A mobile phone charger charging detection method and system

Abstract

The application relates to the technical field of mobile phone charging and discloses a mobile phone charger charging detection method and system, which can obtain electrical characteristic parameters of an electric energy transmission path at multiple frequencies by injecting an alternating test signal with a preset frequency range into the electric energy transmission path and measuring voltage response and current response of the alternating test signal at key points. By comparing the real-time measured electrical characteristic parameters with reference electrical characteristic parameters under a preset state, the application can accurately identify the deviation of the electric energy transmission path and further judge the electrical characteristic abnormalities of each link. On this basis, the application can quantize the influence proportion of each link on the electric energy supplement efficiency reduction according to the electrical characteristic abnormality degree, so that fine identification of a fault source is realized. According to the quantized influence proportion, the application can intelligently adjust an electric energy supplement strategy and optimize a charging process.

Description

Technical Field

[0001] This invention relates to the field of mobile phone charging technology, and in particular to a method and system for detecting charging of a mobile phone charger. Background Technology

[0002] In daily life, charging a smartphone is a frequent and important operation. To ensure efficient and safe charging, the phone's internal charging management system is meticulously designed. It communicates with the charger, understands its capabilities, and continuously monitors key information such as battery voltage, charge level, internal resistance, and temperature. Based on this real-time data, the system intelligently adjusts the charging current and voltage to optimize the entire charging process. For example, when the battery is low, the system uses a larger current for fast charging; as the battery gradually fills, the current smoothly decreases to protect the battery and prevent overheating. Under ideal conditions, such as using a new, compatible charger and cable, and with the battery in good condition, this charging process is usually completed smoothly and efficiently.

[0003] However, real-world usage environments are far more complex than these ideal conditions. A series of seemingly minor but interconnected factors pose significant challenges to existing charging detection systems. Current mobile phone charging detection and control methods primarily focus on monitoring the battery's internal states, such as voltage, current, and temperature, and negotiating with the charger to adjust charging parameters. However, in practical use, their diagnostic capabilities are severely inadequate when the charging system faces multiple, non-obvious fault sources. Specifically, when battery aging leads to increased internal resistance, charger wear increases resistance, external power supply exhibits slight fluctuations, and the charger itself has minor, non-fatal faults (such as increased output ripple or delayed response), these factors work together to significantly reduce charging efficiency, drastically extend charging time, and even when the charging icon shows normal operation, the battery level barely increases or decreases slowly. Existing systems can detect deviations in charging current or voltage from expected values, or abnormal increases in battery temperature, but they cannot effectively distinguish whether these anomalies are caused by excessively high battery internal resistance, charger wear, unstable external power input, or internal charger faults. This lack of refined fault source identification capabilities leads the system to adopt conservative, one-size-fits-all strategies, such as reducing the charging current or frequently restarting the charging process, thus sacrificing charging efficiency and user experience, and failing to provide targeted fault diagnosis information or optimization suggestions.

[0004] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0005] This invention provides a charging detection method and system for mobile phone chargers, aiming to solve the problem that existing mobile phone charging detection systems have insufficient diagnostic capabilities when faced with multiple, non-obvious fault sources, and cannot accurately identify fault sources, resulting in decreased charging efficiency and poor user experience.

[0006] The technical solution of this application is as follows:

[0007] Firstly, this application discloses a method for detecting charging of a mobile phone charger, including:

[0008] Inject an AC test signal with a preset frequency range into the power transmission path;

[0009] Measure the voltage and current responses of key points along the power transmission path to AC test signals;

[0010] Based on the voltage and current responses, calculate the electrical characteristic parameters of the power transmission path at multiple frequencies;

[0011] Store the reference electrical characteristic parameters of each link in the power transmission path under preset conditions;

[0012] By comparing electrical characteristic parameters with reference electrical characteristic parameters, deviations in the power transmission path can be identified.

[0013] Based on the deviation, determine the abnormal electrical characteristics of each link in the power transmission path;

[0014] Based on the degree of electrical characteristic anomaly, the proportion of the impact of each link on the decrease in power replenishment efficiency is quantified.

[0015] Adjust the power replenishment strategy according to the proportion of impact;

[0016] Provide users with diagnostic information and operational suggestions for the power transmission path.

[0017] This technical solution enables the calculation of electrical characteristic parameters of the power transmission path by injecting AC test signals and measuring the response. These parameters are then compared with benchmark parameters to identify deviations in the power transmission path and abnormalities in the electrical characteristics of each stage. This allows for the quantification of the impact of each stage on the reduction in power replenishment efficiency. Based on this, the power replenishment strategy can be adjusted, ultimately providing users with diagnostic information and operational suggestions. This effectively solves the problem of existing technologies being unable to accurately identify multiple fault sources, thereby improving charging efficiency and user experience.

[0018] Furthermore, in the above method, the impact ratio of each link on the decrease in power replenishment efficiency is quantified according to the degree of electrical characteristic anomaly, including:

[0019] Based on the equivalent circuit model of the power transmission path, the electrical characteristics of the power transmission path are simulated.

[0020] Adjust the parameters corresponding to each component in the equivalent circuit model according to the deviation;

[0021] Based on the equivalent circuit model, identify the independent contribution of each component to the decrease in power replenishment efficiency; and

[0022] Based on independent contributions, the proportion of each link in the decline of power replenishment efficiency is quantified.

[0023] This technical solution enables the simulation of the power transmission path using an equivalent circuit model, and the model parameters can be adjusted according to deviations. This allows for the identification of the independent contribution of each link to the decrease in power replenishment efficiency, achieving more accurate quantification and further improving the accuracy of fault diagnosis.

[0024] Based on the above, this application also proposes that the reference electrical characteristic parameters of each link in the stored power transmission path under preset conditions include:

[0025] Assess the health of the power transmission path;

[0026] Determine the difference between the electrical characteristic parameters of the power transmission path and the reference electrical characteristic parameters;

[0027] When the difference is within the preset allowable range, the reference electrical characteristic parameters are adjusted according to the electrical characteristic parameters of the power transmission path.

[0028] Record the update information of the reference electrical characteristic parameters.

[0029] This technical solution enables dynamic assessment of the health status of the power transmission path. Based on the differences between the actual electrical characteristic parameters and the reference parameters, the reference parameters can be adjusted and updated within a preset allowable range, thereby making the reference parameters closer to actual usage and improving the accuracy and adaptability of the detection.

[0030] Furthermore, based on the proportion of impact, the power replenishment strategy is adjusted, including:

[0031] Identify the combination of power replenishment strategies corresponding to multiple abnormal links in the power transmission path;

[0032] Based on preset priority rules, determine the dominant strategy in the strategy combination;

[0033] Within the allowable output range of the power replenishment equipment, adjust the power replenishment current, power replenishment voltage, and power replenishment mode according to the dominant strategy and the proportion of influence.

[0034] Output power replenishment strategy.

[0035] This technical solution enables the identification of multiple abnormal links and strategy combinations, and determines the dominant strategy based on priority rules. Then, based on the dominant strategy and its influence ratio, the power replenishment current, voltage, and mode are adjusted within the allowable range, achieving a more intelligent and refined power replenishment strategy adjustment and effectively optimizing the charging process.

[0036] In some preferred embodiments, diagnostic information and operational recommendations for the power transmission path are provided to the user, including:

[0037] The diagnostic information and operational recommendations are sorted according to their impact ratio;

[0038] On the handheld terminal's display interface, diagnostic information and operational suggestions corresponding to the abnormal links with the highest impact ratio are displayed first.

[0039] The system links and displays action suggestions with diagnostic information, and sends a link to each action suggestion to guide the user to perform the action.

[0040] After the user performs the operation suggestion, the phone charger charging test is performed again, and the diagnostic information and operation suggestions are updated based on the latest test results;

[0041] When displaying diagnostic information, a hierarchical display method is used to present a general diagnostic conclusion. When the user selects to view details, the abnormal electrical characteristics data and analysis results are displayed in an expanded manner.

[0042] This technical solution can sort diagnostic information and operational suggestions according to their impact ratio, prioritize displaying the most impactful abnormalities on handheld terminals, provide related displays and operation links, re-detect and update after the user performs the operation, and display diagnostic conclusions in a hierarchical manner, which greatly improves the efficiency of users obtaining diagnostic information and the convenience of operation, thus enhancing the user experience.

[0043] Preferably, on the display interface of the handheld terminal, diagnostic information and operational suggestions corresponding to the abnormal links with the highest impact ratio are displayed first, including:

[0044] When the handheld terminal is in a call, diagnostic information and operation suggestions will be notified by vibration or low volume prompt tone, and after the call ends, the diagnostic information and operation suggestions will be automatically displayed on the display interface.

[0045] When the handheld terminal is in a game or video playback state, diagnostic information and operation suggestions are overlaid on the display interface in the form of a semi-transparent floating window, and the position and size of the semi-transparent floating window are automatically adjusted.

[0046] When a user is inputting text, diagnostic information and operation suggestions will be displayed in the notification bar. After the user finishes inputting text, the diagnostic information and operation suggestions will be automatically expanded and displayed.

[0047] When the handheld device is in a low battery state, diagnostic information and operation suggestions will be forcibly displayed in the form of a full-screen pop-up window;

[0048] When the handheld device is charging, diagnostic information and operation suggestions are displayed in the form of a charging animation or screensaver, and automatically switch to a detailed display interface when the user unlocks the screen.

[0049] This technical solution enables the use of diverse notification and display methods based on different operating states of the handheld terminal, ensuring that diagnostic information and operational suggestions can be delivered to the user in a timely and effective manner without interfering with normal use, thus significantly improving the intelligence and humanization of the user experience.

[0050] Building upon the above, this application further proposes that, when displaying diagnostic information, a hierarchical display method be used to present a general diagnostic conclusion, and when the user selects to view details, the abnormal electrical characteristic data and analysis results are expanded and displayed, including:

[0051] Identify key abnormalities in general diagnostic conclusions;

[0052] Based on the key abnormal links, extract and highlight the electrical characteristic parameters and their deviations from the key abnormal links from the electrical characteristic anomaly data and analysis results;

[0053] Generate explanatory text, which includes a general diagnostic conclusion based on deviations in the electrical characteristic parameters of key abnormal links.

[0054] This technical solution can extract and highlight electrical characteristic parameters and their deviations related to key abnormalities from massive amounts of data through layered display and identification of key abnormalities, and generate explanatory text, enabling users to quickly understand the diagnostic conclusions and gain a deeper understanding of the causes of abnormalities, thereby improving the readability and comprehensibility of diagnostic information.

