts the input AC to DC through full-bridge rectification, and then generates the target AC voltage (such as 50Hz / 60Hz, 110V / 220V) through the inverter module, supporting wide voltage input and multi-standard output.

[0038] The load sensing module can use a high-precision Hall sensor or shunt resistor to collect current, and a voltage divider resistor to collect voltage. The signal is converted into a digital quantity by an ADC (analog-to-digital converter) and input into the MCU. For devices that support protocol communication (such as USB PD devices), the voltage / current parameters requested by the device are read through an interface chip (such as a PD controller) to improve recognition accuracy.

[0039] The step-down circuit can be implemented using a synchronous buck converter (such as the LM2596 or TPS5430). This converter supports a wide input voltage range (e.g., 40V-300V DC), has an adjustable output voltage (1.23V-37V), and boasts an efficiency exceeding 90%. The MCU configures the buck chip's feedback resistor or PWM frequency through the SPI / I2C interface, dynamically adjusting the output voltage while controlling the output current through the current loop to ensure it does not exceed the device's rated value.

[0040] The bridge circuit can be implemented by using a bridge rectifier (such as GBJ2006) in the rectification part to convert the input AC into pulsating DC, which is smoothed by the filter capacitor and then enters the inverter module; the inverter part uses an IGBT or MOSFET full-bridge circuit, and the MCU generates an SPWM (sine wave pulse width modulation) signal to drive the switching tube, converting the DC into the target AC voltage (such as 110V / 60Hz), and filtering out harmonics through an LC filter.

[0041] Multi-socket independent control: Each socket corresponds to an independent sensor, buck / bridge circuit sub-module, and the MCU controls them separately through time division multiplexing or parallel IO ports to ensure the regulation accuracy when multiple devices are connected at the same time.

[0042] The device type identification algorithm establishes a device feature database to store the power range and voltage / current waveform characteristics of common devices (such as the sudden increase in current during the fast charging stage of mobile phones and the stable high power requirements of laptops). It uses pattern matching algorithms (such as threshold comparison and machine learning classification) to identify device types based on real-time power curves and dynamically call corresponding adjustment strategies (such as prioritizing stable voltage for laptops and optimizing energy efficiency for mobile phones).

[0043] The dynamic adjustment logic includes: low-voltage DC scenario: if it is monitored that the actual required voltage of the device is lower than the current output voltage, the MCU gradually reduces the output voltage of the step-down circuit to the device rated value, while limiting the current to not exceed the maximum allowable value of the device; AC power conversion scenario: when the difference between the input voltage and the rated voltage of the device exceeds the preset threshold (such as ±10%), the bridge circuit is triggered to start the conversion. During the conversion process, the output voltage fluctuation is monitored in real time, and the output is stabilized through the PID (proportional-integral-differential) algorithm.

[0044] The safety protection mechanism includes: preset overvoltage (such as output voltage exceeding the rated value by 15%), overcurrent (exceeding the rated current of the device by 20%), and overheating (temperature exceeding 85°C) thresholds. Once triggered, the MCU immediately cuts off the power supply to the corresponding socket and alarms through the LED or APP; dynamically adjusts the protection threshold based on the device type (such as small household appliances allow slightly higher current fluctuations, and precision electronic equipment set stricter thresholds), realizing "predictive protection" rather than simple hardware triggering.

[0045] User Interface: An optional LED screen displays the real-time voltage, current, and power of each socket, or connects to the app via Bluetooth / Wi-Fi to support manual setting of output parameters (requires permission control to avoid security risks). Firmware Upgrade: Supports OTA (Over-the-Air) updates to the device feature database and adjustment algorithm to adapt to the access requirements of new devices (such as higher-power fast-charging devices).

[0046] Through real-time power monitoring and device type identification, the system provides matching voltage and current for low-power devices (such as mobile phones), eliminating energy waste caused by fixed high-voltage output and extending device life. A built-in bridge circuit supports bidirectional conversion between 110V and 220V mains power, eliminating the need for an external transformer and maintaining compatibility with global voltage standards. Multiple independent outlets allow simultaneous connection of devices with different voltage requirements (e.g., powering a 220V coffee maker and a 110V shaver simultaneously), making it ideal for travel and multi-device office environments. A real-time load-based adjustment strategy (e.g., reducing circuit losses at low loads and optimizing conversion efficiency at full load) improves overall system efficiency compared to traditional fixed-efficiency designs, particularly under light-load conditions, significantly reducing internal losses. Predictive protection based on device type and real-time data (e.g., preemptively adjusting output before detecting abnormal voltage fluctuations) avoids the hysteresis inherent in traditional hardware threshold triggering, reducing the risk of device damage from overvoltage and overcurrent, and enhancing safety.

[0047] It supports multiple types of sockets such as USB and AC, and is suitable for a full range of devices from 5V mobile phones to 220V household appliances. It replaces multiple single-function converters and simplifies user device management. Each socket works independently, and a single socket failure does not affect the operation of other sockets, improving system reliability. The hardware is expandable (such as adding a wireless charging module) to adapt to future device upgrades.

[0048] Through the combination of "hardware intelligence + software strategy", the system upgrades the traditional power converter from "fixed parameter output" to "dynamic adaptive adjustment", which not only solves practical problems such as energy waste and scene restrictions, but also conforms to the current development trends of "energy conservation and emission reduction" and "equipment intelligence", and has broad application prospects in home, office and industrial fields.

[0049] In some embodiments, when the device connected to the socket requires low-voltage DC power supply, the microcontroller unit controls the step-down circuit to reduce the input voltage to the voltage required by the device and adjust the output current, including: when the device is plugged into the socket, the load sensing sensor obtains the rated voltage parameters of the device in real time, and the microcontroller unit controls the step-down circuit to gradually reduce the input AC voltage to the DC voltage required by the device according to the rated voltage parameters, and dynamically adjusts the current according to the corresponding real-time power demand of the device, so that the output voltage fluctuation range is within the preset fluctuation range of the rated voltage.

