Fast charging optimization method of FFC connector and related device

Abstract

The invention relates to the technical field of charging connectors, and discloses a quick charging optimization method of an FFC connector and a related device. The method comprises the following steps: carrying out hierarchical filtering and preprocessing on multi-source original sensing data of a collected operating state of a connector, and carrying out multi-scale decomposition and reconstruction on the preprocessed data as well as association of rapid charging working condition characteristics to obtain a working condition characteristic spectrum of the connector; performing time sequence decomposition of a preset rapid charging characteristic component and prediction of a working condition evolution trend on the connector working condition characteristic spectrum to obtain multiple charging state prediction data, and performing determination of a charging safety boundary and multi-level threshold calculation of preset multiple rapid charging constraint parameters on each charging state prediction data; charging control parameter data are obtained; and based on the charging control parameter data, controlling the FFC connector to monitor rapid charging adjustment and state adjustment to obtain a rapid charging optimization result. According to the invention, efficient and safe control of quick charging of the FFC connector is realized.

Description

Technical Field

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

[0002] In the field of electronic device fast charging technology, FFC connectors are an important electrical connection component. Real-time monitoring of their operating status and performance optimization are key links to ensure the safety and reliability of fast charging. Especially in high-current fast charging scenarios, the terminal contact status, temperature rise characteristics, and current carrying capacity of FFC connectors 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 to improving the charging performance of FFC connectors.

[0003] Existing technologies usually use a single temperature monitoring or current control method to optimize the charging process, or try 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, the nonlinear characteristics of the terminal contact resistance changing with temperature and pressure are ignored, resulting in inaccurate contact status monitoring during the charging process; second, the coupling relationship of multi-dimensional parameters such as temperature distribution, current density and contact reliability is not effectively integrated, which affects the optimization effect of the charging strategy; third, the local overheating, uneven current distribution and unstable contact pressure of the FFC connector during fast charging are not considered enough, which increases the potential safety hazards of charging. That is, the existing FFC connector fast charging method is difficult to achieve comprehensive optimization of multi-dimensional charging characteristics, resulting in the inability to effectively guarantee charging efficiency and safety. Summary of the invention

[0004] The main purpose of the present invention is to solve the problem that the existing FFC connector fast charging method is difficult to achieve comprehensive optimization of multi-dimensional charging characteristics, resulting in the inability to effectively ensure charging efficiency and safety.

[0005] A first aspect of the present invention provides a fast charging optimization method for an FFC connector, wherein the FFC connector includes a charging monitoring unit and a charging management unit, and the fast charging optimization method for the FFC connector includes: using the charging monitoring unit to collect multi-source original sensor data corresponding to the operating state of the FFC connector, and performing hierarchical filtering and preprocessing on the multi-source original sensor data to obtain preliminary filtered data; performing multi-scale decomposition and reconstruction of multiple FFC connector features on the preliminary filtered data to obtain a connector state feature matrix, and correlating the connector state feature matrix with fast charging condition features to obtain a connector condition feature spectrum; performing 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 determining the charging safety boundary of each charging state prediction data and performing multi-level threshold calculation of preset multiple fast charging constraint parameters to obtain charging control parameter data; based on the charging control parameter data, using the charging management unit 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.

[0006] Optionally, in a first implementation method of the first aspect of the present invention, 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 layered filtering and preprocessing of the multi-source original sensor data to obtain preliminary filtered data includes: high-frequency noise filtering of the terminal contact area temperature data to obtain terminal temperature initial data, high-speed mutation suppression of the cable connection temperature data to obtain cable temperature initial data, current segmentation filtering of the transmission current data to obtain current distribution data, and voltage interference elimination of the transmission voltage data to obtain voltage change data; timestamp alignment of 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 delay calibration of the time alignment sequence based on the acquisition delay parameter of the sensor corresponding to the charging monitoring unit to obtain preliminary filtered data.

[0007] Optionally, in a second implementation method of the first aspect of the present invention, the preliminary filtered data is subjected to multi-scale decomposition and reconstruction of multiple FFC connector features to obtain a connector state feature matrix, including: performing time series division and differential calculation on the initial terminal temperature data in the preliminary filtered data to obtain a rapid temperature rise rate, and based on the terminal temperature safety threshold interval corresponding to the FFC connector, performing threshold segmented mapping on the rapid temperature rise rate to obtain terminal temperature rise segmented data; performing ratio calculation on the terminal temperature rise segmented data and the current distribution data to obtain a terminal instantaneous contact resistance value, and performing spatial mapping of heat source distribution and heat conduction calculation on the initial cable temperature data and the terminal instantaneous contact resistance value in the preliminary filtered data to obtain high-power temperature distribution characteristics; performing current distribution data in the preliminary filtered data The current density distribution calculation and the current extreme value calculation are performed on the high-power temperature distribution characteristics to obtain the maximum current carrying data of the connector, and the voltage change data in the preliminary filtered data and the maximum current carrying data of the connector are voltage-related mapped to generate a voltage fluctuation feature; based on the preset fluctuation feature parameters, the voltage fluctuation feature is numerically calculated and feature-weighted to generate a voltage stability feature, and based on the 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 feature are numerically normalized and weightedly fused to obtain a fast charging feature vector; the fast charging feature vector is subjected to a multi-dimensional feature transformation to obtain a feature conversion matrix, and the working state features of the feature conversion matrix are extracted to obtain a connector state feature matrix.