[0055] More specifically, in some implementation schemes, after the user performs the suggested operation, the phone charger charging test is re-performed, and the diagnostic information and operation suggestions are updated based on the latest test results, including:

[0056] Start-up operation effectiveness evaluation cycle;

[0057] During the operational effectiveness evaluation period, the electrical characteristic parameters of the power transmission path are continuously monitored.

[0058] Compare the electrical characteristic parameters with the electrical characteristic parameters of the power transmission path before the operation recommendation was implemented;

[0059] Based on the comparison results, determine whether the operation has achieved the preset improvement target;

[0060] When the operation effect does not achieve the preset improvement target, adjust the operation suggestion according to the type of operation suggestion and the deviation of the electrical characteristic parameters;

[0061] Update diagnostic information based on the revised operational recommendations.

[0062] This technical solution enables continuous monitoring of electrical characteristic parameters by initiating an operational effectiveness evaluation cycle and comparing the data with that before implementing operational recommendations. This allows for a determination of whether the operational effectiveness has met the improvement target, and adjustments to the operational recommendations if the target is not met. This achieves closed-loop management and continuous optimization of user operational recommendations, ensuring the effectiveness of diagnosis and recommendations.

[0063] Preferably, during the operational performance evaluation period, the electrical characteristic parameters of the power transmission path are continuously monitored, including:

[0064] Identify the operating status of the handheld terminal;

[0065] When the handheld terminal is in low power mode or not charging, intermittent monitoring is initiated, and the sampling accuracy of the relevant sensors is briefly increased before each monitoring.

[0066] When the handheld terminal is charging, the electrical characteristic parameters of the power transmission path are continuously monitored at a high frequency.

[0067] During the monitoring process, voltage and current data at key points along the power transmission path are collected, and combined with time series analysis, abnormal data points caused by transient or intermittent interference are identified and filtered out.

[0068] Monitor the temperature and state of charge of the energy storage unit, and calibrate the monitored electrical characteristic parameters based on the temperature and state of charge of the energy storage unit; dynamically adjust the monitoring strategy of the electrical characteristic parameters according to the type of operation recommendation.

[0069] This technical solution enables dynamic adjustment of monitoring strategies based on the operating status of handheld terminals, employing appropriate monitoring frequencies and accuracies in different scenarios. It also utilizes time-series analysis to filter out interference, considers the temperature and state of charge of energy storage units for calibration, and dynamically adjusts monitoring strategies according to the type of operational recommendations. This ensures the accuracy and reliability of monitoring data, providing a solid foundation for subsequent diagnosis and recommendations.

[0070] Secondly, this application also discloses a mobile phone charger charging detection system, comprising:

[0071] The input terminal is used to inject an AC test signal with a preset frequency range into the power transmission path; and to measure the voltage and current responses of key points on the power transmission path to the AC test signal.

[0072] The computing end is used to calculate the electrical characteristic parameters of the power transmission path at multiple frequencies based on the voltage and current responses; store the reference electrical characteristic parameters of each link in the power transmission path under preset conditions; and compare the electrical characteristic parameters with the reference electrical characteristic parameters to identify deviations in the power transmission path.

[0073] The adjustment unit is used to determine the abnormal electrical characteristics of each link in the power transmission path based on the deviation; quantify the impact ratio of each link on the decrease in power replenishment efficiency based on the degree of electrical characteristic abnormality; adjust the power replenishment strategy based on the impact ratio; and provide users with diagnostic information and operation suggestions for the power transmission path.

[0074] This technical solution enables comprehensive detection, fault identification, impact quantification, strategy adjustment, and information feedback of the power transmission path through the coordinated operation of the input end, computing end, and adjustment end. It provides a complete charging detection solution for mobile phone chargers and effectively solves the problem of insufficient systematic diagnostic capabilities in existing technologies. Attached Figure Description

[0075] Figure 1 This is a flowchart of a mobile phone charger charging detection method provided in an embodiment of the present invention;

[0076] Figure 2 This is a flowchart of a method for quantifying the decrease in power replenishment efficiency at each stage, provided by an embodiment of the present invention.

[0077] Figure 3 This is a schematic diagram of a mobile phone charger charging detection system provided in an embodiment of the present invention. Detailed Implementation

[0078] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0079] Reference Figure 1 , Figure 1 This is a flowchart of a mobile phone charger charging detection method provided by an embodiment of the present invention, including the following steps:

[0080] S1, inject an AC test signal with a preset frequency range into the power transmission path;

[0081] S2 measures the voltage and current responses of key points along the power transmission path to AC test signals.

[0082] S3. Calculate the electrical characteristic parameters of the power transmission path at multiple frequencies based on the voltage and current responses.

[0083] S4 stores the reference electrical characteristic parameters of each link in the power transmission path under preset conditions;

[0084] S5, compare the electrical characteristic parameters with the reference electrical characteristic parameters to identify deviations in the power transmission path;

[0085] S6. Based on the deviation, determine the abnormal electrical characteristics of each link in the power transmission path;

[0086] S7, based on the degree of electrical characteristic anomaly, quantify the proportion of the impact of each link on the decrease in power replenishment efficiency;

[0087] S8, adjust the power replenishment strategy according to the impact ratio;

[0088] S9 provides users with diagnostic information and operational suggestions for the power transmission path.

[0089] This application aims to achieve refined fault diagnosis and optimization of each link in the power transmission path by introducing a series of innovative steps, such as AC test signal injection, multi-frequency electrical characteristic parameter calculation, benchmark parameter comparison, anomaly quantification and strategy adjustment, thereby effectively improving charging efficiency and user experience.

[0090] The "power transmission path" mentioned in this application refers to the entire power transmission link from the power socket to the charger, which typically includes multiple components such as the charger, the charging port, the phone's internal charging management module, and the battery itself. Each component has specific electrical characteristics, such as resistance, inductance, and capacitance. These electrical characteristic parameters have preset reference values ​​under ideal conditions, but in actual use, due to factors such as aging, wear, and environmental changes, these parameters may deviate, thereby affecting the power transmission efficiency.

[0091] Specifically, the mobile phone charger charging detection method of this application can be implemented as follows:

[0092] First, an AC test signal with a preset frequency range is injected into the power transmission path. This AC test signal can be generated by a dedicated signal generator and injected into the power transmission path through a charger or mobile phone charging port. The preset frequency range can be selected to cover the characteristic frequencies of each link in the power transmission path, in order to more comprehensively evaluate its electrical characteristics. For example, a swept-frequency signal can be injected, with its frequency continuously varying from tens of hertz to several megahertz. As an alternative implementation, multiple fixed-frequency AC test signals can also be injected, such as Hz, 1kHz, 10kHz, kHz, etc., to simplify the complexity of signal injection and measurement equipment.

[0093] Secondly, the voltage and current responses of key points along the power transmission path to AC test signals are measured. These key points can include the charger output, both ends of the charger, the phone charging port, and the battery input. Voltage and current responses can be acquired in real time using high-precision voltmeters and ammeters. For example, voltage and current sensors can be installed at the charger output and the phone charging port, respectively, to obtain voltage and current data at these two key points. Alternatively, an analog-to-digital converter (ADC) integrated into the phone's internal charging management chip can be used to measure the voltage and current responses at key points within the phone.

[0094] Next, based on the voltage and current responses, the electrical characteristic parameters of the power transmission path at multiple frequencies are calculated. These electrical characteristic parameters may include impedance, phase angle, conductance, susceptance, etc. For example, the impedance values ​​at different frequencies can be calculated based on the measured voltage and current responses using Ohm's law and complex impedance calculation methods. As a preferred implementation, Fourier transform can be used to convert the time-domain voltage and current responses into frequency-domain data, thereby more accurately calculating the electrical characteristic parameters at multiple frequencies.

[0095] Then, the reference electrical characteristic parameters of each link in the power transmission path under preset conditions are stored. These reference parameters are obtained through experimental measurement or theoretical calculation when the power transmission path is in a healthy and normal operating state. For example, the impedance, capacitance, inductance, and other parameters of a brand-new charger, a brand-new charger, and a healthy battery can be pre-stored. These reference parameters can be stored in the phone's non-volatile memory or on a cloud server for remote access and updates.

[0096] Subsequently, the electrical characteristic parameters are compared with reference electrical characteristic parameters to identify deviations in the power transmission path. By comparing the real-time calculated electrical characteristic parameters with the stored reference parameters, significant differences can be detected. For example, the percentage deviation between the real-time impedance and the reference impedance at each frequency can be calculated. When the deviation exceeds a preset threshold, a deviation is considered to exist.

[0097] Furthermore, based on the deviation, abnormalities in the electrical characteristics of each link in the power transmission path can be determined. For example, if the charger's impedance is significantly higher than a reference value at a certain frequency, it can be determined that the charger is malfunctioning. This determination can be achieved through a pre-set rule base or a machine learning model. For instance, a classifier can be trained to automatically identify abnormal links based on the deviation patterns of electrical characteristic parameters in different links.

[0098] Therefore, based on the degree of electrical characteristic anomalies, the proportion of each component's impact on the decrease in energy replenishment efficiency can be quantified. For example, if an increase in charger impedance leads to a 10% increase in energy loss, while an increase in battery internal resistance leads to a 5% increase in energy loss, then the charger's impact on efficiency reduction can be quantified as 2 / 3, and the battery's as 1 / 3. This quantification can be achieved by establishing an equivalent circuit model of the energy transmission path and combining it with simulation analysis.

[0099] Next, the power replenishment strategy is adjusted based on the impact ratio. For example, if severe damage to the charger is detected, leading to a significant decrease in charging efficiency, the system can suggest that the user replace the charger, or, before replacement, appropriately increase the charging voltage to compensate for cable losses, thereby maintaining a certain charging efficiency. As one implementation method, the charging current, charging voltage, or charging mode (such as switching from fast charging mode to slow charging mode) can be dynamically adjusted based on the impact ratio.

[0100] Finally, provide users with diagnostic information and operational suggestions regarding the power transmission path. Diagnostic information may include which link is malfunctioning, the specific type and severity of the malfunction, etc. Operational suggestions may include replacing the charger, cleaning the charging port, and inspecting the charger. For example, a message such as "Charger is aging, replacement recommended" could be displayed on the phone screen, along with a link to purchase a new cable.

[0101] The mobile phone charger charging detection method of this application obtains the electrical characteristic parameters of the power transmission path at multiple frequencies by injecting an AC test signal into the power transmission path and measuring its response. By comparing these parameters with preset benchmark parameters, deviations in each link of the power transmission path can be identified, and specific electrical characteristic anomalies can be further determined. More importantly, this application can quantify the proportion of the impact of each abnormal link on the decrease in power replenishment efficiency, and adjust the power replenishment strategy accordingly, as well as provide users with refined diagnostic information and operational suggestions.

