Charging temperature control method and system for mobile phone charger

Abstract

The invention relates to a charging temperature control method and system for a mobile phone charger. The charging temperature control method comprises the following steps: periodically outputting a test signal to a connected charging data line at each charging output port of a mobile phone charger, and collecting voltage response data and current response data of the ports in real time; calculating an impedance spectrum of the port according to the collected voltage response data and current response data; the impedance spectrum is analyzed, abnormal deviation in the impedance spectrum is recognized, the abnormal deviation is quantized into a connection quality deviation value, and the connection quality deviation value is related to the charging temperature; and when the connection quality deviation value exceeds a preset threshold value, starting an adaptive compensation mechanism to adjust the electric energy output of the port. Therefore, the problems of local overheating and element performance degradation caused by connection quality problems in the prior art can be effectively solved, and the safety and stability of the charger are improved.

Description

Technical Field

[0001] The present application relates to the technical field of mobile phone chargers, and in particular to a method and system for controlling the charging temperature of a mobile phone charger. Background Art

[0002] In modern society, multi-port mobile phone chargers have become an indispensable energy supply device in daily life.

[0003] Existing chargers are inadequate in identifying and responding to local overheating caused by connection quality issues. On the one hand, due to incomplete compatibility of the communication protocols between the connected device and the charger, it is difficult for the charger to accurately obtain the device's true power requirements or battery temperature, and it may be forced to adopt a less efficient universal charging mode, resulting in additional heat loss in the charging data cable and the charging management chip inside the mobile phone during power transmission, and local temperature increases. On the other hand, the long-term physical stress on the charging data cable at the charging output port may cause intermittent instability in the connection state, which in turn causes microstructural wear of the metal contacts inside the charger and the charging data cable interface, resulting in an irregular increase in the contact resistance of specific ports, exacerbating power output fluctuations and generating more Joule heat.

[0004] The existing technical solution is that when irregular power fluctuations or inefficient power transmission caused by connection quality issues occur, the charger may misinterpret this as the device frequently requesting different power levels, causing frequent adjustments to the power distribution strategy. This increases the workload of internal power conversion components and causes instantaneous heat accumulation. The combination of these factors can lead to localized hotspots within the charger that are difficult to effectively mitigate using existing load balancing strategies, posing a potential threat to component performance and lifespan.

[0005] In view of the above problems, the existing technology is in urgent need of improvement. Summary of the Invention

[0006] This application discloses a charging temperature control method and system for a mobile phone charger, aiming to address the shortcomings of existing charging temperature control methods in identifying and responding to local overheating caused by connection quality problems, especially in terms of local heat accumulation and component performance degradation. It is difficult to effectively reduce local hot spots through existing load balancing strategies, which poses a potential threat to component performance and life.

[0007] The technical solution of this application is as follows: In a first aspect, the present application discloses a method for controlling charging temperature of a mobile phone charger, comprising: At each charging output port of the mobile phone charger, a test signal is periodically output to the connected charging data line, and the voltage response data and current response data of the port are collected in real time; Calculate the impedance spectrum of the port based on the collected voltage response data and current response data; analyzing the impedance spectrum, identifying abnormal deviations in the impedance spectrum, and quantifying the abnormal deviations as connection quality deviation values, where the connection quality deviation values ​​are related to charging temperature; When the connection quality deviation value exceeds a preset threshold, the adaptive compensation mechanism is activated to adjust the power output of the port.

[0008] Optionally, the step of adjusting the power output of the port includes: Adjust the output voltage, output current, or perform pulse width modulation of this port.

[0009] Optionally, the step of adjusting the output voltage or output current of the port, or performing pulse width modulation, further includes: Determining a connection degradation level according to the connection quality deviation value, the connection degradation level including a first degradation and a second degradation, wherein the second degradation level is higher than the first degradation level; When the connection degradation level is the first degradation, continuously adjusting the output voltage or the output current of the port, or performing pulse width modulation; When the connection degradation level is the second degradation level, the mode is switched to the limited power output mode or the non-power output compensation mode according to the overall power output state of the charger or the temperature of the power conversion element.

[0010] Optionally, the step of analyzing the real-time impedance spectrum, identifying abnormal deviations in the impedance spectrum, and quantifying the abnormal deviations as connection quality deviation values ​​includes: Extracting electrical characteristics of the impedance spectrum within multiple preset frequency ranges; Identifying the physical degradation type to which the abnormal deviation in the impedance spectrum belongs based on the degree of matching between the electrical characteristics and preset characteristic patterns corresponding to different physical degradation mechanisms; The abnormal deviation is determined according to the physical degradation type, and the abnormal deviation is quantified as a connection quality deviation value.

[0011] Optionally, the step of extracting electrical characteristics of the impedance spectrum within a plurality of preset frequency ranges includes: Get the temperature data inside the charger near the port; determining temperature-related reference electrical characteristics within the plurality of preset frequency ranges based on the temperature data; Extracting electrical characteristics of the real-time impedance spectrum within multiple preset frequency ranges; Based on the extracted electrical feature and the temperature-dependent reference electrical characteristic, a difference between the electrical feature and the temperature-dependent reference electrical characteristic is calculated to obtain an electrical feature reflecting the physical degradation.

[0012] Optionally, the step of identifying the physical degradation type to which the abnormal deviation in the impedance spectrum belongs according to the degree of matching between the electrical characteristic and preset characteristic patterns corresponding to different physical degradation mechanisms includes: Identifying the variation trend and amplitude distribution of the electrical characteristics within a plurality of preset frequency ranges; Comparing the change trend and amplitude distribution with a preset characteristic pattern reflecting a single physical degradation mechanism to determine the degree of match between the electrical characteristics and the characteristic pattern; If the degree of matching indicates that the electrical feature cannot be matched to any single predetermined feature pattern, then analyzing the independent factors of multiple single physical degradation mechanisms contained in the electrical feature; The physical degradation type to which the abnormal deviation belongs is determined based on the independent factor.

[0013] Optionally, the step of analyzing independent factors of multiple single physical degradation mechanisms included in the electrical characteristics includes: Decomposing the electrical characteristics into components; Make the decomposed components reflect the characteristic mode of a single physical degradation mechanism; According to the components of the characteristic mode reflecting the single physical degradation mechanism, the independent factors of each single physical degradation mechanism are determined.

[0014] Optionally, the steps of analyzing the impedance spectrum, identifying abnormal deviations in the impedance spectrum, and quantifying the abnormal deviations as connection quality deviation values ​​include: According to the physical degradation type, a corresponding parameter is selected from a preset quantization parameter set corresponding to each physical degradation type, and based on the original electrical characteristics of the abnormal deviation, the connection quality deviation value is calculated using the selected quantization parameter.

[0015] In a second aspect, the present application further discloses a charger comprising a memory and a processor, wherein the memory stores computer-readable instructions, and the processor is configured to implement the steps of the method described above when executing the computer-readable instructions.

[0016] In a third aspect, the present application further discloses a computer program product, which includes a computer program, and the computer program is used to implement the steps of the method described above when executed by a computer.

[0017] Beneficial effects

[0018] This application provides a charging temperature control method for a mobile phone charger. By periodically outputting a test signal at each charging output port and collecting voltage and current response data in real time, the impedance spectrum of the port can be accurately calculated. The method further analyzes the impedance spectrum to identify abnormal deviations related to connection quality and quantifies them as a connection quality deviation value directly related to the charging temperature. When this deviation value exceeds a preset threshold, the system can promptly activate an adaptive compensation mechanism to accurately adjust the power output of the port.

