Multi-mode power management method and device for gallium nitride adapter

Abstract

The invention relates to the technical field of thermal management of power adapters, and discloses a multi-mode power management method and device of a gallium nitride adapter. The multi-mode power management method of the gallium nitride adapter comprises the following steps: dividing the interior of the adapter into a plurality of cooling priority regions according to the thermal sensitivity of elements, and integrating a three-dimensional layered micro-channel structure; monitoring the temperature of each area and the state of a cooling system in real time; constructing a self-adaptive flow distribution algorithm, and dynamically adjusting the flow distribution of the cooling liquid according to the real-time temperature state of each region; the maximum allowable power under the current cooling capacity is calculated, and power parameters are dynamically adjusted; dynamically switching the working mode of the adapter; through the synergistic effect of the regional differentiation micro-channel cooling structure and multi-mode power management, the technical effects that the temperature management effect is improved, the reliability is improved, the service life is prolonged, and the power output capacity is enhanced are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of power adapter thermal management, and more specifically, it relates to a multi-mode power management method and device for a gallium nitride adapter. Background Art

[0002] With the development of electronic devices towards higher performance and smaller volume, power adapters are also facing the requirements of miniaturization and high power density. Gallium nitride (GaN), as a new generation of wide-bandgap semiconductor material, with its excellent characteristics such as high breakdown electric field, high electron mobility, and low on-resistance, enables power adapters based on gallium nitride to achieve higher power density.

[0003] However, the concentrated heat load problem brought about by high power density poses severe challenges to the reliability, efficiency, and service life of the adapter. In a miniaturized gallium nitride adapter, the power components are densely arranged, resulting in uneven hot spot distribution, and the traditional uniform cooling strategy cannot specifically solve the differentiated heat dissipation requirements of each region. In addition, the existing cooling system adopts a uniform cooling strategy and cannot provide customized cooling according to the differences in thermal sensitivity and heat generation rate in different regions inside the adapter, resulting in unreasonable allocation of cooling resources and a decline in overall performance.

[0004] At the same time, the existing thermal management system and power management system are often independent of each other, lacking a cooperative control mechanism and unable to intelligently adjust the working mode according to the real-time thermal state. Especially in ultra-small adapters with limited heat dissipation channels, traditional passive heat dissipation or simple temperature control protection methods are difficult to meet the continuous and stable requirements of high-power output. The high power density of gallium nitride devices leads to concentrated hot spots, and the temperature control response lags, making it impossible to prevent overheating in a timely manner. Traditional temperature control methods can only simply reduce power or shut down when the temperature reaches the critical point, and cannot achieve a smooth transition, affecting the user experience.

[0005] Therefore, there is an urgent need for a multi-mode power management method for a gallium nitride adapter that can solve the above problems to improve the thermal management efficiency and power output stability of the adapter. Summary of the Invention

[0006] The present invention provides a multi-mode power management method and device for a gallium nitride adapter, which solves the technical problems of low thermal management efficiency and unstable power control in a miniaturized gallium nitride adapter in the related art.

[0007] The present invention provides a multi-mode power management method and device for a gallium nitride adapter, including: Dividing the inside of the adapter into multiple cooling priority regions according to the thermal sensitivity of components and integrating a three-dimensional hierarchical microchannel structure; Constructing a sensor network system according to the division of the cooling priority regions and the three-dimensional hierarchical microchannel structure to monitor the temperature of each region and the state of the cooling system in real time; Based on the monitoring data of the temperature in each region and the status of the cooling system, an adaptive flow allocation algorithm is constructed to dynamically adjust the coolant flow allocation according to the real-time temperature status of multiple divided cooling priority regions; According to the monitoring data of the temperature in each region and the status of the cooling system and the coolant flow allocation result, calculate the maximum allowable power under the current cooling capacity, and dynamically adjust the power parameters; Dynamically switch the working mode of the adapter according to the result of calculating the maximum allowable power under the current cooling capacity, the dynamically adjusted power parameters, the load status and the temperature condition.

[0008] Furthermore, the division into multiple cooling priority regions includes: The interior of the adapter is divided into a high-priority cooling area, a medium-priority cooling area, and a low-priority cooling area; The high-priority cooling area includes GaN power devices and driver ICs, the medium-priority cooling area includes transformers and high-power resistors, and the low-priority cooling area includes filter capacitors and interface circuits.

[0009] Furthermore, the integrated three-dimensional hierarchical microchannel structure includes: Configure microchannels with different densities and orientations for different priority regions. The high-priority region uses high-density serpentine microchannels, the medium-priority region uses medium-density straight microchannels, and the low-priority region uses low-density radial microchannels; Select a dielectric liquid with high thermal conductivity, low electrical conductivity, and high dielectric strength characteristics as the cooling medium.

