Temperature-current cooperative control method of intelligent temperature-control fast-charging charger

Abstract

The invention discloses a temperature-current cooperative control method of an intelligent temperature-control fast-charging charger, and relates to the technical field of charger temperature control. The method comprises the following specific steps: full-link temperature sensing: synchronously acquiring temperatures of a core power device, a charging interface contact area and a charged equipment battery end in a charger and instantaneous temperature change in a pulse period through a distributed high-frequency temperature sensor array to form a multi-dimensional temperature sensing network; instantaneous temperature change data of a core power device, a charging interface contact area, a charged equipment battery end and a pulse period in a charger are collected in an omnibearing mode through full-link temperature sensing and a distributed high-frequency temperature sensor array, a monitoring blind area is eliminated, temperature data fusion and fluctuation analysis are carried out on the basis, and the monitoring accuracy is improved. And generating a comprehensive temperature value and quantifying the temperature oscillation degree.

Description

Technical Field

[0001] This invention relates to the field of charger temperature control technology, specifically a temperature-current coordinated control method for intelligent temperature-controlled fast chargers. Background Technology

[0002] With the widespread adoption and performance improvement of electronic devices, users' demand for charging efficiency is increasing. Pulse fast charging technology, through pulsed current output, can effectively reduce battery polarization, thereby improving charging efficiency and shortening charging time, bringing great convenience to users and becoming an important direction for the development of current charger technology. However, during fast charging, a large amount of heat is generated in the core power devices, charging interface, and battery terminal of the device being charged. If temperature control is not timely and effective, it will not only affect the performance and stability of the charger, but may also damage the device being charged and even cause safety hazards. Therefore, while achieving fast charging, precise temperature control of the charger has become a critical issue that urgently needs to be addressed.

[0003] Current fast charger temperature control solutions have many obvious shortcomings. In terms of temperature acquisition, they are mostly limited to a single location, failing to comprehensively acquire temperature information of key components inside the charger and the device being charged. This results in lag in temperature control, making it impossible to adjust charging parameters in a timely manner according to the actual temperature conditions. Consequently, current regulation is severely out of sync with actual temperature changes. In terms of pulse parameter settings, most use fixed parameters. During the conduction phase, the instantaneous large current causes a sudden temperature rise, while during the turn-off phase, the temperature drops rapidly, forming obvious periodic temperature fluctuations. Prolonged exposure to this condition will exacerbate thermal fatigue of power devices, reduce charging stability, seriously affect the lifespan of the device, and may even lead to serious safety hazards. Traditional technologies struggle to achieve real-time coordinated control of temperature, current, and pulse parameters, often presenting a dilemma in practical applications: either sacrifice fast charging efficiency for safety, or allow temperature fluctuations to threaten device lifespan. It is impossible to maintain good fast charging performance while ensuring safety and stability. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a temperature-current coordinated control method for intelligent temperature-controlled fast chargers. This method utilizes a distributed high-frequency temperature sensor array through a full-link temperature sensing step to simultaneously acquire multi-dimensional temperature information from the charger's core components, charging interface, and the battery of the device being charged. A temperature data fusion and fluctuation analysis step performs weighted fusion calculations on multi-source temperature data to generate a comprehensive temperature value and extracts temperature fluctuation peaks, providing key characteristic quantities for subsequent parameter adjustment. A current and pulse parameter coordinated decision-making step, based on the comprehensive temperature value and temperature fluctuation peaks, uses a PID adaptive algorithm and an experimentally calibrated correlation model to achieve dual-dimensional dynamic adjustment of charging current and pulse parameters. A feedback and anomaly protection step converts the decision results into actual outputs, forming a high-frequency closed-loop control. Simultaneously, anomaly monitoring and protection are performed to ensure the safety and stability of the charging process. This effectively solves problems such as temperature control lag, parameter adjustment disconnect, and significant temperature fluctuations in existing fast charging technologies. It maintains fast charging performance while ensuring safety and stability, extends device lifespan, and has good adaptability, applicable to different fast charging protocols and various electronic devices.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a temperature-current coordinated control method for an intelligent temperature-controlled fast charger, the method comprising the following specific steps:

[0006] Full-link temperature sensing: The distributed high-frequency temperature sensor array synchronously collects the temperature of the core power devices inside the charger, the contact area of ​​the charging interface, the battery end of the device being charged, and the instantaneous temperature changes within the pulse cycle, forming a multi-dimensional temperature sensing network.

