Battery control system and base station power supply according to voltage matching of battery to be charged

Abstract

The application discloses a battery control system and a base station power supply according to a voltage to be matched by a battery, relates to the technical field of battery charging control, and comprises a front-end signal buffering module, an initial static sampling module, a multi-period confirmation module, an anti-interference screening module, a target voltage identification module and a voltage output control module; the front-end signal buffering module starts an electrical state buffering mechanism at the moment when a device to be charged is connected, delays the sampling time of a main control circuit through an isolation capacitor group and a voltage stabilizing and filtering module, and stabilizes the front-end input signal. Through buffering sampling and multi-period confirmation, the application ensures that the voltage signal is stable and reliable in the identification stage, avoids equipment damage caused by misjudgment, simultaneously combines spectrum analysis and a closed-loop adjustment mechanism, improves the anti-interference capability and the output voltage precision of the system, and realizes intelligent power supply control with high safety and high adaptability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of battery charging control, specifically to a battery control system matching voltage according to a body to be charged and a base station power supply. BACKGROUND

[0002] The "battery control according to the voltage matching of the body to be charged" is an intelligent power supply adjustment technology, the core of which is that the battery control system can identify the voltage demand of the object to be charged (i.e. "the body to be charged") and adjust the output voltage accordingly to achieve the best match. Specifically, this control method is no longer limited to fixed output voltage, but through the detection of the identification information of the body to be charged, the initial connection load characteristics or the communication protocol, etc., the working voltage or the optimal charging voltage range is analyzed. Then, the control system adjusts the internal voltage conversion module (such as DC-DC converter, voltage regulation chip, etc.) to adjust the battery output to the appropriate voltage level, thereby improving the charging efficiency, prolonging the battery life and protecting the charged equipment, avoiding the energy waste or equipment damage caused by voltage mismatch. This strategy is suitable for a variety of terminal devices with different voltage standards, such as portable electronic devices, intelligent sensors, wearable devices, etc., has good compatibility and intelligence, and is a new type of battery control mechanism for the power supply needs of multiple devices.

[0003] The prior art has the following disadvantages: In the process of "battery control according to the voltage matching of the body to be charged" in the prior art, there is a problem of transient voltage feedback distortion in the identification stage of the body to be charged. Specifically, in the initial stage of identifying the voltage level of the body to be charged or communicating, due to the interference factors such as cable transient voltage drop, high-frequency noise interference, electromagnetic coupling, etc., the feedback voltage signal collected by the control system may be distorted, thereby causing misjudgment of the voltage demand of the device. For example, a device that should be identified as 5V input is incorrectly identified as 12V level, and the battery outputs excessive voltage, which is easy to cause overvoltage breakdown of the charging management chip, internal circuit burning, and even cause device short circuit or fire. This problem is particularly prominent in the use scenarios of frequent plugging, complex power supply environment or multiple devices in parallel, and once it occurs, it will directly cause device hardware damage and serious system safety accidents.

[0004] The above information disclosed in the background section is only used to enhance the understanding of the background of the present disclosure, and therefore it can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0005] The application aims to provide a battery control system for matching voltage of a device to be charged and a base station power supply, which ensures stable and reliable voltage signal in the identification stage by buffering sampling and multi-cycle confirmation, avoids misjudgment to cause damage to the device, and combines spectrum analysis and closed-loop regulation mechanism to improve the anti-interference ability and output voltage precision of the system, so as to realize intelligent power supply control with high safety and high adaptability, and solve the problems in the background technology.

[0006] To achieve the above-mentioned purpose, the application provides the following technical scheme: a battery control system for matching voltage of a device to be charged, comprising a front-end signal buffering module, an initial static sampling module, a multi-cycle confirmation module, an anti-interference screening module, a target voltage identification module and a voltage output control module.

[0007] The front-end signal buffering module starts the electrical state buffering mechanism at the moment of connecting the device to be charged, delays the sampling time of the main control circuit through the isolation capacitor group and the voltage stabilizing and filtering module, and stabilizes the front-end input signal.

[0008] The initial static sampling module collects the static voltage signal of the device to be charged in the micro-current mode in the buffering state, and is used for judging the initial voltage grade of the device.

[0009] The multi-cycle confirmation module executes the multi-cycle signal confirmation program after the initial voltage judgment, repeatedly collects the static signal three times in a time sequence control mode, and compares and checks the mean value.

[0010] The anti-interference screening module introduces the electromagnetic interference judgment mechanism, detects the high-frequency interference characteristic value in the sampling data, performs the rejection processing on the signal segment exceeding the interference threshold, and ensures the sampling effectiveness.

[0011] The target voltage identification module compares the voltage grade after the multi-cycle confirmation and the interference rejection with the preset voltage matching table, and obtains the closest target output voltage grade.