[0102] Compared to existing technologies that primarily rely on monitoring battery internal status and negotiating charging protocols, the solution presented in this application offers significant advantages. Existing methods often fail to effectively differentiate fault sources when faced with multiple, non-obvious faults, resorting to a conservative "one-size-fits-all" approach that leads to decreased charging efficiency and a poor user experience. In contrast, this application achieves refined identification and quantification of fault sources by performing multi-frequency, multi-stage electrical characteristic analysis of the entire power transmission path. For example, when charging efficiency declines, this application can clearly identify whether the problem lies with the charger, the charger itself, or the battery, and quantify the degree of their respective impact. This refined diagnostic capability allows the system to adopt more targeted optimization strategies. For instance, if the problem is found to be caused by charger aging, the system can suggest replacing the cable instead of simply reducing the charging current. Furthermore, this application can dynamically adjust the power replenishment strategy based on the degree of anomaly and the proportion of impact, thereby maximizing charging efficiency while ensuring safety. By providing users with clear diagnostic information and actionable suggestions, this application significantly improves the user experience and addresses the pain points of insufficient diagnostic capabilities and the inability to provide targeted solutions in existing technologies.

[0103] In some of the embodiments described above in this application, the influence ratio of each link on the decline in power replenishment efficiency is quantified according to the degree of electrical characteristic anomaly. However, in its implementation, it may be difficult to accurately identify the independent contribution of each link in the power transmission path to the decline in power replenishment efficiency, especially when multiple links are abnormal at the same time. This may lead to an inaccurate judgment of the source of influence, thereby affecting the pertinence and effectiveness of power replenishment strategy adjustment.

[0104] In this regard, refer to Figure 2 , Figure 2 This is a flowchart of a method for quantifying the decrease in power replenishment efficiency at each stage, provided by an embodiment of the present invention. S7 includes:

[0105] S71, Based on the equivalent circuit model of the power transmission path, simulate the electrical characteristics of the power transmission path;

[0106] S72, adjust the parameters corresponding to each component in the equivalent circuit model according to the deviation;

[0107] S73, based on the equivalent circuit model, identify the independent contribution of each component to the decrease in power replenishment efficiency; and based on the independent contribution, quantify the proportion of the impact of each component on the decrease in power replenishment efficiency.

[0108] Specifically, "simulating the electrical characteristics of the power transmission path based on its equivalent circuit model" refers to constructing a mathematical or physical model that reflects the electrical behavior of an actual power transmission path (e.g., the entire link from charger to charger, including the charger's internal circuitry, the charger itself, the phone's charging interface, and the phone's internal power management module). This equivalent circuit model can consist of basic circuit elements such as resistors, capacitors, and inductors, and is used to simulate the impedance, loss, and power transmission efficiency of the power transmission path at different frequencies. Its purpose is to provide a framework for quantitative analysis to gain a deeper understanding of the complex electrical behavior of the power transmission path. In practical applications, this equivalent circuit model can be a lumped parameter model or a distributed parameter model, depending on the required accuracy and computational complexity.

[0109] The phrase "adjusting the parameters corresponding to each stage in the equivalent circuit model according to the deviation" can be understood as mapping the deviation information to the corresponding parameters in the equivalent circuit model after identifying the deviation in the power transmission path. For example, if an abnormal increase in the charger's resistance is detected, the resistance parameter representing the charger is adjusted in the equivalent circuit model. The purpose is to ensure that the equivalent circuit model accurately reflects the actual abnormal state of the current power transmission path, providing accurate input for subsequent independent contribution identification. Specifically, parameter adjustment can be achieved through optimization algorithms, such as the least squares method, to make the simulation results of the model match the actual measured voltage and current responses as closely as possible.

[0110] Furthermore, "identifying the independent contribution of each component to the decrease in power replenishment efficiency based on the equivalent circuit model" refers to using the adjusted equivalent circuit model, through simulation or calculation, to analyze the energy loss or efficiency decrease caused by each component (e.g., charger, cable, interface, power management module, etc.) during power transmission. Identifying independent contributions means being able to distinguish the individual impact of different components on the overall efficiency decrease, avoiding attributing a problem in one component to another. Its purpose is to accurately identify the main causes of efficiency decrease, providing a basis for targeted strategy adjustments. For example, independent contributions can be identified by observing the impact on overall efficiency when abnormal parameters of a component are "disabled" or "restored" one by one in the model.

[0111] Therefore, "quantifying the proportion of the impact of each link on the decrease in power replenishment efficiency based on the independent contribution" means converting the independent contribution of each identified link into its percentage or weight in the total efficiency decrease. The purpose is to intuitively present the severity of the decrease in power replenishment efficiency caused by each abnormal link, facilitating user understanding and system decision-making. For example, if the charger's independent contribution leads to a 60% decrease in total efficiency, while the charging interface's independent contribution leads to a 30% decrease, this can be quantified as 60% and 30%, respectively.

[0112] This application's solution, by introducing an equivalent circuit model of the power transmission path, abstracts the actual physical system into a computable electrical model. When deviations occur in the power transmission path, these deviations are precisely mapped and adjusted to the parameters corresponding to each component in the equivalent circuit model, enabling the model to accurately reflect the current state of the system. Based on this, simulation and analysis using the adjusted equivalent circuit model can effectively isolate and identify the independent contribution of each component to the decrease in power replenishment efficiency. This model-based analysis method overcomes the limitations of traditional methods that may struggle to distinguish multiple anomalies, making the diagnosis of the causes of efficiency degradation more refined and accurate. Finally, based on the identified independent contributions, the influence ratio of each component can be quantified, providing solid data support for subsequent adjustments to power replenishment strategies.

[0113] Through the above technical solution, this application can achieve a more precise and detailed quantification of the proportion of the impact of each link in the power transmission path on the decrease in power replenishment efficiency. Compared with a rough judgment based solely on the degree of abnormality in electrical characteristics, this solution, by constructing an equivalent circuit model and adjusting the parameters, can effectively distinguish and identify the independent contribution of each abnormal link, thereby avoiding diagnostic ambiguity caused by the interaction of multiple abnormalities. Therefore, the obtained quantitative results are more targeted, providing a more accurate basis for subsequent adjustments to power replenishment strategies, and significantly improving the diagnostic accuracy of charging detection and the effectiveness of strategy adjustments.

[0114] In some preferred embodiments, a specific example is given below. Suppose a mobile phone charger charging detection system detects a significant decrease in the charging efficiency of a mobile phone. First, the system injects an AC test signal with a preset frequency range into the power transmission path and measures the voltage and current responses at key points. Based on these responses, the system calculates the electrical characteristic parameters of the power transmission path at multiple frequencies. By comparing these parameters with preset reference electrical characteristic parameters, the system identifies deviations in the power transmission path, such as a higher resistance value in the charger and a slight increase in the contact resistance of the phone's charging interface.

[0115] To accurately quantify the impact of these two abnormal factors on the decrease in charging efficiency, the system performs simulations based on a preset equivalent circuit model of the power transmission path. This model may include resistive, inductive, and capacitive components representing the charger, charging port, and the phone's power management module. Based on the detected deviations, the system adjusts the resistance parameters corresponding to the charger in the equivalent circuit model (e.g., from 0.1 ohms to 0.5 ohms) and the contact resistance parameters corresponding to the charging port (e.g., from 0.05 ohms to 0.15 ohms).

[0116] Subsequently, the system performs simulations using the adjusted equivalent circuit model. By simulating the impact of changes in parameters at different stages on overall power loss, the system can identify the independent contributions of increased charger resistance and increased charging interface contact resistance to the decrease in energy replenishment efficiency. For example, simulation results might show that a charger malfunction leads to a 70% decrease in total efficiency, while a charging interface malfunction leads to a 25% decrease. Based on these independent contributions, the system ultimately quantifies the charger's contribution to the efficiency decrease as 70%, and the charging interface as 25%. These precise quantifications will guide the system to adjust energy replenishment strategies, such as recommending users replace the charger and clean the charging interface, thereby more effectively restoring charging efficiency.

[0117] In some embodiments described above, reference electrical characteristic parameters of each link in the power transmission path under preset states are proposed. However, in practical applications, the electrical characteristic parameters of the power transmission path may fluctuate within a normal range or drift slowly due to usage time, environmental changes, or slight wear. If the reference electrical characteristic parameters remain fixed, these normal, non-abnormal fluctuations may be misjudged as electrical characteristic abnormalities, leading to decreased accuracy of diagnostic results and potentially generating unnecessary alarms or misleading operational suggestions. Therefore, this application further proposes a method for dynamically adjusting the reference electrical characteristic parameters to ensure the real-time performance and accuracy of the reference parameters.

[0118] In this regard, this application further proposes a step for storing the reference electrical characteristic parameters of each link in the above-mentioned power transmission path under a preset state, including:

[0119] Assess the health status of the power transmission path;

[0120] Determine the difference between the electrical characteristic parameters of the power transmission path and the reference electrical characteristic parameters;

[0121] When the difference is within a preset allowable range, the reference electrical characteristic parameters are adjusted according to the electrical characteristic parameters of the power transmission path;

[0122] Record the update information of the reference electrical characteristic parameters.

[0123] Specifically, assessing the health status of a power transmission path involves making a preliminary judgment on its overall operational condition by comprehensively analyzing various factors such as currently monitored electrical characteristic parameters, historical data, usage duration, and environmental conditions. The aim is to distinguish between normal aging and wear and tear, and sudden failures or severe anomalies. For example, machine learning models or preset threshold rules can be used to determine whether the current state falls into the category of "healthy" or "sub-healthy."

[0124] Determining the difference between the electrical characteristic parameters of the power transmission path and the reference electrical characteristic parameters can be understood as comparing the currently calculated electrical characteristic parameters of the power transmission path at multiple frequencies with the currently stored reference electrical characteristic parameters one by one, quantifying the degree of deviation in their values. The purpose is to accurately identify the specific gap between the current state and the ideal reference.

[0125] In practical applications, when the aforementioned differences are within a preset acceptable range, adjusting the reference electrical characteristic parameters based on the electrical characteristic parameters of the power transmission path means that if the difference between the current electrical characteristic parameters and the reference parameters is within an acceptable fluctuation range (e.g., less than a certain percentage threshold), then this difference is considered normal system evolution rather than a fault. In this case, the current electrical characteristic parameters or their weighted average are updated as the new reference electrical characteristic parameters. For example, algorithms such as moving averages and exponential smoothing can be used to incorporate the latest measurement data into the reference parameters, allowing them to gradually adapt to normal system changes. The purpose is to enable the reference parameters to dynamically reflect the actual "health" state of the power transmission path, avoiding misjudgments caused by a fixed reference.