[0007] Temperature data fusion and fluctuation analysis: The collected multi-source temperature data are weighted and fused according to their influence weights to generate a comprehensive temperature value that reflects the overall heating state of the system. At the same time, the temperature fluctuation peak within the pulse period is extracted to quantify the degree of temperature oscillation.

[0008] Coordinated decision-making of current and pulse parameters: Based on the comprehensive temperature value and the preset temperature range, the target average charging current is determined, and the pulse duty cycle and frequency are dynamically optimized in combination with the temperature fluctuation peak to suppress temperature fluctuation while maintaining the target average current.

[0009] Feedback and anomaly protection: The system outputs current according to the decision parameters and returns it to the temperature acquisition step to form a closed-loop control. If an abnormal temperature or fluctuation is detected during the closed-loop process, the output will be cut off immediately and an alarm will be triggered.

[0010] Furthermore, in the end-to-end temperature sensing step, a distributed high-frequency temperature sensor array is deployed to achieve synchronous acquisition of multi-dimensional temperature information. This includes NTC thermistors attached to the surface of the core power devices inside the charger to collect the operating temperatures of multiple core devices in real time, forming a core power device temperature set; infrared temperature sensors installed inside the charging interface to collect the temperature of the interface contact area non-contactly; high-frequency response thermocouples attached to the surface of the power switch tube and the battery interface to capture temperature changes during the pulse conduction and turn-off periods with a high-frequency sampling period, forming an instantaneous temperature sequence within the pulse period; and simultaneously, the battery end temperature fed back by the charged device is obtained in real time through charging protocol interaction.

[0011] Furthermore, in the temperature data fusion and fluctuation analysis step, the collected multi-source temperature data is weighted and fused, and weights are assigned according to the degree of influence of temperature at each location on system safety and fast charging performance. The weights are dynamically adjusted according to the fast charging protocol type, and finally a comprehensive temperature value reflecting the overall heating state of the system is generated. Based on the instantaneous temperature data within the pulse cycle collected by the high-frequency thermocouple, the difference between the highest and lowest temperatures within the cycle is extracted as the temperature fluctuation peak value. The temperature fluctuation peak value correction formula is used to quantify the temperature oscillation amplitude under the pulse working mode.

[0012] Furthermore, in the temperature data fusion and fluctuation analysis step, the collected multi-source temperature data undergoes weighted fusion calculation, and the calculation formula is as follows: , For dynamic weighting coefficients, These correspond to the core components, interfaces, and battery terminals, respectively. , The effective temperature values ​​for each location. It is the core power device temperature cluster The arithmetic mean, , , Based on the weighting coefficients, satisfying , The rate of temperature change at each location, For the current sampling period, For the previous sampling period, The sampling interval is... This is the temperature change sensitivity coefficient.

[0013] Furthermore, in the temperature data fusion and fluctuation analysis step, a temperature fluctuation peak correction formula is used to quantify the degree of temperature oscillation under pulse working mode, thereby obtaining the corrected temperature fluctuation peak value. The calculation formula is as follows: ,in, , These are the instantaneous temperature sequences within the pulse period. The maximum and minimum values ​​in var Instantaneous temperature sequence within a pulse period The variance is used to characterize the irregularity of temperature fluctuations. It is a fluctuation smoothing coefficient used to enhance the correction effect of variance on fluctuation peaks.

