A Fast Charging Optimization Method and Related Devices for an FFC Connector

Abstract

The present invention relates to the technical field of charging connectors, and discloses a fast charging optimization method and related device for an FFC connector. The method includes: performing hierarchical filtering and preprocessing on multi-source original sensing data for collecting the operating state of the connector, performing multi-scale decomposition and reconstruction on the preprocessed data and associating fast charging condition characteristics to obtain a connector condition characteristic spectrum; performing time series decomposition of preset fast charging characteristic components and predicting the condition evolution trend on the connector condition characteristic spectrum to obtain a variety of charging state prediction data, and determining the charging safety boundary and calculating multi-level thresholds of preset multiple fast charging constraint parameters for each charging state prediction data to obtain charging control parameter data; based on the charging control parameter data, controlling the FFC connector to perform monitoring of fast charging adjustment and state adjustment to obtain a fast charging optimization result. This application realizes the efficient and safe control of fast charging of the FFC connector.

Description

Technical Field

[0001] The present invention relates to the technical field of charging connectors, and particularly to a fast charging optimization method and related device for an FFC connector. Background Art

[0002] In the technical field of fast charging of electronic devices, as an important electrical connection component, real-time monitoring of the operating state and performance optimization of an FFC connector are key links to ensure the safety and reliability of fast charging. Especially in the scenario of high-current fast charging, the terminal contact state, temperature rise characteristics, and current-carrying capacity of the FFC connector directly affect the charging efficiency and service life. Therefore, developing an effective fast charging optimization method to monitor and regulate these key parameters is crucial for improving the charging performance of the FFC connector.

[0003] Existing technologies usually adopt a single temperature monitoring or current control method to optimize the charging process, or attempt to apply intelligent algorithms to the dynamic adjustment of charging parameters. However, these methods still have significant deficiencies in dealing with the multi-dimensional characteristics unique to FFC connectors: First, they ignore the non-linear characteristics of the terminal contact resistance changing with temperature and pressure, resulting in inaccurate monitoring of the contact state during the charging process; Second, they fail to effectively integrate the coupling relationships of multi-dimensional parameters such as temperature distribution, current density, and contact reliability, affecting the optimization effect of the charging strategy; Third, they insufficiently consider characteristics such as local overheating, uneven current distribution, and unstable contact pressure that occur during the fast charging process of the FFC connector, increasing the charging safety hazards. That is, the existing fast charging methods for FFC connectors are difficult to achieve comprehensive optimization of multi-dimensional charging characteristics, resulting in the inability to effectively guarantee the charging efficiency and safety. Summary of the Invention

[0004] The main objective of the present invention is to solve the problem that the existing fast charging methods for FFC connectors are difficult to achieve comprehensive optimization of multi-dimensional charging characteristics, resulting in the inability to effectively guarantee the charging efficiency and safety.

[0005] The first aspect of the present invention provides a method for optimizing fast charging of an FFC connector. The FFC connector includes a charging monitoring unit and a charging management unit. The method for optimizing fast charging of the FFC connector includes: using the charging monitoring unit to collect multi-source original sensing data corresponding to the operating state of the FFC connector, and performing hierarchical filtering and preprocessing on the multi-source original sensing data to obtain preliminary filtered data; performing multi-scale decomposition and reconstruction of various FFC connector features on the preliminary filtered data to obtain a connector state feature matrix, and correlating the fast charging working condition features of the connector state feature matrix to obtain a connector working condition feature spectrum; performing time series decomposition of preset fast charging feature components and prediction of the working condition evolution trend on the connector working condition feature spectrum to obtain various charging state prediction data, and determining the charging safety boundary and calculating multi-level thresholds of preset various fast charging constraint parameters for each charging state prediction data to obtain charging control parameter data; based on the charging control parameter data, using the charging management unit to control the FFC connector to monitor fast charging adjustment and state adjustment, and obtain the fast charging optimization result of the FFC connector.

[0006] Optionally, in the first implementation manner of the first aspect of the present invention, the multi-source original sensing data includes terminal contact area temperature data, cable connection temperature data, transmission current data, and transmission voltage data. The performing hierarchical filtering and preprocessing on the multi-source original sensing data to obtain preliminary filtered data includes: filtering high-frequency noise from the terminal contact area temperature data to obtain initial terminal temperature data, suppressing high-speed mutations of the cable connection temperature data to obtain initial cable temperature data, performing current segment filtering on the transmission current data to obtain current distribution data, and eliminating voltage interference from the transmission voltage data to obtain voltage change data; aligning the time stamps of the initial terminal temperature data, the initial cable temperature data, the current distribution data, and the voltage change data to obtain a time-aligned sequence, and performing delay calibration on the time-aligned sequence based on the acquisition delay parameters of the corresponding sensors of the charging monitoring unit to obtain preliminary filtered data.

[0007] Optionally, in the second implementation manner of the first aspect of the present invention, the multi-scale decomposition and reconstruction of the preliminary filtering data for various FFC connector features to obtain a connector state feature matrix includes: performing time series partitioning and difference calculation on the initial terminal temperature data in the preliminary filtering data to obtain a rapid temperature rise rate, and based on the terminal temperature safety threshold interval corresponding to the FFC connector, performing piecewise mapping of the threshold on the rapid temperature rise rate to obtain piecewise terminal temperature rise data; calculating the ratio of the piecewise terminal temperature rise data and the current distribution data to obtain the instantaneous terminal contact resistance value, and performing spatial mapping and heat conduction calculation of the heat source distribution on the initial cable temperature data and the instantaneous terminal contact resistance value in the preliminary filtering data to obtain a high-power temperature distribution feature; performing current density distribution calculation and current-carrying extreme value calculation on the current distribution data and the high-power temperature distribution feature in the preliminary filtering data to obtain the maximum current-carrying data of the connector, and performing voltage correlation mapping on the voltage change data and the maximum current-carrying data of the connector in the preliminary filtering data to generate a voltage fluctuation feature; based on preset fluctuation feature parameters, performing numerical calculation of the fluctuation interval and feature weighting calculation on the voltage fluctuation feature to generate a voltage stability feature, and based on the preset connector feature importance coefficient, performing numerical normalization and weighted fusion on the instantaneous terminal contact resistance value, the high-power temperature distribution feature, the maximum current-carrying data of the connector, and the voltage stability feature to obtain a fast charging feature vector; performing multi-dimensional feature transformation on the fast charging feature vector to obtain a feature transformation matrix, and extracting the working state features of the feature transformation matrix to obtain a connector state feature matrix.

[0008] Optionally, in the third implementation manner of the first aspect of the present invention, the association of the connector state feature matrix with fast charging operating condition features to obtain a connector operating condition feature spectrum includes: performing isothermal surface segmentation and temperature gradient calculation on the corresponding temperature state features in the connector state feature matrix to obtain a high-power temperature distribution map, and based on the preset unit cross-sectional area, performing area partitioning and standard deviation calculation on the corresponding current state features in the connector state feature matrix to obtain a current distribution map, and performing time series change value calculation and extraction of contact change features on the corresponding resistance state features in the connector state feature matrix to obtain a contact state map; performing spatial registration and correlation degree calculation on the temperature distribution map, the current distribution map, and the contact state map to obtain a feature correlation map, and performing feature clustering and operating condition feature marking on the feature correlation map to obtain fast charging operating condition type data; performing time-frequency transformation on the fast charging operating condition type data to obtain a fast charging operating condition spectrum, and performing principal component calculation and extraction of target operating condition features on the fast charging operating condition spectrum to generate a connector operating condition feature spectrum.