[0012] The voltage output control module controls the output voltage conversion module to accurately adjust the battery output voltage to the target grade, and executes the voltage stabilizing and maintaining logic after the conversion is completed, and starts to supply power to the device to be charged.

[0013] Preferably, in the electrical state buffering mechanism, the isolation capacitor group is composed of at least two series electrolytic capacitors and one parallel ceramic capacitor, wherein the electrolytic capacitor is used for large-current filtering, and the ceramic capacitor is used for high-frequency interference absorption.

[0014] The voltage stabilizing and filtering module is internally provided with an overvoltage clamping circuit, which automatically shunts to the grounding line when the transient voltage exceeds the set safety threshold, slowly restores the working voltage of the main control circuit through the soft start controller, so that the control system maintains electrical stability in the initial identification stage, and prevents being mis-triggered or damaged by the peak voltage.

[0015] Preferably, in static voltage signal acquisition, the micro-current mode is provided by a constant current source with an output current not exceeding 0.5mA, ensuring that it will not cause load interference to the device to be charged;

[0016] The sampling controller completes a static measurement according to a preset time window and completes sampling at least three different times during the entire identification period. Before each sampling, the internal noise shielding logic is activated to generate the sampling data under interference-free conditions, further ensuring the reliability and representativeness of the initial signal data.

[0017] Preferably, a signal consistency verification mechanism is introduced in the multi-cycle signal confirmation procedure;

[0018] The difference between the maximum and minimum values ​​of the three static signal sampling results must not exceed a preset floating threshold. If the threshold is exceeded, the resampling logic is triggered.

[0019] The resampling logic limits the number of retries to no more than two to avoid long recognition delays.

[0020] After all samples pass the test, the average value will be stored in a temporary register and locked as the current device voltage reference value for subsequent comparison.

[0021] Preferably, in the static voltage judgment stage, to suppress the judgment error caused by transient noise, electromagnetic interference, and sampling deviation, an adaptive voltage stability index calculation mechanism is introduced to improve the accuracy and robustness of voltage identification of the device to be charged. The specific steps are as follows:

[0022] The average voltage of the three sampled values ​​is calculated as follows:

[0023] In the formula, These represent the voltage values ​​obtained during three consecutive static voltage samplings at the initial stage of identifying the device to be charged. It is the average voltage;

[0024] After obtaining the baseline voltage level, the sample variance is introduced, and the calculation formula is as follows: In the formula, It is the sample variance;

[0025] The total electromagnetic interference energy within the current time period is extracted using a Fast Fourier Transform, and the calculation expression is as follows: In the formula, At frequency Below, the spectral power density obtained after the sampled signal undergoes a Fast Fourier Transform is... It is the total value of electromagnetic noise energy;

[0026] The comprehensive voltage stability index is calculated using the following expression: In the formula, It is the voltage stability index. It is the standard deviation of the sampled voltage, i.e. .

[0027] Preferably, in the electromagnetic interference determination mechanism, the control system is equipped with a spectrum analysis module, which performs fast Fourier transform processing on the sampled signal in 25kHz units to extract the frequency band energy distribution characteristics.

[0028] If the peak energy of any frequency band exceeds the set baseline, the current sampling is considered to be affected by high-frequency interference, and the current data is then disabled for the current time period.

[0029] Preferably, in the target output voltage matching and comparison process, a fuzzy logic comparison model is adopted, which does not use a single voltage value as a threshold, but constructs a voltage range based on adjacent voltage levels;

[0030] A confidence interval judgment mechanism is introduced. When the voltage sample value falls into the overlapping interval of two levels, the probability value of each level is calculated, and the level with the highest probability is taken as the output target, thereby enhancing the fault tolerance capability of the output voltage matching.

[0031] Preferably, during the voltage output conversion stage, a set of dynamic feedback regulation logic is set to ensure the stability and responsiveness of the battery system after the voltage conversion is completed. The specific steps are as follows:

[0032] Using the identified target matching voltage as the desired output reference, and by monitoring the current conversion output voltage in real time, a feedback adjustment coefficient is introduced as the starting point for deviation adjustment. The calculation expression is as follows:

[0033] In the formula, It is the standard matching voltage. This is the current conversion output voltage. It is the feedback adjustment coefficient;

[0034] The feedback adjustment coefficient is applied to the module control gain to calculate the voltage correction amount, thereby obtaining the current required voltage adjustment step size, forming a closed-loop regulation. The calculation expression is as follows: In the formula, It is the module gain factor. It is a voltage correction amount;

[0035] The output value for the next cycle is adjusted according to the calculation results, and a dynamic update is performed, continuously refreshed in 10ms increments until the error between the target output voltage and the current output is less than 0.05V. The update formula is as follows: In the formula, This is the new output voltage value.