[0019] This technical solution effectively solves the problems of local overheating and component performance degradation caused by connection quality problems in the prior art. Specifically, by real-time monitoring of the impedance spectrum, the present application can overcome the limitations of the prior art in that it is difficult to accurately obtain the true power demand of the device or the battery temperature, and avoids the irregular increase in contact resistance and Joule heat accumulation caused by unstable connection or microstructure wear. By quantifying the abnormal deviation as a connection quality deviation value and initiating adaptive compensation accordingly, the present application can prevent the charger from misjudging the connection problem as a change in the device power request, thereby reducing the workload and instantaneous heat accumulation of the internal power conversion components. Therefore, the present application can effectively eliminate local hot spots inside the charger, significantly improve the safety and stability of the charger, extend the service life of the components, and optimize the overall charging efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a flow chart of a method for controlling charging temperature of a mobile phone charger provided in an embodiment of the present application; Figure 2 This is a flow chart of another method for controlling charging temperature of a mobile phone charger provided in an embodiment of the present application; Figure 3 This is a flow chart of another method for controlling charging temperature of a mobile phone charger provided in an embodiment of the present application; Figure 4 This is a flow chart of another method for controlling charging temperature of a mobile phone charger provided in an embodiment of the present application; Figure 5 This is a flow chart of another method for controlling charging temperature of a mobile phone charger provided in an embodiment of the present application; Figure 6 This is a flow chart of another method for controlling charging temperature of a mobile phone charger provided in an embodiment of the present application; Figure 7 This is a flow chart of another method for controlling charging temperature of a mobile phone charger provided in an embodiment of the present application; Figure 8 This is a schematic diagram of the structure of a mobile phone charger charging temperature control system provided in an embodiment of the present application; Figure 9This is a basic structural block diagram of a charger provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] The technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. The components of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for which protection is claimed, but merely represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0022] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0023] See also Figure 1 , this application proposes a method for controlling the charging temperature of a mobile phone charger, which specifically includes the following steps: Step S1: At each charging output port of the mobile phone charger, a test signal is periodically output to the connected charging data line, and voltage response data and current response data of the port are collected in real time; Step S2: Calculating the impedance spectrum of the port based on the collected voltage response data and current response data; Step S3: Analyze the impedance spectrum, identify abnormal deviations in the impedance spectrum, and quantify the abnormal deviations into connection quality deviation values, where the connection quality deviation values ​​are related to the charging temperature; Step S4: When the connection quality deviation value exceeds a preset threshold, the adaptive compensation mechanism is activated to adjust the power output of the port.

[0024] This application can accurately calculate the impedance spectrum of each charging output port by periodically outputting a test signal and collecting voltage response data and current response data in real time. Through in-depth analysis of the impedance spectrum, abnormal deviations caused by connection quality problems can be identified and quantified, and converted into a connection quality deviation value related to the charging temperature. When this value exceeds the preset threshold, the system will activate the adaptive compensation mechanism to adjust the power output of the port, thereby effectively avoiding local overheating and improving charging safety and component life.

[0025] A mobile phone charger is a device that provides power to mobile communication devices (such as smartphones and tablets). It typically includes multiple charging output ports to allow simultaneous charging of multiple devices. The charging output port is the physical interface between the charger and the charging data cable, responsible for transmitting power. The charging data cable connects the charger to the device being charged, transmitting not only power but also data.

[0026] A test signal is a specific electrical signal that the charger actively outputs to the charging data cable to detect the connection status. It can take various forms, such as a sine wave, square wave, or pulse train. Voltage response data and current response data are collected in real time from the charging output port after the charger outputs the test signal. These data reflect the electrical response of the charging data cable and connected device to the test signal.

[0027] The impedance spectrum refers to a curve or data set showing how the complex impedance of the charging output port and its connection circuit changes with frequency at different frequencies. It can reflect the electrical characteristics of the connection circuit, such as resistance, inductance, and capacitance, and is sensitive to small changes in connection quality. Abnormal deviation refers to a significant difference between the impedance spectrum and the normal impedance spectrum or the baseline impedance spectrum. This difference usually indicates a deterioration in connection quality, such as increased contact resistance or internal cable damage. The connection quality deviation value is a quantitative representation of the degree of this abnormal deviation. Its numerical value directly reflects the degree of deterioration in connection quality and is directly related to the local temperature increase that may occur during the charging process.

[0028] The adaptive compensation mechanism is an intelligent regulation strategy that automatically adjusts the power output parameters of the charging output port when a deviation in connection quality is detected, mitigating or eliminating adverse effects caused by the connection quality issue, such as overheating. Power output adjustment involves changing the voltage, current, or pulse width of the charging output port to accommodate varying connection conditions and charging requirements.

[0029] The embodiments of this application will elaborate on the main features of the above method in detail.

[0030] First, regarding step S1, "periodically outputting a test signal to the connected charging data cable at each charging output port of the mobile phone charger," as one embodiment, the charger can be configured to output a sinusoidal test signal with a preset frequency (e.g., 1kHz) and amplitude (e.g., 100mV) to each charging output port at regular intervals (e.g., every 5 seconds). The output of this test signal can be controlled by a signal generator module within the charger. As another embodiment, a series of square wave pulses with different frequencies can be periodically output as the test signal. For example, a composite square wave signal containing multiple frequency components, such as 50Hz, 100Hz, and 500Hz, can be output every 10 seconds during the charging process to cover a wider frequency range.

[0031] Secondly, regarding the step of "real-time acquisition of port voltage response data and current response data" in step S1. Specifically, when the test signal is output to the charging data line, the voltage acquisition circuit and current acquisition circuit inside the charger will work synchronously. For example, the voltage acquisition circuit can use a high-precision analog-to-digital converter (ADC) to continuously sample the voltage across the port, while the current acquisition circuit can use a precision sampling resistor connected in series in the loop to measure the voltage drop across it. Then, using Ohm's law, it calculates the current flowing through the port and also digitizes it using the ADC. These collected voltage and current data will be stored and processed in the form of a time series.

[0032] Furthermore, regarding the step of "calculating the impedance spectrum of the port based on the collected voltage response data and current response data" in step S2. After obtaining the real-time voltage response data and current response data, a variety of methods can be used to calculate the impedance spectrum. For example, the collected time-domain voltage and current data can be converted into frequency-domain data through a fast Fourier transform (FFT), and then the frequency-domain voltage is divided by the frequency-domain current to obtain the complex impedance values ​​at different frequencies, thereby constructing the impedance spectrum. As another embodiment, a swept frequency measurement method can be used, that is, the test signals are output at different frequency points respectively, and the corresponding steady-state voltage and current responses are measured, and then the impedance value of each frequency point is calculated, and finally a complete impedance spectrum is formed.

[0033] Furthermore, regarding step S3 of "analyzing the impedance spectrum, identifying abnormal deviations in the impedance spectrum, and quantifying the abnormal deviations into a connection quality deviation value, wherein the connection quality deviation value is correlated with the charging temperature," after obtaining the port impedance spectrum, it can be compared with a pre-stored reference impedance spectrum obtained under normal connection conditions. For example, the amplitude or phase difference between the real-time impedance spectrum and the reference impedance spectrum within a specific frequency range can be calculated, and these differences can be used as preliminary evidence for identifying abnormal deviations. When these differences exceed a preset tolerance, they are determined to be abnormal deviations. The extent of these abnormal deviations can then be converted into a specific connection quality deviation value using a pre-set quantification model (e.g., a linear function or a lookup table). This quantification model is designed to take into account temperature data within the charger or near the port, ensuring that the final connection quality deviation value reflects the degree of connection degradation under current temperature conditions. For example, at higher temperatures, even small impedance changes may be quantified as higher deviation values, more sensitively reflecting potential overheating risks.