[0009] Optionally, in the fourth implementation manner of the first aspect of the present invention, the time-series decomposition of the preset fast-charging characteristic components and the prediction of the working condition evolution trend of the connector working condition characteristic spectrum are performed to obtain a variety of charging state prediction data, including: performing time-series division and extrapolation calculation on the working condition characteristics of the temperature component corresponding to the connector working condition characteristic spectrum to obtain a fast temperature rise prediction curve, and calculating the charging fluctuation value and performing charging power conversion on the working condition characteristics of the current component corresponding to the connector working condition characteristic spectrum to obtain a curve of the large power change borne by the terminal, and determining the time-varying characteristics and evaluating the contact state of the working condition characteristics of the resistance component corresponding to the connector working condition characteristic spectrum to obtain a terminal contact state curve; based on the tolerance threshold of the connector material corresponding to the FFC connector, performing piecewise fitting and threshold value comparison on the fast temperature rise prediction curve to obtain a terminal temperature risk value, and based on the rated power of the connector corresponding to the FFC connector, performing interval statistics and difference calculation on the curve of the large power change borne by the terminal to obtain a terminal power risk value, and based on the preset terminal contact pressure corresponding to the FFC connector, performing mutation detection and deviation calculation on the terminal contact state curve to obtain a contact reliability risk value; performing extreme value detection on the terminal temperature risk value, the power risk value, and the contact reliability risk value to obtain a variety of critical state data, and performing over-limit determination on each of the critical state data to obtain a variety of fast-charging state prediction data.

[0010] Optionally, in the fifth implementation manner of the first aspect of the present invention, the charging state prediction data includes terminal temperature rise prediction data, terminal power prediction data, and terminal contact state prediction data. Determining the charging safety boundary for each of the charging state prediction data and calculating multi-level thresholds for a variety of preset fast charging constraint parameters to obtain charging control parameter data includes: performing interval threshold segmentation on the terminal temperature rise data and extracting the current values in the corresponding temperature grading intervals to generate terminal temperature control values, and extracting the fluctuation intervals of the terminal power prediction data and calculating the maximum allowable current in the power fluctuation intervals to obtain terminal power limits, and performing time series fluctuation extraction on the terminal contact state prediction data and calculating the safety interval threshold of the contact pressure change value to obtain terminal contact thresholds; performing intersection operation and boundary contraction of the current values on the terminal temperature control values, the terminal power limits, and the terminal contact thresholds to obtain terminal operation boundary data, and performing equally spaced sampling on the current boundary values of the terminal operation boundary data to obtain a current sampling point sequence; performing fluctuation detection of the terminal temperature rise on adjacent points in the current sampling point sequence to obtain terminal stable working points, and based on a preset target operation strategy, calculating the charging efficiency and extracting the target operation points for the terminal stable working points to obtain target operation parameters; performing current control quantity conversion on the target operation parameters to obtain a charging control sequence, and dividing the charging control sequence into time periods to generate charging control parameter data.

[0011] Optionally, in the sixth implementation manner of the first aspect of the present invention, based on the charging control parameter data, using the charging management unit to control the FFC connector to monitor fast charging adjustment and status adjustment to obtain the fast charging optimization result of the FFC connector includes: segmenting and intercepting the charging control sequence in the charging control parameter data according to the corresponding charging time tags to obtain discrete control instructions, and performing proportional conversion on the discrete control instructions based on the rated current of the terminal corresponding to the FFC connector to obtain real-time control instructions; collecting temperature state response data corresponding to the real-time control instructions executed by the charging management unit controlling the FFC connector based on a preset terminal temperature acquisition instruction, and comparing the temperature state response data with a temperature threshold to obtain a temperature deviation value; performing safety range judgment and compensation calculation of the adjustment demand on the temperature deviation value to obtain a current correction value, and based on the current correction value, performing secondary update and execution on the real-time control instructions to obtain the fast charging optimization result of the FFC connector.

[0012] In a second aspect of the present invention, there is provided a fast charging optimization device for an FFC connector. The FFC connector includes a charging monitoring unit and a charging management unit. The fast charging optimization device for the FFC connector includes: a preprocessing module, configured to collect multi-source original sensing data corresponding to the operating state of the FFC connector by using the charging monitoring unit, and perform hierarchical filtering and preprocessing on the multi-source original sensing data to obtain preliminarily filtered data; a feature correlation module, configured to perform multi-scale decomposition and reconstruction of various FFC connector features on the preliminarily filtered data to obtain a connector state feature matrix, and perform correlation of fast charging condition features on the connector state feature matrix to obtain a connector condition feature spectrum; a trend prediction module, configured to perform time series decomposition of preset fast charging feature components and prediction of the condition evolution trend on the connector condition feature spectrum to obtain various charging state prediction data, and perform determination of charging safety boundaries and multi-level threshold calculation of preset various fast charging constraint parameters on each of the charging state prediction data to obtain charging control parameter data; a state optimization module, configured to, based on the charging control parameter data, use the charging management unit to control the FFC connector to monitor fast charging adjustment and state adjustment, and obtain the fast charging optimization result of the FFC connector.

[0013] In a third aspect of the present invention, there is provided a fast charging optimization device for an FFC connector, including: a memory and at least one processor, wherein instructions are stored in the memory; the at least one processor invokes the instructions in the memory so that the fast charging optimization device for the FFC connector executes each step of the above-mentioned fast charging optimization method for the FFC connector.

[0014] In a fourth aspect of the present invention, there is provided a computer-readable storage medium, wherein instructions are stored in the computer-readable storage medium, and when the instructions are run on a computer, the computer is caused to execute each step of the above-mentioned fast charging optimization method for the FFC connector.

[0015] The above-mentioned fast charging optimization method and related device for FFC connectors. In the embodiments of the present invention, a charging monitoring unit is adopted to collect multi-source original sensing data corresponding to the operating state of the FFC connector, and the multi-source original sensing data is subjected to hierarchical filtering and preprocessing to obtain preliminary filtered data; the preliminary filtered data is subjected to multi-scale decomposition and reconstruction of various FFC connector features to obtain a connector state feature matrix, and the connector state feature matrix is correlated with fast charging condition features to obtain a connector condition feature spectrum; the connector condition feature spectrum is subjected to time series decomposition of preset fast charging feature components and prediction of the condition evolution trend to obtain various charging state prediction data, and the charging safety boundary is determined for each charging state prediction data and multi-level threshold calculation of preset various fast charging constraint parameters is performed to obtain charging control parameter data; based on the charging control parameter data, the charging management unit is used to control the FFC connector to monitor fast charging adjustment and state adjustment, and the fast charging optimization result of the FFC connector is obtained. Compared with the prior art, the present application collects multi-dimensional sensing data of the FFC connector and performs hierarchical filtering preprocessing to obtain basic charging features, and performs multi-scale decomposition and reconstruction on these features to obtain a connector state feature matrix; furthermore, through fast charging condition correlation calculation and feature spectrum extraction, a condition feature spectrum is obtained and the charging state is mapped; finally, based on charging state prediction and multi-level threshold calculation, a charging control result is output. Through hierarchical data processing and feature analysis, the optimized control of fast charging of the FFC connector is realized. Especially in terms of terminal temperature rise, current distribution and contact reliability, the dynamic characteristics and fast charging safety of the connector are fully considered, and the charging efficiency is effectively improved; and a multi-level feature extraction and state prediction strategy is adopted, which not only realizes the correlation analysis between multi-dimensional charging parameters, but also enhances the reliability of the control strategy; in addition, through condition feature reconstruction and state monitoring, charging anomalies and optimization opportunities are accurately identified, so as to overall realize the efficient and safe control of fast charging of the FFC connector.