[0126] Furthermore, recording the update information of the reference electrical characteristic parameters refers to storing information such as the adjustment time of each reference parameter, the values ​​before and after the adjustment, and the reason for the adjustment (e.g., normal drift update). The purpose is to provide historical evidence for subsequent system analysis, fault tracing, or performance evaluation, and to ensure the traceability of the reference parameter update process.

[0127] This application's solution effectively addresses the potential misjudgment issues that can arise from traditional fixed reference parameters when facing normal system fluctuations and slow aging by introducing an assessment of the health status of the power transmission path and a dynamic adjustment mechanism for reference electrical characteristic parameters. Specifically, firstly, by assessing the health status of the power transmission path, it's possible to preliminarily determine whether the current system is operating normally, providing context for subsequent difference assessments. Secondly, by judging the difference between the current electrical characteristic parameters and the reference electrical characteristic parameters, the degree of deviation between the two can be quantified. More importantly, when this difference is determined to be within a preset allowable range, the system does not immediately consider it abnormal, but rather adjusts the reference electrical characteristic parameters based on the current electrical characteristic parameters. This mechanism allows the reference parameters to be updated moderately and gradually with normal wear and tear, aging, or environmental changes in the power transmission path, ensuring that the reference parameters always accurately represent the electrical characteristics under the current "healthy" or "normal" state. Finally, by recording the update information of the reference electrical characteristic parameters, the transparency and traceability of the entire adjustment process are guaranteed.

[0128] Through the above technical solution, this application can significantly improve the accuracy and robustness of mobile phone charger charging detection. Since the reference electrical characteristic parameters can dynamically adapt to normal changes in the power transmission path, false alarms or missed alarms caused by fixed reference parameters can be effectively avoided, reducing unnecessary diagnostic information and operational suggestions, thereby improving the user experience. Furthermore, by continuously updating and recording the reference parameters, the system can better understand the long-term behavior patterns of the power transmission path, providing a data foundation for more refined fault prediction and maintenance, and extending the equipment's lifespan.

[0129] In some preferred embodiments, a specific example is given below. Suppose that after a year of use, the microstructure of the internal conductors of a mobile phone charger undergoes slight changes, resulting in a slight increase in its equivalent resistance and inductance parameters. If a fixed reference electrical characteristic parameter is used, this slight increase may be identified as an anomaly by the system, issuing a "charger performance degradation" warning to the user. However, according to the solution of this application, upon detecting such a slight change in electrical characteristic parameters, the system first assesses the health of the power transmission path and determines the difference between the current electrical characteristic parameter and the initial reference electrical characteristic parameter. If the difference is determined to be within a preset allowable range (e.g., resistance increase less than 5%), the system considers this to be normal wear or aging, rather than a fault. At this time, the system will adjust and update the reference electrical characteristic parameter based on the current electrical characteristic parameter, for example, by calculating the average value or trend of the electrical characteristic parameter over a period of time. For example, the new reference resistance value will be set slightly higher than the old reference value. Simultaneously, the update time of the reference parameter, the values ​​before and after the update, and the reason for the update (e.g., "normal aging adaptation adjustment") will be recorded. In this way, the system can avoid misjudging normal system evolution as abnormal, thus providing more accurate diagnostic information and reducing user interference. When larger deviations beyond the new baseline tolerance occur in the future, the system can more accurately identify the true anomalies.

[0130] In some of the embodiments described above in this application, a power replenishment strategy is proposed to be adjusted according to the influence ratio. However, in practical applications, when there are multiple links with abnormal electrical characteristics in the power transmission path, each link may correspond to a different power replenishment strategy. If the strategy is simply adjusted according to the total influence ratio, it may cause conflicts between the strategies or fail to effectively solve the most critical problem, thereby affecting charging efficiency and equipment safety.

[0131] In this regard, this application further proposes the steps for adjusting the power replenishment strategy according to the impact ratio, specifically including:

[0132] Identify the combination of power replenishment strategies among multiple abnormal links on the power transmission path;

[0133] The dominant strategy in the strategy combination is determined according to the preset priority rules.

[0134] Within the allowable output range of the power replenishment device, adjust the power replenishment current, power replenishment voltage, and power replenishment mode according to the dominant strategy and the influence ratio;

[0135] Output the power replenishment strategy.

[0136] Specifically, identifying the power replenishment strategies corresponding to multiple abnormal links in the power transmission path involves combining these strategies. When multiple links in the power transmission path exhibit abnormal electrical characteristics, such as chargers, charging heads, mobile phone charging interfaces, or battery management systems, each abnormal link may correspond to one or more recommended power replenishment strategies. This step aims to collect and integrate the suggested power replenishment strategies for all these abnormal links to form a strategy combination. For example, a charger malfunction might suggest reducing the charging current, while battery overheating might suggest reducing the charging voltage and switching to trickle charging mode.

[0137] The process of determining the dominant strategy in the strategy combination based on preset priority rules can be understood as a predefined decision-making logic used to select one or more of the most important or urgent strategies from multiple conflicting or complementary strategies as the dominant strategy. For example, strategies involving safety issues (such as overheat protection) typically have the highest priority, followed by strategies that have the greatest impact on charging efficiency, and then strategies that extend battery life. Priority rules can be set based on factors such as the severity of the abnormal situation, its impact on device safety, its impact on charging efficiency, and user preferences.

[0138] In practical applications, adjusting the charging current, charging voltage, and charging mode within the allowable output range of the charging device, based on the dominant strategy and the influence ratio, means that the charging device (such as a charger) has inherent output capacity limitations. This step involves finely adjusting the charging current, charging voltage, and charging mode without exceeding these limitations, based on the determined dominant strategy and the influence ratio of each abnormal component on the reduction in charging efficiency. For example, if the dominant strategy is to reduce the charging current to protect the battery, and the influence ratio of a certain component is 30%, a suitable reduction range can be calculated between the minimum and maximum allowable current of the charger, based on the 30% influence ratio. Charging modes can include constant current charging, constant voltage charging, trickle charging, fast charging mode, slow charging mode, etc. Outputting the charging strategy means sending the final charging strategy, after the above adjustments and determination, to the charging device or battery management system for actual execution of the charging parameter adjustments.

[0139] This application's solution effectively addresses the potential for strategy conflicts or improper adjustments in complex, multi-abnormal scenarios by introducing strategy combination identification and priority rules for multiple abnormal links. Specifically, when multiple abnormal links exist in the power transmission path, the degree of abnormality and the proportion of impact on charging efficiency may differ for each link, and their corresponding power replenishment strategies may also vary. By identifying all relevant strategy combinations and applying preset priority rules, the system can intelligently select the most critical or priority-based dominant strategy. Subsequently, based on the proportion of each link's impact on the power replenishment efficiency reduction, the power replenishment current, voltage, and mode are finely adjusted within the allowable output range of the power replenishment device. This mechanism ensures that, under multiple abnormal conditions, an optimized charging strategy can be formulated that effectively solves the primary problem while also addressing other secondary issues, and meets the safety and performance requirements of the equipment. This avoids blind or conflicting adjustments, improving charging safety, efficiency, and battery life.

[0140] Through the above technical solution, this application enables intelligent and refined adjustment of the power replenishment strategy. Compared to basic solutions that adjust based solely on a single impact ratio, this application effectively avoids adjustment failures or suboptimal results caused by strategy conflicts or unclear priorities when facing complex situations with multiple abnormal links in the power transmission path. By introducing strategy combination identification and priority rules, it ensures that when multiple anomalies coexist, the most critical issues are addressed first, and the impact of all anomalies is comprehensively considered, thereby formulating a more targeted and effective power replenishment strategy. This not only significantly improves the safety, stability, and efficiency of the charging process but also better protects the battery, extends device lifespan, and provides users with a more reliable and intelligent charging experience.

[0141] As a specific implementation method, suppose that during a charging test, the system identifies that the mobile phone charger has slight aging, resulting in a slight increase in resistance, which accounts for 20% of the decrease in energy replenishment efficiency. The recommended strategy is to slightly increase the charging voltage to compensate for the voltage drop. At the same time, the charger temperature is too high, which accounts for 40% of the decrease in energy replenishment efficiency. The recommended strategy is to reduce the charging current and switch to slow charging mode to protect the battery.

[0142] In this situation, the system first identifies two strategies: increasing voltage and reducing current / slow charging. According to preset priority rules, excessively high battery temperature is usually given higher priority because it directly affects device safety and battery life. Therefore, the system determines "reducing charging current and switching to slow charging mode" as the dominant strategy.

[0143] Subsequently, within the allowable output range of the power replenishment equipment, the system adjusts the charger's output based on the dominant strategy and the 40% impact of abnormal battery temperature. For example, it might reduce the charging current from 2A to 1.5A and switch the charging mode from fast charging to slow charging. Simultaneously, considering the impact of cable aging, the system may fine-tune the voltage while reducing the current, ensuring that overall adjustments prioritize battery safety. Finally, the system outputs this comprehensively adjusted power replenishment strategy to the charger for execution, thereby optimizing charging efficiency as much as possible while ensuring battery safety.

[0144] In some embodiments described above, this application proposes providing users with diagnostic information and operational suggestions regarding the power transmission path. However, during implementation, if the presentation of this diagnostic information and operational suggestions is not intuitive enough, lacks prioritization, or fails to effectively guide users to take action, users may find it difficult to understand the problem and resolve the issue of decreased charging efficiency in a timely and effective manner. If these problems are not addressed, the user experience will be affected, and the actual effectiveness of charging detection may be significantly reduced. Therefore, this application further proposes an optimized method for providing users with diagnostic information and operational suggestions regarding the power transmission path, aiming to significantly improve users' understanding and resolution efficiency of charging problems through structured, prioritized information display and interactive guidance.

[0145] In this regard, this application further proposes the following steps for providing users with diagnostic information and operational suggestions regarding the power transmission path:

[0146] The diagnostic information and operational suggestions are sorted according to the impact ratio;

[0147] On the display interface of the handheld terminal, the diagnostic information and operation suggestions corresponding to the abnormal links with the greatest impact ratio are displayed first.

[0148] The operation suggestions are displayed in association with the diagnostic information, and a link is sent to each operation suggestion to guide the user to perform the operation;

[0149] After the user performs the operation suggestion, the phone charger charging test is performed again, and the diagnostic information and operation suggestion are updated according to the latest test results;

[0150] When displaying the diagnostic information, a general diagnostic conclusion is presented in a hierarchical display manner. When the user selects to view details, the abnormal electrical characteristics data and analysis results are displayed in an expanded manner.