[0010] Furthermore, the flow allocation of the adaptive flow allocation algorithm distributes the total coolant flow according to the proportion of the cooling demand index of each region in the total demand; The cooling demand index of the multiple divided cooling priority regions is calculated based on the difference between the current temperature and the reference temperature of the multiple divided cooling priority regions and the weight coefficient of the region. The weight coefficient of the high-priority region is 1.5 to 2.0, the weight coefficient of the medium-priority region is 0.8 to 1.2, and the weight coefficient of the low-priority region is 0.3 to 0.6.

[0011] Furthermore, the calculation of the maximum allowable power under the current cooling capacity determines the power upper limit according to the real-time measured thermal resistance value and the target maximum temperature; the maximum allowable power is equal to the difference between the target maximum temperature and the ambient temperature divided by the thermal resistance value.

[0012] Furthermore, the dynamic adjustment of the power parameters includes: When the predicted temperature rising trend is obvious, reduce the switching frequency and driving voltage; When the predicted temperature tends to stabilize or decrease, increase the switching frequency and driving voltage; The adjustment range of the switching frequency is from 65 kHz to 1 MHz, and the adjustment range of the driving voltage is from 3.3 V to 6.5 V.

[0013] Furthermore, there are four working modes in the working mode of the dynamic switching adapter, including: Normal mode: The temperature is within the safe range, that is , with the main goal of full-power output; Low-temperature optimization mode: When the temperature is low, that is , optimize energy efficiency by increasing the switching frequency; High-temperature derating mode: When the temperature is close to the threshold, that is , reduce the power output and give priority to ensuring heat dissipation; Critical protection mode: When the temperature is close to the limit, that is , quickly reduce the power and increase the cooling intensity to ensure system safety.

[0014] Furthermore, the working mode of the dynamic switching adapter avoids power fluctuations caused by mode switching. During the switching process, the power and cooling parameters gradually change according to the set time constant. The specific steps are as follows: Define the state transition function to make the power and cooling parameters gradually change according to the set time constant during the switching process; Use a shorter time constant for the power parameter and a longer time constant for the cooling parameter; Update the parameter status every 5 ms during the mode switching process to ensure a smooth transition.

[0015] Furthermore, the dynamic adjustment of the power parameter also includes implementing a power management strategy based on heat redistribution. The specific steps are as follows: Through the topological structure of the microchannel network, form a heat transfer path from the heat-sensitive area to the heat-resistant area; Establish a direct connection between the microchannel outlet in the heat-sensitive area and the microchannel inlet in the heat-resistant area; By controlling the flow distribution ratio of each microchannel segment, achieve directional heat transfer, reduce the temperature of the GaN power device, and at the same time increase the temperature of the transformer and capacitor to achieve a more uniform temperature distribution.

[0016] The present invention provides a multi-mode power management device for a gallium nitride adapter, including a memory and one or more processors. The memory stores executable code. When the one or more processors execute the executable code, it is used to execute the above-mentioned multi-mode power management method for a gallium nitride adapter.

[0017] The beneficial effects of the present invention are as follows: Through the synergistic effect of the regional differential microchannel cooling structure and multi-mode power management, the technical problems of thermal management and power control of miniaturized gallium nitride adapters are solved, and the technical effects of improved temperature management, extended reliability and service life, and enhanced power output capacity are achieved; The maximum temperature of the adapter is reduced, the temperature difference of hot spots is reduced, and efficient operation is achieved within the full temperature range; the trigger rate of thermal protection is reduced, and the service life is extended; without changing the volume, due to the improvement of heat dissipation efficiency, both the continuous power density and the peak power are increased; it is realized to adaptively adjust the working mode according to the load and temperature without manual intervention; through precise temperature management and a dual-mode heat dissipation system, the energy consumption of the cooling system is reduced, and the efficiency within the full load range is improved; smoothly transition between various working modes, avoid sudden frequency reduction or shutdown of traditional adapters, and provide stable and continuous power supply. Brief Description of the Drawings

[0018] Figure 1 is a flowchart of a multi-mode power management method for a gallium nitride adapter in the present invention; Figure 2 is a flowchart of dividing multiple cooling priority areas and integrating a three-dimensional hierarchical microchannel structure in the present invention; Figure 3 is a flowchart of a sensor network system constructed in the present invention for real-time monitoring of the temperature of each area and the status of the cooling system; Figure 4 is a flowchart of dynamically adjusting the coolant flow distribution in the present invention; Figure 5 is a flowchart of calculating the maximum allowable power under the current cooling capacity and dynamically adjusting the power parameters in the present invention; Figure 6 is a flowchart of dynamically switching the working mode of the adapter in the present invention. Detailed Embodiments

[0019] Now, the subject matter described herein will be discussed with reference to exemplary embodiments. It should be understood that discussing these embodiments is only to enable those skilled in the art to better understand and thus implement the subject matter described herein. The functions and arrangements of the elements discussed can be changed without departing from the scope of protection of the content of this specification. Each example can omit, substitute, or add various processes or components as needed. Additionally, the features described in some examples can also be combined in other examples.