[0016] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the specification, claims and drawings.

[0017] To make the above objectives, features and advantages of the present invention more obvious and understandable, the following specific preferred embodiments are given, and in conjunction with the accompanying drawings, the detailed description is as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the first embodiment of the fast charging optimization method for the FFC connector in the embodiments of the present invention;

[0019] Figure 2Schematic diagram of an embodiment of the fast charging optimization device for the FFC connector in the embodiments of the present invention;

[0020] Figure 3 Schematic diagram of an embodiment of the fast charging optimization device for the FFC connector in the embodiments of the present invention. Specific implementation manners

[0021] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0022] The terms "including" and "having" and any variations thereof mentioned in the embodiments of the present invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but optionally further includes other unlisted steps or units, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0023] For ease of understanding of this embodiment, the specific process of the embodiments of the present invention will be described below. Please refer to Figure 1 , the first embodiment of the fast charging optimization method for the FFC connector in the embodiments of the present invention includes:

[0024] 101. Use a charging monitoring unit to collect multi-source raw sensing data corresponding to the operating state of the FFC connector, and perform hierarchical filtering and preprocessing on the multi-source raw sensing data to obtain preliminary filtered data;

[0025] Embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to obtain the best results in theory, methods, technologies, and application systems.

[0026] Artificial intelligence basic technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation / interaction systems, and mechatronics. Artificial intelligence software technologies mainly include several major directions such as computer vision technology, robotics, biometric technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0027] In this embodiment, the FFC connector includes a charging monitoring unit and a charging management unit. The charging monitoring unit may but is not limited to include a first temperature sensor for detecting the temperature of the terminal contact area, a second temperature sensor for detecting the temperature of the cable connection, a current sensor for detecting the charging current, and a voltage sensor for detecting the terminal voltage. The charging management unit may but is not limited to include a power conversion unit for high-current charging control, a heat dissipation unit for temperature regulation, and a control unit for data processing. The multi-source raw sensing data includes terminal contact area temperature data, cable connection temperature data, transmitted current data, and transmitted voltage data. High-frequency noise filtering is performed on the terminal contact area temperature data to obtain initial terminal temperature data, and high-speed mutation suppression is performed on the cable connection temperature data to obtain initial cable temperature data. Current segmentation filtering is performed on the transmitted current data to obtain current distribution data, and voltage interference elimination is performed on the transmitted voltage data to obtain voltage change data. Timestamp alignment is performed on the initial terminal temperature data, initial cable temperature data, current distribution data, and voltage change data to obtain a time-aligned sequence, and delay calibration is performed on the time-aligned sequence based on the acquisition delay parameters of the corresponding sensors of the charging monitoring unit to obtain preliminary filtered data.

[0028] In practical applications, the charging monitoring unit first collects multi-source sensing data on the operating state of the FFC connector. Among them, the first temperature sensor collects the temperature data of the terminal contact area in real time at a sampling frequency of 1 kHz, eliminates the high-frequency noise components above 50 Hz through a preset high-pass filter, and obtains accurate initial terminal temperature data; the second temperature sensor also collects the temperature data of the cable connection at a frequency of 1 kHz, and uses a mutation suppression algorithm based on wavelet transform to eliminate the mutation interference in the temperature data, and obtains stable initial cable temperature data; the current sensor uses a Hall effect sensor to perform high-precision sampling on the transmission current during charging, and smooths the current data through a segmented Kalman filtering algorithm to obtain current distribution data reflecting the current distribution characteristics; the voltage sensor uses a high-precision operational amplifier to sample the terminal voltage, eliminates the power frequency and its harmonic interference through a band-stop filter, and obtains accurate voltage change data; furthermore, considering the slight differences in the sampling timings of different sensors, the collected initial terminal temperature data, initial cable temperature data, current distribution data, and voltage change data are marked with unified timestamps, and these data are aligned to a unified time reference based on the timestamp information to generate a time-aligned sequence; furthermore, due to the different response times and signal transmission delays of various sensors, according to the pre-calibrated sensor acquisition delay parameters, the data in the time-aligned sequence is compensated for delay, and precise alignment of the data is achieved through an interpolation algorithm, and finally, the preliminary filtered data after complete preprocessing is obtained. For example: During a fast charging process, the initial temperature of the terminal contact area is 25 °C, and the charging current is 5 A. Through the above processing, the temperature noise fluctuation of ±0.5 °C can be effectively filtered out, the temperature mutation of 0.2 °C / ms caused by the sudden change of the charging current can be suppressed, and the accuracy of current measurement can reach ±0.1 A and the accuracy of voltage measurement can reach ±0.05 V; and after time alignment and calibration, the time synchronization error of the four-channel data is controlled within 0.1 ms. The entire data collection and preprocessing process fully considers the characteristics of the FFC connector in the fast charging scenario. Through the collaborative collection and preprocessing of multi-source data, the influence of various interference factors is effectively eliminated, ensuring the accuracy and timing consistency of the data, and laying a foundation for realizing accurate charging state monitoring and optimized control; especially when processing key parameters such as temperature, current, and voltage, targeted filtering and calibration strategies are adopted to ensure that the data can truly reflect the operating state of the FFC connector.

[0029] 102. Perform multi-scale decomposition and reconstruction of various FFC connector characteristics on the preliminary filtered data to obtain a connector state feature matrix, and correlate the connector state feature matrix with the fast charging condition characteristics to obtain a connector condition feature spectrum;