[0034] Finally, regarding step S4, "When the connection quality deviation exceeds a preset threshold, an adaptive compensation mechanism is activated to adjust the power output of the port." Specifically, once the calculated connection quality deviation exceeds a preset safety threshold (e.g., a value indicating slight degradation), the charger's internal control unit immediately activates the adaptive compensation mechanism. This mechanism adjusts the power output of the charging output port based on the deviation. For example, when the deviation reaches a first threshold, the system can moderately reduce the output voltage of the port to reduce Joule heating. When the deviation increases further, reaching a second threshold, the system can further reduce the output current or switch to a more conservative charging mode to effectively control the port temperature and prevent overheating.

[0035] This application first actively detects the electrical characteristics of the connection loop by periodically outputting a test signal at each charging output port and collecting voltage response data and current response data in real time. This active detection mechanism breaks through the limitations of traditional passive monitoring of temperature or power and can capture subtle changes in the connection status. Subsequently, the impedance spectrum of the port is accurately calculated based on the collected voltage response data and current response data. As a comprehensive electrical fingerprint, the impedance spectrum can sensitively reflect the health status of the charging data cable, interface contacts, and even the charging path inside the connected device, including an increase in contact resistance, micro-damage inside the cable, etc., which are potential sources of local heating.

[0036] Furthermore, the system conducts an in-depth analysis of the calculated impedance spectrum to identify abnormal deviations. The identification of such abnormal deviations is not a simple threshold judgment, but rather a comparison with the impedance spectrum under normal conditions, accurately capturing the characteristic changes caused by connection degradation. The identified abnormal deviations are then quantified into a connection quality deviation value, which not only reflects the degree of connection degradation but, more importantly, is directly related to the charging temperature. This means that this value can intuitively indicate the potential impact of the current connection quality on the charging temperature, providing a quantitative basis for subsequent temperature control.

[0037] When the connection quality deviation exceeds a preset threshold, the system immediately activates an adaptive compensation mechanism to adjust the port's power output. This adjustment is proactive and preventative, optimizing power transmission parameters to reduce heat generation before local overheating becomes a serious problem. For example, by moderately reducing the output voltage or current, the accumulation of Joule heat can be effectively reduced, thereby maintaining the port temperature within a safe range. The entire process forms a closed-loop control system: from actively detecting the connection status, to accurately diagnosing the degree of degradation, to intelligently adjusting the power output, each link is closely linked to ensure the safety and stability of the charging process and significantly improve the charger's thermal management capabilities.

[0038] Specifically, the step of adjusting the power output of the port may include adjusting the output voltage or output current of the port, or performing pulse width modulation.

[0039] Adjusting the output voltage of the port refers to controlling the power delivered to the connected device by varying the voltage level at the charger's output. For example, when a high connection quality deviation is detected, the output voltage can be appropriately reduced to reduce charging power, thereby reducing heat generation on the charging data cable or at the connection port. Adjusting the output current refers to controlling the power delivered to the connected device by varying the current at the charger's output. For example, while maintaining the voltage constant, reducing the output current can effectively reduce the power flowing through the charging data cable, thereby reducing heat generation caused by the current heating effect. Pulse width modulation (PWM) controls the average output power by periodically switching the power output on and off and adjusting the proportion of time the power is on within each cycle (i.e., the duty cycle). By varying the duty cycle, fine-grained control of the output power can be achieved without directly changing the voltage or peak current, effectively managing heat generation during the charging process.

[0040] The solution of the present application provides multiple power output adjustment methods, so that the charger can flexibly and accurately control the power transmitted to the connected device according to the connection quality deviation value detected in real time.

[0041] In some of the aforementioned embodiments of this application, it is proposed that when the connection quality deviation value exceeds a preset threshold, the power output of the port be adjusted by adjusting the output voltage or output current of the port or performing pulse width modulation. However, in actual applications, the degree of connection quality degradation may vary significantly. If a single compensation strategy is adopted without distinguishing the degradation level, it may not provide the optimal or safest response for different degrees of degradation. For example, in the case of severe degradation, simple voltage or current adjustment may not be sufficient to effectively control the charging temperature or avoid potential risks.

[0042] In this regard, the present application further proposes the above-mentioned scheme for adjusting the power output of the port. For details, please refer to Figure 2 , including the following: Step S41: determining the connection degradation level according to the connection quality deviation value, where the connection degradation level includes a first degradation level and a second degradation level, wherein the second degradation level is higher than the first degradation level; Step S42: When the connection degradation level is the first degradation level, continuously adjusting the output voltage or the output current of the port, or performing pulse width modulation; Step S43: When the connection degradation level is the second degradation level, switching to a limited power output mode or a non-power output compensation mode according to the overall power output state of the charger or the temperature of the power conversion element.

[0043] Specifically, the connection quality deviation value is an indicator that quantifies the connection abnormality deviation, and its numerical value reflects the degree of connection degradation. Based on the connection quality deviation value, the connection degradation level can be determined. For example, multiple thresholds can be preset to divide the connection quality deviation value into different intervals, and each interval corresponds to a connection degradation level. In the present application, the connection degradation level is divided into first degradation and second degradation, where the degree of second degradation is higher than the first degradation. The first degradation usually refers to a mild or moderate connection abnormality, such as a slight increase in contact resistance, slight oxidation, etc. At this time, the charger can still work, but the efficiency may be reduced or the temperature may increase slightly. The second degradation refers to a more serious connection abnormality, such as severe poor contact, risk of local short circuit, or severe internal damage to the cable. If stronger measures are not taken at this time, it may cause the charging temperature to rise sharply, and even cause safety hazards.

[0044] When the connection degradation level reaches level 1, the system continuously adjusts the port's output voltage, output current, or performs pulse width modulation. This adjustment is gradual and continuous, aiming to compensate for minor connection degradation by fine-tuning power output parameters to maintain a stable charging state and control temperature. For example, it can reduce heat generation by lowering the output voltage or current, or finely control energy delivery through pulse width modulation.

[0045] When the connection degradation level is determined to be the second degradation level, due to the high degree of degradation, the system will switch to limited power output mode or non-power output compensation mode based on the overall power output status of the charger or the temperature of the power conversion element. Limited power output mode means that the charger will actively reduce its maximum output power to reduce overall heat generation and protect the charger and connected devices. Non-power output compensation mode means suspending or terminating power output. For example, when it is detected that the temperature of the power conversion element is too high or the overall load of the charger is too large, in order to avoid overheating damage, the system will stop power supply and can solve the problem by prompting the user to check the connection or disconnect.

[0046] This solution introduces a classification system for determining the level of connection degradation, enabling differentiated responses to varying degrees of connection anomalies. This tiered response allows for more accurate and effective charging temperature management, avoiding the potential shortcomings of a single compensation strategy.

[0047] Through the above technical solution, this application can intelligently select the most appropriate power output adjustment strategy based on the actual severity of connection degradation. This not only makes charging temperature control more precise and effective, enabling smooth compensation for minor degradation, but also enables timely and strong protection measures in the face of severe degradation, thereby significantly improving the safety, stability, and reliability of the charging process.

[0048] In some preferred embodiments, a specific example is provided below. Assume that a mobile phone charger detects a connection quality deviation of 0.15 at a charging output port, with a preset first degradation threshold of 0.1 and a second degradation threshold of 0.3. Since 0.1 < 0.15 < 0.3, the system determines that the connection degradation level is the first degradation level. At this point, the charger will continuously fine-tune the output voltage of that port, for example, from 5.0V to 4.9V, or reduce the output current from 2.0A to 1.9A, to reduce heat at the connection while maintaining charging continuity.