[0151] Specifically, prioritizing diagnostic information and operational recommendations based on their impact ratio means arranging all detected diagnostic information and corresponding operational recommendations according to the proportion of each link in the aforementioned power transmission path that contributes to the decrease in power replenishment efficiency. The impact ratio can be understood as the degree to which a particular abnormal link contributes to the overall decrease in charging efficiency; the higher the value, the more severe the problem in that link and the greater its impact on charging efficiency. This prioritization ensures that users focus first on the most critical and urgent issues.

[0152] Furthermore, on the handheld terminal's display interface, diagnostic information and operational suggestions corresponding to the most impactful anomalies are prioritized for display. This aims to focus the user's attention on the most pressing issues. For example, if a charger malfunction has the highest impact on charging efficiency, diagnostic information regarding the cable and operational suggestions for replacing it will be prominently displayed on the interface.

[0153] Furthermore, by linking operational suggestions with diagnostic information and providing a link for each suggestion to guide users in performing the action, the system aims to offer a convenient and intuitive way for users to jump directly from the diagnostic information to the interface or instructions for performing the action. For example, for the suggestion to "replace the charger," a link could be provided that leads to an e-commerce platform page for purchasing a new cable, or displays a graphic tutorial on replacing the cable.

[0154] In practical applications, after the user executes the suggested operation, the phone charger charging test is performed again. The diagnostic information and operation suggestions are updated based on the latest test results, aiming to form a closed-loop feedback mechanism. Through this re-test, the system can verify the effectiveness of the user's operation and update the diagnostic results and operation suggestions based on the latest electrical characteristic parameters, ensuring the accuracy and timeliness of the information.

[0155] In displaying diagnostic information, a layered approach is used to present general diagnostic conclusions. When users choose to view details, the system expands to show abnormal electrical characteristics and analysis results. This can be understood as a progressive information disclosure strategy. First, users are shown easily understandable general conclusions, such as "charger is aging, charging efficiency is reduced." When users are interested in specific details, they can choose to view more in-depth abnormal electrical characteristics (such as impedance and capacitance deviations) and professional analysis results, meeting the needs of different users.

[0156] This application's solution effectively addresses the limitations of traditional charging detection methods in information presentation and user interaction by introducing a sorting, priority display, association guidance, feedback updates, and hierarchical display mechanism for diagnostic information and operational suggestions. Specifically, by sorting and prioritizing display based on impact ratio, it ensures users first focus on anomalies that have the greatest impact on charging efficiency, avoiding information overload and decision-making difficulties. Linking operational suggestions with diagnostic information and providing execution links greatly simplifies the user's action path, improving convenience and compliance. Furthermore, re-detection and updates after user actions form an effective closed loop, allowing diagnostic information and operational suggestions to reflect the progress of problem-solving in real time and be adjusted based on actual results, ensuring the dynamism and accuracy of the solution. The hierarchical display caters to the needs of different users, providing both concise and clear general conclusions and allowing professional users to view detailed data, thereby comprehensively improving users' understanding and problem-solving efficiency regarding charging issues.

[0157] Through the above technical solution, this application can significantly improve users' understanding and response efficiency to mobile phone charger charging test results. Users no longer need to deal with cumbersome test data, but can intuitively understand the most critical charging issues and their impact on efficiency, and obtain clear and actionable solutions. This optimization not only improves the user experience, but also accelerates the diagnosis and resolution of charging problems, effectively avoiding persistently low charging efficiency due to poor information transmission or inconvenient operation, thereby ensuring timely adjustment of power replenishment strategies and the long-term healthy operation of charging equipment.

[0158] In some preferred embodiments, a specific example is given below. Suppose the system detects a significant decrease in the charging efficiency of a mobile phone. After calculating and comparing the electrical characteristic parameters, it is found that the internal resistance of the charger is abnormally high, and its influence on the decrease in energy replenishment efficiency accounts for 80%, while the output voltage of the charger fluctuates slightly, with an influence of 15%, and the internal impedance of the charger increases slightly, with an influence of 5%.

[0159] At this point, the system will sort the diagnostic information and operational suggestions according to their impact ratio. On the handheld terminal's display interface, diagnostic information about the charger will be prominently displayed first, such as "Charger is aging, internal resistance is too high, severely affecting charging speed," along with the operational suggestion "It is recommended to replace the charger immediately." This operational suggestion will provide a clickable link, such as redirecting to a page recommending compatible cables on an e-commerce platform.

[0160] When the user clicks the link and replaces the charger with a new one, the system will automatically trigger a retest. If the new test results show that the charging efficiency has returned to normal and the charger's electrical characteristics have returned to the baseline range, the system will update the diagnostic information and display "Charger repaired, charging efficiency returned to normal".

[0161] When displaying diagnostic information, the initial interface may only show "Charging efficiency has decreased, the main problem lies with the charger." Only when the user clicks "View Details" will it expand to display detailed electrical characteristic anomaly data, such as the percentage deviation of the specific measured value of cable impedance from the reference value, and the corresponding analysis charts. This hierarchical display method allows users to choose the depth of information they need to view.

[0162] In some of the embodiments described above in this application, it is proposed to prioritize displaying diagnostic information and operation suggestions corresponding to the abnormal links with the highest impact ratio on the display interface of the handheld terminal. However, in its implementation, if it is simply prioritized, it may cause interference when the user is performing important operations (such as making calls, playing games, or text input), or fail to attract the user's attention in certain specific states (such as low battery or charging), thereby affecting the user experience and the effectiveness of information transmission.

[0163] In response, this application further proposes prioritizing the display of diagnostic information and operational suggestions corresponding to the abnormal process with the highest impact ratio on the handheld terminal's display interface, including:

[0164] When the handheld terminal is in a call, the diagnostic information and operation suggestions are notified by vibration or low-volume prompt tone, and after the call ends, the diagnostic information and operation suggestions are automatically presented on the display interface.

[0165] When the handheld terminal is in a game or video playback state, the diagnostic information and the operation suggestions are superimposed on the display interface in the form of a semi-transparent floating window, and the position and size of the semi-transparent floating window are automatically adjusted.

[0166] When a user is performing text input, the diagnostic information and operation suggestions will be displayed in the form of a notification bar message, and the diagnostic information and operation suggestions will be automatically expanded and displayed after the user finishes text input;

[0167] When the handheld terminal is in a low battery state, the diagnostic information and operation suggestions will be forcibly displayed in the form of a full-screen pop-up window;

[0168] When the handheld terminal is charging, the diagnostic information and operation suggestions are displayed in the form of a charging animation or screensaver, and automatically switch to a detailed display interface when the user unlocks the screen.

[0169] Specifically, when the handheld terminal is in a call, to avoid interfering with the user's conversation, diagnostic information and operational suggestions will not be displayed visually on the screen. Instead, they will be communicated via vibration or a low-volume alert. Vibration can be understood as tactile feedback, used to attract the user's attention without interrupting their auditory experience; the low-volume alert provides an auditory reminder without affecting the call content. After the call ends, the system will automatically display detailed diagnostic information and operational suggestions on the screen, ensuring the user can view them at their convenience.

[0170] When the handheld device is playing a game or video, to avoid completely interrupting the user's entertainment experience, diagnostic information and operation suggestions are overlaid on the display screen as a semi-transparent floating window. This semi-transparent floating window means its background has a certain degree of transparency, allowing the user to see the game or video content below while viewing the diagnostic information. Furthermore, the position and size of this semi-transparent floating window are automatically adjusted to minimize obstruction of core content areas, thus providing necessary information while minimizing the impact on the user experience.

[0171] While the user is inputting text, diagnostic information and operational suggestions will be displayed as notification messages in the notification bar. These notifications are a non-intrusive method that does not forcibly interrupt the user's input process. After the user finishes inputting text, the system will automatically expand to display detailed diagnostic information and operational suggestions, ensuring that the user can promptly obtain and process relevant information after completing the current task.

[0172] When a handheld device is low on battery, diagnostic information and operational suggestions will be forcibly displayed as a full-screen pop-up, as charging efficiency is crucial to user experience. This full-screen pop-up is a strong reminder designed to ensure users are immediately aware of and can take appropriate action when battery life is critical, thus preventing device shutdown due to charging issues.

[0173] When the handheld device is charging, diagnostic information and operational suggestions are displayed as a charging animation or screensaver. This charging animation or screensaver is a gentler display method, integrating the diagnostic information into the everyday charging interface for a more natural presentation. When the user unlocks the screen, the system automatically switches to a detailed display interface, allowing the user to gain a deeper understanding of the diagnostic results and operational suggestions.

[0174] This application's solution effectively addresses the problem of traditional solutions displaying diagnostic information and operational suggestions in a single way, potentially interfering with users or failing to effectively convey information, by identifying multiple operating states of the handheld terminal and employing customized information presentation methods for each state. Specifically, when the user performs important operations, a non-intrusive or low-interference prompt method is used to avoid negative impacts on the user experience; while in scenarios requiring high user attention (such as low battery), a forced display method is used to ensure timely information delivery. Therefore, this application's solution can intelligently adjust the information presentation strategy according to the actual usage scenario, thereby improving the user's efficiency in receiving and complying with diagnostic information and operational suggestions.

[0175] Through the above technical solutions, the presentation of diagnostic information and operational suggestions can be highly matched with the current operating status of the handheld terminal, significantly improving the smoothness of the user experience and the effective delivery of information. Users can receive crucial charging detection information in the most appropriate way in different scenarios, avoiding unnecessary interference while ensuring mandatory information delivery in emergency situations. This not only increases users' attention to the charger's charging detection results but also encourages them to adopt operational suggestions more promptly, thereby effectively improving power replenishment efficiency and extending device lifespan.

[0176] In some preferred embodiments, it is assumed that the handheld terminal is conducting an important video conference. At this time, if the charging detection system detects a slight anomaly in the charger and calculates that its impact on the reduced power replenishment efficiency is significant, according to this embodiment, the system will not immediately display a full-screen warning. Instead, it will notify the user via the handheld terminal's vibration function or by emitting a low-volume alert tone. After the meeting ends, when the user unlocks the screen, detailed diagnostic information (e.g., "Charger impedance is too high, replacement recommended") and operational suggestions (e.g., "Click here to purchase an original charger") will automatically appear on the display interface. This ensures that the user can promptly understand the charging problem without interrupting the meeting and can address it conveniently at their convenience.