[0036] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0037] This invention effectively solves the problem of feedback signal distortion caused by transient interference during the device identification stage by introducing an electrical state buffering mechanism and a multi-cycle voltage confirmation strategy. When the device is first connected, the sampling timing of the main control is delayed by using an isolation capacitor bank and a voltage stabilization filter module, which filters out voltage spikes generated at the moment of insertion and removal. Subsequently, combined with micro-current sampling and multiple repeated confirmation mechanisms, the accuracy of initial voltage identification is further improved. This combined strategy greatly reduces the false judgment rate while ensuring power supply response speed, providing a stable and accurate basis for subsequent output voltage matching, thereby avoiding the risk of circuit damage caused by erroneous high voltage output.

[0038] This invention further enhances the system's adaptability to complex electromagnetic environments by constructing an electromagnetic interference analysis mechanism and introducing a stability index (VSI) and a closed-loop adjustment function. High-frequency interference bands are identified and eliminated through spectrum analysis, and the sampled voltage is intelligently corrected based on the VSI judgment value, ensuring high stability of the identification results. During the voltage output stage, the closed-loop control function dynamically adjusts the output voltage according to time slices, quickly approaching the target voltage level while maintaining the error within an extremely low range. This ensures the electrical safety and power supply continuity of the device throughout the identification and charging process, effectively improving the system's safety, reliability, and intelligence level.

[0039] This invention also boasts excellent device compatibility and scalability, applicable to various terminal devices, voltage levels, and multi-interface power supply scenarios. During the identification and matching process, by constructing a fuzzy logic comparison mechanism and an attribution probability model, it no longer relies on a single voltage judgment threshold but dynamically analyzes adjacent voltage ranges to intelligently select the most suitable target output voltage level. This approach is particularly suitable for use in charging environments with multiple standards (such as USB-PD, QC, and proprietary protocols), effectively avoiding identification failures or poor adaptation issues caused by standard differences, and improving the system's compatibility and deployment flexibility in practical applications. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0041] Figure 1 This is a schematic diagram of a battery control system based on the matching voltage of the battery to be charged according to the present invention. Detailed Implementation

[0042] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0043] This invention provides, for example Figure 1 The battery control system shown includes a front-end signal buffer module, an initial static sampling module, a multi-cycle confirmation module, an anti-interference screening module, a target voltage identification module, and a voltage output control module.

[0044] The front-end signal buffer module activates the electrical state buffering mechanism the moment the device to be charged is connected. It stabilizes the front-end input signal by delaying the sampling time of the main control circuit through the isolation capacitor bank and the voltage stabilizing filter module.

[0045] In the electrical state buffering mechanism, the isolation capacitor bank consists of at least two series electrolytic capacitors and one parallel ceramic capacitor, where the electrolytic capacitors are used for high current filtering and the ceramic capacitors are used for high frequency interference absorption.

[0046] The voltage stabilizing and filtering module has a built-in overvoltage clamping circuit. When the transient voltage exceeds the set safety threshold, it automatically diverts the current to the ground line and slowly restores the main control circuit's operating voltage through the soft-start controller. This ensures that the control system remains electrically stable during the initial identification phase and prevents it from being falsely triggered or damaged by voltage spikes.

[0047] This step primarily involves implementing an electrical state buffer mechanism when the device to be charged is connected. This allows for electrical stability processing of the input voltage within a very short time, ensuring the quality of the basic signal during the system sampling phase. In practical applications, the instant a user inserts a device into the battery interface, transient voltage spikes, voltage drops, or rebounds can occur in the circuit due to factors such as changes in contact resistance caused by the insertion and removal action, unstable cable characteristics, physical jitter, or connector quality issues. If these abnormal transient waveforms are not filtered, they are highly likely to directly enter the main control chip of the control system, interfering with its operation and even causing the sampling unit to misread the voltage level and make incorrect judgments. The isolation capacitor bank plays a role in two aspects: firstly, electrolytic capacitors, with their large energy storage capacity, can effectively absorb large transient voltage fluctuations and reduce voltage waveform jitter; secondly, ceramic capacitors have a strong response speed and absorption capacity for high-frequency interference, and can quickly suppress high-frequency noise such as radio frequency interference and digital communication interference. Based on this, the voltage regulation and filtering module further uses an overvoltage clamping circuit to limit and protect against abnormally high voltages, preventing damage to the main control chip. Simultaneously, the soft-start logic is activated at this stage. By delaying the main control's power-on, it allows time for the voltage input to stabilize, ensuring that the sampling signal is stable and usable when the main control system enters working mode. This mechanism not only improves the system's robustness in terms of technical logic but also adds a hardware protection layer to the system's structural design. It effectively prevents overvoltage breakdown, sampling interference, or irreversible system errors during interface plugging and unplugging, laying a fundamental guarantee for the entire identification and power supply control process.

[0048] The initial static sampling module acquires the static voltage signal of the device to be charged in micro-current mode under buffered conditions to determine the initial voltage level of the device.