[0014] Furthermore, in the collaborative decision-making step for current and pulse parameters, the calculation of dual-dimensional adjustment parameters is completed based on the comprehensive temperature value and temperature fluctuation peak value output from the temperature data fusion and fluctuation analysis stage. In the current adjustment dimension, according to the preset range of the comprehensive temperature value, namely the safe range, transition range, and warning range, the target average charging current is generated through a PID adaptive algorithm: within the safe range, the charger's rated maximum fast charging current is maintained; within the transition range, the current is reduced to the median level linearly as the comprehensive temperature rises; within the warning range, the current is immediately reduced to the safe current. In the pulse parameter optimization dimension, combined with the comparison result of the temperature fluctuation peak value and the preset threshold, the parameters are dynamically adjusted by calling the temperature fluctuation-pulse parameter correlation model calibrated through experiments: when the fluctuation peak value exceeds the preset threshold, the duty cycle is shortened during the heating stage and extended during the cooling stage. At the same time, the differential coefficient is corrected according to the comprehensive temperature change rate and the temperature fluctuation peak value to avoid oscillations during the parameter adjustment process.

[0015] Furthermore, in the current and pulse parameter collaborative decision-making step, a target average charging current is generated through a PID adaptive algorithm: maintaining the charger's rated maximum fast charging current within the safe range. The algorithm formula is as follows: ,in, This serves as the reference current for the current temperature range, taking into account the overall temperature. When in a safe zone, The charger's rated maximum fast charging current When in the transition range, This is the intermediate current value that decreases linearly with temperature; when within the warning range, For safe current, This represents the temperature deviation, which is the difference between the current overall temperature and the ideal control temperature for the current range. The calculation formula is: ,in, The ideal control temperature for the current temperature range. The dynamic scaling factor is calculated using the following formula: ,in As a benchmark value for the proportion, It is the positive rate of temperature change. This is a proportional adjustment coefficient; the faster the temperature rises... The larger the current, the faster the current regulation. The dynamic integral coefficient is calculated using the following formula: ,in As the integral baseline value, the faster the temperature rises... The smaller the value, the less likely it is to cause drastic current fluctuations due to integral overshoot; The differential reference coefficient, The rate of change of temperature deviation is represented by the following formula: , The fluctuation influence coefficient represents the peak temperature fluctuation. The larger the value, the stronger the differential action, effectively suppressing oscillations during parameter adjustment. , These represent the baseline values ​​for proportion and integral, respectively. The representative proportional adjustment coefficient is used to control... and The adjustment range of the rate of change with temperature.

[0016] Furthermore, in the collaborative decision-making step involving current and pulse parameters, the pulse duty cycle is dynamically optimized by invoking an experimentally calibrated temperature fluctuation-pulse parameter correlation model. With frequency The formula for calculating the corresponding heating stage is as follows: For the cooling phase, the calculation formula is: ,in, , These are the optimized duty cycle and frequency for the heating phase, respectively. , These are the optimized duty cycle and frequency for the cooling phase, respectively. , These are the initial values ​​for the pulse parameters. Let be the parameter adjustment coefficient, and satisfy . To ensure the target average charging current Constant.

[0017] Furthermore, in the execution feedback and abnormal protection steps, the results of the collaborative decision-making process of current and pulse parameters are transformed into actual outputs, forming a closed-loop control and safety protection. During the closed-loop process, the comprehensive temperature value, the temperature at a single location, and the peak value of temperature fluctuation are monitored simultaneously. When the comprehensive temperature reaches the preset limit protection threshold, the temperature at a single location exceeds its corresponding limit threshold, or the peak value of temperature fluctuation reaches the abnormal threshold and lasts for multiple pulse cycles, the charging output is immediately cut off, an alarm signal is issued through indicator light flashing or charging protocol feedback, and the closed-loop cycle is terminated.

