A power adaptive regulation charging power management method and system

Abstract

The application discloses a power self-adaptive adjusting charging power management method and system, and relates to the technical field of power management, which comprises the following steps: obtaining a terminal device charging capability image and performing template matching to obtain initial charging power output parameters; controlling a charging power to charge and monitoring to obtain an interactive state monitoring data sequence; performing iterative fluctuation identification on the interactive state monitoring data sequence to determine a terminal device charging stability coefficient; obtaining a voltage sampling sequence and a current sampling sequence of the charging power to perform output error identification and obtain a steady-state output error; adjusting the initial charging power output parameters to obtain adjusted charging power output parameters, and transmitting the adjusted charging power output parameters to a management module for charging power management. The application solves the technical problems that the charging power output parameters are fixed in the prior art, it is difficult to adapt to the charging capability and state changes of different terminal devices, and the charging efficiency is low and the stability is poor, and achieves the technical effect of improving the charging efficiency and stability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power management, in particular to a power adaptive adjustment charging power management method and system. BACKGROUND

[0002] In the traditional charging power management scheme, the charging power usually charges the terminal device according to the preset fixed output parameters, lacking the dynamic perception and response mechanism to the current charging capacity and state change of the terminal device. In actual operation, the state of charge, voltage, current demand and charging interface temperature of the terminal device will change with the change of the use environment and the battery characteristics. If the charging power cannot adaptively adjust the output parameters according to these real-time changes, it is easy to cause power deviation and current fluctuation during charging, thereby affecting the overall charging efficiency and the use stability of the device. SUMMARY

[0003] The present application provides a power adaptive adjustment charging power management method and system, which is used to solve the technical problems that the output parameters of the charging power are fixed in the prior art, and it is difficult to adapt to the charging capacity and state change of different terminal devices, resulting in low charging efficiency and poor stability.

[0004] In view of the above problems, the present application provides a power adaptive adjustment charging power management method and system.

[0005] The first aspect of the present application provides a power adaptive adjustment charging power management method, which comprises:

[0006] When the charging power is connected to the terminal device, the state perception module is activated to perceive the state of the terminal device and obtain the charging capacity profile of the terminal device. Based on the charging capacity profile of the terminal device, the output parameter template of the charging power is matched to obtain the initial charging power output parameter. Through the management module, the charging power is controlled to charge the terminal device according to the initial charging power output parameter, and the state perception module is called to continuously monitor the state of the terminal device to obtain the interactive state monitoring data sequence. The interactive state monitoring data sequence is iteratively identified to determine the charging stability coefficient of the terminal device. The voltage sampling sequence and the current sampling sequence of the charging power are obtained, and the output error is identified in combination with the initial charging power output parameter to obtain the steady-state output error. Based on the charging stability coefficient and the steady-state output error, the initial charging power output parameter is adjusted to obtain the adjusted charging power output parameter, and the adjusted charging power output parameter is transmitted to the management module for charging power management.

[0007] The second aspect of the present application provides a power adaptive adjustment charging power management system, which comprises:

[0008] The state sensing module is used to activate the state sensing module to sense the state of the terminal device and obtain a charging capability profile of the terminal device when the charging power supply is connected to the terminal device; the matching module is used to match the charging power supply output parameter template based on the charging capability profile of the terminal device to obtain an initial charging power supply output parameter; the state monitoring module is used to control the charging power supply to charge the terminal device according to the initial charging power supply output parameter through the management module, and continuously monitor the state of the terminal device by calling the state sensing module to obtain an interactive state monitoring data sequence; the fluctuation identification module is used to identify the iterative fluctuation of the interactive state monitoring data sequence to determine a charging stability coefficient of the terminal device; the error identification module is used to obtain the voltage sampling sequence and the current sampling sequence of the charging power supply, identify the output error in combination with the initial charging power supply output parameter, and obtain a steady-state output error; and the charging management module is used to adjust the initial charging power supply output parameter based on the charging stability coefficient and the steady-state output error to obtain an adjusted charging power supply output parameter, and transmit the adjusted charging power supply output parameter to the management module for charging power supply management.

[0009] The one or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0010] When the charging power supply is connected to the terminal device, the state sensing module is activated to sense the state of the terminal device and obtain a charging capability profile of the terminal device; the matching module is used to match the charging power supply output parameter template based on the charging capability profile of the terminal device to obtain an initial charging power supply output parameter; the state monitoring module is used to control the charging power supply to charge the terminal device according to the initial charging power supply output parameter through the management module, and continuously monitor the state of the terminal device by calling the state sensing module to obtain an interactive state monitoring data sequence; the fluctuation identification module is used to identify the iterative fluctuation of the interactive state monitoring data sequence to determine a charging stability coefficient of the terminal device; the error identification module is used to obtain the voltage sampling sequence and the current sampling sequence of the charging power supply, identify the output error in combination with the initial charging power supply output parameter, and obtain a steady-state output error; and the charging management module is used to adjust the initial charging power supply output parameter based on the charging stability coefficient and the steady-state output error to obtain an adjusted charging power supply output parameter, and transmit the adjusted charging power supply output parameter to the management module for charging power supply management. The present application solves the technical problems in the prior art that the charging power supply output parameter is fixed and difficult to adapt to the charging capability and state changes of different terminal devices, resulting in low charging efficiency and poor stability. By constructing a charging capability profile of the terminal device and dynamically adjusting the charging parameters based on the charging stability coefficient and the steady-state output error, the technical effects of improving the charging efficiency and stability are achieved. BRIEF DESCRIPTION OF DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort based on these drawings.