[0030] In this embodiment, the initial terminal temperature data in the preliminarily filtered data is divided into time series and differential calculation is performed to obtain the rapid temperature rise rate. Based on the terminal temperature safety threshold interval corresponding to the FFC connector, the rapid temperature rise rate is subjected to segmented mapping of thresholds to obtain the segmented terminal temperature rise data; the ratio of the segmented terminal temperature rise data and the current distribution data is calculated to obtain the instantaneous terminal contact resistance value, and the initial cable temperature data and the instantaneous terminal contact resistance value in the preliminarily filtered data are subjected to spatial mapping and heat conduction calculation of the heat source distribution to obtain the high-power temperature distribution characteristics; the distribution calculation of the current density and the calculation of the current-carrying extreme value are performed on the current distribution data and the high-power temperature distribution characteristics in the preliminarily filtered data to obtain the maximum current-carrying data of the connector, and the voltage change data and the maximum current-carrying data of the connector in the preliminarily filtered data are subjected to voltage correlation mapping to generate the voltage fluctuation characteristics; based on the preset fluctuation characteristic parameters, the voltage fluctuation characteristics are subjected to numerical calculation of the fluctuation interval and characteristic weighting calculation to generate the voltage stability characteristics, and based on the preset connector characteristic importance coefficient, the instantaneous terminal contact resistance value, the high-power temperature distribution characteristics, the maximum current-carrying data of the connector, and the voltage stability characteristics are subjected to numerical normalization and weighted fusion to obtain the fast charging feature vector; the fast charging feature vector is subjected to multi-dimensional feature transformation to obtain the feature transformation matrix, and the working state characteristics are extracted from the feature transformation matrix to obtain the connector state characteristic matrix; the corresponding temperature state characteristics in the connector state characteristic matrix are subjected to isothermal surface segmentation and temperature gradient calculation to obtain the high-power temperature distribution map, and based on the preset unit cross-sectional area, the corresponding current state characteristics in the connector state characteristic matrix are subjected to area division and standard deviation calculation to obtain the current distribution map, and the corresponding resistance state characteristics in the connector state characteristic matrix are subjected to time series change value calculation and contact change characteristic extraction to obtain the contact state map; the temperature distribution map, the current distribution map, and the contact state map are subjected to spatial registration and correlation calculation to obtain the feature correlation map, and the feature correlation map is subjected to feature clustering and working condition feature marking to obtain the fast charging working condition type data; the fast charging working condition type data is subjected to time-frequency transformation to obtain the fast charging working condition spectrum, and the principal component calculation and the extraction of the target working condition characteristics are performed on the fast charging working condition spectrum to generate the connector working condition characteristic spectrum.The fluctuation characteristic parameters here include the voltage fluctuation amplitude (the change range relative to the rated voltage, usually expressed as a percentage), the fluctuation frequency (the time characteristic of voltage fluctuation, that is, the number of fluctuations per unit time), the fluctuation duration (the duration of each fluctuation), the fluctuation slope (the speed characteristic of voltage change), the fluctuation periodicity (the repeated characteristic of voltage fluctuation), etc.; the importance coefficient of the connector characteristics here refers to the weight coefficient used to measure the influence degree of different characteristics on the fast charging performance of the FFC connector. For example, the temperature characteristic weight (0.4), the resistance characteristic weight (0.3), the current characteristic weight (0.2), and the voltage characteristic weight (0.1) can be set; the unit cross-sectional area here refers to the cross-sectional area perpendicular to the current flow direction of the terminals and wires of the FFC connector; the connector state characteristic matrix includes the temperature state characteristic, the current state characteristic, and the resistance state characteristic.

[0031] In practical applications, first, the initial terminal temperature data in the preliminary filtered data is divided into time series with a time window of every 100 ms, and the temperature change rate is obtained by using differential calculation within each time window, so as to obtain a rapid temperature rise rate reflecting the terminal temperature rise speed. Based on a preset terminal temperature safety threshold range (generally 25°C - 85°C), the rapid temperature rise rate is segmented and mapped, and the temperature rise rate is divided into three levels: low speed (less than 1°C / s), medium speed (1 - 2°C / s), and high speed (greater than 2°C / s), to obtain terminal temperature rise segmented data that can reflect the characteristics of temperature rise changes. Then, the ratio calculation of the corresponding moments of the terminal temperature rise segmented data and the current distribution data is carried out, and based on Ohm's law, the instantaneous contact resistance value characterizing the terminal contact quality is obtained. And the initial cable temperature data and the terminal instantaneous contact resistance value are subjected to spatial correlation analysis, that is, by establishing a heat source distribution model, the terminal contact area is divided into several tiny grids of 0.1 mm × 0.1 mm, and the temperature distribution of each grid point is calculated based on the heat conduction equation, and finally the temperature distribution characteristics of the connector in the high-power transmission state are obtained. Then, the current distribution data is associated with the high-power temperature distribution characteristics, the current density distribution per unit cross-sectional area is calculated, and combined with the influence of temperature on the wire resistivity, the current-carrying capacity of each point is obtained. By finding the maximum value point of the current density and considering the temperature limit factors, the maximum current-carrying data of the connector in the current state is calculated, and the voltage change data is associated with the maximum current-carrying data. By calculating the dynamic relationship between voltage and current, the voltage fluctuation characteristics reflecting the power supply stability of the connector are generated. Then, based on the preset fluctuation characteristic parameters (including voltage fluctuation amplitude, frequency, and duration, etc.), the range and degree of voltage fluctuation corresponding to the voltage fluctuation characteristics are calculated, and the voltage stability characteristics characterizing the voltage stability are obtained through characteristic weighted calculation. According to the preset characteristic importance coefficients (generally, the temperature characteristic weight is 0.4, the resistance characteristic weight is 0.3, the current characteristic weight is 0.2, and the voltage characteristic weight is 0.1), the terminal instantaneous contact resistance value, the high-power temperature distribution characteristics, the connector maximum current-carrying data, and the voltage stability characteristics are normalized and weighted and fused, and all characteristics are unified into the same numerical range, and finally the fast charging characteristic vector that can comprehensively reflect the charging performance of the connector is obtained. Then, multi-dimensional characteristic transformations such as principal component analysis are carried out on the fast charging characteristic vector, the main characteristic components are extracted and the characteristic space is reconstructed to obtain a characteristic transformation matrix. By carrying out characteristic clustering and pattern recognition on the characteristic transformation matrix, the characteristic combinations that can reflect different working states of the connector are extracted, and finally the connector state characteristic matrix including multi-dimensional information such as temperature state, resistance state, current state, and voltage state is obtained. It not only considers the mutual influence between various physical quantities, but also realizes the comprehensive characterization of the working state of the FFC connector through multi-level characteristic transformation and fusion, providing the necessary state information for realizing precise charging control.

[0032] Secondly, for the temperature state characteristics corresponding in the connector state characteristic matrix, by dividing the monitoring area of the FFC connector into isothermal surfaces according to a grid of 0.1 mm × 0.1 mm, calculating the temperature gradient between each grid point and its adjacent points, a high-power temperature distribution map reflecting the spatial distribution of the connector temperature is generated, and based on a preset unit cross-sectional area of 1 mm², the current state characteristics are spatially divided, the standard deviation of the current density in each area is calculated, and a current distribution map characterizing the uniformity of the current distribution is generated. For the resistance state characteristics, by calculating the change rate of the contact resistance within a continuous time window and extracting the mutation points and change trends therein, a contact state map reflecting the change of the terminal contact state is obtained; furthermore, the spatial coordinate mapping method is used to perform spatial registration on the temperature distribution map, the current distribution map, and the contact state map to ensure the corresponding relationship of the three maps in terms of spatial position, and by calculating the cross-correlation coefficient and covariance matrix between different characteristics, a characteristic correlation map characterizing the correlation relationship between each characteristic is obtained; and the K-means clustering algorithm is applied to the characteristic correlation map for feature grouping, and each type of feature combination is marked based on a preset working condition characteristic template, and finally, fast charging working condition type data including different working condition types such as normal charging, fast charging, overheat warning, etc. are obtained; furthermore, wavelet transform is performed on the fast charging working condition type data to convert the time-domain information to the time-frequency domain, and a fast charging working condition spectrum that can simultaneously reflect the working condition change frequency and time characteristics is obtained, and by performing principal component analysis on the working condition spectrum, the main feature components with a contribution rate exceeding 95% (i.e., the target working condition characteristics) are extracted, and the working condition feature space is reconstructed by combining these main features, and finally, a connector working condition characteristic spectrum that can comprehensively characterize the charging working condition of the FFC connector is generated (where this working condition characteristic spectrum not only includes multi-dimensional characteristic information such as temperature, current, and contact state, but also reflects the evolution law of these characteristics over time). Through multi-level feature extraction and fusion, the conversion from local features to global working conditions is realized, especially when dealing with high-power fast charging scenarios, the change characteristics of various physical quantities and their mutual influences can be accurately captured.