[0018] Compared with existing technologies, the temperature-current coordinated control method of this intelligent temperature-controlled fast charger has the following advantages:

[0019] I. This invention utilizes a distributed high-frequency temperature sensor array to collect instantaneous temperature change data from the charger's core power devices, charging interface contact areas, the battery end of the charged device, and within the pulse cycle through end-to-end temperature sensing. This eliminates monitoring blind spots. Based on this, temperature data fusion and fluctuation analysis are performed to generate a comprehensive temperature value and quantify the degree of temperature oscillation. Subsequently, in the collaborative decision-making stage of current and pulse parameters, the target average charging current and pulse parameters are dynamically adjusted based on the comprehensive temperature value and the peak temperature fluctuation, effectively suppressing temperature fluctuations and avoiding safety hazards caused by excessive temperature. This ensures the safety of both the charger and the charged device while fully leveraging the high efficiency advantages of pulse fast charging.

[0020] Second, this invention transforms raw data into key characteristic quantities through temperature data fusion and fluctuation analysis; current and pulse parameters are used to make collaborative decisions to calculate adjustment parameters based on these characteristic quantities; execution feedback and abnormal protection transform the decision results into actual output and form a closed loop, so that parameter adjustment and temperature change are synchronized in real time, eliminating lag, and pulse parameters are adjusted in real time with temperature fluctuations, reducing fatigue of power devices caused by periodic thermal stress and reducing cycle life loss of batteries caused by temperature fluctuations.

[0021] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0023] Figure 1 A flowchart of a temperature-current coordinated control method for an intelligent temperature-controlled fast charger;

[0024] Figure 2 This is a flowchart of the temperature-current coordinated control method for intelligent temperature-controlled fast chargers, outlining the collaborative decision-making steps for current and pulse parameters. Detailed Implementation

[0025] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0026] This invention provides a temperature-current coordinated control method for an intelligent temperature-controlled fast charger. It utilizes a distributed high-frequency temperature sensor array through a full-link temperature sensing step to synchronously acquire multi-dimensional temperature information from the charger's core components, charging interface, and the battery of the device being charged. A temperature data fusion and fluctuation analysis step performs weighted fusion calculations on multi-source temperature data to generate a comprehensive temperature value and extracts temperature fluctuation peaks, providing key characteristic quantities for subsequent parameter adjustment. A current and pulse parameter coordinated decision-making step, based on the comprehensive temperature value and temperature fluctuation peaks, uses a PID adaptive algorithm and an experimentally calibrated correlation model to achieve dual-dimensional dynamic adjustment of charging current and pulse parameters. A feedback and anomaly protection step converts the decision results into actual outputs, forming a high-frequency closed-loop control. Simultaneously, anomaly monitoring and protection are performed to ensure the safety and stability of the charging process. This effectively solves problems such as temperature control lag, parameter adjustment disconnect, and significant temperature fluctuations in existing fast charging technologies. It maintains fast charging performance while ensuring safety and stability, extends device lifespan, and has good adaptability, applicable to different fast charging protocols and various electronic devices.

[0027] Example 1

[0028] When the charger is turned on at room temperature, the distributed high-frequency temperature sensor array immediately enters working mode. The NTC thermistors attached to the GaN power chip and high-frequency transformer track the temperature rise of the core components in real time during the initial power-on process, forming a continuous temperature set of the core power components. The infrared temperature sensor inside the charging interface not only captures the basic temperature of the interface contact area, but also accurately identifies local temperature fluctuations caused by brief poor contact when the user plugs and unplugs the phone. The high-frequency response thermocouple attached to the power switch and battery interface records the rapid rise of temperature during the pulse conduction period and the slow drop of temperature during the turn-off period with a high-frequency sampling period, forming a continuous instantaneous temperature sequence within the pulse period. At the same time, it establishes real-time interaction with the phone through the PD protocol, continuously obtaining the battery temperature feedback from the phone's battery management system. Even when the phone is in use with the screen on or an app is running in the background, it can synchronously capture subtle changes in battery temperature.