[0050] When the socket is connected to a device that requires low-voltage DC power supply, the system obtains the device's rated voltage parameters through a load-sensing sensor. The microcontroller unit (MCU) controls the step-down circuit to gradually step down the input AC voltage (such as 220V AC) to the DC voltage required by the device (such as 5V / 9V / 12V), and dynamically adjusts the current based on the real-time power to ensure that the output voltage fluctuation range is within the preset fluctuation range of the rated voltage (such as ±5%).

[0051] Rated voltage acquisition: For devices that support the communication protocol (such as USB PD devices), the voltage request (such as "9V / 2A required") issued by the device is read through an interface chip (such as the RT5400). For non-intelligent devices (such as ordinary USB devices), the current / voltage data collected during initial connection by a load-sensing sensor is combined with built-in default parameters (such as the 5V standard) to infer the rated voltage.

[0052] Step-by-step voltage control uses a multi-stage Buck converter cascade or a single-stage adjustable Buck circuit (such as the LM2596) in the buck circuit. The MCU controls the switch tube through the PWM signal to reduce the voltage in stages (for example, from 310V DC after rectification of 220V AC, first to 20V DC, and then to the target voltage of 9V DC). The step size of each step does not exceed 20% of the target voltage to prevent sudden voltage drops from impacting the equipment.

[0053] Dynamic current regulation calculates device power (P=U×I) in real time, and the MCU adjusts the output current of the Buck circuit through a current feedback loop. For example, when the device enters the trickle charging phase (power reduction), the current is automatically reduced to 0.5A. At the same time, the ADC monitors the output voltage in real time to ensure that the fluctuation does not exceed ±5%.

[0054] It avoids the "overvoltage" problem of traditional fixed voltage output, for example, providing a precise 5V±0.25V voltage for 5V mobile phones, reducing the loss of the device's internal voltage regulator and extending battery life; the step-by-step voltage reduction prevents inrush current, which is especially suitable for capacitive load devices (such as wireless earphone charging boxes), reducing the risk of voltage shock during startup; it supports DC output devices from 3.3V to 20V without replacing the converter, improving the versatility of the socket.

[0055] In some embodiments, when the socket is connected to different mains voltage inputs, the microcontroller unit controls the bridge circuit to convert the input mains voltage into a target voltage suitable for the socket, including: when the socket is connected to the mains as input, the bridge circuit converts the mains power corresponding to the mains into a target voltage suitable for the socket according to the socket specification parameters, and during the conversion process, the frequency and phase of the output voltage are monitored in real time by the microcontroller unit to ensure that the distortion of the converted voltage waveform is less than the preset distortion, and the on-off frequency of the switching tube of the bridge circuit is adjusted to achieve voltage level matching and two-way transmission of electric energy between different sockets.

[0056] When the socket is connected to different mains voltages (such as 110V / 220V), the bridge circuit converts the input mains into an adaptive target voltage according to the socket specifications (such as the target voltage 110V or 220V). During the conversion process, the MCU monitors the frequency (such as 50Hz / 60Hz) and phase of the output voltage in real time to ensure that the waveform distortion is less than 5%. By adjusting the on-off frequency of the switching tube, voltage level matching and two-way power transmission between multiple sockets are achieved (for example, a 220V input port powers 110V devices and directly supplies other 220V devices at the same time).

[0057] The bridge circuit structure uses a full-bridge inverter circuit (four IGBT switches) + LC filter. The input AC power is converted to DC through a bridge rectifier (such as the KBPC3510), and then the target AC voltage is generated through the inverter module. The MCU locks the frequency and phase of the input voltage through a digital phase-locked loop (PLL) algorithm to ensure the frequency accuracy of the output voltage (such as 50Hz±0.1Hz). The switching tube is controlled by SPWM technology to control the harmonic distortion (THD) within 5%.

[0058] The bidirectional conversion control operates in step-down inverter mode when the input is 220V AC and the device requires 110V. When the input is 110V and the device requires 220V, the step-up inverter mode is activated (achieved by adjusting the SPWM duty cycle). When multiple sockets are controlled independently, the MCU assigns an independent switching frequency to the bridge sub-module of each socket (for example, socket 1 operates at 60Hz and socket 2 operates at 50Hz) to avoid mutual interference.

[0059] No external transformer is required, and it directly adapts to the 100-240V wide input range to meet the needs of international travel and mixed device use in multiple regions; the low-distortion waveform (THD < 5%) protects precision equipment (such as laptop power adapters) and avoids equipment failure caused by waveform distortion of traditional converters; it can simultaneously power 110V / 60Hz and 220V / 50Hz devices, for example, powering an American electric shaver and a Chinese desk lamp on the same socket without switching modes.

[0060] In some embodiments, the step-down circuit and the bridge circuit are controlled to automatically adjust the output voltage and current of the corresponding socket according to the power demand of the device monitored by the load sensing sensor to achieve adaptive load regulation for each socket, including: when the load sensing sensor detects that the power of the device connected to the socket is less than a preset threshold, the microcontroller unit adjusts the output voltage to the minimum effective voltage actually required by the device, and reduces the output current according to the adjustment ratio corresponding to the minimum effective voltage, so that the device can reduce the energy loss caused by the internal resistance of the circuit while meeting normal operation.

[0061] When the load sensing sensor detects that the device power is less than the preset threshold (such as 10W), the MCU adjusts the output voltage to the minimum effective voltage actually required by the device (such as from 9V to 5V when the mobile phone is in standby mode) and reduces the current in proportion to the voltage adjustment ratio (such as from 2A to 1.1A) to minimize the loss caused by the internal resistance of the circuit (such as the resistance of the connecting wire and solder joint) (P=I 2 R).

[0062] Low-power detection and threshold setting can be configured by factory preset thresholds (such as 10W) ​​or user-defined. The MCU calculates the power P = U × I in real time. When P is less than the threshold for 5 consecutive seconds, the energy-saving mode is triggered. The minimum effective voltage is matched against the device feature database (for example, the minimum operating voltage of a mobile phone charging chip is 4.5V, and the minimum operating voltage of a laptop USB port is 5V), ensuring that the device does not restart or report errors.