[0049] In static voltage signal acquisition, the micro-current mode is provided by a constant current source, and its output current does not exceed 0.5mA, ensuring that it will not cause load interference to the device to be charged.

[0050] The sampling controller completes a static measurement according to a preset time window (less than 5ms). It completes sampling at least three different times during the entire identification period. Before each sampling, the internal noise shielding logic is activated to generate the sampling data under interference-free conditions, further ensuring the reliability and representativeness of the initial signal data.

[0051] This step designs an initial static voltage sampling mechanism in micro-current mode, aiming to achieve the most fundamental identification of the electrical characteristics of the device to be charged, thereby obtaining the true voltage demand signal. In electronic system identification, the electrical parameters obtained from the initial sampling often directly determine the accuracy of subsequent voltage matching logic. However, in practical applications, if the current during the identification process is too large, it will not only trigger the internal voltage regulator chip of the device to work, affecting its true voltage reflection, but may also cause some intelligent devices to enter the power supply startup process prematurely, resulting in the feedback signal having dynamic working characteristics and deviating from its static voltage level. This invention avoids the identification deviation caused by such excitation disturbances by introducing a constant micro-current source to read the voltage at the device end with a weak excitation method not exceeding 0.5mA. At the same time, to prevent environmental voltage fluctuations from affecting data sampling accuracy, the system is designed to perform short-time sampling at multiple moments, with each sampling limited to a time window of less than 5ms, significantly reducing the interference of external noise and internal timing changes on voltage reading. This step not only ensures the accuracy of the original data, but also, through a noise shielding strategy before sampling, enables the controller to enter a low-noise state at critical moments, structurally avoiding EMC problems from interfering with sampling accuracy. It is particularly suitable for fast charging devices that require accurate input voltage identification, multi-protocol power interfaces, or medical electronic devices with stringent voltage requirements, and is a key component in improving the input identification accuracy of the entire system.

[0052] The multi-cycle confirmation module executes a multi-cycle signal confirmation program after the initial voltage judgment, which repeatedly collects three static signals using a timing control method and compares and verifies their average values.

[0053] In the multi-cycle signal confirmation procedure, a signal consistency verification mechanism is introduced;

[0054] The difference between the maximum and minimum values ​​of the three static signal sampling results must not exceed a preset floating threshold (e.g., 0.3V). If the threshold is exceeded, the resampling logic will be triggered.

[0055] The resampling logic limits the number of retries to no more than two to avoid long recognition delays.

[0056] After all samples pass the test, the average value will be stored in a temporary register and locked as the current device voltage reference value for subsequent comparison.

[0057] During the identification process, the multi-cycle confirmation mechanism acts as a "signal stability examiner," ensuring that the system does not make misjudgments due to occasional interference or isolated outliers, thereby guaranteeing the data quality of the entire voltage identification process. Single voltage sampling is highly susceptible to electromagnetic fluctuations, power supply glitches, and crosstalk between components in complex environments. These interferences often cannot be completely eliminated by a single filter. If the system blindly relies on single sample values, it is easy to misjudge voltage levels during device identification, leading to subsequent voltage output mismatch. This step proposes a consistency verification method based on the criterion that the "minimum-maximum difference does not exceed a preset threshold," requiring that the data from each sampling group undergo stability verification before being accepted. This approach effectively introduces a data distribution range judgment mechanism, simulating the mindset of manually reviewing signal trends, significantly improving the system's tolerance and ability to distinguish data anomalies. When a sampling group is determined to have excessive value fluctuations, the system will execute a limited number of automatic resampling operations to capture a true and stable data window. The introduction of the resampling mechanism not only increases the system's ability to cope with sudden interference but also enhances its intelligence in adapting to environmental changes. Finally, all qualified sampled values ​​are averaged to effectively mitigate short-term anomalies caused by voltage fluctuations, while avoiding severe judgment deviations due to isolated anomalies. This mechanism is particularly suitable for high-error-probability scenarios such as complex electromagnetic environments (e.g., industrial workshops, power control rooms), interface wear and aging, and cable quality fluctuations, and is a key guarantee for identification stability and system fault tolerance.

[0058] In the static voltage judgment stage, to suppress judgment errors caused by transient noise, electromagnetic interference, and sampling deviation, an adaptive voltage stability index (VSI) calculation mechanism is introduced to improve the accuracy and robustness of voltage identification of the device to be charged. This mechanism is based on the initial three voltage sampling values ​​and comprehensively judges the stability of the signal through the mean, variance, and frequency domain energy index. The specific steps are as follows:

[0059] The average voltage of the three sampled values ​​is calculated as follows:

[0060] In the formula, These represent the voltage values ​​obtained during three consecutive static voltage samplings at the initial stage of identifying the device to be charged. Each sampling was performed in micro-current mode, with a current not exceeding 0.5mA and a sampling window of less than 5ms, to ensure that the voltage state of the device being identified would not be affected. It is the average voltage, representing the arithmetic mean of three sampled voltages, used to initially reflect the stable voltage level of the object to be charged; this value serves as the basic judgment quantity for subsequent matching calculations and is the reference voltage benchmark in the entire identification process;

[0061] After obtaining the baseline voltage level, the sample variance is introduced, and the calculation formula is as follows: In the formula, This is the sample variance, a statistical indicator used to measure the fluctuation range of three voltage samples. The larger the value, the greater the fluctuation between the three measurements, and the worse the stability of the voltage signal. The system uses this value to determine whether the current voltage value is stable and reliable enough. If the variance is too high, it indicates that there may be cable contact transients, power rebound, or external interference.