[0020] In at least one embodiment of the present invention, a multi-mode power management method for a gallium nitride adapter is disclosed, as Figures 1 to 6 shown, including: Step 1: Divide the interior of the adapter into multiple cooling priority regions according to the thermal sensitivity of components and integrate a three-dimensional hierarchical microchannel structure; Specifically, it includes: Step 1.1: Perform region classification according to the thermal sensitivity and heat generation characteristics of components; Divide the interior of the adapter into a high-priority cooling area (including key components such as GaN power devices and driver ICs), a medium-priority cooling area (including transformers, high-power resistors, etc.), and a low-priority cooling area (including high-temperature-resistant components such as filter capacitors and interface circuits); Optionally, in some embodiments, the high-priority cooling area can be further divided into an ultra-high-priority area (such as a GaN power transistor chip) and a high-priority area (such as a driver IC), and different microchannel densities and cooling strategies are adopted respectively; Step 1.2: Integrate a three-dimensional hierarchical microchannel structure inside the PCB; Configure microchannels with different densities and orientations for different priority regions. The high-priority region uses high-density serpentine microchannels, the medium-priority region uses medium-density straight microchannels, and the low-priority region uses low-density radial microchannels; In some embodiments, the microchannels can adopt a multi-layer structure. For example, independent microchannel networks are constructed on different layers of the PCB, and three-dimensional cooling is achieved through vertical connection channels; or variable cross-section microchannels are used, with a larger cross-section at the inlet and a gradually shrinking cross-section at the outlet to enhance the coolant flow rate; Step 1.3: Select a dielectric liquid as the cooling medium; This dielectric liquid has the characteristics of high thermal conductivity, low electrical conductivity, and high dielectric strength, ensuring safety when used around electronic components; Optionally, the cooling medium can be a fluorinated liquid (such as FC-72, HFE-7100, etc.) or mineral insulating oil, which is selected according to the specific temperature range and insulation requirements; in application scenarios with higher power density, nanoparticles (such as alumina, boron nitride, etc.) can also be added to enhance the thermal conductivity; Step 1.4: Integrate a micro temperature sensor array; Arrange at least 5 micro temperature sensors at key positions inside the adapter to monitor the temperature status of each region in real time.

[0021] In specific application scenarios, such as medical device chargers or server power supplies that require more precise temperature monitoring, the number of temperature sensors can be increased to 8 - 12; or a combination of different types of sensors can be used, such as a hybrid application of thermocouples, thermistors, and bandgap temperature sensors, to improve the accuracy and reliability of measurement.

[0022] Step 2: Based on the division of the cooling priority areas and the three-dimensional hierarchical microchannel structure, construct a sensor network system to monitor the temperature of each area and the status of the cooling system in real time; On the basis of the region-differentiated microchannel cooling structure constructed by the region-differentiated microchannel cooling structure, construct a complete sensor network system to monitor the internal temperature distribution of the adapter and the status of the cooling system in real time, providing data support for subsequent flow distribution and temperature prediction, specifically including: Step 2.1: Integrate micro pressure and flow sensors; The micro pressure and flow sensors are respectively installed at the coolant inlet and outlet to monitor the pressure difference and flow rate change of the cooling system; Step 2.2: Calculate the cooling efficiency according to the monitored data; Cooling efficiency The calculation formula is: ; Where represents the cooling efficiency, represents the removed heat, represents the pump power, represents the specific heat capacity of the coolant, represents the mass flow of the coolant, represents the temperature difference between the coolant inlet and outlet, represents the pump drive voltage, represents the pump drive current.

[0023] Step 2.3: Construct a data processing unit for the temperature monitoring network; Filter, standardize and perform anomaly detection on the collected temperature, pressure and flow data to ensure data accuracy; Step 2.4: Establish a thermal characteristics database; Store the temperature distribution characteristics under different working conditions to provide data support for subsequent power management strategies.