[0063] Voltage-current coordinated regulation uses an "equal power factor" regulation strategy: output power P'=U'×I', where U'≥the device's minimum operating voltage, I'=P' / U', and I'≤the device's maximum allowable current. For example, if the device's current power is 5W and the minimum effective voltage is 5V, then I'=1A (5W / 5V). Compared to the original fixed output of 9V, the actual current may be 0.55A (5W / 9V), and the loss is (0.55A). 2 R; after adjustment 5V / 1A, the loss is (1A) 2 When the device's actual power demand is fixed, lowering the voltage requires increasing the current. However, the circuit's internal resistance loss is proportional to the square of the current. Therefore, when the device's power is low, its actual required voltage may be lower than the rated voltage (for example, a mobile phone in standby mode doesn't require high-voltage fast charging). In this case, actively reducing the voltage to the lowest value at which the device can still operate may result in the device's actual current remaining unchanged or decreasing (because power = voltage × current, if power is reduced, both voltage and current can be reduced simultaneously). The correct adjustment should be: when the device's power is reduced, if the voltage is allowed to decrease (for example, from 9V fast charging to 5V slow charging), the current may remain the same or decrease slightly, ultimately reducing total losses (including the converter's own losses and line losses).

[0064] In low-power scenarios (such as device standby and trickle charging), by reducing the voltage to the lowest effective value, the internal switching loss of the converter and the line resistance loss are reduced, and it is calculated that the light-load efficiency can be improved; for devices that rely on battery power (such as smart watch chargers), the voltage and current are provided to just meet the needs, avoiding "excess power supply" caused by battery heating and life loss; universal energy-saving strategy: no equipment cooperation is required, and it is actively adapted through sensor data, suitable for all types of low-voltage DC equipment.

[0065] In some embodiments, the microcontroller unit is also used to automatically identify the device type based on the device startup current waveform and continuous power data collected by the load sensing sensor, and match the optimal voltage regulation strategy according to a preset device type database, wherein the preset device type database includes voltage-power matching parameters of multiple electrical devices.

[0066] The MCU uses load-sensing sensors to collect the startup current waveform (such as the inrush current curve at the moment of power-on) and continuous power data (such as the power value during stable operation) when the device is connected, and matches them with the preset device type database (which stores the voltage-power matching parameters of devices such as mobile phones, laptops, and routers, such as the startup current of mobile phones ≤2A and the startup current of laptops 3-5A). It automatically identifies the device type and calls the optimal adjustment strategy (such as the fast charging strategy that prioritizes mobile phones and the stable voltage strategy that prioritizes laptops).

[0067] Characteristic data collection includes: startup phase: within 0.1-1 second after the device is plugged in, the current waveform is collected at a sampling rate of 10kHz to capture the inrush current peak and duration (for example, when a mobile phone fast charging device is started, the current suddenly rises to 2A, lasts for 0.2 seconds and then stabilizes); continuous phase: after stable operation, power data is collected every 1 second, and the average value and fluctuation range are recorded (for example, the router power is stable at 5W±0.5W).

[0068] Pattern matching algorithm: The database stores the characteristic vectors of each device, such as mobile phones: [starting current peak 1.8-2.4A, stable power 5-18W, voltage requirement 5 / 9 / 12V]; laptops: [starting current 3-6A, stable power 30-100W, voltage requirement 12-20V]. The dynamic time warping (DTW) algorithm is used to match the real-time waveform with the database template. When the match degree is greater than 80%, the device type is confirmed and the corresponding policy is invoked (for example, laptops trigger "constant voltage mode" and mobile phones trigger "fast charging protocol handshake").

[0069] There is no need for users to manually select the device type. The system automatically identifies and optimizes the output, for example, distinguishing between mobile phones and mobile power supplies (the latter may require reverse power supply) to avoid incorrect adjustments. It provides exclusive strategies for the characteristics of different devices (such as the startup surge of motor equipment and the voltage sensitivity of precision chips) to reduce compatibility issues caused by "one-size-fits-all" adjustments. Through universal sensor and database matching, it supports adding new device types by simply updating the database without hardware changes.

[0070] Exemplarily, the microcontroller unit stores power regulation data of historically connected devices, and dynamically optimizes the response speed and accuracy of voltage regulation by analyzing the voltage adaptation process when the device is repeatedly connected, thereby shortening the voltage adjustment time when the same type of device is connected again.

[0071] The MCU stores historical power adjustment data for connected devices (for example, when device A is first connected, it takes 0.5 seconds for the voltage to drop from 20V to 15V, with an adjustment step of 2V). When the same type of device is connected again, the MCU analyzes the voltage adaptation process in the historical data (such as the optimal step-down step and stabilization time) and dynamically optimizes the response speed and accuracy of the adjustment algorithm, reducing the voltage adjustment time for similar devices by more than 50% (for example, from 0.5 seconds to 0.25 seconds).

[0072] Data storage and management: By establishing a mapping table between device ID and adjustment log, the stored content includes: the time the device was first connected, the type (identified by Example 4), the voltage / current change curve during the adjustment process, the stabilization time, and the final parameters (U_target, I_target); a hash table is used to quickly retrieve historical data of similar devices. For example, a unique key value is generated by device type + rated voltage (for example, "mobile phone - 9V" corresponds to a set of optimized parameters).

[0073] Optimization algorithm implementation: A conservative strategy (small 1V step-down) is used for initial adjustment, and the stabilization time is recorded. For repeated connections, the step size is adjusted based on historical data (for example, if it is known that a certain type of mobile phone can accept a 3V / step step without triggering protection, then a larger step size is used directly). The target voltage is also predicted (for example, by skipping intermediate redundant steps and directly reducing the voltage from 310V DC after 220V rectification to the target 9V DC without stepping through intermediate values ​​such as 20V and 15V).

[0074] When a similar device is connected again, the voltage adjustment time is shortened from "seconds" to "hundreds of milliseconds", reducing device waiting time (for example, when charging a laptop, there is no need to renegotiate the voltage and it can directly enter the optimal state); the longer the system is used, the more accurate the adjustment strategy, which is especially suitable for multi-device scenarios in the home (just like a mobile phone is charged multiple times, the adaptation speed gradually increases); by predicting the target parameters, energy loss during multiple invalid adjustments is avoided, and the dynamic adjustment efficiency is improved.