[0062] The total electromagnetic interference energy within the current time period is extracted using a Fast Fourier Transform, and the calculation expression is as follows: In the formula, At frequency The following is the spectral power density obtained after the sampled signal undergoes a Fast Fourier Transform (FFT). This power density quantifies the energy distribution of the signal at different frequencies. This is the total electromagnetic noise energy, which is the sum of the spectral power of the sampled signal within the 25kHz to 250kHz frequency band. This frequency band covers most common sources of electromagnetic interference (such as switching power supplies, wireless signals, etc.). The higher the value, the stronger the high-frequency noise encountered in the current sample. As an important parameter reflecting the reliability of sampling, it directly affects the degree of trust in voltage identification;

[0063] The comprehensive voltage stability index is calculated using the following expression: In the formula, It is a voltage stability index that comprehensively reflects the reliability of the average voltage, and is evaluated by combining two factors: volatility and interference. A higher value indicates that the voltage sampling in that segment is more stable and reliable. It is the standard deviation of the sampled voltage, i.e. .

[0064] The voltage stability index is used as a reference for the final voltage judgment correction value. In identifying critical points at multiple voltage levels, it is the preferred choice. The higher value is used as the target voltage level for the device to ensure that the identification process has good anti-interference ability and can meet the high reliability voltage identification requirements in complex physical connection scenarios.

[0065] In voltage identification, a single voltage value often fails to fully reflect the reliability of the data, especially when the device operates in a complex environment where voltage fluctuates due to multiple factors. To resolve the contradiction between identification accuracy and signal authenticity, this step innovatively introduces a "Voltage Stability Index" (VSI) calculation mechanism, constructing a stability assessment model using three factors: mean, variance, and spectral energy. The first step calculates the center value of the current voltage using a simple average, serving as a static judgment benchmark. The second step introduces a sample variance index to assess the deviation between three sampled values, thus measuring voltage volatility. The third step performs FFT to extract high-frequency energy indicators, reflecting whether the sampling process is affected by EMI interference. Finally, a composite formula integrates these three factors to derive a comprehensive stability index. A high index indicates stable and reliable voltage data, allowing the system to proceed to the next identification step; a low index triggers data resampling logic or outputs a warning. This mechanism breaks away from the traditional identification system's singular identification logic of "only looking at voltage, not considering the environment," quantifying unstable factors to endow the system with stronger judgment and self-correction capabilities. It is suitable for high-reliability applications such as mobile power supply, industrial automatic control, and military communication equipment. It is a high-order recognition model with predictive, evaluative, and control capabilities.

[0066] The anti-interference screening module introduces an electromagnetic interference judgment mechanism to detect high-frequency interference characteristics in the sampled data and remove signal segments that exceed the interference threshold to ensure the effectiveness of the sampling.

[0067] In the electromagnetic interference determination mechanism, the control system is equipped with a spectrum analysis module, which performs Fast Fourier Transform (FFT) processing on the sampled signal in 25kHz units to extract the frequency band energy distribution characteristics.

[0068] If the peak energy of any frequency band exceeds the set baseline (e.g., 0.05V²), it is considered that the current sampling is affected by high-frequency interference, and the current data is then disabled for the current time period.

[0069] The entire mechanism cycle is completed within 50ms to avoid affecting the overall recognition latency.

[0070] With the increasing electrical complexity of equipment operating environments, electromagnetic interference has become one of the main factors affecting the accuracy of voltage identification systems. Especially in embedded systems, wireless communication devices, and industrial automation scenarios, power supply lines harbor a large number of interference waveforms from high-frequency signal lines, motor starts, and wireless signals, making it difficult for traditional time-domain filtering to effectively identify their components. This invention introduces frequency domain analysis, specifically calling a Fast Fourier Transform (FFT) immediately after signal sampling to deconstruct its spectrum. This allows for the identification of abnormal frequency band energy concentrations within the signal in a very short time. Specifically, each 25kHz frequency band is meticulously scanned, and its spectral power is quantified and compared with a preset energy threshold. Once an energy peak in a frequency band exceeds the threshold, the sample is determined to be subject to EMI interference and is discarded. Compared to traditional low-pass filtering, this process offers higher frequency selectivity and identification accuracy, enabling pinpoint analysis of interference sources with rapid response. The identification window is controlled within 50ms, fully meeting the requirements for rapid identification. This mechanism is widely applicable to high-speed plugging and unplugging scenarios, multi-device parallel identification scenarios, and parallel wireless charging and data communication scenarios, providing the system with a set of highly efficient and accurate anti-interference measures so that its identification performance is not hampered by complex environments.