[0029] To address the different heat dissipation characteristics of mobile phones from low battery to fast charging and then to trickle charging under the PD fast charging protocol, a dynamic weighted fusion formula is adopted. Perform calculations, where , The effective temperature values ​​for each location. It is the core power device temperature cluster The arithmetic mean, , , Based on the weighting coefficients, satisfying , The rate of temperature change at each location, For the current sampling period, For the previous sampling period, The sampling interval is... A temperature change sensitivity coefficient is used, and weights are assigned based on the impact of temperature at each location on system safety and fast charging performance. In the early stages of low-battery fast charging, the core power devices generate the most heat, so their weight is automatically increased. In the trickle charging stage, which is close to full charge, the battery temperature has a more significant impact, so its weight is appropriately increased. The weight allocation is further optimized by combining the temperature change rate at each location, ultimately generating a comprehensive temperature value that accurately reflects the overall heating state at different charging stages. At the same time, based on the instantaneous temperature sequence collected by high-frequency thermocouples, the difference between the highest and lowest temperatures within the period is first extracted, and then corrected using a temperature fluctuation peak correction formula. By combining the variance of the temperature sequence within the period, the corrected peak value of temperature fluctuation is obtained, avoiding misjudgment of fluctuations caused by changes in the charging stage.

[0030] During the initial charging phase, the overall temperature remains within a preset safe range. Based on the temperature-current mapping relationship across multiple ranges, an adaptive PID formula is used. The target average charging current is determined to be the rated maximum fast charging current adapted to PD65W. At this point, the temperature fluctuation peak has not exceeded the threshold, and the pulse parameters maintain the initial configuration. As charging progresses, the phone battery temperature rises slowly with the increase in charge, and the overall temperature value enters the transition range. The adaptive PID formula immediately increases the proportional coefficient dynamically to accelerate current adjustment based on the current temperature deviation (the difference between the actual temperature and the ideal temperature in the transition range) and the temperature change rate, while decreasing the integral coefficient to avoid integral overshoot, thus smoothly reducing the target average charging current to the median level in a linear proportion. During this period, due to the continuous heating of core components, the temperature fluctuation peak exceeds the preset threshold. The system immediately calls the temperature fluctuation-pulse parameter correlation model and optimizes the parameters through the nonlinear adjustment formula of the pulse parameters. The calculation formula for the corresponding heating stage is as follows: During the heating phase, shortening the duty cycle and increasing the frequency reduces the energy input to the device from single current surges, mitigating the rapid temperature rise. For the cooling phase, the calculation formula is as follows: During the cooling phase, the duty cycle is extended and the frequency is reduced to minimize losses caused by switching actions. Furthermore, through the complementary matching of the adjustment ranges of the two, the target average charging current is ensured to remain stable without affecting the user's perception of fast charging speed.

[0031] The charger's power output module strictly follows the decision results to output the target average charging current and optimized pulse parameters. At the same time, based on the current comprehensive temperature change rate (such as when the temperature rises slowly in the transition range) and the proportion of temperature fluctuation peaks (not reaching abnormal levels), the closed-loop cycle is maintained at a moderate level, ensuring timely response while avoiding excessive consumption of computing power. Subsequently, it returns to the end-to-end temperature sensing step to re-collect data, forming a stable dynamic closed loop. Throughout the charging process, even if the user briefly moves the phone, causing slight fluctuations in the interface temperature, the closed-loop system can quickly adjust the parameters to ensure that the comprehensive temperature, the temperature at a single location (such as the temperature of core components and the interface temperature), and the temperature fluctuation peaks are all within a safe range. The closed loop automatically terminates when the phone is fully charged, without triggering any abnormal protection mechanisms.