[0049] Furthermore, assume that at another moment, the connection quality deviation value of the port rises to 0.45. Since 0.45 > 0.3, the system determines that the connection degradation level is the second degradation. At this time, the system will immediately check the temperature of the power conversion element inside the charger. If the temperature is close to the preset safety upper limit, or the overall power output of the charger is close to its design limit, the system will immediately switch to the power output limit mode, such as limiting the maximum output power of the port to a lower level, or directly entering the non-power output compensation mode, suspending the power output of the port, and prompting the user to check the charging data cable or connected device through an indicator light or screen information, or a voice signal, thereby effectively avoiding the risk of overheating due to severe connection degradation.

[0050] See also Figure 3 The step of "analyzing the impedance spectrum, identifying abnormal deviations in the impedance spectrum, and quantifying the abnormal deviations as connection quality deviation values" in the above step S3 may include the following specific steps: Step S31: extracting electrical characteristics of the impedance spectrum within a plurality of preset frequency ranges; Step S32: identifying the physical degradation type to which the abnormal deviation in the impedance spectrum belongs based on the degree of matching between the electrical characteristics and preset characteristic patterns corresponding to different physical degradation mechanisms; Step S33: determining the abnormal deviation according to the physical degradation type, and quantifying the abnormal deviation into a connection quality deviation value.

[0051] Extracting electrical characteristics from the impedance spectrum within multiple preset frequency ranges involves selecting specific frequency intervals from the calculated impedance spectrum of the port and extracting electrical parameters within these intervals that reflect the connection status, such as resistance, inductance, capacitance, or a combination thereof. These electrical characteristics can be quantitative descriptions of the impedance spectrum curve shape, amplitude, phase, and other aspects.

[0052] Furthermore, the physical degradation type to which the abnormal deviation in the impedance spectrum belongs is identified based on the degree of match between the electrical characteristics and preset characteristic patterns corresponding to different physical degradation mechanisms. Specifically, the preset characteristic patterns are established based on a large amount of experimental data or theoretical models, and each pattern corresponds to one or more specific physical degradation mechanisms, such as poor contact, cable aging, insulation damage, etc. By comparing the extracted electrical characteristics with these preset patterns, their degree of match can be evaluated, thereby determining which physical degradation mechanism or mechanisms are causing the current connection anomaly. The purpose is to classify connection anomalies and provide a basis for subsequent precise compensation.

[0053] Thus, based on the type of physical degradation, the abnormal deviation is determined and quantified into a connection quality deviation value. Once the specific type of physical degradation is identified, a specific quantification method can be used to calculate the connection quality deviation value for that type. For example, for impedance increase caused by poor contact, the deviation can be quantified based on the amplitude and frequency characteristics of the impedance increase; for capacitance change caused by cable aging, the deviation can be quantified based on the capacitance change. The purpose is to convert abstract physical degradation into actionable and comparable values ​​to facilitate threshold judgment and adaptive adjustment of the system.

[0054] In some of the above-mentioned embodiments of the present application, it is proposed to identify the type of physical degradation to which the abnormal deviation belongs by extracting the electrical characteristics of the impedance spectrum. However, in actual applications, when the mobile phone charger is working, its internal ambient temperature will change with the charging state, load conditions and external environment. This temperature change will have a significant impact on the impedance spectrum of the charging port. If the temperature factor is not taken into account, directly comparing the electrical characteristics of the real-time impedance spectrum with a single preset benchmark may lead to inaccurate identification of connection quality deviations, or even misjudgment, thereby affecting the effectiveness and accuracy of the subsequent adaptive compensation mechanism.

[0055] In this regard, this application further proposes a more accurate electrical feature extraction method, which aims to eliminate the interference of temperature changes on impedance spectrum analysis, thereby more accurately identifying and quantifying physical degradation. Figure 4 The step of "extracting the electrical characteristics of the impedance spectrum within multiple preset frequency ranges" in step S31 above specifically includes the following steps: Step S311: Acquire temperature data inside the charger near the port; Step S312: determining temperature-related reference electrical characteristics within the plurality of preset frequency ranges based on the temperature data; Step S313: extracting electrical characteristics of the real-time impedance spectrum within multiple preset frequency ranges; Step S314: Based on the extracted electrical characteristics and the temperature-dependent reference electrical characteristics, a difference between the electrical characteristics and the temperature-dependent reference electrical characteristics is calculated to obtain an electrical characteristic reflecting the physical degradation.

[0056] Specifically, obtaining temperature data within the charger near the port involves deploying a temperature sensor within the mobile phone charger, for example, near the charging output port or near key power conversion components, to monitor and acquire temperature data in real time in that area. Based on this temperature data, temperature-related benchmark electrical characteristics within multiple preset frequency ranges are determined. It can be understood that the impedance spectrum of a healthy charging port exhibits different electrical characteristics under different temperature conditions. Therefore, a mapping relationship between temperature and benchmark electrical characteristics needs to be pre-established so that, after acquiring real-time temperature data, the corresponding non-degraded benchmark electrical characteristics at the current temperature can be accurately determined. Extracting electrical characteristics from the real-time impedance spectrum within multiple preset frequency ranges involves continuously collecting voltage and current response data from the port during the charging process, calculating a real-time impedance spectrum, and then extracting electrical characteristics within specific frequency ranges from the real-time impedance spectrum, such as impedance amplitude, phase, real part, imaginary part, or rate of change.

[0057] Through the above technical solution, this application can effectively eliminate the interference of temperature changes on impedance spectrum analysis, significantly improving the accuracy of identifying abnormal deviations in the impedance spectrum. As a result, the connection quality deviation value can be quantified more accurately, avoiding misjudgments or omissions caused by temperature fluctuations. This allows the subsequent adaptive compensation mechanism to make decisions and adjustments based on more reliable data, further improving the robustness and effectiveness of the mobile phone charger charging temperature control.

[0058] For details, please refer to Figure 5 The step S32 of "identifying the physical degradation type to which the abnormal deviation in the impedance spectrum belongs based on the degree of matching between the electrical characteristics and the preset characteristic patterns corresponding to different physical degradation mechanisms" can be further refined into the following steps: Step S321: Identifying the change trend and amplitude distribution of the electrical characteristics within a plurality of preset frequency ranges; Step S322: comparing the change trend and amplitude distribution with a preset characteristic pattern reflecting a single physical degradation mechanism to determine the degree of matching between the electrical characteristics and the characteristic pattern; Step S323: If the matching degree indicates that the electrical feature cannot match any single preset feature pattern, then analyzing independent factors of multiple single physical degradation mechanisms contained in the electrical feature; Step S324: Determine the physical degradation type to which the abnormal deviation belongs based on the independent factor.

[0059] Identifying the variation trends and amplitude distribution of electrical characteristics within multiple preset frequency ranges involves analyzing the numerical variation patterns and distribution of the electrical characteristics extracted from the impedance spectrum, such as resistance, capacitance, inductance, and other parameters, at different frequency points or frequency intervals. For example, the variation trends of impedance with increasing or decreasing frequency, as well as the peak or valley values ​​of impedance within a specific frequency range, can be analyzed.