[0008] Optionally, in a third implementation method of the first aspect of the present invention, the fast charging operating condition characteristics of the connector state feature matrix are associated to obtain a connector operating condition characteristic spectrum, including: isothermal surface segmentation and temperature gradient calculation of corresponding temperature state characteristics in the connector state feature matrix to obtain a high-power temperature distribution map, and area division and standard deviation calculation of corresponding current state characteristics in the connector state feature matrix based on a preset unit cross-sectional area to obtain a current distribution map, and timing change value calculation and contact change feature extraction of corresponding resistance state characteristics in the connector state feature matrix to obtain a contact state map; spatially aligning and calculating correlation of the temperature distribution map, the current distribution map and the contact state map to obtain a feature association map, and performing feature clustering and operating condition feature labeling on the feature association 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 target operating condition feature extraction on the fast charging operating condition spectrum to generate a connector operating condition characteristic spectrum.

[0009] Optionally, in a fourth implementation of the first aspect of the present invention, the connector operating condition characteristic spectrum is subjected to time series decomposition of preset fast charging characteristic components and prediction of operating condition evolution trends to obtain a variety of charging state prediction data, including: time series division and extrapolation calculation of corresponding temperature component operating condition characteristics in the connector operating condition characteristic spectrum to obtain a rapid temperature rise prediction curve, and charging fluctuation value calculation and charging power conversion of corresponding current component operating condition characteristics in the connector operating condition characteristic spectrum to obtain a terminal high power bearing change curve, and time-varying characteristics determination and contact state evaluation of corresponding resistance component operating condition characteristics in the connector operating condition characteristic spectrum to obtain a terminal contact state curve; based on the FFC connector The corresponding connector material tolerance threshold is used to perform segmented fitting and threshold value comparison on the rapid temperature rise prediction curve to obtain the terminal temperature risk value, and based on the connector rated power corresponding to the FFC connector, interval statistics and difference calculation are performed on the terminal high-power change curve to obtain the terminal power risk value, and based on the preset terminal contact pressure corresponding to the FFC connector, mutation detection and deviation calculation are performed on the terminal contact state curve to obtain the 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.

[0010] Optionally, in a fifth implementation 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, and the determination of the charging safety boundary of each of the charging state prediction data and the multi-level threshold calculation of preset multiple fast charging constraint parameters to obtain charging control parameter data include: performing interval threshold segmentation on the terminal temperature rise data and extracting the current value of the corresponding temperature grading interval to generate a terminal temperature control value, as well as extracting the fluctuation interval of the terminal power prediction data and calculating the maximum allowable current of the power fluctuation interval to obtain the terminal power limit, and performing timing fluctuation extraction on the terminal contact state prediction data and a safe interval of the contact pressure change value. The terminal temperature control value, the terminal power limit value and the terminal contact threshold value are calculated to obtain the terminal contact threshold value; the intersection operation of the current value and the boundary contraction are performed on the terminal temperature control value, the terminal power limit value and the terminal contact threshold value to obtain the terminal operation boundary data, and the current boundary value is sampled at equal intervals 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 operating point, and based on the preset target operation strategy, the charging efficiency of the terminal stable operating point is calculated and the target operation point is extracted to obtain the target operation parameter; the target operation parameter is converted into the current control amount to obtain the charging control sequence, and the charging control sequence is divided into time periods to generate the charging control parameter data.

[0011] Optionally, in a sixth implementation manner of the first aspect of the present invention, 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, including: segmenting the charging control sequence in the charging control parameter data corresponding to the charging time label to obtain a discrete control instruction, and proportionally converting the discrete control instruction 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, collecting the temperature state response data corresponding to the real-time control instruction executed by the charging management unit to control the FFC connector, and comparing the temperature state response data with a temperature threshold to obtain a temperature deviation value; performing a safety range judgment and a compensation calculation for the adjustment demand on the temperature deviation value to obtain a current correction value, and based on the current correction value, performing a secondary update and execution of the real-time control instruction to obtain the fast charging optimization result of the FFC connector.

[0012] The second aspect of the present invention provides a fast charging optimization device for an FFC connector, wherein the FFC connector includes a charging monitoring unit and a charging management unit, and the fast charging optimization device for the FFC connector includes: a preprocessing module, which is used to use the charging monitoring unit to collect multi-source original sensor data corresponding to the operating state of the FFC connector, and perform hierarchical filtering and preprocessing on the multi-source original sensor data to obtain preliminary filtered data; a feature association module, which is used to perform multi-scale decomposition and reconstruction of multiple FFC connector features on the preliminary filtered data to obtain a connector state feature matrix, and perform rapid processing on the connector state feature matrix. A trend prediction module is used to perform time series decomposition of preset fast charging characteristic components and prediction of the operating condition evolution trend of the connector operating condition characteristic spectrum to obtain a variety of charging state prediction data, and to determine the charging safety boundary of each charging state prediction data and perform multi-level threshold calculation of preset multiple fast charging constraint parameters to obtain charging control parameter data; a 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.