[0032] Example 2

[0033] Due to prolonged high-frequency use, the internal power switching transistor of a charger aged. Upon initiating fast charging for a mobile phone, a distributed high-frequency temperature sensor array immediately detected an abnormal signal. The core power device temperature display showed that the switching transistor's temperature rose at a significantly faster rate than normal, and the temperature fluctuated frequently. Although the interface temperature collected by the infrared temperature sensor inside the charging port was within the normal range, the difference between it and the core device temperature was significantly increased. The high-frequency response thermocouple attached to the switching transistor surface further detected that the fluctuation amplitude of the instantaneous temperature sequence within the pulse cycle far exceeded the normal level, with a larger temperature rise during the conduction period and a slower temperature drop during the turn-off period, forming an abnormal fluctuation curve of steep rise and slow fall. The temperature of the mobile phone battery obtained through the protocol remained within the normal range, indicating that the abnormal heat source was concentrated in the aging power device inside the charger.

[0034] When using a dynamic weighted fusion formula for the collected multi-source temperature data, the dynamic weight of the core power device is automatically and significantly increased due to its extremely high temperature change rate, far exceeding the proportion during normal use. Although the final comprehensive temperature value does not exceed the warning range, the upward trend is obvious, and the frequency of numerical fluctuations increases. At the same time, based on the abnormal instantaneous temperature sequence collected by high-frequency thermocouples, after extracting the difference between the highest and lowest temperatures within the period, the temperature fluctuation peak value is calculated using the temperature fluctuation peak correction formula. Due to the extremely large variance of the temperature sequence within the period, the corrected temperature fluctuation peak value far exceeds the preset threshold, directly triggering the system's risk warning for abnormal fluctuations.

[0035] The overall temperature value is still in the transition range. The adaptive PID formula combines the current temperature deviation, temperature change rate, and abnormal temperature fluctuation peaks to specifically increase the derivative coefficient to suppress oscillations during parameter adjustment. This further linearly reduces the target average charging current to a level close to the safe current, attempting to alleviate device heating by reducing the total power input. Meanwhile, for temperature fluctuation peaks far exceeding the threshold, the system repeatedly calls the temperature fluctuation-pulse parameter correlation model and repeatedly optimizes the parameters through the nonlinear adjustment formula of the pulse parameters: significantly shortening the duty cycle and increasing the frequency during the heating phase, and extending the duty cycle and decreasing the frequency during the cooling phase. However, due to the heat dissipation defects caused by the aging of power devices, these defects cannot be compensated for by parameter adjustment. The adjusted temperature fluctuation peaks only decrease briefly before rapidly rebounding, remaining at an abnormally high level.

[0036] The charger outputs current according to the adjusted parameters and maintains closed-loop operation. During this period, the closed-loop cycle dynamic adjustment formula continuously shortens the closed-loop cycle to the minimum reference cycle when the detected temperature fluctuation peak ratio is too high, so as to track temperature changes as quickly as possible. When the detected temperature fluctuation peak reaches the abnormal threshold and lasts for multiple pulse cycles, the system immediately triggers the abnormal protection mechanism: it quickly cuts off the charging output circuit and stops supplying power to the mobile phone; at the same time, it controls the indicator light of the Type-C interface to enter the red flashing state to intuitively prompt the user of the fault; and sends an alarm message to the mobile phone via the PD protocol, requesting that the charger temperature fluctuation is abnormal and that the charger be checked or replaced. The mobile phone receives the message and displays the prompt in a pop-up window; finally, the closed-loop cycle is terminated to prevent further damage to aging power devices due to continuous and severe temperature fluctuations, and to prevent abnormal current from posing a potential risk to the mobile phone battery. If the user disconnects the charger and tries again, the system will still detect the same abnormal fluctuation and trigger the protection again, prompting the user to repair or replace the charger.