[0071] The target voltage identification module compares the voltage level after multiple cycles of confirmation and interference removal with a preset voltage matching table to obtain the closest target output voltage level.

[0072] During the target output voltage matching and comparison process, a fuzzy logic comparison model is adopted. Instead of using a single voltage value as a threshold, a voltage range is constructed based on adjacent voltage levels, such as mapping 4.8V-5.2V to the 5V level.

[0073] A confidence interval judgment mechanism is introduced. When the voltage sample value falls into the overlapping interval of two levels, the probability value of each level is calculated, and the level with the highest probability is taken as the output target, thereby enhancing the fault tolerance capability of the output voltage matching.

[0074] There is often a trade-off between accuracy and fault tolerance in voltage identification. Traditional "fixed value identification" methods are prone to misclassification when faced with voltage fluctuations. For example, the actual voltage of a device may be 5.0V, but due to circuit aging, poor contact, or abnormal initial conditions, the sampled value may be 4.79V or 5.21V. If the system only compares absolute values, it is highly likely to misclassify the device as 4.5V or 5.5V. This invention introduces a fuzzy logic model in this step. By setting each voltage level as a certain width interval (e.g., 4.8V~5.2V is classified as 5V), the above-mentioned "critical value misclassification" problem is effectively solved. When the sampling result falls into the overlapping area of ​​two intervals, the system further calculates the confidence probability, for example, based on factors such as the device's historical usage data, fluctuation trends, and sampling stability, to form a comprehensive judgment model. The level with the higher probability is ultimately output as the identification target. This method maintains the flexibility of judgment and has a certain degree of adaptive intelligence. This technology is particularly suitable for scenarios such as multi-protocol fast charging (e.g., USB-PD, QC), smart wearable devices, or medical monitoring equipment. These devices have high requirements for power supply voltage accuracy, and the feedback signal is prone to drift in the initial state. This fuzzy logic mechanism not only improves the system's fault tolerance for voltage recognition but also lays the technical foundation for adaptive power supply strategies for complex devices.

[0075] The voltage output control module controls the output voltage conversion module to precisely adjust the battery output voltage to the target level, and executes voltage stabilization logic after the conversion is completed to start supplying power to the device to be charged.

[0076] During the voltage output conversion stage, a set of dynamic feedback regulation logic is set up to ensure the stability and responsiveness of the battery system after the voltage conversion is completed. The specific steps are as follows:

[0077] Using the identified target matching voltage as the desired output reference, and by monitoring the current conversion output voltage in real time, a feedback adjustment coefficient is introduced as the starting point for deviation adjustment. The calculation expression is as follows:

[0078] In the formula, The standard matching voltage refers to the rated operating voltage level that best matches the device being charged, as determined by the system's identification logic (such as static voltage acquisition, noise rejection, and mean value determination). This refers to the current output voltage, which is the real-time voltage value output from the DC-DC voltage conversion module or regulation circuit to the port of the device to be charged, compared to the target voltage. Real-time comparison to determine whether the current output meets the target is the main input in the feedback control logic. It is the feedback adjustment coefficient, used to quantify the current output voltage. With target voltage The relative deviation ratio between them;

[0079] The feedback adjustment coefficient is applied to the module control gain to calculate the voltage correction amount, thereby obtaining the current required voltage adjustment step size, forming a closed-loop regulation. The calculation expression is as follows: In the formula, This is the module gain factor, representing the maximum adjustment speed of the voltage regulation system within each update cycle, i.e., the maximum allowable voltage change rate of the system per unit time, controlling the strength and sensitivity of the system's regulation action. Setting it too high may lead to voltage overshoot and system oscillation, while setting it too low will result in a slow adjustment process. Typical values ​​are 0.5V / s - 2.0V / s, and can be set and optimized according to the performance of different power modules. It is the voltage correction amount, which represents the voltage value that should be adjusted according to the deviation ratio and module gain in the current cycle. It is the actual step size of each output update. A positive value indicates an increase in output, and a negative value indicates a decrease in output. It ensures that the output voltage gradually approaches the target voltage, while suppressing oscillation and error accumulation.

[0080] The output value for the next cycle is adjusted according to the calculation results, and a dynamic update is performed, continuously refreshed in 10ms increments until the error between the target output voltage and the current output is less than 0.05V. The update formula is as follows: In the formula, The new output voltage value represents the voltage value that will be applied in the next control cycle after the battery control module adjusts the output. It is an instantaneous output decision made by the system based on the current state and control logic. It is implemented by the voltage regulation module to drive the power supply output to slowly approach the target voltage. The old output is calculated and replaced every update cycle (e.g., 10ms) to achieve dynamic voltage closed-loop adjustment.