[0033] 103. Perform time series decomposition of the preset fast charging feature components and prediction of the working condition evolution trend on the connector working condition characteristic spectrum to obtain a variety of charging state prediction data, and determine the charging safety boundary for each charging state prediction data and calculate the multi-level thresholds of a variety of preset fast charging constraint parameters to obtain charging control parameter data;

[0034] In this embodiment, the charging state prediction data includes terminal temperature rise prediction data, terminal power prediction data, and terminal contact state prediction data. The time series division and extrapolation calculation are performed on the working condition characteristics corresponding to the temperature component in the connector working condition characteristic spectrum to obtain the rapid temperature rise prediction curve. The charging fluctuation value calculation and charging power conversion are performed on the working condition characteristics corresponding to the current component in the connector working condition characteristic spectrum to obtain the curve of the maximum power carried by the terminal. The determination of the time-varying characteristics and the contact state evaluation are performed on the working condition characteristics corresponding to the resistance component in the connector working condition characteristic spectrum to obtain the terminal contact state curve. Based on the tolerance threshold of the connector material corresponding to the FFC connector, the rapid temperature rise prediction curve is segmented and fitted, and the threshold values are compared to obtain the terminal temperature risk value. Based on the rated power of the connector corresponding to the FFC connector, the interval statistics and difference calculation are performed on the curve of the maximum power carried by the terminal to obtain the terminal power risk value. Based on the preset terminal contact pressure corresponding to the FFC connector, the mutation detection and deviation calculation are performed on the terminal contact state curve to obtain the contact reliability risk value. The extreme value detection is performed on the terminal temperature risk value, power risk value, and contact reliability risk value to obtain various critical state data, and the over-limit determination is performed on each critical state data to obtain various fast charging state prediction data. The interval threshold segmentation is performed on the terminal temperature rise data, and the current values in the corresponding temperature grading intervals are extracted to generate the terminal temperature control values. The fluctuation intervals are extracted from the terminal power prediction data, and the maximum allowable current in the power fluctuation intervals is calculated to obtain the terminal power limit values. The time series fluctuations are extracted from the terminal contact state prediction data, and the safety interval threshold values of the contact pressure change values are calculated to obtain the terminal contact thresholds. The intersection operation and boundary contraction of the current values are performed on the terminal temperature control values, terminal power limit values, and terminal contact thresholds to obtain the terminal operation boundary data, and the equal-interval sampling of the current boundary values is performed on the terminal operation boundary data to obtain the current sampling point sequence. The fluctuation detection of the terminal temperature rise is performed on adjacent points in the current sampling point sequence to obtain the terminal stable working points, and based on the preset target operation strategy, the charging efficiency calculation and the extraction of the target operation points are performed on the terminal stable working points to obtain the target operation parameters. The current control quantity conversion is performed on the target operation parameters to obtain the charging control sequence, and the charging control sequence is divided into time periods to generate the charging control parameter data. The fast charging characteristic components here include temperature characteristic components, current characteristic components, and contact state characteristic components. The terminal contact pressure here refers to the positive pressure between the connector terminal and the mating terminal. The various fast charging constraint parameters here refer to temperature constraint parameters, current constraint parameters, contact state constraint parameters, and power constraint parameters. The target operation strategy here refers to the set of control objectives that achieve the optimal charging efficiency on the premise of ensuring safety.

[0035] In practical applications, first, the temperature component working condition characteristics in the working condition characteristic spectrum are divided into time series at a time interval of 0.5 s. The historical temperature data is analyzed by using the adaptive Kalman filtering algorithm, and the exponential smoothing method is combined to extrapolate the temperature change trend in the next 30 s, so as to obtain a rapid temperature rise prediction curve reflecting the terminal temperature rise trend. For the current component working condition characteristics, the charging fluctuation value is obtained by calculating the standard deviation of the current fluctuation per unit time, and the power is calculated in combination with the terminal voltage value to generate a high-power change curve characterizing the terminal carrying capacity. For the resistance component working condition characteristics, by analyzing the time-varying characteristics and fluctuation rules of the resistance value and combining the stability evaluation index of the contact state, a terminal contact state curve reflecting the change of the terminal contact quality is obtained. Furthermore, in order to evaluate various risks during the charging process, based on the tolerance threshold of the connector material corresponding to the FFC connector (such as the 85 °C tolerance threshold of the copper alloy material used), the rapid temperature rise prediction curve is linearly fitted in segments. By calculating the difference ratio between the predicted temperature and the threshold, the terminal temperature risk value characterizing the temperature safety margin is obtained. Based on the rated power of the FFC connector (such as the rated power index of 200 W), the interval statistical analysis is carried out on the terminal high-power change curve. By calculating the difference ratio between the actual power and the rated power, the terminal power risk value characterizing the degree of power overrun is obtained. For the evaluation of the contact state, based on the preset terminal contact pressure corresponding to the FFC connector (such as the preset terminal contact pressure standard of 2 N), the mutation detection algorithm based on wavelet transform is applied to the terminal contact state curve. By calculating the cumulative amount of the contact state deviation, the contact reliability risk value characterizing the contact reliability is obtained. Then, the extreme value detection is carried out on the three types of risk values obtained. By finding the local maximum points of various risk indicators, a variety of critical state data including the temperature critical state, power critical state, and contact critical state are obtained. By comparing these critical state data with the preset safety thresholds (temperature risk threshold 0.8, power risk threshold 0.9, and contact risk threshold 0.85), a variety of fast charging state prediction data reflecting the future operating state of the FFC connector are finally obtained (wherein, these data not only include the development trends of various risks, but also provide safety margin information under different working conditions). Through multi-dimensional state prediction and risk assessment, a comprehensive assessment of the charging safety of the FFC connector is realized. Especially when dealing with high-power fast charging scenarios, potential safety hazards can be warned in time.

[0036] Secondly, the terminal temperature rise data is segmented by interval thresholds at a temperature interval of 5°C, dividing the temperature range into multiple hierarchical intervals (25 - 30°C, 30 - 35°C, 35 - 40°C, etc.), and the safety current values corresponding to each temperature interval are extracted from the historical data. Through this temperature-current mapping relationship, the terminal temperature control values are generated. For the terminal power prediction data, the power fluctuation range is determined by statistically analyzing the peak and valley values of the power fluctuations, and based on the square relationship between power and current, the maximum allowable current value under each power fluctuation range is calculated, thereby obtaining the terminal power limit. For the terminal contact state prediction data, by analyzing the temporal variation law of the contact pressure, the standard deviation of the pressure fluctuation is calculated, and based on the standard contact pressure of 2N, the safety fluctuation range is determined, and finally the terminal contact threshold is obtained. Furthermore, an intersection operation is performed on the current values corresponding to the terminal temperature control values, the terminal power limit, and the terminal contact threshold to obtain the current range that simultaneously meets the requirements of temperature control, power limitation, and contact reliability. Through a shrinkage boundary operation (usually shrinking by a margin of 10%), more conservative terminal operating boundary data is obtained. Based on these boundary data, the current range is evenly sampled at an interval of 0.1A to generate a sequence of current sampling points to be evaluated. Then, by analyzing the temperature rise fluctuation of adjacent sampling points, the changing trend of the temperature rise rate is calculated, and the stable operating points with a temperature rise fluctuation less than 0.5°C / s are selected. Then, based on a preset target operation strategy (giving priority to charging efficiency while ensuring that the temperature rise rate does not exceed 1°C / s), the selected terminal stable operating points are evaluated. The charging efficiency is obtained by calculating the ratio of the input power to the effective charging power using a multi-objective optimization function, and combined with the constraint condition of the temperature rise rate, the operating point with the highest charging efficiency and meeting the temperature rise requirements is selected as the target operation parameter, where the multi-objective optimization function is:

[0037] ;

[0038] Among them, 、 、 are weight coefficients, ΔT is the temperature rise value, P is the operating power, R is the contact resistance, is the maximum allowable temperature rise value, which is the highest temperature rise that the FFC connector can withstand, is the rated power, is the reference contact resistance, and the optimal operating point is selected by minimizing the J value. Then, the target operation parameters are converted into actual current control quantities, a detailed charging control sequence is generated, and the control sequence is segmented by time according to different stages of the charging process (such as pre-charging stage, constant current charging stage, constant voltage charging stage, etc.), and finally, complete charging control parameter data is generated. The balance between charging efficiency and safety is achieved, especially in dealing with high-current fast charging scenarios, accurately grasping the relationship between charging power and temperature rise rate.

[0039] 104. Based on the charging control parameter data, use the charging management unit to monitor the fast charging adjustment and status adjustment of the FFC connector, and obtain the fast charging optimization result of the FFC connector.

[0040] In this embodiment, segment the charging control sequence in the charging control parameter data according to the corresponding charging time tags to obtain discrete control instructions, and perform proportional conversion on the discrete control instructions based on the rated current of the terminals corresponding to the FFC connector to obtain real-time control instructions; based on the preset terminal temperature acquisition instruction, collect the temperature status response data corresponding to the real-time control instruction executed by the charging management unit to control the FFC connector, and compare the temperature status response data with the temperature threshold to obtain a temperature deviation value; perform a safety range judgment and compensation calculation of the adjustment demand on the temperature deviation value to obtain a current correction value, and based on the current correction value, perform secondary update and execution on the real-time control instruction to obtain the fast charging optimization result of the FFC connector. The terminal temperature acquisition instruction here refers to the instruction for standardizing the data acquisition of the terminal temperature of the FFC connector according to these preset acquisition parameters and control requirements.

[0041] In practical applications, the charging control sequence in the charging control parameter data is segmented and intercepted at 10 ms time intervals, converting the continuous control sequence into discrete control instruction points. Based on the terminal rated current of the FFC connector (usually 10 A), these discrete control instructions are proportionally converted to convert the theoretical control value into the actual current control quantity, thus obtaining real-time control instructions that can be directly used for control execution to ensure the execution accuracy and timing accuracy of the control instructions. Furthermore, during the control execution process, based on the terminal temperature acquisition instruction with a preset sampling frequency of 1 kHz, the first temperature sensor and the second temperature sensor in the charging monitoring unit are used to collect the temperature state response data of the FFC connector during the execution of the control instructions in real time, including the terminal contact area temperature and the cable connection temperature. The collected temperature state response data is compared with the preset safe temperature threshold (usually 85 °C) in real time, and the difference between the actual temperature and the threshold is calculated to obtain the temperature deviation value reflecting the safety margin of the current charging state. Furthermore, to ensure the safety and stability of the charging process, when the temperature deviation value falls within the safe range (the temperature is more than 10 °C below the threshold), the current charging strategy is maintained; when the temperature deviation value approaches the warning range (the temperature is less than 10 °C away from the threshold), the required current adjustment amount is calculated through a preset compensation algorithm, and based on the quadratic relationship model between temperature and current, the current correction value for optimized control is obtained. Furthermore, the current correction value is superimposed on the original real-time control instruction, and the updated control instruction is executed through the power conversion unit in the charging management unit, while cooperating with the coordinated work of the heat dissipation unit, ultimately realizing the fast charging optimization control of the FFC connector under the premise of ensuring safety. Through real-time temperature monitoring and dynamic control adjustment, the safety and efficiency of the fast charging process are ensured. Especially in dealing with the large current fast charging scenario, it can respond to temperature changes in a timely manner and make appropriate control adjustments, effectively preventing the occurrence of safety hazards such as overheating.

[0042] In the embodiments of the present invention, by collecting multi-dimensional sensing data of the FFC connector and performing hierarchical filtering preprocessing, basic charging characteristics are obtained, and these characteristics are subjected to multi-scale decomposition and reconstruction to obtain a connector state feature matrix. Furthermore, through fast charging condition correlation calculation and feature spectrum extraction, a condition feature spectrum is obtained and mapped to the charging state. Finally, based on charging state prediction and multi-level threshold calculation, a charging control result is output. Through hierarchical data processing and feature analysis, the optimal control of fast charging of the FFC connector is realized. Especially in terms of terminal temperature rise, current distribution, and contact reliability, the dynamic characteristics and fast charging safety of the connector are fully considered, effectively improving the charging efficiency. And a multi-level feature extraction and state prediction strategy is adopted, which not only realizes the correlation analysis between multi-dimensional charging parameters but also enhances the reliability of the control strategy. In addition, through condition feature reconstruction and state monitoring, charging anomalies and optimization opportunities are accurately identified, thus realizing the efficient and safe control of fast charging of the FFC connector as a whole.

[0043] The fast charging optimization method of the FFC connector in the embodiments of the present invention has been described above. Next, the fast charging optimization device of the FFC connector in the embodiments of the present invention will be described. Please refer to Figure 2 , an embodiment of the fast charging optimization device of the FFC connector in the embodiments of the present invention includes:

[0044] A preprocessing module 201, configured to collect multi-source original sensing data corresponding to the operating state of the FFC connector by using the charging monitoring unit, and perform hierarchical filtering and preprocessing on the multi-source original sensing data to obtain preliminary filtered data;

[0045] A feature correlation module 202, configured to perform multi-scale decomposition and reconstruction of various FFC connector features on the preliminary filtered data to obtain a connector state feature matrix, and perform correlation of fast charging condition features on the connector state feature matrix to obtain a connector condition feature spectrum;

[0046] A trend prediction module 203, configured to perform time series decomposition of preset fast charging feature components and prediction of condition evolution trends on the connector condition feature spectrum to obtain multiple charging state prediction data, and determine the charging safety boundary and perform multi-level threshold calculation of preset multiple fast charging constraint parameters on each charging state prediction data to obtain charging control parameter data;

[0047] A state optimization module 204, configured to monitor the fast charging adjustment and state adjustment of the FFC connector by using the charging management unit based on the charging control parameter data to obtain the fast charging optimization result of the FFC connector.

[0048] In the embodiments of the present invention, by collecting multi-dimensional sensing data of the FFC connector and performing hierarchical filtering preprocessing, basic charging characteristics are obtained, and these characteristics are subjected to multi-scale decomposition and reconstruction to obtain a connector state feature matrix. Furthermore, through fast charging condition correlation calculation and feature spectrum extraction, a condition feature spectrum is obtained and the charging state is mapped. Finally, based on charging state prediction and multi-level threshold calculation, a charging control result is output. Through hierarchical data processing and feature analysis, the optimal control of fast charging of the FFC connector is realized. Especially in terms of terminal temperature rise, current distribution, and contact reliability, the dynamic characteristics and fast charging safety of the connector are fully considered, effectively improving the charging efficiency. And by adopting a multi-level feature extraction and state prediction strategy, the correlation analysis between multi-dimensional charging parameters is realized, and the reliability of the control strategy is enhanced. In addition, through condition feature reconstruction and state monitoring, charging anomalies and optimization opportunities are accurately identified, thus realizing the efficient and safe control of fast charging of the FFC connector as a whole.