[0075] For example, by introducing a deep learning neural network, the system eliminates the need to rely on a pre-set device type database. Instead, it autonomously trains and generates device characteristic models using real-time data collected from device startup current waveforms, steady-state power curves, and voltage response data. When a new device is first connected, the system extracts waveform features using a convolutional neural network (CNN) and compares them with historically learned feature vectors. This dynamically expands the device type library, enabling adaptive identification and regulation strategy generation for unknown devices.

[0076] Data acquisition and feature engineering: Sensors collect the current waveform for 0-2 seconds (including the startup surge phase) when the device is connected at a sampling rate of 20kHz, and convert it into a grayscale image (time on the horizontal axis, current amplitude on the vertical axis) as CNN input. Time domain features (such as surge peak value and rise time) and frequency domain features (harmonic distribution after FFT) are extracted to construct a multidimensional feature vector.

[0077] The incremental learning neural network uses the lightweight ResNet-18 model, and the initial weights are obtained through pre-training data from common devices (mobile phones, laptops, routers). When a new device is connected, if the matching degree is less than 70%, incremental learning is triggered: the new feature data is added to the training set, and the model is updated using transfer learning. At the same time, "catastrophic forgetting" is avoided through dynamic weight allocation. The device-specific adjustment strategy is generated: based on the identified device category (such as "unknown charging device"), the initial voltage adjustment sequence is generated through the reinforcement learning algorithm (Q-Learning) (such as reducing the voltage in 1V steps and waiting 200ms for each step to detect the device response).

[0078] It eliminates the need for manual database maintenance and automatically identifies new devices appearing on the market (such as new smart watches and customized industrial modules), resolving the issue of delayed updates to traditional preset databases. As more devices are connected, the recognition accuracy gradually improves, making the system increasingly "intelligent." It also identifies potential equipment failures (such as battery aging) in advance through abnormal waveform patterns (such as starting current oscillations).

[0079] In some embodiments, the load sensing sensor includes a current transformer and a voltage sensor, which are integrated into the power supply circuit of each socket to respectively collect the input current and port voltage of the device in real time. The microcontroller unit calculates the real-time power based on the collected data and performs abnormality detection. When it is detected that the power mutation exceeds the preset mutation range of the rated value, the overvoltage protection or overcurrent protection mechanism is triggered to cut off the power supply of the corresponding socket.

[0080] Load sensing sensors, consisting of a current transformer (CT, such as the TA123) and a voltage sensor (such as a voltage-divider resistor network), are integrated into the power supply circuit of each outlet to collect real-time data on the device's input current and port voltage. The MCU calculates real-time power consumption and detects anomalies. If power suddenly changes beyond a preset range (e.g., ±30%) of the rated value, overvoltage / overcurrent protection is triggered, immediately shutting off power to the corresponding outlet (with a response time of less than 100 μs).

[0081] Sensor hardware design: The current transformer uses a miniature closed-loop Hall effect sensor with an accuracy of ±1% and a 0-5A measurement range. It is connected in series in the power supply circuit. The voltage sensor uses a resistor divider (such as a 100kΩ + 10kΩ divider circuit) to reduce the port voltage (up to 220V AC) to a 0-3.3V range acceptable to the MCU ADC. The sampling frequency is 1kHz.

[0082] Abnormal detection logic: Real-time power P = U × I, with a preset normal fluctuation range (such as ±10% of the rated power). When P is detected to vary by more than ±30% within 200μs (such as a sudden increase in current due to a short circuit in the device, or a sudden drop in voltage due to a loose interface), a hardware interrupt is immediately triggered, and the MCU disconnects the relay or MOSFET switch of the corresponding socket through the GPIO. The protection threshold can be dynamically adjusted according to the device type (for example, motor devices allow ±20% fluctuation, while precision equipment only allows ±5%).

[0083] Compared with traditional hardware fuses (response time > 10ms), the electronic protection mechanism can cut off the power supply within 100μs, effectively preventing equipment damage due to instantaneous overvoltage / overcurrent (such as lightning surges and internal short circuits in the equipment); each socket is monitored independently, and a single socket failure does not affect other sockets. The fault type (such as the time and waveform of the overvoltage / overcurrent event) is recorded through historical data to facilitate subsequent troubleshooting; for old equipment that does not support protocol communication (such as non-smart home appliances), a safety mechanism equivalent to "intelligent protection" is provided through real-time sensor data, expanding the protection scope.

[0084] For example, the overvoltage and overcurrent protection mechanism in this embodiment uses a fuzzy logic system to finely classify abnormal events (e.g., distinguishing between "lightning surge," "equipment short circuit," and "poor contact"), and then implements different self-healing strategies based on the classification results. For example, if a "poor contact" anomaly is detected, the device will automatically attempt to reconnect the device three times to avoid accidental disconnection; if a "equipment short circuit" is detected, the device will immediately and permanently disconnect the power and lock the socket.

[0085] Fuzzy rule construction: Input variables: power mutation amplitude (large / medium / small), mutation duration (instantaneous / short-term / long-term), voltage and current phase difference (normal / abnormal); output variables: abnormality type (seven categories: surge, short circuit, poor contact, overload, reverse current, voltage oscillation, unknown), self-healing action (retry / power off / alarm); define 27 fuzzy rules (for example, "large power mutation + instantaneous duration + normal phase difference" → "lightning surge", triggering energy storage capacitor discharge protection).

[0086] Self-healing strategy execution: Poor contact processing: When intermittent power drops are detected (occurring more than 3 times every 10 seconds), the control socket relay opens and closes in a cycle (with an interval of 500ms) and attempts to restore the connection; Surge protection enhancement: After identifying a lightning surge, in addition to cutting off the power supply, the input-side MOV varistor bypass is triggered to clamp the residual voltage to a safe value; Data feedback: The abnormal event classification results are stored in the local log and sent to the user's mobile phone app via Bluetooth to provide fault diagnosis suggestions.