[0060] Furthermore, the change trend and amplitude distribution are compared with preset characteristic patterns reflecting a single physical degradation mechanism to determine the degree of match between the electrical characteristics and the characteristic patterns. Preset characteristic patterns are established based on extensive experimental data or theoretical models and are used to characterize the typical electrical characteristic changes exhibited on the impedance spectrum by different physical degradation mechanisms (e.g., increased contact resistance, insulation aging, short circuit, open circuit, etc.). This comparison can be performed by calculating similarity, correlation coefficients, or using machine learning algorithms (e.g., support vector machines, neural networks) for pattern recognition to quantify the degree of match between the current electrical characteristics and each single degradation pattern.

[0061] In practical applications, if the degree of match indicates that the electrical signature cannot be matched to a single pre-defined characteristic pattern, the independent factors of multiple single physical degradation mechanisms contained in the electrical signature are analyzed. This typically occurs when the connection quality degradation is not caused by a single cause, but rather by the combined action of multiple physical degradation mechanisms. For example, poor contact and material aging may coexist. In this case, the complex electrical signature needs to be decomposed to identify and quantify the contributions of each single physical degradation mechanism. This can be achieved through signal processing techniques such as principal component analysis (PCA), independent component analysis (ICA), or blind source separation, which decompose the mixed electrical signature into independent components or factors reflecting different single degradation mechanisms.

[0062] Based on these independent factors, the physical degradation type to which the abnormal deviation belongs is determined. Once the independent factors and their respective contributions to the complex degradation phenomenon are identified, the system can more accurately determine the specific physical degradation types (such as contact resistance degradation, cable insulation degradation, interface oxidation, etc.) that are causing the current abnormal connection quality deviation and their respective severity.

[0063] Through the above technical solution, the present application can achieve more refined and accurate identification of the physical degradation type of abnormal deviation in the connection quality of mobile phone chargers. Especially in practical applications, connection degradation is often the result of the combined action of multiple factors, and traditional single pattern matching methods may not be able to accurately identify it. The present application can effectively solve this problem by analyzing the independent factors of multiple single physical degradation mechanisms contained in the electrical characteristics, thereby improving the accuracy and robustness of degradation type identification, providing a reliable basis for subsequent precise compensation and fault diagnosis, thereby improving the safety and efficiency of the charging process.

[0064] In some of the above embodiments of the present application, when the electrical characteristics cannot match any single preset characteristic pattern, it is necessary to analyze the independent factors of multiple single physical degradation mechanisms contained in the electrical characteristics. Figure 6 The step of "analyzing the independent factors of multiple single physical degradation mechanisms contained in the electrical characteristics" in the above step S323 can be subdivided into the following steps: Step S3231: decomposing the electrical characteristics into components; Step S3232: making the decomposed components reflect the characteristic mode of a single physical degradation mechanism; Step S3233: Determine the independent factors of each single physical degradation mechanism according to the components of the characteristic mode reflecting the single physical degradation mechanism.

[0065] Specifically, component decomposition of electrical characteristics involves breaking down the electrical characteristics extracted from the impedance spectrum, which may contain a mixture of various physical degradation signals, into multiple independent or quasi-independent components through mathematical or signal processing methods. For example, multivariate statistical analysis methods such as principal component analysis (PCA), independent component analysis (ICA), and non-negative matrix factorization (NMF) can be used to project complex electrical characteristic data into a new feature space, thereby isolating different potential influencing factors. The goal is to decouple mixed degradation signals to facilitate the subsequent identification of a single degradation mechanism.

[0066] The phrase "making the decomposed components reflect the characteristic patterns of a single physical degradation mechanism" can be understood as ensuring, based on component decomposition, that each decomposed component clearly represents the electrical change pattern caused by a specific, independent physical degradation mechanism. This can be achieved through pre-trained models, dictionary learning based on known degradation patterns, or constrained optimization algorithms. For example, by introducing sparsity or independence constraints during the decomposition process, the decomposition results are more likely to isolate a single degradation pattern with physical significance. This aims to provide clean, interpretable input for the subsequent determination of independent factors.

[0067] In practical applications, the independent factors for each individual physical degradation mechanism are determined based on the components of the characteristic patterns reflecting that mechanism. Specifically, this involves extracting key parameters from each identified individual physical degradation mechanism component that can quantify the extent or impact of that degradation mechanism. For example, for a component representing contact resistance degradation, its independent factor could be the component's amplitude or its slope within a specific frequency range; for a component representing insulation aging, its independent factor could be the change in its capacitive reactance in the low-frequency region. These independent factors can be directly used in the subsequent calculation of connection quality deviation values, thereby more accurately reflecting the combined impact of different degradation mechanisms on connection quality.

[0068] Through the above technical solution, the present application can overcome the problem that it is difficult to accurately identify and quantify each degradation type when there are multiple physical degradation mechanisms mixed in the electrical characteristics. By performing a refined component decomposition of the electrical characteristics and making the decomposed components directly correspond to a single physical degradation mechanism, the present application can more accurately identify the independent factors of each degradation mechanism. This significantly improves the accuracy and robustness of the numerical quantification of connection quality deviations, especially in the face of complex, multi-factor coupled connection degradation situations, and can provide more detailed and reliable diagnostic information, so that the charging temperature control method can be based on a more accurate connection status assessment, perform more effective adaptive compensation and power output adjustment, and further improve charging safety and user experience.

[0069] Specifically, the steps of analyzing the impedance spectrum, identifying abnormal deviations in the impedance spectrum, and quantifying the abnormal deviations into connection quality deviation values ​​as described above include: selecting corresponding parameters from a preset set of quantization parameters corresponding to each physical degradation type according to the physical degradation type, and calculating the connection quality deviation value using the selected quantization parameters based on the original electrical characteristics of the abnormal deviation.

[0070] The physical degradation type refers to the specific form of connection degradation identified during impedance spectrum analysis, and may include, for example, poor contact, internal cable fracture, interface corrosion, or insulation aging. Each physical degradation type exhibits unique electrical characteristics and variation patterns on the impedance spectrum. The preset set of quantification parameters corresponding to each physical degradation type can be understood as a pre-established database or lookup table, storing the specific algorithms, weighting coefficients, thresholds, or model parameters required to numerically quantify connection quality deviations for different physical degradation types. For example, for poor contact, a linear or nonlinear model based on resistance change might be used for quantification; for internal cable fracture, the focus might be on abnormal changes in inductance or capacitance. The raw electrical characteristics of the abnormal deviation refer to the raw electrical data extracted from the real-time impedance spectrum that reflect the connection anomaly, such as the impedance amplitude, phase angle, or rate of change with frequency at a specific frequency. In actual applications, once the system identifies a specific physical degradation type, it automatically selects the quantification parameter from the aforementioned parameter set that best matches that degradation type. Subsequently, the connection quality deviation value is accurately calculated using these selected quantitative parameters in combination with the original electrical characteristics extracted from the impedance spectrum through a preset calculation formula or model.

[0071] The above technical solution significantly improves the accuracy and reliability of connection quality deviation quantification. Because the quantification process is customized based on the specific type of physical degradation, the resulting deviation value can more accurately indicate the nature and severity of the connection problem, providing more precise input for subsequent adaptive compensation mechanisms. This helps the charger more effectively identify and respond to charging temperature anomalies caused by connection degradation, thereby achieving more refined and intelligent charging temperature control, improving charging safety and user experience.

[0072] In some of the above-mentioned embodiments of the present application, it is proposed to periodically output a test signal to the connected charging data line to collect response data. However, during its implementation, if the output parameters of the test signal (such as time period, frequency range, waveform or amplitude) are fixed, it may cause unnecessary interference to the normal charging process or data transmission in certain specific charging communication states or device charging states, or it may be impossible to obtain response data under optimal conditions, thereby affecting the accuracy of impedance spectrum analysis.