[0177] For example, when the handheld device's battery is down to 5%, the system detects that the charger's output voltage is unstable, affecting the charging efficiency by up to 30%. At this point, the system will immediately display diagnostic information (e.g., "Charger output voltage is abnormal, which may damage the battery") and operational suggestions (e.g., "Please replace the charger immediately and avoid continued use") in a full-screen pop-up window. This forced display ensures that users can notice and take action immediately when the battery is critical and there is a risk of device damage, thereby avoiding potential device damage and further reduction in charging efficiency.

[0178] Specifically, in the above-described implementation of providing users with diagnostic information and operational suggestions regarding the power transmission path, when displaying the diagnostic information, a general diagnostic conclusion is presented in a hierarchical display manner. When the user selects to view details, the abnormal electrical characteristic data and analysis results are expanded and displayed, which specifically includes the following steps:

[0179] Identify the key abnormalities in the general diagnostic conclusions;

[0180] Based on the key abnormal links, extract and highlight the electrical characteristic parameters and their deviations from the key abnormal links from the electrical characteristic abnormal data and the analysis results;

[0181] Generate explanatory text, which includes the general diagnostic conclusion that the deviation of the electrical characteristic parameters of the key abnormal link leads to the deviation.

[0182] The identification of key anomalies in the general diagnostic conclusions refers to the system analyzing these conclusions to determine the main components or connection points that cause decreased power replenishment efficiency or pose potential risks. For example, if the general diagnostic conclusion indicates "charger aging," then the "charger" is identified as the key anomaly. This step aims to focus complex diagnostic results on the most critical issues, facilitating user understanding and subsequent operations.

[0183] Furthermore, based on the key anomaly, the system extracts and highlights the electrical characteristic parameters and their deviations related to the key anomaly from the electrical characteristic anomaly data and the analysis results. This means that when a user selects to view details, the system will, based on the identified key anomaly, filter data directly related to the key anomaly from the detailed electrical characteristic anomaly data (such as resistance, capacitance, and inductance values) and analysis results stored in the background, and display it in a prominent manner (e.g., highlighting, bolding, charts, etc.). For example, for the key anomaly of "charger aging," the system can highlight the significant increase in resistance value compared to the baseline value, and analyze the impact of this increase on voltage drop. The purpose is to provide users with intuitive and quantitative anomaly data support, enhancing the credibility of the diagnostic conclusions.

[0184] Furthermore, generating explanatory text, which includes information on how deviations in the electrical characteristic parameters of the key abnormal link lead to the general diagnostic conclusion, means that the system automatically generates an easy-to-understand textual explanation based on the extracted deviations in the electrical characteristic parameters of the key abnormal link. This text clearly explains how the parameter deviation leads to the general diagnostic conclusion. For example, for the example of "charger aging," the explanatory text could explain that "the charger's resistance value is too high, causing an increased voltage drop during charging, thereby reducing charging efficiency and potentially causing cable overheating." This step aims to help users understand the principles behind the technical details, rather than simply presenting data, thereby better guiding users to take operational recommendations.

[0185] This application's solution presents complex diagnostic information in a layered manner. It first presents a general conclusion, preventing users from being overwhelmed by large amounts of technical data and improving readability. When a user is interested in the general conclusion and chooses to view details, the system accurately identifies key anomalies and selectively extracts and highlights the electrical characteristic parameters related to that point and their deviations. Simultaneously, by generating explanatory text, the system logically connects abstract electrical parameter deviations with specific diagnostic conclusions, enabling users to clearly understand the problem and its causes. This progressive and layered presentation effectively solves the problem of traditional diagnostic information display methods being overly technical and difficult for users to understand.

[0186] Through the above technical solution, this application can significantly improve the efficiency and accuracy of users' understanding of mobile phone charger charging detection and diagnostic information. Users no longer need professional electrical knowledge to quickly understand the general health status of the power transmission path through summary diagnostic conclusions. When a deeper understanding is required, the system provides highlighted key abnormal links, detailed electrical characteristic parameters and their deviations, as well as intuitive explanatory text, which can help users clearly grasp the root cause and impact of the problem, thereby more effectively adopting and implementing operational suggestions, avoiding misjudgments or delays caused by information overload or comprehension barriers, and ultimately improving the practicality of charging detection and user experience.

[0187] In some embodiments described above, a method is proposed to re-test the phone charger after the user executes the suggested operation, updating the diagnostic information and the suggested operation based on the latest test results. However, in its implementation, performing only a one-time test may not comprehensively and accurately assess the long-term or subtle effects of the user's operation, nor can it provide further guidance when the operation results are unsatisfactory. This limitation may lead users to face repeated attempts or ineffective operations when resolving charging problems, thereby affecting user experience and charging efficiency.

[0188] In response, this application further proposes the following steps: after the user performs the aforementioned operation suggestion, re-perform the phone charger charging test, and update the diagnostic information and the operation suggestion based on the latest test results, including:

[0189] Start-up operation effectiveness evaluation cycle;

[0190] During the operational performance evaluation period, the electrical characteristic parameters of the power transmission path are continuously monitored.

[0191] The electrical characteristic parameters are compared with the electrical characteristic parameters of the power transmission path before the operation recommendation was executed;

[0192] Based on the comparison results, determine whether the operation has achieved the preset improvement target;

[0193] When the operation effect fails to achieve the preset improvement target, the operation suggestion is adjusted according to the type of operation suggestion and the deviation of the electrical characteristic parameters;

[0194] Update the diagnostic information according to the adjusted operational recommendations.

[0195] Specifically, the activation operation effect evaluation period refers to a preset time period that the system automatically initiates or the system confirms after the user executes the operation suggestion provided by the system, for observing and evaluating the actual effect of the operation suggestion. This period can be dynamically set according to factors such as the type of operation suggestion and the expected time for the effect to appear. For example, the evaluation period may be shorter for a suggestion to clean the charger; for a suggestion to replace the charger, the evaluation period may need to cover multiple charging cycles.

[0196] During the operational effectiveness evaluation period, the electrical characteristic parameters of the power transmission path are continuously monitored. This can be understood as the system continuously collecting and analyzing key electrical parameters of the charging path, either uninterruptedly or at a preset frequency, during the evaluation period. These parameters include, but are not limited to, voltage, current, impedance, and power loss, with the aim of comprehensively and in real-time understanding changes in the health status of the power transmission path.

[0197] In practical applications, comparing the electrical characteristic parameters with those of the power transmission path before implementing the operational recommendation means comparing the electrical characteristic parameters monitored during the evaluation period with the baseline electrical characteristic parameters recorded before the user implemented the operational recommendation. This comparison aims to quantify the actual improvement of the operational recommendation on the electrical characteristics of the power transmission path, such as comparing improvements in charging efficiency or reductions in impedance.

[0198] Furthermore, judging whether the operation effect has achieved the preset improvement target based on the comparison results means that the system evaluates whether the operation suggestion has successfully solved the problem or achieved the expected optimization effect based on the pre-set performance indicators or thresholds. For example, if the charging efficiency is improved by more than 5%, or the impedance of a specific link is reduced by more than 10%, it may be judged as having achieved the improvement target.

[0199] When the operation fails to achieve the preset improvement target, the operation suggestion is adjusted based on the type of operation suggestion and the deviation of the electrical characteristic parameters. This means the system possesses adaptive learning and optimization capabilities. For example, if the initial suggestion is to clean the charger, but the effect is unsatisfactory, the system may determine that the problem may lie with the charger or the charger itself based on the continued deviation of the electrical characteristic parameters (e.g., the impedance is still too high), and thus adjust the suggestion to replace the charger or a new suggestion for the charger. The purpose of adjusting the operation suggestion is to provide a more accurate and effective solution.

[0200] Therefore, updating the diagnostic information based on the adjusted operational suggestions means that the system integrates the new and optimized operational suggestions into the diagnostic information and presents them to the user again. This ensures that users always receive the latest and most relevant guidance to continuously improve the charging experience.

[0201] This application's solution introduces an operational effectiveness evaluation cycle, continuously monitoring the electrical characteristics of the power transmission path within this cycle. This allows for the systematic tracking of the actual effects of user-initiated operational suggestions. By comparing the monitored electrical characteristics with baseline data prior to the operation, the effectiveness of the operational suggestions can be quantified. When the operational effect fails to meet the preset improvement target, the system can intelligently adjust the operational suggestions based on their type and deviation from the electrical characteristics, thus avoiding simply repeating ineffective suggestions and providing more targeted solutions. This closed-loop feedback mechanism makes the diagnostic and suggestion process more dynamic and intelligent, ensuring users receive a continuously optimized charging experience.

[0202] By employing the aforementioned technical solution, this application overcomes the limitations of traditional methods that only perform a one-time test after the user executes the operational suggestions, thus failing to comprehensively evaluate the operational effectiveness. This solution, through continuous monitoring and dynamic adjustment, ensures the accuracy and effectiveness of diagnostic information and operational suggestions, significantly improving the success rate of users resolving charging problems. Furthermore, the system can adaptively optimize operational suggestions based on actual results, preventing users from wasting time and energy on ineffective operations, thereby improving user satisfaction and charging efficiency.

[0203] In some preferred embodiments, suppose a user receives a diagnostic message indicating slight oxidation of the phone charger, resulting in a slight decrease in charging efficiency, and suggests cleaning the charger with cotton swabs. After the user performs the cleaning as suggested, the system initiates a 24-hour evaluation cycle. During this cycle, the system continuously monitors electrical characteristics such as charging current, voltage, and equivalent impedance at the charger. For example, before cleaning, the charger's equivalent impedance is 1.5 ohms, and the charging efficiency is 85%. After cleaning, the system detects that the initial impedance has decreased to 1.2 ohms, and the charging efficiency has increased to 88%. The system compares these data with the baseline data before cleaning and determines whether the operation has achieved the preset improvement target (e.g., impedance reduction of more than 10%, efficiency improvement of more than 2%). If the system determines that although the impedance has decreased, it is still above the healthy threshold, and the charging efficiency improvement has not reached the expected target, then the operation is deemed not to have fully met the target. At this point, the system will adjust the operation suggestions based on the type of operation suggestion (cleaning) and the deviation of the electrical characteristic parameters (impedance still too high). For example, it may suggest that the user try using a professional electronic device cleaner for deep cleaning, or suggest that the charger may need to be checked for problems. Subsequently, the system will update the diagnostic information based on the adjusted operation suggestions and present it to the user again, guiding the user to the next step.