[0024] Step 3: Based on the monitoring data of the temperature of each area and the status of the cooling system, construct an adaptive flow distribution algorithm to dynamically adjust the coolant flow distribution according to the real-time temperature status of the divided multiple cooling priority areas; Based on the real-time temperature data collected by the multi-layer distributed temperature monitoring network established by the multi-layer distributed temperature monitoring network, construct an adaptive flow distribution algorithm and a temperature prediction model to dynamically optimize the cooling resource allocation of each area, specifically including: Step 3.1: Configure a piezoelectric micropump and a microvalve array system; The micropump is responsible for providing the power for the coolant circulation, and the microvalve array controls the flow distribution of the microchannels in each area; In high-end application scenarios, such as the power supply of data center servers, a backup micro-pump system is optionally configured to automatically switch in case of main pump failure, ensuring the reliability of the cooling system; for application scenarios with limited size, such as wearable device chargers, a valve-less microfluidic system driven by surface acoustic waves can be used to replace traditional micro-pumps and valves to further reduce the size. Step 3.2, construct an adaptive flow distribution algorithm; Dynamically adjust the coolant distribution according to the real-time temperature status of each area. The flow distribution calculation formula is: ; Where represents the coolant flow rate allocated to the th area, represents the total flow rate, and respectively represent the weight coefficients of the cooling priorities of the th and the th areas, represents the temperature of the th area, represents the reference temperature, represents the temperature of the th area, represents the summation over all areas, represents the total number of areas; The implementation process of this adaptive flow distribution algorithm includes: first, normalize the temperature data of each cooling area and calculate the difference between the temperature of each area and the reference temperature; then, according to the preset weight coefficients (the weight coefficient of the high-priority area is 1.5 - 2.0, the weight coefficient of the medium-priority area is 0.8 - 1.2, and the weight coefficient of the low-priority area is 0.3 - 0.6), calculate the cooling demand index of each area; finally, allocate the flow rate according to the proportion of the cooling demand index of each area in the total demand. In practical applications, this algorithm updates the flow distribution every 100 ms, effectively avoiding the problem of excessive temperature in hot spots; Optionally, for different usage scenarios, different variants of the flow distribution strategy can be adopted: for example, for the charger of a gaming laptop with frequent sudden loads, a prediction factor can be added to adjust the flow distribution in advance according to the historical load pattern; for scenarios where safety is crucial, such as the power supply of industrial control systems, a conservative distribution strategy can be adopted to keep the cooling flow rate in critical areas not lower than the minimum safety threshold; Step 3.3, construct a heat diffusion prediction model based on the finite difference method; Predict the temperature change inside the adapter in the next 10 - 300 ms. The discrete form of the heat diffusion equation is: ; Among them represents the position at time step of the temperature, i.e., the temperature at the next moment; represents the position at time step of the temperature, i.e., the temperature at the current moment; represents the thermal diffusivity, describing the rate of heat diffusion in the material; represents the time step, i.e., the interval between two adjacent time points in the calculation; represents the spatial grid size in the x direction, i.e., the spacing of the calculation grid in the x direction; represents the spatial grid size in the y direction, i.e., the spacing of the calculation grid in the y direction; represents the position at time step of the temperature, i.e., the temperature of the adjacent point in the positive x direction of the current point; represents the position at time step of the temperature, i.e., the temperature of the adjacent point in the negative x direction of the current point; represents the position at time step of the temperature, i.e., the temperature of the adjacent point in the positive y direction of the current point; represents the position at time step of the temperature, i.e., the temperature of the adjacent point in the negative y direction of the current point; represents the position of the heat source term, i.e., the heat generated per unit volume; represents the material density, describing the mass-to-volume ratio of the material; represents the specific heat capacity of the material, describing the heat required to raise the temperature of unit mass of the material by unit temperature; The specific implementation method of this thermal diffusion prediction model is as follows: divide the internal space of the adapter into a 10×10×3 three-dimensional grid, establish a thermal network including temperature nodes, heat source nodes and boundary nodes; apply the above discretized thermal diffusion equation to each node, and use the explicit iterative method to solve the temperature field; set the time step to 1ms and the spatial grid size to 1mm×1mm×0.5mm; calibrate the thermal diffusivity of each region by recording the historical power data of each power component and the corresponding temperature response. In practical applications, this model can accurately predict the temperature change trend caused by sudden load changes, predict the temperature change 10 - 300ms in advance, and provide sufficient response time for power parameter adjustment; In some embodiments, this thermal diffusion prediction model can also be coupled with a simplified hydrodynamic model to calculate the fluid flow and heat transfer characteristics in the microchannel; or for low-cost application scenarios with limited computing resources, a simplified lumped parameter thermal model can be adopted, dividing the inside of the adapter into a small number of thermal regions, represented by a thermal resistance-capacitance network, to reduce the computational complexity; Step 3.4, input the current power data as a heat source term into the prediction model; Combine the past temperature data to predict the temperature change trend. In this embodiment, the power data of the main heat-generating components such as the measured GaN power device, drive IC, and transformer are converted into the heat generation rate per unit volume and input into the prediction model as the heat source term to achieve the prediction of future temperatures.

[0025] For example, in the application scenario of charging a high-performance laptop, when the user starts a graphics rendering-intensive application, the power demand of the laptop will increase from 45W to 95W in a short period of time. The prediction model of this embodiment can predict that the temperature in the high-priority area will rise by about 15°C within the subsequent 250ms in the initial stage (within about 50ms) of the rising power demand, so as to initiate preventive power management measures in advance to ensure that a safe temperature range can still be maintained under sudden load increase.