[0073] In this regard, the present application further proposes a specific solution for the step of "periodically outputting a test signal to the connected charging data line" in the above step S1, please refer to Figure 7 , specifically including the following steps: Step S11: Acquire the charging communication status of the charging data cable or the charging status of the connected device; Step S12: determining the output period, frequency range, waveform or amplitude of the test signal according to the charging communication state of the charging data line or the charging state of the connected device; Step S13: periodically outputting the test signal to the connected charging data line, wherein the output period, frequency range, waveform or amplitude of the test signal is performed according to the determined output period, frequency range, waveform or amplitude.

[0074] Specifically, obtaining the charging communication status of the charging data line or the charging status of the connected device refers to obtaining real-time operating mode information for the current charging connection. For example, this information can be used to determine whether the charging data line is in data transmission mode, charging protocol negotiation mode (such as USB PD, QC, etc.), or idle. Furthermore, the charging status of the connected device can be obtained, such as the device's battery level, charging power requirement, and whether it is in the trickle charging, constant current charging, or constant voltage charging phase. This status information can be obtained by monitoring communication signals and voltage and current changes on the charging data line, or through protocol interaction with the connected device.

[0075] Determining the output period, frequency range, waveform, or amplitude of the test signal based on the acquired charging communication status or the charging status of the connected device can be understood as dynamically adjusting the test signal parameters based on the current actual working environment and needs. For example, when the charging data line is idle or the connected device is in low-power mode, the test signal can be output for a longer period of time, using a wider frequency range or a larger amplitude to obtain more comprehensive impedance spectrum data. Conversely, when the charging data line is performing high-speed data transmission or the connected device is in a high-power fast charging state, the test signal can be output during a shorter non-interference period (such as a data transmission gap) and using a specific narrow frequency range or a smaller amplitude to avoid affecting normal communication and charging. The choice of waveform can also be optimized according to different states, such as selecting a pulse waveform to reduce average power consumption or a sine waveform for accurate frequency response analysis.

[0076] In practice, a test signal is periodically output to the connected charging data line. The test signal's output period, frequency range, waveform, or amplitude are determined according to the aforementioned parameters. This means the test signal is no longer static, but instead intelligently adapts to the current charging environment. This adaptive output ensures the effectiveness of the test signal while minimizing potential interference with the charging process.

[0077] The above technical solution can significantly improve the intelligence and adaptability of the test signal output, thereby more accurately and efficiently obtaining the port's voltage and current response data without interfering with normal charging and data transmission. As a result, the calculated impedance spectrum will be more accurate, and the identification and quantification of connection quality deviations will be more reliable, ultimately improving the accuracy and response speed of charging temperature control. In addition, this adaptive test signal output method also helps to optimize the utilization of the charger's internal resources, reduce unnecessary energy consumption, and enhance the charger's compatibility with different charging data cables and connected devices.

[0078] In some preferred embodiments, a specific example is used below to illustrate the above, assuming that a mobile phone charger is connected to a smart phone for charging.

[0079] First, the charger's data acquisition module detects the current charging communication status of the charging data line. For example, if it detects that the charging data line is negotiating the USB Power Delivery (PD) protocol or performing high-speed data transmission (such as USB 3.0), the charger determines that the communication is currently active. It also detects the charging status of the connected device. For example, if a mobile phone's battery is low and is being fast-charged with a high current, the charger determines that it is in high-power charging mode.

[0080] Secondly, based on this acquired status information, the charger dynamically determines the output parameters of the test signal. For example, during PD protocol negotiation or high-speed data transmission, to avoid interference, the test signal output period may be limited to the gaps in protocol negotiation or the microsecond pauses in data transmission. The frequency range may be limited to a range away from the main data transmission frequency band, and the waveform may be selected as a low-amplitude narrow pulse to minimize the impact on communication. When the phone enters the trickle charging stage or charging is completed and the data line is idle, the charger can determine to output the test signal for a longer period of time, using a wider frequency range and appropriate amplitude to obtain more detailed impedance spectrum information.

[0081] Finally, the charger periodically outputs a test signal to the connected charging data line, with the output period, frequency range, waveform, or amplitude strictly adhering to the parameters determined above. For example, in fast-charging mode, a low-amplitude pulse signal of a specific frequency might be sent every 10 seconds during the slight gaps in data transmission; while in trickle-charging mode, a sine wave signal with a slightly longer duration and a wider frequency range might be sent every 5 seconds. In this way, the test signal output can intelligently adapt to different charging scenarios, ensuring the accuracy and non-invasiveness of the impedance spectroscopy measurement.

[0082] While some of the aforementioned implementations propose determining the test signal's output period, frequency range, waveform, or amplitude based on the charging communication status of the charging data line or the charging status of the connected device, they do not specify how to systematically perform this determination. Without a pre-defined, intelligent decision-making mechanism, the test signal's output parameters may not optimally adapt to the real-time charging environment and device status. This could cause the test signal to cause unnecessary interference with normal charging communications, or prevent the efficient and accurate acquisition of the required impedance spectrum data. This could affect the quantification accuracy of the connection quality deviation value and the timeliness and effectiveness of charging temperature control.

[0083] In this regard, the present application further proposes that the above-mentioned step of determining the output time period, frequency range, waveform or amplitude of the test signal according to the charging communication status of the charging data line or the charging status of the connected device includes: determining the output time period, frequency range, waveform or amplitude of the test signal through a preset decision logic or state conversion mechanism according to the charging communication status of the charging data line or the charging status of the connected device.

[0084] Specifically, the "preset decision logic or state transition mechanism" refers to a set of predefined rules or a state machine model that intelligently selects or adjusts various test signal parameters based on the input charging communication state or connected device state. The "decision logic" can be a series of conditional statements or a lookup table. For example, when the charging data line is detected to be in high-speed data transmission, the decision logic selects a test signal in a non-communication frequency band and limits its output amplitude to a low level to avoid interfering with data transmission. When the connected device is detected to be in low-battery fast charging mode, the decision logic may select a wider frequency range and a higher test signal amplitude to ensure sufficiently accurate impedance spectrum data can be obtained during fast charging. The "state transition mechanism" can be a finite state machine that automatically switches to a preset test signal parameter configuration based on the different stages of the charging process (e.g., handshake phase, constant current charging phase, constant voltage charging phase, trickle charging phase) or the specific state of the connected device (e.g., high battery temperature, device entering sleep mode). The "charging communication state of the charging data line" can include, but is not limited to, USB Power Delivery (USB PD) protocol negotiation state, data transmission state, and charging protocol identification state. The "charging status of the connected device" can include information such as the device's battery charge percentage, current charging mode (e.g., fast charging, slow charging), internal device temperature, and real-time charging current or voltage. By comprehensively considering this information, the test signal output can be ensured to meet the requirements of impedance spectroscopy measurement while minimizing any impact on normal charging functionality.

[0085] Through the above technical solution, this application can ensure that the output of the test signal is highly coordinated with the dynamic changes of the charging process, significantly reducing the potential interference of the test signal on charging communication and improving the accuracy and efficiency of impedance spectrum data acquisition. As a result, the quantification of the connection quality deviation value will be more accurate, allowing the charging temperature control method of the mobile phone charger to respond to connection degradation problems more promptly and effectively, thereby improving the safety, stability and user experience of the charging process.