[0204] In some embodiments described above, this application proposes continuously monitoring the electrical characteristic parameters of the power transmission path during the operational effectiveness evaluation period to assess the effectiveness of user operational suggestions. However, in practical applications, simple continuous monitoring may suffer from inefficiency, excessive power consumption, or insufficient data accuracy, especially when the handheld terminal's operating state is variable. For example, high-frequency monitoring when the handheld terminal is in low-power mode or not charging will unnecessarily consume power, while insufficient monitoring frequency during charging may miss critical abnormal changes. Without adopting differentiated monitoring strategies for different operating states, it will be difficult to ensure monitoring effectiveness while simultaneously considering system resource consumption and data reliability. To address this, this application further proposes a method for optimizing the monitoring of electrical characteristic parameters of the power transmission path during the aforementioned operational effectiveness evaluation period. This method identifies the operating state of the handheld terminal and dynamically adjusts the monitoring strategy to improve the efficiency, accuracy, and adaptability of monitoring.

[0205] In response, this application further proposes to continuously monitor the electrical characteristic parameters of the power transmission path during the operational performance evaluation period, including:

[0206] Identify the operating status of the handheld terminal;

[0207] When the handheld terminal is in low power mode or not charging, intermittent monitoring is initiated, and the sampling accuracy of the relevant sensors is briefly increased before each monitoring.

[0208] When the handheld terminal is in a charging state, the electrical characteristic parameters of the power transmission path are continuously monitored at a high frequency.

[0209] During the monitoring process, voltage and current data at key points along the power transmission path are collected, and combined with time series analysis, abnormal data points caused by transient or intermittent interference are identified and filtered out.

[0210] The temperature and state of charge of the energy storage unit are monitored, and the monitored electrical characteristic parameters are calibrated based on the temperature and state of charge of the energy storage unit; the monitoring strategy of the electrical characteristic parameters is dynamically adjusted according to the operation suggestion type.

[0211] Specifically, "identifying the operating status of the handheld terminal" means that the system determines whether the handheld terminal is in a low-power mode, a non-charging state, or a charging state by reading the internal status information of the handheld terminal, such as the charging status of the power management module, the CPU load, the screen's on / off state, and the user's activity mode. Low-power mode typically refers to the handheld terminal being in standby or hibernation mode, with extremely low system resource consumption; non-charging state means the handheld terminal is not connected to a charging device and relies on its own power storage unit for power; charging state means the handheld terminal is replenishing its power through a charger or data cable.

[0212] "When the handheld terminal is in low-power mode or not charging, intermittent monitoring is initiated, and the sampling accuracy of relevant sensors is briefly increased before each monitoring session." This means that, in order to balance the effectiveness of monitoring and system power consumption, when the handheld terminal is not in a critical charging period, the monitoring activity is not continuous, but rather periodically sampled at preset time intervals. Before each sampling, the relevant sensors used to measure voltage and current are temporarily adjusted to a higher sampling frequency or resolution to ensure that sufficiently accurate data is acquired in a short period of time, thereby capturing potential changes in the power transmission path without significantly increasing overall power consumption.

[0213] "When the handheld terminal is in a charging state, continuously monitor the electrical characteristic parameters of the power transmission path at a high frequency" means that when the handheld terminal is connected to a charging device and is replenishing power, the power transmission path is under high workload at this time, and any abnormality may directly affect the charging efficiency and safety. Therefore, the monitoring system will continuously collect electrical characteristic parameters at a higher frequency in order to detect and respond to any subtle abnormal fluctuations in a timely manner.

[0214] "During the monitoring process, voltage and current data at key points along the power transmission path are collected, and time series analysis is used to identify and filter out abnormal data points caused by transient or intermittent interference." This refers to processing the raw voltage and current data using time series analysis algorithms, such as moving average, Kalman filtering, or outlier detection. The aim is to distinguish between changes in electrical characteristics caused by actual anomalies in the power transmission path and transient, non-continuous data anomalies caused by external environmental noise, instantaneous system load fluctuations, or communication interference, thereby improving the reliability and accuracy of the monitoring data.

[0215] "Monitoring the temperature and state of charge (SOC) of the energy storage unit, and calibrating the monitored electrical characteristic parameters based on the temperature and SOC of the energy storage unit" means that the temperature and current SOC of the energy storage unit (e.g., a battery) significantly affect its internal impedance and electrical characteristics. Therefore, when monitoring the electrical characteristic parameters of the power transmission path, the temperature and SOC data of the energy storage unit are simultaneously acquired, and a preset calibration model or lookup table is used to correct the monitored electrical characteristic parameters to eliminate the influence of temperature and SOC on the measurement results, ensuring the authenticity and comparability of the electrical characteristic parameters.

[0216] "Dynamically adjusting the monitoring strategy for electrical characteristic parameters based on the type of operation suggestion" means that the system will adjust the focus and parameters of monitoring accordingly for different operation suggestions performed by the user, such as "clean the charging port," "replace the charger," or "check the charger." For example, if the operation suggestion is to clean the charging port, the monitoring strategy may focus more on changes in contact resistance at the port; if the operation suggestion is to replace the charger, it will pay more attention to the charger's impedance and voltage drop. This dynamic adjustment makes monitoring more targeted and improves the efficiency and accuracy of evaluating the operation's effectiveness.

[0217] This application's solution identifies the operating status of the handheld terminal and dynamically adjusts the monitoring strategy for the power transmission path accordingly, thus solving the problems of low efficiency and excessive power consumption in traditional continuous monitoring solutions under different operating conditions. Specifically, in low-power or non-charging states, intermittent monitoring with brief increases in sampling accuracy effectively balances power consumption and data quality; while during critical charging periods, high-frequency continuous monitoring ensures timely detection of anomalies. Furthermore, time-series analysis filters out interference data, and electrical characteristic parameters are calibrated by combining the temperature and state of charge of the energy storage unit, greatly improving the accuracy and reliability of the monitoring data. Moreover, the monitoring strategy is dynamically adjusted based on the type of operation suggested by the user, making monitoring activities more targeted and enabling more accurate evaluation of the effects of specific operations.

[0218] The aforementioned technical solution significantly reduces power consumption during non-critical monitoring of handheld terminals, extending device battery life. Simultaneously, it ensures rapid and accurate detection of anomalies in the power transmission path during critical states such as charging. This intelligent monitoring strategy not only improves system resource utilization efficiency but also effectively enhances the accuracy and reliability of electrical characteristic parameters through data filtering and calibration mechanisms, providing a solid data foundation for subsequent operational performance evaluation and diagnostic information updates. Furthermore, dynamic monitoring and adjustments based on different operational suggestions make the evaluation process more precise and efficient, thereby improving user experience and the overall health management level of the charging system.

[0219] In some preferred embodiments, it is assumed that the handheld terminal enters an operation effect evaluation cycle after the user performs the operation suggestion of "cleaning the charging interface".

[0220] Specifically, when the handheld terminal is in standby mode (i.e., low-power mode or non-charging state), the system initiates intermittent monitoring every 5 minutes. Before each monitoring session begins, the sampling rate of the sensors used to measure the charging interface voltage and current is briefly increased from the usual Hz to 1kHz for 5 seconds to obtain high-precision instantaneous data. When the handheld terminal is connected to the charger and begins charging, the system immediately switches to a high-frequency continuous monitoring mode, continuously collecting charging current, charging voltage, and voltage drop data at the charging interface at a frequency of 500Hz.

[0221] During data acquisition, if a data point experiences a significant fluctuation within a very short time (e.g., within milliseconds) that does not conform to the overall trend, it will be identified as transient interference and filtered out by the time series analysis algorithm. Simultaneously, the system monitors the temperature of the energy storage unit in real time (e.g., via a built-in temperature sensor) and its state of charge (e.g., via a battery management chip), and calibrates the monitored charging interface resistance value according to a preset temperature-impedance calibration curve to eliminate the influence of temperature changes on resistance measurement.

[0222] Since the user's suggested action is to "clean the charging port", the system will dynamically adjust its monitoring strategy, focusing on changes in the contact resistance of the charging port. For example, during data analysis, it will be more sensitive to small drops in contact resistance and use them as a key indicator for improving operational effectiveness.

[0223] refer to Figure 3 , Figure 3 This is a schematic diagram of a mobile phone charger charging detection system provided in an embodiment of the present invention, comprising:

[0224] The input terminal is used to inject an AC test signal with a preset frequency range into the power transmission path; and to measure the voltage and current responses of key points on the power transmission path to the AC test signal.

[0225] The computing terminal is used to calculate the electrical characteristic parameters of the power transmission path at multiple frequencies based on the voltage response and the current response; store the reference electrical characteristic parameters of each link of the power transmission path under preset conditions; compare the electrical characteristic parameters with the reference electrical characteristic parameters, and identify the deviation of the power transmission path.

[0226] The adjustment terminal is used to determine the abnormal electrical characteristics of each link in the power transmission path based on the deviation; quantify the impact ratio of each link on the decrease in power replenishment efficiency based on the degree of electrical characteristic abnormality; adjust the power replenishment strategy based on the impact ratio; and provide the user with diagnostic information and operation suggestions for the power transmission path.

[0227] This application presents a mobile phone charger charging detection system designed to address the shortcomings of traditional charging detection methods in diagnosing multiple, non-obvious fault sources. By modularizing the detection, analysis, diagnosis, and strategy adjustment functions of the power transmission path into an input end, a calculation end, and an adjustment end, the system can work collaboratively to achieve refined, multi-frequency electrical characteristic analysis of the entire power transmission path. The input end actively injects AC test signals and collects response data, providing a foundation for subsequent analysis. The calculation end performs in-depth processing on the collected data, calculating the electrical characteristic parameters of each stage and comparing them with benchmark parameters to identify potential deviations. Based on this, the adjustment end further identifies abnormal stages, quantifies their impact on charging efficiency, and dynamically adjusts the charging strategy accordingly, while providing users with intuitive diagnostic information and operational suggestions. This systematic design ensures the continuity and efficiency of the entire process from data acquisition to decision output, thereby effectively improving charging efficiency and user experience.

[0228] The mobile phone charger charging detection system of this application, through its specific functional module division, realizes comprehensive detection and intelligent management of the power transmission path.

[0229] The input terminal is used to inject an AC test signal with a preset frequency range into the power transmission path and measure the voltage and current responses of key points along the power transmission path to the AC test signal. The injection method of the AC test signal, the selection of the preset frequency range, the selection of key points, and the measurement methods of the voltage and current responses have already been described in the above embodiments and will not be repeated here. It is important to emphasize that the input terminal can be implemented as an independent hardware module, such as an integrated circuit containing a signal generator and a high-precision data acquisition unit, or as part of a mobile phone charging management chip. The purpose is to ensure accurate injection of the test signal and precise acquisition of the response data, providing reliable raw data for subsequent electrical characteristic analysis.