[0013] A third aspect of the present invention provides a fast charging optimization device for an FFC connector, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the fast charging optimization device for the FFC connector performs the various steps of the above-mentioned fast charging optimization method for the FFC connector.

[0014] A fourth aspect of the present invention provides a computer-readable storage medium, in which instructions are stored. When the computer-readable storage medium is run on a computer, the computer executes the various steps of the above-mentioned fast charging optimization method for the FFC connector.

[0015] The above-mentioned fast charging optimization method and related device of the FFC connector. In the embodiment of the present invention, the multi-source original sensor data corresponding to the operating state of the FFC connector is collected by using a charging monitoring unit, and the multi-source original sensor data is subjected to hierarchical filtering and preprocessing to obtain preliminary filtering data; the preliminary filtering data is subjected to multi-scale decomposition and reconstruction of multiple FFC connector features to obtain a connector state feature matrix, and the connector state feature matrix is ​​associated with the fast charging working condition features to obtain a connector working condition feature spectrum; the connector working condition feature spectrum is subjected to time series decomposition of preset fast charging feature components and prediction of working condition evolution trends to obtain multiple charging state prediction data, and the charging safety boundary of each charging state prediction data is determined and multi-level threshold calculation of preset multiple 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 perform fast charging adjustment and state adjustment monitoring to obtain the fast charging optimization result of the FFC connector. Compared with the prior art, this application acquires basic charging characteristics through multi-dimensional sensing data collection and hierarchical filtering preprocessing of FFC connectors, and decomposes and reconstructs these characteristics at multiple scales to obtain the connector state feature matrix; then, through fast charging condition correlation calculation and feature spectrum extraction, the working condition feature spectrum is obtained and the charging state is mapped; finally, based on charging state prediction and multi-level threshold calculation, the charging control result is output. Through hierarchical data processing and feature analysis, the optimization control of FFC connector fast charging is realized, especially in terms of terminal temperature rise, current distribution and contact reliability, the dynamic characteristics of the connector and the safety of fast charging are fully considered, and the charging efficiency is effectively improved; and the multi-level feature extraction and state prediction strategy are 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 working condition feature reconstruction and state monitoring, charging anomalies and optimization opportunities are accurately identified, thereby realizing efficient and safe control of FFC connector fast charging as a whole.

[0016] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a schematic diagram of a first embodiment of a fast charging optimization method for an FFC connector according to an embodiment of the present invention; Figure 2A schematic diagram of an embodiment of a fast charging optimization device for an FFC connector according to an embodiment of the present invention; Figure 3 Schematic diagram of an embodiment of a fast charging optimization device for an FFC connector in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] The terms "including" and "having" and any variations thereof mentioned in the embodiments of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device end including a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or device ends.

[0021] To facilitate understanding of this embodiment, the specific process of the embodiment of the present invention is described below. Figure 1 The first embodiment of the fast charging optimization method of the FFC connector in the embodiment of the present invention includes: 101. Use a charging monitoring unit to collect multi-source original sensor data corresponding to the operating status of the FFC connector, and perform layered filtering and preprocessing on the multi-source original sensor data to obtain preliminary filtered data; The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology and application system that 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.

[0022] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0023] In this embodiment, the FFC connector includes a charging monitoring unit and a charging management unit, wherein the charging monitoring unit may include but is not limited to 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 include but is not limited to a power conversion unit for large current charging control, a heat dissipation unit for temperature regulation, and a control unit for data processing. The multi-source original sensor data includes terminal contact area temperature data, cable connection temperature data, transmission current data, and transmission voltage data. High-frequency noise is filtered out of 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, and current segmentation filtering is performed on the transmission current data to obtain current distribution data, and voltage interference elimination is performed on the transmission voltage data 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 timestamp aligned to obtain a time alignment sequence, and the time alignment sequence is delay calibrated based on the acquisition delay parameter of the corresponding sensor of the charging monitoring unit to obtain preliminary filtered data.