[0087] Exemplary abnormal event risk assessment and response threshold dynamic adjustment formulas designed for overvoltage protection include: ; Where: R is the comprehensive risk index of abnormal events (dimensionless, range [0,1], the closer R is to 1, the higher the risk, and the higher the priority of triggering the protection action); γ is the device type sensitivity coefficient (dimensionless, range [0.8,1.5], automatically configured by the device rated parameters: precision chip devices γ = 1.5, ordinary appliances γ = 1.0); ωv is the voltage deviation weight (dimensionless, range [0,1], default 0.6, automatically increased to 0.8 when the device contains an MCU); ωi is the current deviation weight (dimensionless, range [0,1], ωv + ωi = 1, motor devices automatically increased to 0.7); V is the real-time voltage (normalized to [Vmin, Vmax], through Z-s core is converted to a dimensionless value); Vnom is the rated voltage of the equipment (also normalized); I is the real-time current (normalized to [Imin, Imax]); Inom is the rated current of the equipment (normalized); τ is the duration of the anomaly (seconds, calculated using a sliding window; if it exceeds 5 seconds, exponential risk growth is triggered); τ0 is the reference time constant (fixed value of 1 second); sgn(ΔP) is the sign function of power change (1 for a sudden power surge, ΔP>0, -1 for a sudden power drop, and 0 for a stable power); t is the time since the last protection action (seconds, used to attenuate the impact of historical risks and avoid repeated triggering); tdecay is the decay time constant (adaptive value, 30 seconds for precision equipment and 60 seconds for ordinary equipment).

[0088] The formula integrates five dimensions: voltage deviation, current deviation, abnormality duration, power change direction, and historical protection intervals. It differentiates protection strategies through dynamic weighting (ωv / ωi) and device type sensitivity coefficient (γ). For example, for voltage-sensitive MCU devices (such as single-chip microcomputer development boards), the voltage deviation weight is increased to 0.8, and γ = 1.5. This amplifies risk perception and ensures that even minor voltage fluctuations trigger early warnings. In some embodiments, an independent power management module is installed within the power converter body. This power management module includes a filter circuit and an energy storage capacitor. The filter circuit is used to filter out high-frequency noise generated by the step-down circuit and bridge circuit. The energy storage capacitor maintains a stable power supply during transient input voltage fluctuations, ensuring continuous monitoring functions of the microcontroller unit and load sensing sensor.

[0089] By setting the abnormal duration magnification term (1+τ / τ0*sgn(ΔP)): when the power surges (such as motor startup) and lasts for more than 1 second, the risk index increases linearly (the risk increases by 100% for every additional second), avoiding false triggering of short-term interference; the historical attenuation factor (e -t / tdecay ): The closer the time to the last protection (such as t=0), the more cautious the current risk assessment is (exponential decay to avoid frequent actions), and precision equipment decays faster (tdecay=30 seconds) to reduce downtime losses.

[0090] Voltage and current parameters are normalized using the device safety interval [Vmin, Vmax] (e.g., for a 5V-rated device with a safety interval of 4.5V-5.5V, V = 5.2V corresponds to a normalized value of 0.4). Time-related parameters are dimensionless using a reference constant (τ0 / tdecay) to ensure calculation consistency across device types.

[0091] Power change direction sensing uses sgn(ΔP) to distinguish between "dangerous surges" (such as a sudden current increase caused by a short circuit, which amplifies the risk when ΔP>0) and "safe dips" (such as a normal device shutdown, which suppresses the risk when ΔP<0). This addresses the defect of traditional overcurrent protection that cannot identify power change trends.

[0092] Compared to traditional fixed threshold protection (such as immediate power-off when the current exceeds 1.2 times the rated value), this formula supports dynamic adjustment of risk levels: When R∈[0.3,0.6], an early warning is triggered but no shutdown is performed, and only a log is recorded (suitable for equipment such as refrigerators that allow short-term fluctuations). When R≥0.7, hierarchical shutdown is performed according to the equipment priority (game theory model of Example 11) (non-critical equipment is shut down first), the triggering threshold of precision equipment is reduced to 0.5, and the protection response speed is increased by 30%.

[0093] For electromagnetic compatibility scenarios (such as voltage glitches caused by the start and stop of nearby motors), the false trigger rate is reduced from 20% in traditional threshold detection to below 5% through τ duration judgment and tdecay historical decay. This is particularly suitable for the complex power grid environments of industrial control scenarios.

[0094] There is no need to manually configure protection parameters. The system automatically generates coefficients such as γ, ωv, and tdecay based on the calibration data (Vnom, Inom, Vmax, Imax) when the device is first connected, achieving full coverage of device types from mobile phone chargers (low sensitivity) to medical equipment (high sensitivity).

[0095] The power converter itself has a built-in independent power management module, which includes a filter circuit (LC filter) and an energy storage capacitor (such as a 1000μF electrolytic capacitor). The filter circuit filters out high-frequency noise (such as harmonics above 100kHz) generated by the buck / bridge circuit to prevent interference with the MCU and sensors. The energy storage capacitor maintains a stable power supply for more than 50ms during transient input voltage fluctuations (such as immediately after a power outage), ensuring uninterrupted monitoring functions.

[0096] Filter circuit design: A two-stage LC filter is used: the first-stage inductor (100μH) + capacitor (100nF) filters out differential-mode noise, and the second-stage common-mode inductor (2mH) + Y capacitor (470pF) filters out common-mode noise, ensuring that the peak-to-peak value of the power supply noise output to the MCU is less than 50mV; the filter circuit is located after the AC input and before each functional module to form an independent power supply channel.

[0097] The energy storage capacitor capacity is calculated based on the system standby power consumption (e.g. the total power consumption of MCU + sensor is 50mW and it needs to maintain power supply for 50ms, then the capacitor capacity C = (P×t) / (0.5×ΔV 2 )≈1000μF@5V); in conjunction with a diode rectifier bridge, when the input voltage is interrupted, the energy storage capacitor supplies power to the control circuit through the discharge loop, ensuring that the MCU completes current data processing and records abnormal events (such as brief power outages).