[0026] Step 4, calculate the maximum allowable power under the current cooling capacity according to the monitoring data of the temperature of each area and the cooling system status and the coolant flow distribution result, and dynamically adjust the power parameters; Utilize the temperature monitoring data and prediction results provided by the intelligent flow distribution and temperature prediction system implemented by the intelligent flow distribution and temperature prediction unit to achieve the coordinated control of the cooling capacity and power parameters, ensuring that the system maximizes the power output capacity while ensuring heat dissipation, specifically including: Step 4.1, calculate the maximum allowable power under the current cooling capacity; Determine the power upper limit according to the real-time measured thermal resistance value and the target maximum temperature, and the calculation formula is: ; where represents the maximum allowable power, represents the allowable maximum temperature, represents the ambient temperature, represents the currently measured thermal resistance; Optionally, in application scenarios where the ambient temperature fluctuates greatly (such as charging portable devices outdoors), the ambient temperature sensor can be integrated into the adapter to monitor the ambient temperature changes in real time and dynamically adjust the maximum allowable power. In extreme temperature environments (such as high altitude or polar environments), multi-level safety redundancy can be used to increase the safety factor (e.g. 1.2-1.5 times) for the thermal resistance value to ensure a more conservative power limit. Step 4.2, dynamically adjusting power parameters according to temperature prediction results; Including switching frequency and driving voltage, the frequency adjustment range is 65kHz-1MHz, and the driving voltage adjustment range is 3.3V-6.5V. The adjustment strategy is: when the predicted temperature rise trend is obvious, reduce the switching frequency and driving voltage; when the predicted temperature tends to be stable or decrease, increase the switching frequency and driving voltage to improve performance; The specific implementation method is as follows: the power parameters are dynamically adjusted through a digitally controlled frequency synthesizer and a programmable drive voltage regulator; a mapping relationship between the temperature change rate and the power parameter adjustment range is established. When the temperature prediction result shows that the temperature rise rate exceeds 1°C / s in the next 100ms, the switching frequency is reduced by 5% each time and the drive voltage is reduced by 0.2V each time; when the temperature change rate is lower than 0.2°C / s and the temperature is lower than the threshold, the switching frequency is increased by 3% each time and the drive voltage is increased by 0.1V; parameter adjustments are performed every 50ms to ensure that the system can respond to temperature changes in a timely manner; For example, in a fast charging scenario, when a high-power mobile phone (such as a flagship mobile phone that supports 65W fast charging) is connected to an adapter, this embodiment can intelligently adjust the switching frequency according to temperature prediction: maintain a higher frequency (about 800kHz) in the early stage of charging to improve efficiency; when it is predicted that the temperature will rise rapidly, reduce the frequency to about 500kHz in advance, and gradually reduce the driving voltage to keep the temperature rise rate within a controllable range, avoiding the problem of charging speed fluctuation caused by reducing power only after the temperature is too high in the traditional method; Step 4.3, implementing a power management strategy based on heat redistribution; By actively controlling the flow of coolant, heat is transferred from heat-sensitive areas (such as GaN power devices) to heat-resistant areas (such as transformers and capacitors), thereby expanding the overall power capacity of the system.

[0027] The specific implementation methods of this heat redistribution strategy include: forming a heat transfer path from the heat-sensitive area to the heat-resistant area through the topological structure of the microchannel network; establishing a direct connection between the microchannel outlet in the heat-sensitive area and the microchannel inlet in the heat-resistant area; and achieving directional heat transfer by controlling the flow distribution ratio of each microchannel segment. In practical applications, this strategy reduces the maximum temperature of the GaN power device by 8°C, while the temperatures of the transformer and capacitor increase by 5 - 7°C, achieving a more uniform temperature distribution overall.

[0028] In some embodiments, the heat redistribution strategy can be used in combination with dynamic adjustment of power parameters. For example, when it is detected that the temperature of the GaN power device is approaching the critical value but there is still some margin in the overall heat capacity of the system, the power load sharing in the heat-resistant area can be increased while reducing the power load of the GaN device to balance the temperatures of all parts without reducing the overall power output.