[0081] This control method not only effectively improves voltage matching accuracy, but also ensures stable system output under conditions of sudden load changes, environmental interference, or changes in connection resistance. It has high reliability and fast response capability, and is particularly suitable for scenarios where multiple devices are frequently connected and voltage control requirements are high.

[0082] This step establishes a closed-loop voltage regulation control method based on error feedback to ensure the accuracy and stability of the voltage output process. After determining the target voltage level in the identification phase, directly implementing voltage jump output can easily lead to actual output deviations under conditions such as sudden load changes, equipment power-on jitter, and line impedance nonlinearity, resulting in abnormal equipment behavior or decreased system efficiency. To solve this problem, this mechanism introduces a feedback error calculation mechanism from control theory. It compares the relative difference between the current actual output voltage and the target voltage to form a standardized error quantity; then, combined with the system adjustment gain G (representing output capability and speed), it calculates the voltage correction amount within each adjustment cycle; by updating the output voltage value cycle by cycle (10ms), the system slowly approaches the target voltage, forming a dynamic closed-loop adjustment process. This method avoids the equipment impact and power supply jitter problems that may be caused by jump output, while balancing response speed and steady-state control. The system can adjust the gain factor according to the voltage error trend to realize adaptive voltage control strategies for various devices, which is an important part of achieving accurate and safe power output management. It is particularly suitable for complex applications such as vehicle power supply systems, embedded power management modules, and electronic platforms with multi-segment variable loads, improving their power supply flexibility and shock resistance.

[0083] This invention effectively solves the problem of feedback signal distortion caused by transient interference during the device identification stage by introducing an electrical state buffering mechanism and a multi-cycle voltage confirmation strategy. When the device is first connected, the sampling timing of the main control is delayed by using an isolation capacitor bank and a voltage stabilization filter module, which filters out voltage spikes generated at the moment of insertion and removal. Subsequently, combined with micro-current sampling and multiple repeated confirmation mechanisms, the accuracy of initial voltage identification is further improved. This combined strategy greatly reduces the false judgment rate while ensuring power supply response speed, providing a stable and accurate basis for subsequent output voltage matching, thereby avoiding the risk of circuit damage caused by erroneous high voltage output.

[0084] This invention further enhances the system's adaptability to complex electromagnetic environments by constructing an electromagnetic interference analysis mechanism and introducing a stability index (VSI) and a closed-loop adjustment function. High-frequency interference bands are identified and eliminated through spectrum analysis, and the sampled voltage is intelligently corrected based on the VSI judgment value, ensuring high stability of the identification results. During the voltage output stage, the closed-loop control function dynamically adjusts the output voltage according to time slices, quickly approaching the target voltage level while maintaining the error within an extremely low range. This ensures the electrical safety and power supply continuity of the device throughout the identification and charging process, effectively improving the system's safety, reliability, and intelligence level.

[0085] This invention also boasts excellent device compatibility and scalability, applicable to various terminal devices, voltage levels, and multi-interface power supply scenarios. During the identification and matching process, by constructing a fuzzy logic comparison mechanism and an attribution probability model, it no longer relies on a single voltage judgment threshold but dynamically analyzes adjacent voltage ranges to intelligently select the most suitable target output voltage level. This approach is particularly suitable for use in charging environments with multiple standards (such as USB-PD, QC, and proprietary protocols), effectively avoiding identification failures or poor adaptation issues caused by standard differences, and improving the system's compatibility and deployment flexibility in practical applications.

[0086] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0087] It should be noted that, in this document, the use of relational terms such as "first" and "second" is merely for distinguishing one entity or operation from another, and does not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0088] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0089] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0090] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0091] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0092] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