[0098] After high-frequency noise is filtered out, the MCU sampling accuracy is improved from ±2% to ±0.5%, avoiding misjudgment of device power requirements due to noise (such as false triggering of protection mechanisms). When the input voltage fluctuates (such as when the air conditioner is started, causing a voltage drop), the energy storage capacitor maintains the operation of the monitoring system to prevent accidental power outages, while ensuring that the protection mechanism is triggered based on stable data to reduce false operations. The independent power management module isolates the main power circuit from the control circuit to prevent main circuit failures (such as bridge circuit short circuit) from directly affecting the control unit, thereby improving overall robustness.

[0099] In some embodiments, a human-computer interaction interface is provided on the surface of the power converter body, and the human-computer interaction interface includes a status indicator light and a parameter adjustment button, through which the voltage upper limit and current protection threshold of any socket can be set.

[0100] The power converter has a human-computer interaction interface on its surface, which includes status indicators (such as a red / green indicator light for each socket, indicating normal / abnormal voltage) and parameter adjustment buttons (such as the "+" and "-" keys). Users can use these buttons to set the voltage upper limit (such as limiting a USB port to a maximum output of 12V) and current protection threshold (such as setting 2A overcurrent protection) for any socket. The set parameters are stored in the MCU's non-volatile memory (EEPROM).

[0101] Hardware interface design: The status indicator uses RGB LED, with one indicator for each socket: green = normal, red = overvoltage / overcurrent, and yellow = standby. The adjustment button uses a waterproof micro switch, and a small LCD screen (optional) displays the current socket number, voltage, current, threshold, and other parameters. It supports switching sockets through buttons (for example, long press to switch to socket 1, short press to adjust the threshold).

[0102] Software interaction logic: The user presses and holds the "Set" button to enter configuration mode, uses the "Up / Down" button to select a socket (1-4), and then uses the "Left / Right" button to adjust the voltage upper limit (1V step) and current threshold (0.1A step). Safety mechanism: The voltage limit must not exceed 120% of the device's rated voltage, and the current threshold must not exceed the maximum carrying capacity of the socket (for example, the default maximum current of a USB-C port is 3A, and users cannot set it to exceed 3.5A).

[0103] This feature improves flexibility by meeting the needs of professional users or special equipment (for example, laboratory equipment requires a fixed 15V voltage, and a manual upper limit can be set to prevent automatic over-regulation). Indicator lights provide real-time visibility into the working status of each socket without relying on a mobile app, making it suitable for offline environments or for quick troubleshooting. It also allows users to set stricter protection thresholds for high-value equipment (such as SLR camera chargers) (for example, current fluctuations exceeding 5% trigger protection), which is more precise than the factory default settings.

[0104] In some embodiments, by analyzing the user's historical settings of socket parameters (such as the user often sets the voltage upper limit of socket 1 to 12V to charge the tablet computer) and the frequency of device access, an association rule algorithm (such as the Apriori algorithm) is used to generate a "user-device-parameter" mapping relationship. When the same device or the same usage scenario is detected, the user's preferred adjustment strategy is automatically called to achieve "seamless" personalized adaptation.

[0105] User habit modeling includes: collecting data: voltage upper limit, current threshold, device connection time (e.g., a user connects to a mobile phone for charging at 8 pm every day), and device connection duration, all set by the user through the human-machine interface (Example 8); mining association rules: identifying high-frequency patterns (e.g., "device type = mobile phone + time = 8:00 PM - 10:00 PM" → "voltage = 9 V + current threshold = 2.4 A"), and setting rules with a confidence level ≥ 80% to store in the user profile.

[0106] The active adaptation mechanism includes: time trigger: when the preset time period (such as 8 pm) is reached, even if the device is not connected, the socket parameters are adjusted to the user's commonly used configuration in advance to reduce the waiting time after the device is connected; device identification trigger: when the deep learning model of Example 9 recognizes that the "user's commonly used mobile phone" is connected, the routine detection process is skipped and the historical optimal parameters are directly applied (the voltage adjustment time is shortened from 1 second to 200ms); the user can temporarily modify the parameters, and the system automatically determines whether it is a long-term preference (if a parameter setting is continued for more than 3 times, the rule will be updated).

[0107] In some embodiments, a long short-term memory (LSTM) network is used to predict the device's power demand curve for the next 5-10 minutes. This, combined with a model predictive control (MPC) algorithm, preemptively adjusts the output parameters of the buck and bridge circuits, minimizing internal converter and line losses while still meeting the device's power requirements. For example, if a phone is predicted to enter the fast charging phase (where power increases from 5W to 18W), the output voltage is preemptively increased to 9V to avoid voltage overshoot caused by the temporary adjustment.

[0108] Time series data modeling collects historical power data (timestamps, real-time power, and device status tags), constructs a sliding window (window size of 300 samples, approximately 5 minutes), and inputs it into the LSTM network to predict power values ​​for the next 10 time points (2 minutes) with a prediction accuracy of ≥90%. If the device temperature is detected to be elevated (via the built-in temperature sensor), the prediction model is modified to lower the power limit to prevent overheating.

[0109] Model Predictive Control (MPC) establishes a converter loss model: total loss = switching loss (frequency-related) + conduction loss (I²R) + iron loss (voltage fluctuation-related); optimizes the objective function: minimize (total loss in the next 10 minutes), and constrains: output voltage fluctuation ≤ ±3%, current ≤ device rating. Control parameters (PWM duty cycle, bridge circuit switching frequency) are optimized every 200ms to achieve advanced regulation.

[0110] In some embodiments, when multiple devices are connected simultaneously, a multi-agent game model is constructed, with each socket acting as an agent. By dynamically adjusting its output voltage and current strategy, it minimizes overall system losses and avoids input-side overload while still meeting the power requirements of its own device. The algorithm, based on Nash equilibrium theory, ensures that each socket's regulation strategy achieves a "win-win" outcome. For example, when a high-power device (laptop) and a low-power device (Bluetooth headset) share input resources, the optimal voltage level is automatically assigned.

[0111] Game model construction: Define the agent strategy space: each socket's adjustable voltage range [U_min, U_max] and current range [I_min, I_max]; design the payoff function: the payoff of a single socket = (device required power / actual output power) - (self-loss + interference coefficient on other sockets), where the interference coefficient is positively correlated with the voltage difference between adjacent sockets; use a distributed gradient descent algorithm, with each socket exchanging current strategy parameters via the CAN bus and updating the strategy every 50ms until a Nash equilibrium is reached.