[0029] Step 5: Dynamically switch the working mode of the adapter according to the result of calculating the maximum allowable power under the current cooling capacity, the dynamically adjusted power parameters, and the load status and temperature conditions; According to the power thermal management results executed by the multi-mode collaborative power thermal management unit, combined with the load status and temperature conditions, dynamically switch the working mode of the adapter to achieve the balance between energy efficiency and heat dissipation, and optimize the system performance under different working conditions, specifically including: Step 5.1: Construct a multi-level temperature response strategy; Divide into four working modes: Normal mode: The temperature is within the safe range, that is , with the main goal of full power output; Low-temperature optimization mode: When the temperature is low, that is , optimize the energy efficiency by increasing the switching frequency; High-temperature derating mode: When the temperature is approaching the threshold, that is , reduce the power output and give priority to ensuring heat dissipation; Critical protection mode: When the temperature is approaching the limit, that is , quickly reduce the power and increase the cooling intensity to ensure system safety; The temperature refers to the real-time monitored temperature of the key heat-generating components inside the adapter (such as GaN power devices, driver ICs, etc.), that is, the representative temperature node of the high-priority cooling area. This temperature is collected in real time by the distributed temperature sensor network, reflecting the actual working temperature of the most heat-affected part of the system, and is used as the criterion for switching the working mode.

[0030] Optionally, the temperature threshold can be adjusted for different application scenarios: for example, for scenarios with high reliability requirements such as avionics chargers, the temperature thresholds for each mode can be reduced by 5 - 10 °C to provide a greater safety margin; for scenarios such as server power supplies that require maximizing power output, the threshold can be increased by 3 - 5 °C to expand the operating range while ensuring safety. Step 5.2, implement a dual-mode cooling system in coordination with the load status; In the light load mode (load < 30% of the rated power), rely only on heat conduction and natural convection for heat dissipation, and deactivate the active cooling system to save energy consumption; In the heavy load mode (load ≥ 30% of the rated power), activate active microfluidic circulation cooling to ensure temperature control during high power output; In some embodiments, an intermediate transition mode (load in the range of 20 - 40% of the rated power) can be added, and a pulsed active cooling strategy can be adopted, that is, intermittently start the microfluidic circulation system to balance the cooling effect and energy consumption; for application scenarios that require low noise (such as bedroom chargers), a night mode can be implemented, preferentially using passive cooling and running the active cooling system at a lower speed when necessary to reduce noise; Step 5.3, implement a mode smooth switching algorithm; Avoid power fluctuations caused by mode switching. During the switching process, the power and cooling parameters gradually change according to the set time constant to ensure output stability.

[0031] The specific implementation method of this mode smooth switching algorithm is: define a state transition function: ; where represents the value of the state parameter at time , is the initial state parameter value, is the target state parameter value, is the time constant (usually set to 50 - 200 ms), represents the time from the start of switching to the current time, represents the exponential factor that decays with time, represents the base of the natural logarithm; Select appropriate time constants for different parameter types. Shorter time constants are used for power parameters (such as switching frequency, drive voltage), and longer time constants are used for cooling parameters (such as flow rate, pump speed); during the mode switching process, the parameter status is updated every 5 ms to ensure smooth transition. In practical applications, this algorithm effectively eliminates the output voltage fluctuations during mode switching, and the fluctuation amplitude is reduced from the traditional 5 - 8% to 0.5 - 1%.

[0032] For example, in the charging scenario of a portable medical device, when the device suddenly enters a high-power diagnostic mode from the standby state, the mode smooth switching algorithm of this embodiment can complete a smooth transition from the low-temperature optimization mode to the normal mode within 200 ms, while activating the active cooling system. During the whole process, the output voltage fluctuation is controlled within ±0.8%, ensuring stable power supply for the medical device and avoiding problems such as diagnostic data distortion or device restart caused by power fluctuations.

[0033] A multi-mode power management device for a gallium nitride adapter, including a memory and one or more processors. Executable code is stored in the memory. When the one or more processors execute the executable code, it is used to execute the above-mentioned multi-mode power management method for a gallium nitride adapter.

[0034] Here, the present invention provides an implementation example: This embodiment has been applied and verified in the product development of a 65W high-power density gallium nitride adapter. The adapter has a volume of only 40×35×30mm, adopts a single-stage LLC topology structure, the output voltage range is 5 - 20V, and the maximum output current is 5A. The specific application of this embodiment in this product will be introduced below.

[0035] This gallium nitride adapter is mainly applied to the fast charging scenarios of high-end laptops, tablets, and smartphones. Especially in extreme usage environments, such as running at high load for a long time and working at high ambient temperatures, these scenarios pose severe challenges to the thermal management and power control capabilities of the adapter. Taking a certain high-performance gaming laptop as an example, when it runs at full load (while running high-load games and rendering software), it continuously requires a power supply of 60 - 65W, and this working mode can last for several hours, which is very likely to cause the traditional adapter to overheat and protect, resulting in a reduction in power output or shutdown.