[0230] The computing terminal is used to calculate the electrical characteristic parameters of the power transmission path at multiple frequencies based on voltage and current responses; store the reference electrical characteristic parameters of each link in the power transmission path under preset states; and compare the electrical characteristic parameters with the reference electrical characteristic parameters to identify deviations in the power transmission path. The calculation method for the electrical characteristic parameters, the storage method for the reference parameters, and the logic for identifying deviations have already been described in the above embodiments, and will not be repeated here. Specifically, the computing terminal can be implemented as a microprocessor, digital signal processor (DSP), or application-specific integrated circuit (ASIC), which integrates a storage unit for storing reference electrical characteristic parameters and processing algorithms. This computing terminal is responsible for performing complex mathematical operations and logical judgments on the raw data collected from the input terminal, thereby revealing the deep electrical characteristics of the power transmission path and identifying differences from a healthy state.

[0231] The adjustment unit is used to determine the abnormal electrical characteristics of each link in the power transmission path based on the deviation; quantify the impact ratio of each link on the decrease in power replenishment efficiency based on the degree of electrical characteristic abnormality; adjust the power replenishment strategy according to the impact ratio; and provide users with diagnostic information and operation suggestions for the power transmission path. The methods for determining abnormal electrical characteristics, quantifying the impact ratio, adjusting the power replenishment strategy, and providing diagnostic information and operation suggestions have already been described in the above embodiments, and will not be repeated here. In practical applications, the adjustment unit can be implemented as a control logic unit, such as a software module running on the mobile phone's main control chip, or an independent intelligent decision-making unit. Its core function is to make intelligent decisions based on the analysis results provided by the computing unit, including dynamically adjusting charging parameters and providing users with personalized and actionable suggestions to optimize the charging process and improve the user experience.

[0232] This application's mobile phone charger charging detection system represents a significant improvement over existing technologies that primarily focus on monitoring battery internal status and charging protocol negotiation. Existing technologies often fail to effectively differentiate fault sources when faced with multiple, non-obvious faults, resorting to a conservative "one-size-fits-all" approach, leading to decreased charging efficiency and a poor user experience. This application modularizes detection, calculation, and adjustment functions into a tightly integrated system capable of multi-frequency, multi-stage electrical characteristic analysis of the entire power transmission path. This systematic design enables more refined and automated fault diagnosis, clearly identifying whether the problem originates with the charger, the battery itself, or the charger itself, and quantifying the degree of their respective impact. Consequently, the system can adopt more targeted optimization strategies. For example, if the problem is found to be caused by charger aging, the system can suggest replacing the cable instead of simply reducing the charging current. Furthermore, the system can dynamically adjust the power replenishment strategy based on the degree of anomaly and the proportion of impact, thereby maximizing charging efficiency while ensuring safety. By providing users with clear diagnostic information and actionable suggestions, this application significantly improves the user experience and addresses the pain points of insufficient diagnostic capabilities and the inability to provide targeted solutions in existing technologies.

[0233] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for detecting charging of a mobile phone charger, characterized in that, include: Inject an AC test signal with a preset frequency range into the power transmission path; Measure the voltage and current responses of key points along the power transmission path to the AC test signal; Based on the voltage response and the current response, calculate the electrical characteristic parameters of the power transmission path at multiple frequencies; Store the reference electrical characteristic parameters of each link in the power transmission path under preset conditions; By comparing the electrical characteristic parameters with the reference electrical characteristic parameters, the deviation of the power transmission path can be identified; Based on the deviation, it is determined that the electrical characteristics of each link in the power transmission path are abnormal; Based on the degree of abnormality in the electrical characteristics, the proportion of the impact of each link on the decrease in power replenishment efficiency is quantified. Adjust the power replenishment strategy according to the aforementioned impact ratio; Provide users with diagnostic information and operational suggestions for the power transmission path; The method of quantifying the impact ratio of each link on the decrease in power replenishment efficiency based on the degree of electrical characteristic anomaly includes: Based on the equivalent circuit model of the power transmission path, the electrical characteristics of the power transmission path are simulated. Based on the deviation, adjust the parameters corresponding to each component in the equivalent circuit model; Based on the equivalent circuit model, identify the independent contribution of each component to the decrease in the power replenishment efficiency; and Based on the independent contributions, the proportion of each link's impact on the decrease in power replenishment efficiency is quantified.

2. The mobile phone charger charging detection method according to claim 1, characterized in that, The storage of reference electrical characteristic parameters of each link in the power transmission path under preset states includes: Assess the health status of the power transmission path; Determine the difference between the electrical characteristic parameters of the power transmission path and the reference electrical characteristic parameters; When the difference is within a preset allowable range, the reference electrical characteristic parameters are adjusted according to the electrical characteristic parameters of the power transmission path; Record the update information of the reference electrical characteristic parameters.

3. The mobile phone charger charging detection method according to claim 1, characterized in that, The adjustment of the power replenishment strategy based on the impact ratio includes: Identify the combination of power replenishment strategies among multiple abnormal links on the power transmission path; The dominant strategy in the strategy combination is determined according to the preset priority rules. Within the allowable output range of the power replenishment device, adjust the power replenishment current, power replenishment voltage, and power replenishment mode according to the dominant strategy and the influence ratio; Output the power replenishment strategy.

4. The mobile phone charger charging detection method according to claim 1, characterized in that, The provision of diagnostic information and operational suggestions for the power transmission path to the user includes: The diagnostic information and operational suggestions are sorted according to the impact ratio; On the display interface of the handheld terminal, the diagnostic information and operation suggestions corresponding to the abnormal links with the greatest impact ratio are displayed first. The operation suggestions are displayed in association with the diagnostic information, and a link is sent to each operation suggestion to guide the user to perform the operation; After the user performs the operation suggestion, the phone charger charging test is performed again, and the diagnostic information and operation suggestion are updated according to the latest test results; When displaying the diagnostic information, a general diagnostic conclusion is presented in a hierarchical display manner. When the user selects to view details, the abnormal electrical characteristics data and analysis results are displayed in an expanded manner.

5. The mobile phone charger charging detection method according to claim 4, characterized in that, On the display interface of the handheld terminal, the diagnostic information and operation suggestions corresponding to the abnormal links with the highest impact ratio are displayed first, including: When the handheld terminal is in a call, the diagnostic information and operation suggestions are notified by vibration or low volume prompt tone, and the diagnostic information and operation suggestions are automatically presented on the display interface after the call ends; When the handheld terminal is in a game or video playback state, the diagnostic information and the operation suggestions are superimposed on the display interface in the form of a semi-transparent floating window, and the position and size of the semi-transparent floating window are automatically adjusted. When a user is performing text input, the diagnostic information and operation suggestions will be displayed in the form of a notification bar message, and the diagnostic information and operation suggestions will be automatically expanded and displayed after the user finishes text input; When the handheld terminal is in a low battery state, the diagnostic information and operation suggestions will be forcibly displayed in the form of a full-screen pop-up window; When the handheld terminal is charging, the diagnostic information and operation suggestions are displayed in the form of a charging animation or screensaver, and automatically switch to a detailed display interface when the user unlocks the screen.

6. The mobile phone charger charging detection method according to claim 4, characterized in that, When displaying the diagnostic information, a hierarchical display method is used to present a general diagnostic conclusion. When the user selects to view details, the abnormal electrical characteristics data and analysis results are expanded and displayed, including: Identify the key abnormalities in the general diagnostic conclusions; Based on the key abnormal links, extract and highlight the electrical characteristic parameters and their deviations from the key abnormal links from the electrical characteristic abnormal data and the analysis results; Generate explanatory text, which includes the deviation of the electrical characteristic parameters of the key abnormal link from the corresponding general diagnostic conclusion.

7. A method for detecting charging of a mobile phone charger according to claim 4, characterized in that, After the user executes the suggested operation, the phone charger charging test is performed again, and the diagnostic information and the suggested operation are updated based on the latest test results, including: Start-up operation effectiveness evaluation cycle; During the operational performance evaluation period, the electrical characteristic parameters of the power transmission path are continuously monitored. The electrical characteristic parameters are compared with the electrical characteristic parameters of the power transmission path before the operation recommendation was executed; Based on the comparison results, determine whether the operation has achieved the preset improvement target; When the operation effect fails to achieve the preset improvement target, the operation suggestion is adjusted according to the type of operation suggestion and the deviation of the electrical characteristic parameters; Update the diagnostic information according to the adjusted operational recommendations.

8. The mobile phone charger charging detection method according to claim 7, characterized in that, The continuous monitoring of electrical characteristic parameters of the power transmission path during the operational performance evaluation period includes: Identify the operating status of the handheld terminal; When the handheld terminal is in low power mode or not charging, intermittent monitoring is initiated, and the sampling accuracy of the relevant sensors is briefly increased before each monitoring. When the handheld terminal is in a charging state, the electrical characteristic parameters of the power transmission path are continuously monitored at a high frequency. During the monitoring process, voltage and current data at key points along the power transmission path are collected, and combined with time series analysis, abnormal data points caused by transient or intermittent interference are identified and filtered out. Monitor the temperature and state of charge of the energy storage unit, and calibrate the monitored electrical characteristic parameters based on the temperature and state of charge of the energy storage unit; dynamically adjust the monitoring strategy of the electrical characteristic parameters according to the operation recommendation type.

9. A mobile phone charger charging detection system, characterized in that, include: The input terminal is used to inject an AC test signal with a preset frequency range into the power transmission path; Measure the voltage and current responses of key points along the power transmission path to the AC test signal; The computing terminal is used to calculate the electrical characteristic parameters of the power transmission path at multiple frequencies based on the voltage response and the current response; store the reference electrical characteristic parameters of each link of the power transmission path under preset states; compare the electrical characteristic parameters with the reference electrical characteristic parameters, and identify the deviation of the power transmission path. The adjustment end is used to determine the abnormality of the electrical characteristics of each link in the power transmission path based on the deviation. Based on the degree of abnormality in the electrical characteristics, the proportion of the impact of each link on the decrease in power replenishment efficiency is quantified. Adjust the power replenishment strategy according to the aforementioned impact ratio; And to provide users with diagnostic information and operational suggestions for the power transmission path; The step of quantifying the impact ratio of each link on the decrease in power replenishment efficiency based on the degree of electrical characteristic anomaly includes: Based on the equivalent circuit model of the power transmission path, the electrical characteristics of the power transmission path are simulated. Based on the deviation, adjust the parameters corresponding to each component in the equivalent circuit model; Based on the equivalent circuit model, identify the independent contribution of each component to the decrease in the power replenishment efficiency; and Based on the independent contributions, the proportion of each link's impact on the decrease in power replenishment efficiency is quantified.

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