[0112] The hardware collaborative design equips each socket with an independent communication module (such as an SPI interface), and the main MCU acts as a coordinator to collect the status of each socket; a total current sensor is set on the input side. When the total current approaches the rated value (such as 10A), the load balancing mechanism is triggered to prioritize the stable power supply of high-priority devices (such as medical equipment).

[0113] See also Figure 3 , Figure 3 This is a schematic flow chart of a control method for an intelligent power converter system based on adaptive load regulation provided by an embodiment of the present application. The execution device of the method is a microcontroller unit of an intelligent power converter system based on adaptive load regulation provided by any embodiment of the present application.

[0114] like Figure 3 As shown, the provided method includes steps S101 to S103.

[0115] Step S101: When the device connected to the socket requires low-voltage DC power supply, the step-down circuit is controlled to reduce the input voltage to the voltage required by the device and adjust the output current.

[0116] Step S102 . When the socket is connected to a different mains voltage input, the bridge circuit is controlled to convert the input mains voltage into a target voltage suitable for the socket.

[0117] Step S103 . Based on the device power demand monitored by the load sensing sensor, the step-down circuit and the bridge circuit are controlled to automatically adjust the output voltage and current of the corresponding socket to achieve adaptive load regulation for each socket.

[0118] In some embodiments, when the device connected to the socket requires low-voltage DC power supply, the microcontroller unit controls the step-down circuit to reduce the input voltage to the voltage required by the device and adjust the output current, including: when the device is plugged into the socket, the load sensing sensor obtains the rated voltage parameters of the device in real time, and the microcontroller unit controls the step-down circuit to gradually reduce the input AC voltage to the DC voltage required by the device according to the rated voltage parameters, and dynamically adjusts the current according to the corresponding real-time power demand of the device, so that the output voltage fluctuation range is within the preset fluctuation range of the rated voltage.

[0119] In some embodiments, when the socket is connected to different mains voltage inputs, the microcontroller unit controls the bridge circuit to convert the input mains voltage into a target voltage suitable for the socket, including: when the socket is connected to the mains as input, the bridge circuit converts the mains power corresponding to the mains into a target voltage suitable for the socket according to the socket specification parameters, and during the conversion process, the frequency and phase of the output voltage are monitored in real time by the microcontroller unit to ensure that the distortion of the converted voltage waveform is less than the preset distortion, and the on-off frequency of the switching tube of the bridge circuit is adjusted to achieve voltage level matching and two-way transmission of electric energy between different sockets.

[0120] In some embodiments, the step-down circuit and the bridge circuit are controlled to automatically adjust the output voltage and current of the corresponding socket according to the power demand of the device monitored by the load sensing sensor to achieve adaptive load regulation for each socket, including: when the load sensing sensor detects that the power of the device connected to the socket is less than a preset threshold, the microcontroller unit adjusts the output voltage to the minimum effective voltage actually required by the device, and reduces the output current according to the adjustment ratio corresponding to the minimum effective voltage, so that the device can reduce the energy loss caused by the internal resistance of the circuit while meeting normal operation.

[0121] In some embodiments, the microcontroller unit is also used to automatically identify the device type based on the device startup current waveform and continuous power data collected by the load sensing sensor, and match the optimal voltage regulation strategy according to a preset device type database, wherein the preset device type database includes voltage-power matching parameters of multiple electrical devices.

[0122] Exemplarily, the microcontroller unit stores power regulation data of historically connected devices, and dynamically optimizes the response speed and accuracy of voltage regulation by analyzing the voltage adaptation process when the device is repeatedly connected, thereby shortening the voltage adjustment time when the same type of device is connected again.

[0123] In some embodiments, the load sensing sensor includes a current transformer and a voltage sensor, which are integrated into the power supply circuit of each socket to respectively collect the input current and port voltage of the device in real time. The microcontroller unit calculates the real-time power based on the collected data and performs abnormality detection. When it is detected that the power mutation exceeds the preset mutation range of the rated value, the overvoltage protection or overcurrent protection mechanism is triggered to cut off the power supply of the corresponding socket.

[0124] In some embodiments, an independent power management module is provided inside the power converter body, and the power management module includes a filtering circuit and an energy storage capacitor. The filtering circuit is used to filter out the high-frequency noise generated when the step-down circuit and the bridge circuit are working, and the energy storage capacitor maintains stable power supply when the input voltage fluctuates instantaneously to ensure the continuous monitoring function of the micro control unit and the load sensing sensor.

[0125] In some embodiments, a human-computer interaction interface is provided on the surface of the power converter body, and the human-computer interaction interface includes a status indicator light and a parameter adjustment button, through which the voltage upper limit and current protection threshold of any socket can be set.

[0126] It should be noted that, those skilled in the art can clearly understand that, for the convenience and conciseness of description, the control method of the intelligent power converter system based on adaptive load regulation and the specific working process of each step described above can refer to the corresponding processes in the embodiments of the intelligent power converter system based on adaptive load regulation described in the above embodiments, and will not be repeated here.

[0127] See also Figure 4 , Figure 4 1 is a schematic block diagram of the structure of a micro control unit provided in an embodiment of the present application. The micro control unit includes a processor, a memory and a network interface connected via a device bus, wherein the memory may include a storage medium and an internal memory.

[0128] The storage medium can store an operating device and a computer program. The computer program includes program instructions, which, when executed, can cause a processor to execute any embodiment of a control method for an intelligent power converter system based on adaptive load regulation.

[0129] The processor is used to provide computing and control capabilities and support the operation of the entire microcontroller unit.

[0130] The internal memory provides an environment for running the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any intelligent power converter system method based on adaptive load regulation.

[0131] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the terminal to which the solution of the present application is applied. The specific micro control unit may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0132] It should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0133] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps: When the device connected to the socket requires low-voltage DC power supply, the step-down circuit is controlled to reduce the input voltage to the voltage required by the device and adjust the output current; When the socket is connected to a different mains voltage input, the control bridge circuit converts the input mains voltage into a target voltage suitable for the socket; According to the power demand of the equipment monitored by the load sensing sensor, the buck circuit and the bridge circuit are controlled to automatically adjust the output voltage and current of the corresponding socket to achieve adaptive load regulation for each socket.