[0036] In this adapter, the specific implementation process of this embodiment is as follows: The microchannel cooling structure is implemented inside the four-layer PCB of the adapter, integrating a microchannel structure with a total length of about 210mm. The GaN power device and its driving IC area (high-priority area) adopt 0.8mm-wide serpentine microchannels with a density of 3.5mm² / mm²; the LLC transformer and rectifier diode area (medium-priority area) adopt 1.2mm-wide linear microchannels with a density of 2.2mm² / mm²; the input and output filter capacitor area (low-priority area) adopt 1.5mm-wide radial microchannels with a density of 1.0mm² / mm². The selected cooling medium is the modified fluorinated liquid HFE-7000, which has a thermal conductivity of 0.075W / (m·K) and a dielectric strength of 35kV / mm. The micro piezoelectric pump (size 8×8×3mm) provides a maximum flow rate of 15ml / min and a maximum pressure of 25kPa.

[0037] The temperature monitoring system realizes the arrangement of 7 micro-thermistor temperature sensors inside the adapter, including 3 in the GaN power device area, 2 in the transformer area, and 1 each in the control IC and output interface areas. The sampling frequency is 200 Hz, and the temperature measurement accuracy is ±0.5 °C. The micro pressure sensor and flow sensor are respectively installed at the coolant inlet and outlet to monitor the system pressure difference and flow rate. The data is collected through a 12-bit ADC and processed by a built-in 32-bit microcontroller (STM32F042, main frequency 48 MHz).

[0038] The realization of adaptive flow distribution is based on real-time temperature data, and the system adjusts the flow distribution every 100 ms. For example, when the laptop suddenly enters the high-load working state from the standby state, the temperature rise rate in the GaN power device area reaches 2.5 °C / s, and the flow distribution algorithm immediately adjusts the distribution ratio, increasing the flow rate in the high-priority area from the initial 40% to 65%, maintaining 35% in the medium-priority area, and reducing the low-priority area to only 10% of the total flow rate. Through this dynamic adjustment, the temperature rise in the GaN area is limited within 8 °C, instead of the 15 °C rise when using the fixed distribution scheme.

[0039] In this adapter, the realization of multi-mode collaborative power thermal management realizes the dynamic adjustment of power parameters. The switching frequency range is 75 kHz - 850 kHz, and the driving voltage range is 3.8 V - 6.2 V. Taking an actual use case as an example, when the adapter charges a gaming laptop and the laptop is running both games and video export tasks simultaneously, the adapter detects the high-load demand, and at the same time, the temperature in the GaN power device area rises rapidly. The system first calculates that the maximum allowable power under the current cooling capacity is 68 W (when the temperature in the GaN area is 65 °C and the thermal resistance is 0.32 °C / W), then reduces the switching frequency from the initial 800 kHz to 600 kHz, reduces the driving voltage from 6.0 V to 5.2 V, and at the same time starts the active cooling with the maximum flow rate, stabilizing the temperature in the GaN area at around 70 °C and maintaining a continuous output power of 60 W.

[0040] The adaptive working mode switching enables the system to automatically and smoothly switch between four working modes under different usage scenarios. For example, when the user connects a mobile phone for fast charging (20W load), the system initially operates in the low-temperature optimization mode (temperature about 45°C), and the switching frequency is maintained at a relatively high level (about 820kHz) to improve energy efficiency. When the user then connects a laptop and starts downloading large files, the load quickly rises to 50W. The system predicts that the temperature will exceed 65°C in a short time, so it smoothly switches to the normal mode in advance and gradually activates the active cooling system. The entire switching process takes about 180ms, and the output voltage fluctuation is controlled within ±0.6%, ensuring the stability of the device operation.

[0041] Two key technical effects of this embodiment are fully verified: the temperature management effect and the power output ability.

[0042] When the ambient temperature is 25°C, the comparison of the highest temperatures under different load conditions is shown in Table 1: Table 1: Comparison of the highest temperatures under different load conditions (ambient temperature 25°C) The comparison of the continuous output power under different ambient temperatures is shown in Table 2: Table 2: Comparison of the continuous output power under different ambient temperatures From the above data, it can be seen that this embodiment has achieved an improvement in temperature management. Under various load conditions, the average highest temperature has decreased by about 21%. In terms of power output ability, especially under high ambient temperature conditions, the continuous output power has increased by up to 47.4% - 62.5%, fully verifying the technical effects of this embodiment.

[0043] The above describes the embodiments of the present invention, but these embodiments are not limited to the above specific implementation manners. The above specific implementation manners are merely illustrative and not restrictive. Under the inspiration of this embodiment, those of ordinary skill in the art can also make more equivalent embodiments in various forms, all of which fall within the protection scope of this embodiment.