[0024] In practical applications, the charging monitoring unit first performs multi-source sensor data collection on the operating status of the FFC connector. The first temperature sensor collects the temperature data of the terminal contact area in real time at a sampling frequency of 1kHz, and eliminates the high-frequency noise components above 50Hz through a preset high-pass filter to obtain accurate initial terminal temperature data; the second temperature sensor also collects the temperature data of the cable connection at a frequency of 1kHz, and uses a mutation suppression algorithm based on wavelet transform to eliminate mutation interference in the temperature data to obtain stable initial cable temperature data; the current sensor uses a Hall effect sensor to perform high-precision sampling of the transmission current during the charging process, and smoothes the current data through a segmented Kalman filter algorithm to obtain a current distribution that reflects the current distribution characteristics. data; the voltage sensor uses a high-precision operational amplifier to sample the terminal voltage, and eliminates the interference of the power frequency and its harmonics through a band-stop filter to obtain accurate voltage change data; considering the slight differences in the sampling timing of different sensors, the collected initial terminal temperature data, cable temperature data, current distribution data and voltage change data are uniformly timestamped, and these data are aligned to a unified time base based on the timestamp information to generate a time alignment sequence; and because various sensors have different response times and signal transmission delays, the data in the time alignment sequence are delayed compensated according to the pre-calibrated sensor acquisition delay parameters, and the data is accurately aligned through the interpolation algorithm, and finally the preliminary filtered data that has been completely preprocessed is obtained. For example: in a fast charging process, the initial temperature of the terminal contact area is 25°C and the charging current is 5A. Through the above processing, the temperature noise fluctuation of ±0.5℃ is effectively filtered out, the temperature mutation of 0.2℃ / ms caused by the charging current mutation is suppressed, and the current measurement accuracy of ±0.1A and the voltage measurement accuracy of ±0.05V are achieved; and after time alignment and calibration, the time synchronization error of the four-way data is controlled within 0.1ms. The entire data acquisition and preprocessing process fully considers the characteristics of the FFC connector in the fast charging scenario. Through the coordinated acquisition and preprocessing of multi-source data, the influence of various interference factors is effectively eliminated, the accuracy and timing consistency of the data are guaranteed, and the foundation is laid for accurate charging status 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 status of the FFC connector.

[0025] 102. Perform multi-scale decomposition and reconstruction of various FFC connector features on the preliminary filtered data to obtain a connector state feature matrix, and associate the connector state feature matrix with fast charging condition features to obtain a connector condition feature spectrum; In this embodiment, the initial terminal temperature data in the preliminary filtering data is time-series divided 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 terminal instantaneous contact resistance value, and the cable temperature initial data and the terminal instantaneous contact resistance value in the preliminary filtering data are spatially mapped with the heat source distribution and heat conduction calculated to obtain the high-power temperature distribution characteristics; the current distribution data and the high-power temperature distribution characteristics in the preliminary filtering data are distributed and calculated as the current density to obtain the maximum current carrying data of the connector, and the voltage change data in the preliminary filtering data and the maximum current carrying data of the connector are voltage-correlated mapped to generate voltage fluctuation characteristics; based on the preset fluctuation characteristic parameters, the voltage fluctuation characteristics are numerically calculated and feature-weighted calculated to generate voltage stability characteristics, and based on the preset connector feature importance coefficient, the terminal instantaneous contact resistance value, the high-power temperature distribution characteristics, the connector maximum The current-carrying data and voltage stability characteristics are numerically normalized and weightedly fused to obtain a fast-charging feature vector; the fast-charging feature vector is subjected to a multi-dimensional feature transformation to obtain a feature conversion matrix, and the working state characteristics of the feature conversion matrix are extracted to obtain a connector state feature matrix; the corresponding temperature state characteristics 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 based on a preset unit cross-sectional area, the corresponding current state characteristics in the connector state feature matrix are divided into areas and the standard deviation is calculated to obtain a current distribution map , and calculate the time series change value of the corresponding resistance state feature in the connector state feature matrix and extract the contact change feature to obtain the contact state map; perform spatial registration and correlation calculation on the temperature distribution map, current distribution map and contact state map to obtain the feature association map, and perform feature clustering and working condition feature labeling on the feature association map to obtain the fast charging working condition type data; perform time-frequency transformation on the fast charging working condition type data to obtain the fast charging working condition spectrum, and perform principal component calculation and target working condition feature extraction on the fast charging working condition spectrum to generate the connector working condition feature spectrum.The fluctuation characteristic parameters here include voltage fluctuation amplitude (variation range relative to rated voltage, usually expressed as a percentage), fluctuation frequency (time characteristics of voltage fluctuation, i.e. the number of fluctuations per unit time), fluctuation duration (duration of each fluctuation), fluctuation slope (speed characteristics of voltage change), fluctuation periodicity (repetitive characteristics of voltage fluctuation), etc.; the connector feature importance coefficient here refers to the weight coefficient used to measure the influence of different features on the fast charging performance of the FFC connector, for example, it can be set to temperature feature weight (0.4), resistance feature weight (0.3), current feature weight (0.2), voltage feature weight (0.1); the unit cross-sectional area here refers to the cross-sectional area of ​​the terminals and wires of the FFC connector perpendicular to the direction of current flow; the connector state feature matrix includes temperature state features, current state features and resistance state features.