[0086] See also Figure 8 , the specific embodiment of the present application also discloses a mobile phone charger charging temperature control system, which is used to realize mobile phone charger charging temperature control, such as Figure 8 As shown, the system 80 includes: A data acquisition module 81 is configured to periodically output a test signal to a connected charging data line at each charging output port of the mobile phone charger, and to collect voltage response data and current response data of the port in real time; an impedance spectrum calculation module 82, configured to calculate the impedance spectrum of the port based on the collected voltage response data and the current response data; a deviation identification and quantification module 83 for analyzing the impedance spectrum, identifying abnormal deviations in the impedance spectrum, and quantifying the abnormal deviations into connection quality deviation values, wherein the connection quality deviation values ​​are related to the charging temperature; The adjustment module 84 is configured to activate an adaptive compensation mechanism to adjust the power output of the port when the connection quality deviation value exceeds a preset threshold.

[0087] Through modular design, the system achieves precise control of the charging temperature of mobile phone chargers, effectively preventing and resolving local overheating caused by connection quality issues, and improving charging safety and system stability.

[0088] The various modules in the system work together to complete the function of charging temperature control.

[0089] First, regarding the data acquisition module 81, the above embodiment has described the specific method of periodically outputting a test signal to the connected charging data line at each charging output port of the mobile phone charger and collecting the voltage response data and current response data of the port in real time, which will not be repeated here.

[0090] Next, regarding the impedance spectrum calculation module 82, the specific method for calculating the port impedance spectrum based on the collected voltage and current response data has been described in the above embodiment and will not be repeated here. Furthermore, regarding the deviation identification and quantification module 83, the specific method for analyzing the impedance spectrum, identifying abnormal deviations in the impedance spectrum, and quantifying the abnormal deviations into connection quality deviation values, and the correlation of the connection quality deviation values ​​with the charging temperature has been described in the above embodiment and will not be repeated here.

[0091] Finally, regarding the adjustment module 84, the above embodiment has described the specific method of activating the adaptive compensation mechanism and adjusting the power output of the port when the connection quality deviation value exceeds the preset threshold, which will not be repeated here.

[0092] As a result, the system of this application achieves a shift from passive response to active prevention. It no longer relies solely on remedial measures after the temperature rises, but instead monitors the electrical characteristics of the connection quality in real time to predict and quantify potential overheating risks in advance, and makes refined adjustments to the power output accordingly. This system mechanism can effectively avoid the formation of local hot spots and reduce the workload of the power conversion components inside the charger, thereby significantly improving the safety and reliability of the charger and extending its service life. This is a significant advantage that existing technologies do not have.

[0093] See also Figure 9 The present application also discloses a charger 6 comprising a memory 61, a processor 62, and a network interface 63. The memory 61 stores computer-readable instructions, and the processor 62 is configured to implement the aforementioned method when executing the computer-readable instructions. The network interface 63 may comprise a wireless network interface or a wired network interface, and is typically used to establish a communication connection between the charger 6 and other electronic devices.

[0094] The charger 6, through the collaborative operation of its internal memory 61 and processor 62, is capable of effectively executing the aforementioned charging temperature control method for a mobile phone charger. Specifically, by reading and executing computer-readable instructions preset in memory 61, the processor 62 implements a series of key steps, including periodically outputting a test signal to the connected charging data line at the charging output port, collecting the port's voltage and current response data in real time, calculating the port's impedance spectrum based on the collected voltage and current response data, analyzing the impedance spectrum to identify abnormal deviations in the impedance spectrum and quantifying them as a connection quality deviation value, and activating an adaptive compensation mechanism to adjust the port's power output when the connection quality deviation value exceeds a preset threshold. As a result, the charger can proactively and intelligently monitor and manage charging connection quality, effectively preventing and resolving local overheating issues caused by connection degradation, thereby improving charging safety and device lifespan.

[0095] The specific steps and principles of the charging temperature control method for a mobile phone charger have been described in detail in the above embodiment and will not be repeated here. It should be emphasized that the charger disclosed in this application is a hardware entity, and its core lies in carrying and executing the above method through a specific hardware configuration.

[0096] Specifically, the charger can be a standalone power adapter or a charging module integrated into other electronic devices (e.g., a multi-function charging station, a smart power strip, etc.). The memory can include, but is not limited to, read-only memory (ROM), random access memory (RAM), flash memory, a solid-state drive (SSD), or any other non-transitory computer-readable storage medium. These storage media are used to store an operating system, application programs, and computer-readable instructions for implementing the aforementioned charging temperature control method. For example, the instructions can be pre-burned in the charger's internal flash memory in the form of firmware, or loaded into RAM via a software update.

[0097] The processor can be a general-purpose processor (such as a microcontroller (MCU) or digital signal processor (DSP), or an application-specific integrated circuit (ASIC) or field-programmable gate array (FPGA). By executing instructions stored in memory, the processor controls hardware modules within the charger, including the signal generator module, data acquisition circuit, and analog-to-digital converter (ADC), to output test signals, collect voltage and current data, calculate impedance spectra, and adjust power output. For example, the processor can be configured to periodically trigger the signal generator module to output test signals and simultaneously read the voltage and current response data converted by the ADC. The processor then executes a pre-set algorithm to perform a Fourier transform on this data to calculate an impedance spectrum. This impedance spectrum is then compared with a preset reference impedance spectrum stored in memory to identify abnormal deviations and calculate a connection quality deviation value. When this value reaches a preset threshold, the processor sends a command to the power output control module to adjust the output voltage or current or perform pulse width modulation to achieve adaptive compensation of power output.

[0098] As a preferred embodiment, the processor can be integrated with a dedicated hardware acceleration unit for efficiently executing computationally intensive tasks such as Fourier transforms or impedance spectroscopy, thereby ensuring real-time performance and responsiveness. Furthermore, the memory and processor can be configured in a low-power mode to reduce energy consumption when the charger is not charging or under low load. For example, when the charger is in standby mode, the processor can enter sleep mode, activating test signal output and data acquisition only upon specific events (such as a new device connection or a scheduled wakeup).

[0099] The charger disclosed in this application demonstrates significant technological progress and core innovation in solving the problem of local overheating of chargers in the prior art.

[0100] The charger of the present application realizes the transition from passive response to active prevention by integrating memory and processor and enabling it to execute the above-mentioned charging temperature control method. The charger no longer relies solely on remedial measures after the temperature rises. Instead, the processor executes the instructions in the memory, periodically outputs test signals to the charging data line, and collects the voltage response data and current response data of the port in real time, thereby directly and accurately obtaining the impedance spectrum of the charging output port. The impedance spectrum can sensitively reflect the changes in the microscopic electrical characteristics of the connection loop, such as the increase in contact resistance or damage inside the cable, which are the direct causes of local Joule heating. This analysis method based on impedance spectrum enables the charger to identify abnormal deviations in the early stage of connection quality problems, that is, before local heat accumulates significantly.

[0101] Therefore, the charger of the present application can effectively avoid the formation of local hot spots and reduce the workload of the power conversion elements inside the charger, thereby significantly improving the safety and reliability of the charger and extending its service life. This is a significant advantage that the existing technology does not have.

[0102] The specific implementation of the present application further discloses a computer program product, which includes a computer program, and the computer program is used to implement the steps of the charging temperature control method of the mobile phone charger when executed by a computer.

[0103] By storing the aforementioned charging temperature control method as executable instructions, this computer program product enables mobile phone chargers to flexibly and efficiently monitor the quality of the charging port connection in real time and adaptively adjust power output. This effectively addresses the existing challenge of localized overheating caused by poor connection quality, improves charging safety and component lifespan, and facilitates charger upgrades and maintenance.