[0049] Above Figure 2 The fast charging optimization device of the FFC connector in the embodiments of the present invention is described in detail from the perspective of modular functional entities. Next, the fast charging optimization device of the FFC connector in the embodiments of the present invention is described in detail from the perspective of hardware processing.

[0050] Figure 3 FIG. is a schematic structural diagram of a fast charging optimization device of an FFC connector provided by an embodiment of the present invention. The fast charging optimization device 300 of the FFC connector may vary greatly due to configuration or performance, and may include one or more processors (central processing units, CPUs) 310 (for example, one or more processors) and a memory 320, and one or more storage media 330 for storing application programs 333 or data 332 (for example, one or more mass storage devices). Among them, the memory 320 and the storage media 330 may be transient storage or persistent storage. The program stored in the storage media 330 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the fast charging optimization device 300 of the FFC connector. Further, the processor 310 may be configured to communicate with the storage media 330 and execute a series of instruction operations in the storage media 330 on the fast charging optimization device 300 of the FFC connector.

[0051] The fast charging optimization device 300 for the FFC connector may further include one or more power supplies 340, one or more wired or wireless network interfaces 350, one or more input / output interfaces 360, and / or one or more operating systems 331, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, and so on. Those skilled in the art can understand that Figure 3 The structure of the fast charging optimization device for the FFC connector shown does not constitute a limitation on the fast charging optimization device for the FFC connector, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0052] The present invention also provides a fast charging optimization device for an FFC connector. The computer device includes a memory and a processor. When computer-readable instructions stored in the memory are executed by the processor, the processor is caused to execute each step of the fast charging optimization method for the FFC connector in the above-mentioned embodiments.

[0053] The present invention also provides a computer-readable storage medium. The computer-readable storage medium may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are run on a computer, the computer is caused to execute each step of the fast charging optimization method for the FFC connector.

[0054] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0055] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in various embodiments of the present invention. The foregoing storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs and other various media that can store program codes.

[0056] This application can be used in numerous general-purpose or special-purpose computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and so on. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0057] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A fast charging optimization method for an FFC connector, the FFC connector comprising a charging monitoring unit and a charging management unit, characterized in that: The fast charging optimization method of the FFC connector includes: The charging monitoring unit is used to collect multi-source original sensor data corresponding to the operating state of the FFC connector, wherein the multi-source original sensor data includes terminal contact area temperature data, cable connection temperature data, transmission current data and transmission voltage data, and the terminal contact area temperature data is subjected to high-frequency noise filtering to obtain terminal temperature initial data, and the cable connection temperature data is subjected to high-speed mutation suppression to obtain cable temperature initial data, and the transmission current data is subjected to current segmentation filtering to obtain current distribution data, and the transmission voltage data is subjected to voltage interference elimination to obtain voltage change data; the terminal temperature initial data, the cable temperature initial data, the current distribution data and the voltage change data are timestamped to obtain a time alignment sequence, and the time alignment sequence is subjected to delay calibration based on the acquisition delay parameter of the corresponding sensor of the charging monitoring unit to obtain preliminary filtering data; The initial terminal temperature data in the preliminary filtering data is divided into time series and differentially calculated to obtain a rapid temperature rise rate, and based on the terminal temperature safety threshold interval corresponding to the FFC connector, the rapid temperature rise rate is segmented by threshold mapping to obtain terminal temperature rise segmented data; the terminal temperature rise segmented data and the current distribution data are ratio-calculated to obtain the instantaneous contact resistance value of the terminal, and the cable temperature initial data and the instantaneous contact resistance value of the terminal in the preliminary filtering data are spatially mapped and heat conduction calculated to obtain high-power temperature distribution characteristics; the current distribution data in the preliminary filtering data and the high-power temperature distribution characteristics are distributed and calculated as the current density, and the maximum current carrying data of the connector is obtained, and the preliminary filtering data is compared with the initial terminal temperature data and the instantaneous contact resistance value of the terminal. The voltage change data in the voltage transformer and the maximum current carrying data of the connector are subjected to voltage correlation mapping to generate voltage fluctuation characteristics; based on preset fluctuation characteristic parameters, the voltage fluctuation characteristics are subjected to numerical calculation of fluctuation intervals and feature weighted calculation to generate voltage stability characteristics, and based on preset connector feature importance coefficients, the instantaneous contact resistance value of the terminal, the high-power temperature distribution characteristics, the maximum current carrying data of the connector and the voltage stability characteristics are subjected to numerical normalization and weighted fusion to obtain a fast charging feature vector; a multi-dimensional feature transformation is performed on the fast charging feature vector to obtain a feature conversion matrix, and working state characteristics are extracted from the feature conversion matrix to obtain a connector state feature matrix, and the connector state feature matrix is ​​associated with fast charging working condition characteristics to obtain a connector working condition feature spectrum; Performing time series decomposition of preset fast charging characteristic components and prediction of working condition evolution trend on the connector working condition characteristic spectrum to obtain multiple charging state prediction data, and determining charging safety boundaries and presetting multi-level threshold calculation of multiple fast charging constraint parameters on each of the charging state prediction data to obtain charging control parameter data; Based on the charging control parameter data, the charging management unit is used to control the FFC connector to perform fast charging adjustment and state adjustment monitoring to obtain a fast charging optimization result of the FFC connector.

2. The fast charging optimization method of the FFC connector according to claim 1, characterized in that: The associating the fast charging condition characteristics of the connector state characteristic matrix to obtain the connector condition characteristic spectrum includes: The corresponding temperature state features in the connector state feature matrix are segmented on isothermal surfaces and the temperature gradient is calculated to obtain a high-power temperature distribution map, and the corresponding current state features in the connector state feature matrix are divided into areas and the standard deviation is calculated based on a preset unit cross-sectional area to obtain a current distribution map, and the corresponding resistance state features in the connector state feature matrix are calculated by timing change values ​​and contact change features are extracted to obtain a contact state map; Performing spatial registration and correlation calculation on the temperature distribution map, the current distribution map, and the contact state map to obtain a feature correlation map, and performing feature clustering and operating condition feature marking on the feature correlation map to obtain fast charging operating condition type data; The fast charging condition type data is subjected to time-frequency transformation to obtain a fast charging condition spectrum, and the main component calculation and target condition feature extraction are performed on the fast charging condition spectrum to generate a connector condition feature spectrum.