[0026] In practical applications, the initial terminal temperature data in the preliminary filtering data is first divided into time windows of 100ms each, and the temperature change rate is obtained by differential calculation in each time window, thereby obtaining a rapid temperature rise rate reflecting the terminal temperature rise speed, and based on the 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 temperature rise change characteristics; then the ratio of the terminal temperature rise segmented data and the current distribution data at the corresponding time is calculated. Based on Ohm's law, the instantaneous contact resistance value that characterizes the contact quality of the terminal is obtained, and the initial cable temperature data and the instantaneous contact resistance value of the terminal are spatially correlated. That is, by establishing a heat source distribution model, the terminal contact area is divided into several 0.1mm×0.1mm tiny grids, and the temperature distribution of each grid point is calculated based on the heat conduction equation, and finally the temperature distribution characteristics reflecting the connector under high-power transmission state are obtained; then the current distribution data is associated with the high-power temperature distribution characteristics, and the current carrying capacity of each point is obtained by calculating the current density distribution per unit cross-sectional area and combining the influence of temperature on the resistivity of the wire, and by finding the maximum value point of the current density and considering Taking the temperature limitation factor into consideration, the maximum current carrying data of the connector in the current state is calculated, and the voltage change data is correlated with the maximum current carrying data for analysis. 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 pre-set fluctuation characteristic parameters (including voltage fluctuation amplitude, frequency and duration, etc.), the voltage fluctuation characteristics corresponding to the voltage fluctuation range and fluctuation degree are calculated, and the voltage stability characteristics representing the voltage stability are obtained through feature weighting calculation. According to the preset feature importance coefficient (generally the temperature feature weight is 0.4, the resistance feature weight is 0.3, the current feature weight is 0.2, and the voltage feature weight is 0. 1) The instantaneous contact resistance value of the terminal, high-power temperature distribution characteristics, maximum current carrying data of the connector, and voltage stability characteristics are normalized and weightedly fused to unify all characteristics into the same numerical range, and finally obtain a fast-charging feature vector that can fully reflect the charging performance of the connector; then the fast-charging feature vector is subjected to multi-dimensional feature transformation such as principal component analysis, the main feature components are extracted, and the feature space is reconstructed to obtain a feature conversion matrix. Baoning extracts feature combinations that can reflect different working states of the connector by performing feature clustering and pattern recognition on the feature conversion matrix, and finally obtains a connector state feature matrix containing multi-dimensional information such as temperature state, resistance state, current state, and voltage state. Not only the mutual influence between various physical quantities is considered, but also the comprehensive characterization of the working state of the FFC connector is achieved through multi-level feature conversion and fusion, providing the necessary state information for accurate charging control.

[0027] Secondly, for the corresponding temperature state features in the connector state feature matrix, the monitoring area of ​​the FFC connector is divided into isothermal surfaces according to a 0.1mm×0.1mm grid, and the temperature gradient between each grid point and the adjacent point is calculated, thereby generating a high-power temperature distribution map reflecting the spatial distribution of the connector temperature. Based on the preset unit cross-sectional area of ​​1mm², the current state features are spatially divided, and the standard deviation of the current density in each area is calculated to generate a current distribution map characterizing the uniformity of the current distribution. For the resistance state features, the contact resistance change rate within the continuous time window is calculated, and the mutation points and change trends therein are extracted to obtain a contact state map reflecting the change of the terminal contact state. Then, the spatial coordinate mapping method is used to spatially align the temperature distribution map, the current distribution map, and the contact state map to ensure the correspondence between the three maps in spatial position, and to calculate the correlation coefficients between different features. and covariance matrix, and obtain the feature association map that characterizes the correlation relationship between each feature; and apply the K-means clustering algorithm to the feature association map for feature grouping, and mark various feature combinations based on the preset working condition feature template, and finally obtain the fast charging working condition type data including normal charging, fast charging, overheating warning and other different working condition types; then perform wavelet transform on the fast charging working condition type data, convert the time domain information to the time-frequency domain, and obtain the fast charging working condition spectrum that can simultaneously reflect the working condition change frequency and time characteristics, and extract the main feature components (i.e., target working condition characteristics) with a contribution rate of more than 95% by performing principal component analysis on the working condition spectrum, and reconstruct the working condition feature space based on these main features, and finally generate the connector working condition feature spectrum that can fully characterize the charging working condition of the FFC connector (where this working condition feature spectrum not only contains multi-dimensional feature information such as temperature, current and contact state, but also reflects the evolution law of these features 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, it can accurately capture the changing characteristics of various physical quantities and their mutual influence.

[0028] 103. Perform 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, determine charging safety boundaries for each charging state prediction data and perform multi-level threshold calculation of preset multiple fast charging constraint parameters to obtain charging control parameter data; 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 corresponding temperature component working condition characteristics in the connector working condition characteristic spectrum are divided into time series and extrapolated to obtain a rapid temperature rise prediction curve, and the corresponding current component working condition characteristics in the connector working condition characteristic spectrum are calculated by charging fluctuation value and charging power conversion to obtain a terminal high-power change curve, and the corresponding resistance component working condition characteristics in the connector working condition characteristic spectrum are determined by time-varying characteristics and contact state evaluation to obtain a terminal contact state curve; based on the connector material tolerance threshold corresponding to 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 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, power risk value, and contact reliability risk value to obtain a variety of The terminal temperature rise data is segmented into interval thresholds and the current value of the corresponding temperature classification interval is extracted to generate the 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 terminal contact state prediction data is extracted by time series fluctuation and the safety interval threshold of the contact pressure change value is calculated to obtain the terminal contact threshold; the terminal temperature control value, the terminal power limit and the terminal contact threshold are subjected to the intersection operation of the current value and the boundary contraction to obtain the terminal operation boundary data, and the terminal operation boundary data is sampled at equal intervals to obtain the current sampling point sequence; the terminal temperature rise fluctuation detection is performed on the adjacent points in the current sampling point sequence to obtain the terminal stable working point, and based on the preset target operation strategy, the charging efficiency of the terminal stable working point is calculated and the target operation point is extracted to obtain the target operation parameter; the target operation parameter is converted into the current control quantity 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 multiple 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 targets for achieving optimal charging efficiency while ensuring safety.