[0104] Specifically, the computer program product can be stored in a non-volatile storage medium, such as a read-only memory (ROM), random access memory (RAM), flash memory, a hard disk, or a solid-state drive. When the computer program is executed by a processor within a mobile phone charger, the processor can drive the charger hardware to execute each step of the charging temperature control method according to a preset logical sequence and algorithm.

[0105] For example, the computer program may include an instruction set for controlling a signal generator to output a test signal, an instruction set for processing voltage and current response data collected by an analog-to-digital converter (ADC), and an instruction set for executing a fast Fourier transform (FFT) or swept frequency measurement algorithm to calculate an impedance spectrum. Furthermore, the computer program may include a logic judgment module for analyzing the impedance spectrum, identifying abnormal deviations, and quantifying the value of connection quality deviations, as well as a control module that triggers an adaptive compensation mechanism and adjusts power output parameters when the deviation value exceeds a preset threshold.

[0106] The above embodiments have recorded the following contents: periodically outputting a test signal to the connected charging data line, collecting the voltage response data and current response data of the port in real time, calculating the impedance spectrum of the port based on the collected voltage response data and current response data, analyzing the impedance spectrum to identify abnormal deviations and quantifying them into connection quality deviation values, and starting the adaptive compensation mechanism to adjust the power output of the port when the connection quality deviation value exceeds a preset threshold. These contents will not be repeated here. It should be emphasized that the steps of these methods are all implemented by executing the computer program on the processor. The computer program can be designed as a modular structure, for example, it can include a data acquisition module, an impedance spectrum calculation module, a deviation identification and quantification module, and an adjustment module, etc. Each module is responsible for implementing one or more specific functions in the method. This modular design facilitates the development, debugging, and subsequent upgrade and maintenance of the program.

[0107] As a preferred embodiment, the computer program product can be pre-installed in the mobile phone charger's firmware or remotely updated and upgraded via a network connection. For example, the charger manufacturer can update the computer program by releasing a new firmware version to optimize the charging temperature control algorithm, adapt to new charging cables or devices, or fix potential software bugs. This flexibility is unavailable in purely hardware-based solutions.

[0108] The core innovation of this application lies in providing the above-mentioned advanced charging temperature control method in the form of a computer program product. This means that the core logic and algorithms of the method are no longer statically fixed, but exist in the form of executable instructions. By executing the computer program through the processor, the charger can achieve active, real-time monitoring of the quality of the charging port connection and intelligently identify and quantify the degree of connection degradation based on the results of impedance spectrum analysis. When a potential overheating risk is detected, the computer program can drive the charger hardware to adaptively adjust the power output, thereby performing preventive intervention before the problem becomes serious.

[0109] As a result, the computer program product of this application enables the charger to continuously optimize its thermal management capabilities and adapt to new technical challenges through software updates, without the need for frequent hardware replacement. This software-defined control solution not only significantly improves the safety, reliability, and service life of the charger, but also provides unprecedented convenience for the iteration and upgrade of charger functions, a significant advantage not available in existing technologies.

[0110] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for controlling charging temperature of a mobile phone charger, characterized in that: include: At each charging output port of the mobile phone charger, a test signal is periodically output to the connected charging data line, and voltage response data and current response data of the port are collected in real time; Calculating the impedance spectrum of the port according to the collected voltage response data and the current response data; analyzing the impedance spectrum, identifying abnormal deviations in the impedance spectrum, and quantifying the abnormal deviations into connection quality deviation values, wherein the connection quality deviation values ​​are related to the charging temperature; When the connection quality deviation value exceeds a preset threshold, an adaptive compensation mechanism is started to adjust the power output of the port.

2. A mobile phone charger charging temperature control method according to claim 1, characterized in that: The step of adjusting the power output of the port includes: Adjust the output voltage or output current of the port, or perform pulse width modulation.

3. A method for controlling charging temperature of a mobile phone charger according to claim 2, characterized in that: The step of adjusting the output voltage or output current of the port, or performing pulse width modulation, further includes: Determining a connection degradation level according to the connection quality deviation value, the connection degradation level including a first degradation and a second degradation, wherein the second degradation level is higher than the first degradation level; When the connection degradation level is the first degradation, continuously adjusting the output voltage or the output current of the port, or performing pulse width modulation; When the connection degradation level is the second degradation level, the charger is switched to a limited power output mode or a non-power output compensation mode according to the overall power output state of the charger or the temperature of a power conversion element.

4. A method for controlling charging temperature of a mobile phone charger according to claim 1, characterized in that: The step of analyzing the impedance spectrum, identifying abnormal deviations in the impedance spectrum, and quantifying the abnormal deviations into connection quality deviation values ​​comprises: extracting electrical characteristics of the impedance spectrum within a plurality of preset frequency ranges; identifying the type of physical degradation to which the abnormal deviation in the impedance spectrum belongs based on a degree of matching between the electrical characteristics and preset characteristic patterns corresponding to different physical degradation mechanisms; The abnormal deviation is determined according to the physical degradation type, and the abnormal deviation is quantified into a connection quality deviation value.

5. A method for controlling charging temperature of a mobile phone charger according to claim 4, characterized in that: The step of extracting electrical characteristics of the impedance spectrum within a plurality of preset frequency ranges includes: Acquiring temperature data inside the charger near the port; determining temperature-related reference electrical characteristics within the plurality of preset frequency ranges based on the temperature data; extracting electrical characteristics of the impedance spectrum within a plurality of preset frequency ranges; Based on the extracted electrical feature and the temperature-dependent reference electrical characteristic, a difference between the electrical feature and the temperature-dependent reference electrical characteristic is calculated to obtain an electrical feature reflecting the physical degradation.

6. A method for controlling charging temperature of a mobile phone charger according to claim 4, characterized in that: The step of identifying the physical degradation type to which the abnormal deviation in the impedance spectrum belongs based on the degree of matching between the electrical characteristics and preset characteristic patterns corresponding to different physical degradation mechanisms includes: Identifying a change trend and amplitude distribution of the electrical characteristics within a plurality of preset frequency ranges; Comparing the change trend and amplitude distribution with a preset characteristic pattern reflecting a single physical degradation mechanism to determine the degree of match between the electrical characteristics and the characteristic pattern; If the degree of matching indicates that the electrical characteristic cannot be matched to any single predetermined characteristic pattern, analyzing independent factors of multiple single physical degradation mechanisms contained in the electrical characteristic; The physical degradation type to which the abnormal deviation belongs is determined according to the independent factors.

7. A method for controlling charging temperature of a mobile phone charger according to claim 6, characterized in that: The step of analyzing the independent factors of multiple single physical degradation mechanisms included in the electrical characteristics includes: performing component decomposition on the electrical characteristics; Make the decomposed components reflect the characteristic patterns of a single physical degradation mechanism; An independent factor of each single physical degradation mechanism is determined based on the components of the characteristic mode reflecting the single physical degradation mechanism.

8. A method for controlling charging temperature of a mobile phone charger according to claim 4, characterized in that: The step of analyzing the impedance spectrum, identifying abnormal deviations in the impedance spectrum, and quantifying the abnormal deviations into connection quality deviation values ​​comprises: According to the physical degradation type, a corresponding parameter is selected from a preset quantization parameter set corresponding to each physical degradation type, and based on the original electrical characteristics of the abnormal deviation, the connection quality deviation value is calculated using the selected quantization parameter.

9. A charger, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor is configured to implement the steps of the method according to any one of claims 1 to 8 when executing the computer-readable instructions.

10. A computer program product, characterized in that The computer program product comprises a computer program for implementing the steps of the method according to any one of claims 1 to 8 when the computer program is executed by a computer.

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