Claims

1. A multi-mode power management method for a gallium nitride adapter, characterized in that: include: The interior of the adapter is divided into multiple cooling priority areas according to the thermal sensitivity of the components and a three-dimensional hierarchical microchannel structure is integrated; According to the division of cooling priority areas and the three-dimensional hierarchical microchannel structure, a sensor network system is constructed to monitor the temperature of each area and the status of the cooling system in real time; Based on the monitoring data of the temperature of each area and the status of the cooling system, an adaptive flow distribution algorithm is constructed to dynamically adjust the coolant flow distribution according to the real-time temperature status of multiple cooling priority areas; According to the monitoring data of the temperature and cooling system status of each area and the coolant flow distribution results, the maximum allowable power under the current cooling capacity is calculated, and the power parameters are adjusted dynamically; The working mode of the adapter is dynamically switched according to the result of calculating the maximum allowable power under the current cooling capacity, the dynamically adjusted power parameters, and the load status and temperature conditions.

2. The multi-mode power management method of a gallium nitride adapter according to claim 1, characterized in that: The division into multiple cooling priority areas includes: Divide the interior of the adapter into a high priority cooling zone, a medium priority cooling zone, and a low priority cooling zone; The high priority cooling zone includes GaN power devices and driver ICs, the medium priority cooling zone includes transformers and high power resistors, and the low priority cooling zone includes filter capacitors and interface circuits.

3. The multi-mode power management method of a gallium nitride adapter according to claim 1, characterized in that: The integrated three-dimensional hierarchical microchannel structure comprises: Microchannels of different densities and directions are configured for different priority areas. High-priority areas use high-density serpentine microchannels, medium-priority areas use medium-density linear microchannels, and low-priority areas use low-density radial microchannels. A dielectric liquid having high thermal conductivity, low electrical conductivity and high dielectric strength properties is selected as the cooling medium.

4. The multi-mode power management method of a gallium nitride adapter according to claim 1, characterized in that: The flow distribution of the adaptive flow distribution algorithm is to distribute the total flow of the coolant according to the proportion of the cooling demand index of each area to the total demand; The cooling demand index of the multiple cooling priority areas is calculated based on the difference between the current temperature of the multiple cooling priority areas and the reference temperature and the weight coefficient of the area. The weight coefficient of the high priority area is 1.5 to 2.0, the weight coefficient of the medium priority area is 0.8 to 1.2, and the weight coefficient of the low priority area is 0.3 to 0.

6.

5. The multi-mode power management method of a gallium nitride adapter according to claim 1, characterized in that: The maximum allowable power under the current cooling capacity is calculated to determine the power upper limit according to the thermal resistance value measured in real time and the target maximum temperature; the maximum allowable power is equal to the difference between the target maximum temperature and the ambient temperature divided by the thermal resistance value.

6. The multi-mode power management method of a gallium nitride adapter according to claim 1, characterized in that: The dynamically adjusting power parameters includes: When the predicted temperature rise trend is obvious, reduce the switching frequency and drive voltage; When the temperature is predicted to stabilize or decrease, the switching frequency and drive voltage are increased; The switching frequency can be adjusted from 65kHz to 1MHz, and the drive voltage can be adjusted from 3.3V to 6.5V.

7. The multi-mode power management method of a gallium nitride adapter according to claim 1, characterized in that: There are four working modes in the working mode of the dynamic switching adapter, including: Normal mode: The temperature is within the safe range, i.e. , with full power output as the main goal; Low temperature optimization mode: When the temperature is low, , optimize energy efficiency by increasing the switching frequency; High temperature derating mode: When the temperature approaches the threshold, , reduce power output and give priority to heat dissipation; Critical protection mode: When the temperature approaches the limit, , quickly reduce power and increase cooling efforts to ensure system safety.

8. The multi-mode power management method of a gallium nitride adapter according to claim 1, characterized in that: The working mode of the dynamic switching adapter avoids power fluctuations caused by switching between modes. During the switching process, the power and cooling parameters gradually change according to the set time constant. The specific steps are: Define the state transition function so that the power and cooling parameters during the switching process change gradually according to the set time constant; The power parameters use shorter time constants, and the cooling parameters use longer time constants; During the mode switching process, the parameter status is updated every 5ms to ensure a smooth transition.

9. The multi-mode power management method of a gallium nitride adapter according to claim 1, characterized in that: The dynamic adjustment of power parameters also includes implementing a power management strategy based on heat redistribution, and the specific steps are: Through the topological structure of the microchannel network, a heat transfer pathway is formed from the heat-sensitive area to the heat-resistant area; establishing a direct connection between the microchannel outlet of the heat-sensitive region and the microchannel inlet of the heat-resistant region; By controlling the flow distribution ratio of each microchannel segment, directional heat transfer is achieved, which reduces the temperature of GaN power devices, while increasing the temperature of transformers and capacitors to achieve a more uniform temperature distribution.

10. A multi-mode power management device for a gallium nitride adapter, characterized in that: The invention comprises a memory and one or more processors, wherein the memory stores executable codes, and when the one or more processors execute the executable codes, they are used to execute the multi-mode power management method of a gallium nitride adapter according to any one of claims 1 to 9.

Images