[0029] In practical applications, the corresponding temperature component working condition characteristics in the working condition characteristic spectrum are first divided into time series according to the time interval of 0.5s. The historical temperature data are analyzed by using the adaptive Kalman filtering algorithm, and the temperature change trend of the next 30s is extrapolated and calculated in combination with the exponential smoothing method, so as to obtain a fast temperature rise prediction curve reflecting the terminal temperature rise trend. For the working condition characteristics of the current component, 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 representing the terminal carrying capacity. For the working condition characteristics of the resistance component, 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 representing the terminal carrying capacity. The time-varying characteristics and fluctuation laws of the resistance value are analyzed, and combined with the stability evaluation index of the contact state, the terminal contact state curve reflecting the change of the terminal contact quality is obtained; in order to evaluate the various risks in the charging process, based on the connector material tolerance threshold 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 piecewise linearly fitted, and the terminal temperature risk value representing the temperature safety margin is obtained by calculating the difference ratio between the predicted temperature and the threshold, as well as the terminal high power carrying change curve based on the connector rated power corresponding to the FFC connector (such as the rated power index of 200W). Interval statistical analysis is performed, and the terminal power risk value representing the degree of power overrun is obtained by calculating the difference ratio between the actual power and the rated power. 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 2N), a mutation detection algorithm based on wavelet transform is applied to the terminal contact state curve, and the contact reliability risk value representing the contact reliability is obtained by calculating the cumulative amount of contact state deviation; then, extreme value detection is performed on the three types of risk values ​​obtained, and a variety of critical state data including temperature critical state, power critical state and contact critical state are obtained by finding the local maximum points of various risk indicators. These critical state data are compared with the preset safety thresholds (temperature risk threshold 0.8, power risk threshold 0.9 and contact risk threshold 0.85), and finally a variety of fast charging state prediction data reflecting the future operating state of the FFC connector are 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 evaluation of the charging safety of the FFC connector is achieved, especially when dealing with high-power fast charging scenarios, it can timely warn of potential safety hazards.

[0030] Secondly, the terminal temperature rise data is segmented into interval thresholds according to the temperature interval of 5°C, and the temperature range is divided into multiple level intervals (25-30°C, 30-35°C, 35-40°C, etc.), and the safe current value corresponding to each temperature interval is extracted from the historical data. The terminal temperature control value is generated through this temperature-current mapping relationship. For the terminal power prediction data, the power fluctuation interval is determined by statistically analyzing the peak and valley values ​​of the power fluctuation, and based on the square relationship between power and current, the maximum allowable current value in each power fluctuation interval is calculated to obtain the terminal power limit. For the terminal contact state prediction data, the standard deviation of the pressure fluctuation is calculated by analyzing the time series change law of the contact pressure, and the safe fluctuation range is determined based on the standard contact pressure of 2N, and finally the terminal contact threshold is obtained; then the intersection operation is performed on the current value corresponding to the terminal temperature control value, the terminal power limit and the terminal contact threshold to obtain the simultaneous The current range that meets the requirements of temperature control, power limitation and contact reliability is obtained, and more conservative terminal operation boundary data is obtained by shrinking the boundary operation (generally shrinking the margin by 10%). Based on these boundary data, the current range is sampled at equal intervals with an interval of 0.1A to generate a sequence of current sampling points to be evaluated; then, the terminal temperature rise fluctuation is analyzed for adjacent sampling points, the change trend of the temperature rise rate is calculated, and the stable operating point with a temperature rise fluctuation of less than 0.5℃ / s is screened out; then, based on the preset target operation strategy (giving priority to charging efficiency, while ensuring that the temperature rise rate does not exceed 1℃ / s), the screened terminal stable operating point is evaluated, and the charging efficiency is obtained by calculating the ratio of input power to effective charging power using a multi-objective optimization function, and combined with the constraint 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: ; in, , , is the weight coefficient, ΔT is the temperature rise value, P is the working 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, The optimal working point is selected by minimizing the J value as a reference contact resistance; the target operating parameters are then converted into actual current control quantities, a detailed charging control sequence is generated, and the control sequence is divided into time segments according to different stages of the charging process (such as pre-charging stage, constant current charging stage, constant voltage charging stage, etc.), and finally a complete charging control parameter data is generated. A balance between charging efficiency and safety is achieved, especially when dealing with high-current fast charging scenarios, and the relationship between charging power and temperature rise rate is accurately grasped.

[0031] 104. 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.