[0134] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the processor described above can refer to the corresponding process in the method embodiments described in the above embodiments, and will not be repeated here.

[0135] A computer-readable storage medium is also provided in an embodiment of the present application, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and the processor executes the program instructions to implement the steps of the control method of the intelligent power converter system based on adaptive load regulation provided in the above-mentioned embodiments of the present application.

[0136] The computer-readable storage medium may be an internal storage unit of the microcontroller described in the aforementioned embodiment, such as a hard disk or memory of the microcontroller. The computer-readable storage medium may also be an external storage device of the microcontroller, such as a plug-in hard disk, a SmartMedia Card (SMC), a Secure Digital (SD) card, a flash memory card, etc., equipped on the microcontroller.

[0137] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present application, and such modifications or substitutions should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. An intelligent power converter system based on adaptive load regulation, characterized in that: include: A power converter body, the power converter body being provided with a plurality of different types of sockets, and the power converter body being equipped with a load sensing sensor, a microcontroller unit, a step-down circuit, and a bridge circuit; the load sensing sensor being electrically connected to the microcontroller unit for real-time monitoring of the power demand of the device connected to each socket and transmitting a corresponding monitoring signal to the microcontroller unit; the microcontroller unit being electrically connected to the step-down circuit and the bridge circuit, respectively, for controlling the step-down circuit and the bridge circuit to adjust the output voltage and current according to the monitoring signal transmitted by the load sensing sensor; When the device connected to the socket requires low-voltage DC power supply, the microcontroller controls the step-down circuit to reduce the input voltage to the voltage required by the device and adjust the output current; when the socket is connected to different mains voltage inputs, the microcontroller controls the bridge circuit to convert the input mains voltage into a target voltage suitable for the socket; the microcontroller controls the step-down circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding socket according to the power demand of the device monitored by the load sensing sensor, so as to achieve adaptive load regulation for each socket.

2. The system according to claim 1, wherein: When the device connected to the socket requires low-voltage DC power supply, the microcontroller controls the step-down circuit to reduce the input voltage to the voltage required by the device and adjust the output current, including: When a device is plugged into a socket, the load sensing sensor obtains the rated voltage parameters of the device in real time. The microcontroller controls the step-down circuit to gradually step down the input AC voltage to the DC voltage required by the device based on the rated voltage parameters, and dynamically adjusts the current based on the real-time power demand of the device, so that the output voltage fluctuation range is within the preset fluctuation range of the rated voltage.

3. The system according to claim 1, wherein: When the socket is connected to a different mains voltage input, the micro control unit controls the bridge circuit to convert the input mains voltage into a target voltage suitable for the socket, including: When the socket is connected to the mains as input, the bridge circuit converts the mains power corresponding to the mains into the target voltage of the adapter socket according to the socket specification parameters. During the conversion process, the frequency and phase of the output voltage are monitored in real time by the microcontroller unit to ensure that the distortion of the converted voltage waveform is less than the preset distortion. The on-off frequency of the switching tube of the bridge circuit is adjusted to achieve voltage level matching and two-way transmission of electric energy between different sockets.

4. The system according to claim 1, wherein: The method of controlling the step-down circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding socket according to the power demand of the device monitored by the load sensing sensor to achieve adaptive load regulation for each socket includes: When the load sensing sensor detects that the power of the device connected to the socket is less than a preset threshold, the microcontroller unit adjusts the output voltage to the minimum effective voltage actually required by the device, and reduces the output current according to the adjustment ratio corresponding to the minimum effective voltage, so that the device can reduce the energy loss caused by the internal resistance of the circuit while meeting normal operation.

5. The system according to claim 1, wherein: The microcontroller unit is also used to automatically identify the device type based on the device startup current waveform and continuous power data collected by the load sensing sensor, and match the optimal voltage regulation strategy according to a preset device type database, wherein the preset device type database includes voltage-power matching parameters of multiple electrical devices.

6. The system according to claim 5, characterized in that The microcontroller unit stores power regulation data of historically connected devices, and dynamically optimizes the response speed and accuracy of voltage regulation by analyzing the voltage adaptation process when the device is repeatedly connected, thereby shortening the voltage adjustment time when the same type of device is connected again.

7. The system according to claim 1, wherein: The load sensing sensor includes a current transformer and a voltage sensor, which are integrated into the power supply circuit of each socket to respectively collect the input current and port voltage of the device in real time. The microcontroller unit calculates the real-time power based on the collected data and performs anomaly detection. When it detects that the power mutation exceeds the preset mutation range of the rated value, it triggers the overvoltage protection or overcurrent protection mechanism and cuts off the power supply to the corresponding socket.

8. The system according to claim 1, wherein: An independent power management module is provided inside the power converter body. The power management module includes a filter circuit and an energy storage capacitor. The filter circuit is used to filter out the high-frequency noise generated when the step-down circuit and the bridge circuit are working. The energy storage capacitor maintains stable power supply when the input voltage fluctuates instantaneously, thereby ensuring the continuous monitoring function of the microcontroller unit and the load sensing sensor.

9. The system according to claim 1, wherein: A human-machine interaction interface is provided on the surface of the power converter body. The human-machine interaction interface includes a status indicator light and a parameter adjustment button. The voltage upper limit and current protection threshold of any socket can be set through the adjustment button.

10. A control method for an intelligent power converter system based on adaptive load regulation, characterized in that: An intelligent power converter system according to any one of claims 1 to 9; the method comprising: When the device connected to the socket requires low-voltage DC power supply, the step-down circuit is controlled to reduce the input voltage to the voltage required by the device and adjust the output current; When the socket is connected to a different mains voltage input, the control bridge circuit converts the input mains voltage into a target voltage suitable for the socket; According to the power demand of the equipment monitored by the load sensing sensor, the buck circuit and the bridge circuit are controlled to automatically adjust the output voltage and current of the corresponding socket to achieve adaptive load regulation for each socket.

Images