Claims

1. A battery control system based on the matching voltage of the battery to be charged, characterized in that, It includes a front-end signal buffer module, an initial static sampling module, a multi-cycle confirmation module, an anti-interference screening module, a target voltage identification module, and a voltage output control module. The front-end signal buffer module activates the electrical state buffering mechanism the moment the device to be charged is connected. It stabilizes the front-end input signal by delaying the sampling time of the main control circuit through the isolation capacitor bank and the voltage stabilizing filter module. The initial static sampling module acquires the static voltage signal of the device to be charged in micro-current mode under buffered conditions to determine the initial voltage level of the device. The multi-cycle confirmation module executes a multi-cycle signal confirmation program after the initial voltage judgment, which repeatedly collects three static signals using a timing control method and compares and verifies their average values. In the static voltage judgment stage, to suppress the judgment error caused by transient noise, electromagnetic interference, and sampling deviation, an adaptive voltage stability index calculation mechanism is introduced to improve the accuracy and robustness of voltage identification of the device to be charged. The specific steps are as follows: The average voltage of the three sampled values ​​is calculated as follows: In the formula, These represent the voltage values ​​obtained during three consecutive static voltage samplings at the initial stage of identifying the device to be charged. It is the average voltage; After obtaining the baseline voltage level, the sample variance is introduced, and the calculation formula is as follows: In the formula, It is the sample variance; The total electromagnetic interference energy within the current time period is extracted using a Fast Fourier Transform, and the calculation expression is as follows: In the formula, At frequency Below, the spectral power density obtained after the sampled signal undergoes a Fast Fourier Transform is... It is the total value of electromagnetic noise energy; The comprehensive voltage stability index is calculated using the following expression: In the formula, It is the voltage stability index. It is the standard deviation of the sampled voltage, i.e. ; The anti-interference screening module introduces an electromagnetic interference judgment mechanism to detect high-frequency interference characteristic values ​​in the sampled data and remove signal segments that exceed the interference threshold. The target voltage identification module compares the voltage level after multiple cycles of confirmation and interference removal with a preset voltage matching table to obtain the closest target output voltage level. The voltage output control module controls the output voltage conversion module to precisely adjust the battery output voltage to the target level, and executes voltage stabilization logic after the conversion is completed to start supplying power to the device to be charged.

2. The battery control system according to claim 1, characterized in that, In the electrical state buffering mechanism, the isolation capacitor bank consists of at least two series electrolytic capacitors and one parallel ceramic capacitor, where the electrolytic capacitors are used for high current filtering and the ceramic capacitors are used for high frequency interference absorption. The voltage stabilizing and filtering module has a built-in overvoltage clamping circuit. When the transient voltage exceeds the set safety threshold, it automatically diverts the current to the grounding line and slowly restores the operating voltage of the main control circuit through the soft start controller, so that the control system maintains electrical stability in the initial identification stage.

3. A battery control system based on the matching voltage of the charging element according to claim 1, characterized in that, In static voltage signal acquisition, the micro-current mode is provided by a constant current source, and its output current does not exceed 0.5mA, ensuring that it will not cause load interference to the device to be charged. The sampling controller completes a static measurement according to a preset time window and completes sampling at least three different times during the entire recognition period. Before each sampling, the internal noise shielding logic is activated to ensure that the sampling data is generated under interference-free conditions.

4. A battery control system based on the matching voltage of the charging element according to claim 1, characterized in that, In the multi-cycle signal confirmation procedure, a signal consistency verification mechanism is introduced; The difference between the maximum and minimum values ​​of the three static signal sampling results must not exceed a preset floating threshold. If the threshold is exceeded, the resampling logic is triggered. The resampling logic limits the number of retries to no more than two. After all samples pass the test, the average value will be stored in a temporary register and locked as the current device voltage reference value for subsequent comparison.

5. A battery control system according to claim 1, characterized in that, In the electromagnetic interference determination mechanism, the control system is equipped with a spectrum analysis module, which performs fast Fourier transform on the sampled signal in 25kHz units to extract the frequency band energy distribution characteristics. If the peak energy of any frequency band exceeds the set baseline, the current sampling is considered to be affected by high-frequency interference, and the current data is then disabled for the current time period.

6. A battery control system according to claim 1, characterized in that, During the target output voltage matching and comparison process, a fuzzy logic comparison model is adopted, which does not use a single voltage value as a threshold, but constructs a voltage range based on adjacent voltage levels; A confidence interval judgment mechanism is introduced. When the voltage sample value falls into the overlapping interval of two levels, the probability value of each level is calculated, and the level with the highest probability is taken as the output target, thereby enhancing the fault tolerance capability of the output voltage matching.

7. A battery control system according to claim 1, characterized in that, During the voltage output conversion stage, a set of dynamic feedback regulation logic is set up to ensure the stability and responsiveness of the battery system after the voltage conversion is completed. The specific steps are as follows: Using the identified target matching voltage as the desired output reference, and by monitoring the current conversion output voltage in real time, a feedback adjustment coefficient is introduced as the starting point for deviation adjustment. The calculation expression is as follows: In the formula, It is the standard matching voltage. This is the current conversion output voltage. It is the feedback adjustment coefficient; The feedback adjustment coefficient is applied to the module control gain to calculate the voltage correction amount, thereby obtaining the current required voltage adjustment step size, forming a closed-loop regulation. The calculation expression is as follows: In the formula, It is the module gain factor. It is a voltage correction amount; The output value for the next cycle is adjusted according to the calculation results, and a dynamic update is performed, continuously refreshing every 10ms until the error between the target output voltage and the current output is less than 0.05V. The update formula is as follows: In the formula, This is the new output voltage value.

8. A base station power supply, characterized in that, Includes a battery control system according to the matching voltage of the charging body as described in any one of claims 1-7.

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