[0032] In this embodiment, the charging control sequence in the charging control parameter data is segmented and intercepted corresponding to the charging time label to obtain discrete control instructions, and the discrete control instructions are proportionally converted based on the terminal rated current corresponding to the FFC connector to obtain real-time control instructions; based on the preset terminal temperature acquisition instruction, the charging management unit controls the FFC connector to execute the temperature state response data corresponding to the real-time control instruction, and the temperature state response data is compared with the temperature threshold to obtain the temperature deviation value; the temperature deviation value is judged in the safety range and the compensation calculation of the adjustment demand is performed to obtain the current correction value, and based on the current correction value, the real-time control instruction is updated and executed for the second time to obtain the fast charging optimization result of the FFC connector. The terminal temperature acquisition instruction here refers to the instruction for standardized data acquisition of the terminal temperature of the FFC connector according to these pre-set acquisition parameters and control requirements.

[0033] In practical applications, the charging control sequence in the charging control parameter data is segmented and intercepted at a time interval of 10ms, and the continuous control sequence is converted into discrete control instruction points. Based on the terminal rated current of the FFC connector (usually 10A), these discrete control instructions are proportionally converted, and the theoretical control value is converted into the actual current control amount, so as to obtain real-time control instructions that can be directly used for control execution, so as to ensure the execution accuracy and timing accuracy of the control instructions; further, in the control execution process, based on the preset terminal temperature acquisition instruction with a sampling frequency of 1kHz, the temperature state response data of the FFC connector in the process of executing the control instruction is collected in real time through the first temperature sensor and the second temperature sensor in the charging monitoring unit, including the terminal contact area temperature and the cable connection temperature, and the collected temperature state response data is compared with the preset The temperature deviation value is calculated by comparing the actual temperature with the set safety 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; in order to ensure the safety and stability of the charging process, when the temperature deviation value falls within the safety range (the temperature is more than 10°C below the threshold), the current charging strategy is maintained; when the temperature deviation value is close to the warning range (the temperature is less than 10°C from the threshold), the required current adjustment amount is calculated by the preset compensation algorithm, and the current correction value for optimized control is obtained based on the quadratic relationship model between temperature and current; the current correction value is then superimposed on the original real-time control instruction, and the updated control instruction is executed by the power conversion unit in the charging management unit, and the cooling unit cooperates with the work, and finally the fast charging optimization control of the FFC connector is realized 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 when dealing with large current fast charging scenarios, 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.

[0034] In the embodiment of the present invention, the basic charging characteristics are obtained by multi-dimensional sensing data acquisition and hierarchical filtering preprocessing of the FFC connector, and these characteristics are multi-scale decomposed and reconstructed to obtain the connector state feature matrix; then, through the fast charging condition correlation calculation and feature spectrum extraction, the working condition feature spectrum is obtained and the charging state is mapped; finally, based on the charging state prediction and multi-level threshold calculation, the charging control result is output. Through hierarchical data processing and feature analysis, the optimization control of the fast charging of the FFC connector is realized, especially in terms of terminal temperature rise, current distribution and contact reliability, the dynamic characteristics of the connector and the safety of fast charging are fully considered, and the charging efficiency is effectively improved; and the multi-level feature extraction and state prediction strategy are 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 the reconstruction of working condition characteristics and state monitoring, the charging anomaly and optimization timing are accurately identified, thereby realizing the efficient and safe control of the fast charging of the FFC connector as a whole.

[0035] The above describes the fast charging optimization method of the FFC connector in the embodiment of the present invention. The following describes the fast charging optimization device of the FFC connector in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a fast charging optimization device for an FFC connector includes: A preprocessing module 201 is used to collect multi-source original sensor data corresponding to the operating state of the FFC connector using the charging monitoring unit, and perform hierarchical filtering and preprocessing on the multi-source original sensor data to obtain preliminary filtered data; A feature association module 202 is used to perform multi-scale decomposition and reconstruction of multiple FFC connector features on the preliminary filtered data to obtain a connector state feature matrix, and to associate the connector state feature matrix with fast charging condition features to obtain a connector condition feature spectrum; The trend prediction module 203 is used to perform time series decomposition of the preset fast charging characteristic components and predict the working condition evolution trend of the connector working condition characteristic spectrum to obtain multiple charging state prediction data, and determine the charging safety boundary of each charging state prediction data and calculate the multi-level threshold of multiple fast charging constraint parameters to obtain charging control parameter data; The state optimization module 204 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.

[0036] In the embodiment of the present invention, the basic charging characteristics are obtained by multi-dimensional sensing data acquisition and hierarchical filtering preprocessing of the FFC connector, and these characteristics are multi-scale decomposed and reconstructed to obtain the connector state feature matrix; then, through the fast charging condition correlation calculation and feature spectrum extraction, the working condition feature spectrum is obtained and the charging state is mapped; finally, based on the charging state prediction and multi-level threshold calculation, the charging control result is output. Through hierarchical data processing and feature analysis, the optimization control of the fast charging of the FFC connector is realized, especially in terms of terminal temperature rise, current distribution and contact reliability, the dynamic characteristics of the connector and the safety of fast charging are fully considered, and the charging efficiency is effectively improved; and the multi-level feature extraction and state prediction strategy are 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 the reconstruction of working condition characteristics and state monitoring, the charging anomaly and optimization timing are accurately identified, thereby realizing the efficient and safe control of the fast charging of the FFC connector as a whole.