[0037] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A temperature-current collaborative control method for an intelligent temperature-controlled fast charger, characterized in that, The method comprises the following specific steps: Full-link temperature sensing: Synchronously collect the temperatures of the internal core power devices of the charger, the contact area of the charging interface, the battery end of the charged device, and the instantaneous temperature changes in the pulse period through a distributed high-frequency temperature sensor array to form a multi-dimensional temperature sensing network; Temperature data fusion and fluctuation analysis: Weighted fusion is performed on the collected multi-source temperature data according to the influence weight to generate a comprehensive temperature value reflecting the overall heating state of the system, and the temperature fluctuation peak value in the pulse period is extracted to quantify the temperature shock degree; Current and pulse parameter collaborative decision-making: Based on the comprehensive temperature value and the preset temperature interval, the target average charging current is determined, the pulse duty cycle and frequency are dynamically optimized according to the temperature fluctuation peak value, and the temperature fluctuation is suppressed while maintaining the target average current; Execute feedback and abnormal protection: Output the current according to the decision parameters and return to the temperature collection step to form a closed-loop control. If abnormal temperature or fluctuation is monitored during the closed-loop process, the output is immediately cut off and an alarm is given. 2.The temperature-current collaborative control method of the intelligent temperature-controlled fast charger of claim 1, wherein, In the full-link temperature sensing step, multi-dimensional temperature information is synchronously acquired through the deployment of a distributed high-frequency temperature sensor array, including NTC thermistors attached to the surfaces of the internal core power devices of the charger, which collect the working temperatures of multiple core devices in real time to form a core power device temperature set; an infrared temperature sensor installed on the inner side of the charging interface non-contact collects the temperature of the interface contact area; high-frequency response thermocouples attached to the surfaces of the power switch tubes and the battery interface capture the temperature changes in the pulse on period and off period with high-frequency sampling periods to form an instantaneous temperature sequence in the pulse period; and the battery end temperature feedback by the charged device is obtained in real time through the charging protocol interaction. 3.The temperature-current collaborative control method of the intelligent temperature-controlled fast charger of claim 1, wherein, In the temperature data fusion and fluctuation analysis step, the collected multi-source temperature data is weighted and fused, the weight is allocated according to the influence of the temperature at each position on the system safety and fast charging performance, and the weight is dynamically adjusted according to the fast charging protocol type. Finally, a comprehensive temperature value reflecting the overall heating state of the system is generated, and based on the instantaneous temperature data in the pulse period collected by the high-frequency thermocouple, the difference between the highest temperature and the lowest temperature in the period is extracted as the temperature fluctuation peak value. The temperature fluctuation peak value correction formula is used to quantify the shock amplitude of the temperature in the pulse working mode.

4. The temperature-current collaborative control method of the intelligent temperature-controlled fast charger according to claim 3, characterized in that, In the temperature data fusion and fluctuation analysis step, the collected multi-source temperature data is weighted and fused for calculation, and the calculation formula is: , is a dynamic weight coefficient, respectively corresponding to the core device, the interface and the battery end, wherein , is the effective temperature value of each position, is the arithmetic mean of the core power device temperature set , , , is a basic weight coefficient, satisfying , is the temperature change rate of each position, is the current sampling period, is the last sampling period, is the sampling interval, is the temperature change sensitivity coefficient. 5.The temperature-current collaborative control method of the intelligent temperature-controlled fast charger of claim 3, wherein, In the temperature data fusion and fluctuation analysis step, the temperature fluctuation peak correction formula is used to quantify the temperature oscillation degree in the pulse working mode, and the corrected temperature fluctuation peak is obtained , and the calculation formula is: , , The maximum and minimum values of the instantaneous temperature sequence in the pulse period are respectively , The variance of the instantaneous temperature sequence in the pulse period is , The fluctuation smoothing coefficient is used to strengthen the correction effect of the variance on the fluctuation peak. 6.The temperature-current collaborative control method of the intelligent temperature-controlled fast charger of claim 1, wherein, In the current and pulse parameter collaborative decision step, the comprehensive temperature value and the temperature fluctuation peak value output by the temperature data fusion and fluctuation analysis link are used to complete the calculation of the double-dimension adjustment parameters. In the current adjustment dimension, the target average charging current is generated by the PID adaptive algorithm according to the preset interval of the comprehensive temperature value, i.e., the safety interval, the transition interval and the early warning interval. In the safety interval, the maximum fast charging current of the charger is maintained. In the transition interval, the current is reduced to the median level in a linear proportion as the comprehensive temperature rises. In the early warning interval, the current is immediately reduced to the safety current. In the pulse parameter optimization dimension, the temperature fluctuation-pulse parameter correlation model calibrated through experiments is called to dynamically adjust the parameters according to the comparison result of the temperature fluctuation peak value and the preset threshold value. When the fluctuation peak value exceeds the preset threshold value, the duty cycle of the warming-up stage is shortened and the duty cycle of the cooling-down stage is lengthened. At the same time, the differential coefficient is corrected according to the comprehensive temperature change rate combined with the temperature fluctuation peak value to avoid oscillation in the parameter adjustment process.