3. The fast charging optimization method of the FFC connector according to claim 1, characterized in that: The connector working condition characteristic spectrum is subjected to time series decomposition of preset fast charging characteristic components and prediction of working condition evolution trend to obtain a variety of charging state prediction data, including: Perform time-series division and extrapolation calculation on the working condition characteristics of the corresponding temperature component in the working condition characteristic spectrum of the connector to obtain a rapid temperature rise prediction curve, perform charging fluctuation value calculation and charging power conversion on the working condition characteristics of the corresponding current component in the working condition characteristic spectrum of the connector to obtain a terminal high-power bearing change curve, and perform time-varying feature determination and contact state evaluation on the working condition characteristics of the corresponding resistance component in the working condition characteristic spectrum of the connector to obtain a terminal contact state curve; Based on the FFC connector, the rapid temperature rise prediction curve is segmentedly fitted and the threshold value is compared to obtain a terminal temperature risk value, and based on the connector rated power corresponding to the FFC connector, the terminal high power carrying change curve is interval-statisticed and difference-calculated to obtain a terminal power risk value, and based on the preset terminal contact pressure corresponding to the FFC connector, the terminal contact state curve is subjected to mutation detection and deviation calculation to obtain a contact reliability risk value; Extreme value detection is performed on the terminal temperature risk value, the power risk value and the contact reliability risk value to obtain a variety of critical state data, and over-limit judgment is performed on each of the critical state data to obtain a variety of fast charging state prediction data.

4. The fast charging optimization method of the FFC connector according to claim 1, characterized in that: The charging state prediction data includes terminal temperature rise prediction data, terminal power prediction data, and terminal contact state prediction data. The charging safety boundary is determined for each of the charging state prediction data and a multi-level threshold calculation of multiple fast charging constraint parameters is preset to obtain charging control parameter data, including: The terminal temperature rise prediction data is segmented into interval thresholds and the current value of the corresponding temperature classification interval is extracted to generate a terminal temperature control value, and the fluctuation interval of the terminal power prediction data is extracted and the maximum allowable current of the power fluctuation interval is calculated to obtain the terminal power limit, and the timing fluctuation of the terminal contact state prediction data is extracted and the safety interval threshold of the contact pressure change value is calculated to obtain the terminal contact threshold; Performing an intersection operation of current values ​​and boundary shrinkage on the terminal temperature control value, the terminal power limit value, and the terminal contact threshold value to obtain terminal operation boundary data, and performing equal-interval sampling of current boundary values ​​on the terminal operation boundary data to obtain a current sampling point sequence; Performing fluctuation detection of terminal temperature rise on adjacent points in the current sampling point sequence to obtain a stable terminal operating point, and performing charging efficiency calculation and target operating point extraction on the stable terminal operating point based on a preset target operating strategy to obtain a target operating parameter; The target operating parameter is converted into a current control amount to obtain a charging control sequence, and the charging control sequence is divided into time periods to generate charging control parameter data.

5. The fast charging optimization method of the FFC connector according to claim 4, characterized in that: The method of controlling the FFC connector to perform fast charging adjustment and state adjustment monitoring using the charging management unit based on the charging control parameter data to obtain a fast charging optimization result of the FFC connector includes: The charging control sequence in the charging control parameter data is segmented and intercepted corresponding to the charging time tag to obtain a discrete control instruction, and the discrete control instruction is proportionally converted based on the terminal rated current corresponding to the FFC connector to obtain a real-time control instruction; Based on a preset terminal temperature collection instruction, the temperature state response data corresponding to the real-time control instruction executed by the charging management unit to control the FFC connector is collected, and the temperature state response data is compared with a temperature threshold to obtain a temperature deviation value; A safety range judgment and a compensation calculation of the adjustment demand are performed on the temperature deviation value to obtain a current correction value, and based on the current correction value, the real-time control instruction is updated and executed for a second time to obtain a fast charging optimization result of the FFC connector.

6. A fast charging optimization device for an FFC connector, the FFC connector comprising a charging monitoring unit and a charging management unit, characterized in that: The fast charging optimization device of the FFC connector comprises: A preprocessing module, for collecting multi-source original sensor data corresponding to the operating state of the FFC connector by using the charging monitoring unit, wherein the multi-source original sensor data includes terminal contact area temperature data, cable connection temperature data, transmission current data and transmission voltage data, and performing high-frequency noise filtering on the terminal contact area temperature data to obtain terminal temperature initial data, and performing high-speed mutation suppression on the cable connection temperature data to obtain cable temperature initial data, and performing current segmentation filtering on the transmission current data to obtain current distribution data, and performing voltage interference elimination on the transmission voltage data to obtain voltage change data; performing timestamp alignment on the terminal temperature initial data, the cable temperature initial data, the current distribution data and the voltage change data to obtain a time alignment sequence, and performing delay calibration on the time alignment sequence based on the acquisition delay parameter of the corresponding sensor of the charging monitoring unit to obtain preliminary filtered data; A feature association module is used to perform time-series division and differential calculation on the initial terminal temperature data in the preliminary filtering data to obtain a rapid temperature rise rate, and based on the terminal temperature safety threshold interval corresponding to the FFC connector, perform segmented mapping of the threshold on the rapid temperature rise rate to obtain terminal temperature rise segmented data; perform ratio calculation on the terminal temperature rise segmented data and the current distribution data to obtain the terminal instantaneous contact resistance value, and perform spatial mapping of heat source distribution and heat conduction calculation on the cable temperature initial data and the terminal instantaneous contact resistance value in the preliminary filtering data to obtain high-power temperature distribution characteristics; perform current density distribution calculation and current extreme value calculation on the current distribution data in the preliminary filtering data and the high-power temperature distribution characteristics to obtain the maximum current carrying data of the connector, and perform ratio calculation on the terminal temperature rise segmented data and the current distribution data to obtain the terminal instantaneous contact resistance value; and perform spatial mapping of heat source distribution and heat conduction calculation on the cable temperature initial data and the terminal instantaneous contact resistance value in the preliminary filtering data to obtain high-power temperature distribution characteristics. The voltage change data in the step-filtered data and the maximum current carrying data of the connector are voltage-correlated mapped to generate voltage fluctuation characteristics; based on preset fluctuation characteristic parameters, the voltage fluctuation characteristics are numerically calculated and feature-weighted calculated to generate voltage stability characteristics, and based on a preset connector feature importance coefficient, the instantaneous contact resistance value of the terminal, the high-power temperature distribution characteristics, the maximum current carrying data of the connector and the voltage stability characteristics are numerically normalized and weightedly fused to obtain a fast charging feature vector; a multi-dimensional feature transformation is performed on the fast charging feature vector to obtain a feature conversion matrix, and working state characteristics are extracted from the feature conversion matrix to obtain a connector state feature matrix, and the connector state feature matrix is ​​associated with fast charging working condition characteristics to obtain a connector working condition feature spectrum; A trend prediction module, used to perform time series decomposition of preset fast charging characteristic components and prediction of working condition evolution trend on the connector working condition characteristic spectrum, obtain multiple charging state prediction data, determine charging safety boundaries for each of the charging state prediction data, and perform multi-level threshold calculation of preset multiple fast charging constraint parameters to obtain charging control parameter data; The state optimization module is used to control the FFC connector to perform fast charging adjustment and state adjustment monitoring based on the charging control parameter data using the charging management unit to obtain a fast charging optimization result of the FFC connector.

7. A fast charging optimization device for an FFC connector, characterized in that: The fast charging optimization device of the FFC connector includes: a memory and at least one processor, wherein the memory stores instructions; The at least one processor calls the instructions in the memory to enable the fast charging optimization device of the FFC connector to perform each step of the fast charging optimization method of the FFC connector as described in any one of claims 1-5.

8. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the various steps of the fast charging optimization method for the FFC connector as described in any one of claims 1 to 5 are implemented.

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