[0037] above Figure 2 The fast charging optimization device of the FFC connector in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The fast charging optimization device of the FFC connector in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0038] Figure 3 It is a structural schematic diagram of a fast charging optimization device for an FFC connector provided by an embodiment of the present invention. The fast charging optimization device 300 for the FFC connector may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 310 (for example, one or more processors) and a memory 320, and one or more storage media 330 (for example, one or more mass storage devices) storing application programs 333 or data 332. Among them, the memory 320 and the storage medium 330 can be short-term storage or permanent storage. The program stored in the storage medium 330 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the fast charging optimization device 300 of the FFC connector. Furthermore, the processor 310 can be configured to communicate with the storage medium 330 to execute a series of instruction operations in the storage medium 330 on the fast charging optimization device 300 of the FFC connector.

[0039] The fast charging optimization device 300 of the FFC connector may also include one or more power supplies 340, one or more wired or wireless network interfaces 350, one or more input and output interfaces 360, and / or one or more operating systems 331, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Figure 3 The structure of the fast charging optimization device of the FFC connector shown does not constitute a limitation on the fast charging optimization device of the FFC connector, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0040] The present invention also provides a fast charging optimization device for an FFC connector, wherein the computer device includes a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes each step of the fast charging optimization method for the FFC connector in the above-mentioned embodiments.

[0041] The present invention also provides a computer-readable storage medium, which 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 executed on a computer, the computer executes the various steps of the fast charging optimization method of the FFC connector.

[0042] 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 aforementioned method embodiments and will not be repeated here.

[0043] 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 is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0044] The present application can be used in many general or special 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, etc. The present 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. The present application can also be practiced in distributed computing environments, in which 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.

[0045] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions 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, and the multi-source original sensor data is subjected to layered filtering and preprocessing to obtain preliminary filtered data; Performing multi-scale decomposition and reconstruction of multiple FFC connector features on the preliminary filtered data to obtain a connector state feature matrix, and correlating the connector state feature matrix with fast charging condition features to obtain a connector 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 multi-source original sensor data includes terminal contact area temperature data, cable connection temperature data, transmission current data and transmission voltage data. The multi-source original sensor data is subjected to layered filtering and preprocessing to obtain preliminary filtered data, including: Performing high-frequency noise filtering on the temperature data of the terminal contact area to obtain initial terminal temperature data, and performing high-speed mutation suppression on the temperature data at the cable connection to obtain initial cable temperature 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; 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 based on the acquisition delay parameter of the corresponding sensor of the charging monitoring unit, the time alignment sequence is delay calibrated to obtain preliminary filtered data.

3. The fast charging optimization method of the FFC connector according to claim 2, characterized in that: The preliminary filtering data is subjected to multi-scale decomposition and reconstruction of various FFC connector features to obtain a connector state feature matrix, including: Performing 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 performing segmented mapping of the threshold value on the rapid temperature rise rate based on the terminal temperature safety threshold interval corresponding to the FFC connector to obtain terminal temperature rise segmented data; Performing ratio calculation on the terminal temperature rise segmented data and the current distribution data to obtain the terminal instantaneous contact resistance value, and performing spatial mapping of heat source distribution and heat conduction calculation on the cable temperature initial data in the preliminary filtering data and the terminal instantaneous contact resistance value to obtain high-power temperature distribution characteristics; Performing current density distribution calculation and current carrying 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 performing voltage correlation mapping on the voltage change data in the preliminary filtering data and the maximum current carrying data of the connector to generate voltage fluctuation characteristics; Based on the preset fluctuation characteristic parameters, the voltage fluctuation characteristic is numerically calculated and feature weighted to generate a voltage stability characteristic, and based on the preset connector feature importance coefficient, the instantaneous contact resistance value of the terminal, the high-power temperature distribution characteristic, the maximum current carrying data of the connector and the voltage stability characteristic are numerically normalized and weightedly fused to obtain a fast charging feature vector; The fast charging feature vector is transformed into a multi-dimensional feature to obtain a feature conversion matrix, and the working state features are extracted from the feature conversion matrix to obtain a connector state feature matrix.

4. 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.

5. 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.

6. 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 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.

7. The fast charging optimization method of the FFC connector according to claim 6, 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.

8. 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, configured to collect multi-source original sensor data corresponding to the operating state of the FFC connector using the charging monitoring unit, and perform hierarchical filtering and preprocessing on the multi-source original sensor data to obtain preliminary filtered data; A feature association module is used to perform multi-scale decomposition and reconstruction of multiple FFC connector features on the preliminary filtered data to obtain a connector state feature matrix, and to associate the connector state feature matrix with fast charging condition features to obtain a connector 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.

9. 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 1-7.

10. 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 7 are implemented.

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