7. The temperature-current collaborative control method of the intelligent temperature-controlled fast charger according to claim 6, characterized in that, The current and pulse parameter collaborative decision step, through the PID adaptive algorithm to generate the target average charging current: the safety interval maintains the maximum fast charging current of the charger, the algorithm formula is: Wherein, The reference current of the current temperature interval, the comprehensive temperature When in the safety interval, The maximum fast charging current of the charger ; When in the transition interval, The intermediate current value linearly decreasing with temperature; When in the early warning interval, The safety current, The temperature deviation, that is, the difference between the current comprehensive temperature and the ideal control temperature of the current interval, the calculation formula is: Wherein, The ideal control temperature of the current temperature interval, The dynamic proportional coefficient, the calculation formula is Wherein The proportional reference value, The positive temperature change rate, The proportional adjustment coefficient, the faster the temperature rises The greater, the current adjustment is accelerated, The dynamic integral coefficient, the calculation formula is Wherein The integral reference value, the faster the temperature rises The smaller, to avoid the current fluctuation caused by integral overshoot; The differential reference coefficient, The temperature deviation change rate, the calculation formula is: , The fluctuation influence coefficient, the greater the temperature fluctuation peak The stronger the differential action, effectively inhibiting the shock in the parameter adjustment process, 、 The proportional and integral reference values, The proportional adjustment coefficient, used to control And The adjustment range of the temperature change rate. 8.The temperature-current collaborative control method of the intelligent temperature-controlled fast charger of claim 6, wherein, The current and pulse parameter cooperative decision step calls a temperature fluctuation-pulse parameter correlation model calibrated through experiments to dynamically optimize the pulse duty cycle And the frequency , the calculation formula is: , for the cooling stage, the calculation formula is: , wherein , The optimized duty cycle and frequency of the heating stage are respectively , The optimized duty cycle and frequency of the cooling stage are respectively , The pulse parameter initial value is The parameter adjustment coefficient is satisfied , and the target average charging current is constant. 9.The temperature-current collaborative control method of the intelligent temperature-controlled fast charger of claim 1, wherein, In the feedback and abnormal protection execution step, the results of the current and pulse parameter collaborative decision link are converted into actual output, and closed-loop control and safety protection are formed. In the closed-loop process, the comprehensive temperature value, the single position temperature and the temperature fluctuation peak value are synchronously monitored. When the comprehensive temperature reaches the preset limit protection threshold value, the single position temperature exceeds the corresponding limit threshold value, or the temperature fluctuation peak value reaches the abnormal threshold value and lasts for multiple pulse periods, the charging output is immediately cut off, an alarm signal is sent out through the indicator light flickering or the charging protocol feedback, and the closed-loop cycle is terminated.

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