[0012] Figure 1 A power adaptive adjustment charging power supply management method flow chart provided by the embodiment of the present application;

[0013] Figure 2 A power adaptive adjustment charging power supply management system structure diagram provided by the embodiment of the present application.

[0014] Legend: state awareness module 11, matching module 12, state monitoring module 13, fluctuation identification module 14, error identification module 15, charging management module 16. DETAILED DESCRIPTION

[0015] The present application provides a power adaptive adjustment charging power supply management method and system, which solves the technical problems of fixed charging power supply output parameters, difficulty in adapting to charging capacity and state changes of different terminal devices, and low charging efficiency and poor stability in the prior art. By constructing a terminal device charging capacity portrait and dynamically adjusting charging parameters based on charging stability coefficient and steady-state output error, the technical effects of improving charging efficiency and stability are achieved.

[0016] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings of the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort fall within the scope of protection of the present application.

[0017] It should be noted that any variation of the terms "comprise" and "have" is intended to cover non-exclusive inclusion, for example, a process, method, system, product or server comprising a series of steps or units does not have to be limited to those clearly listed steps or units, but can include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices.

[0018] Embodiment one, as shown in the present application provides a power adaptive adjustment charging power supply management method, which comprises: Figure 1

[0019] ​Step S100: When the charging power supply is connected to the terminal device, activate the state sensing module to sense the state of the terminal device, and obtain the charging capability profile of the terminal device.

[0020] In the embodiment of the present application, when the charging power supply is connected to the terminal device, the actual charging operation has not yet started, at this time, the state sensing module is activated to sense the state of the terminal device. Specifically, by activating the state sensing module, the load identification unit and the temperature control sensing unit are called respectively, the electrical parameters and temperature information of the terminal device are collected, and the charging capability profile of the terminal device is constructed based on these multi-dimensional sensing data.

[0021] Further, the method provided by the application embodiment further comprises:

[0022] The load identification unit of the state sensing module communicates with the BMS to collect the state of charge (SOC), voltage, current and maximum allowable charging power of the terminal device; the temperature control sensing unit of the state sensing module is called to collect the ambient temperature and the thermal distribution map of the charging interface; and the charging capability profile of the terminal device is constructed based on the state of charge (SOC), voltage, current and maximum allowable charging power, and the ambient temperature and the thermal distribution map of the charging interface.

[0023] In the embodiment of the present application, first, the state sensing module is activated, the load identification unit therein establishes a standard communication connection with the built-in battery management system (Battery Management System, BMS) of the terminal device, preferably adopts CAN bus protocol or UART serial communication mode, and realizes real-time collection of core battery parameters of the device. The process includes calling the data reading instruction set built in the load identification unit, and sequentially collecting the state of charge (State of Charge, SOC) of the terminal device, the current voltage value of the battery, the current charging current and the maximum allowable charging power.

[0024] After the electrical parameter collection is completed, the temperature control sensing unit in the state sensing module is called synchronously, the temperature control sensing unit internally integrates an infrared temperature measurement module and a thermal image sensing processor, measures the ambient temperature of the charging interface area through the infrared sensing component, and performs thermal imaging scanning on the interface connection area to generate a thermal distribution map of the charging interface.

[0025] After the above electrical parameters and thermal parameters are obtained, the SOC, voltage, current, maximum allowable charging power, ambient temperature and thermal distribution map are extracted as a set of ordered parameters in a raw form, which is used as a direct representation of the current state of the terminal device, and a charging capability profile of the terminal device is constructed.

[0026] Step S200: Based on the charging capability profile of the terminal device, the output parameter template of the charging power supply is matched, and the initial output parameter of the charging power supply is obtained.

[0027] In the embodiment of the present application, when the charging power output parameter template matching is performed based on the terminal device charging capability profile, first, the charging capability profiles of a plurality of historical sample terminal devices and the corresponding charging power output parameters are obtained, and after heterogeneous division and mean value processing, a plurality of representative template terminal charging capability profiles are generated; then the corresponding output parameters are aggregated and screened to form a plurality of charging power output parameter templates. Subsequently, the current terminal device charging capability profile is matched and searched with the template profiles in the template library, the closest template is selected therefrom, and the initial charging power output parameter for controlling the current charging behavior is obtained.

[0028] Further, the method provided by the application embodiment further comprises the following steps:

[0029] obtaining a plurality of sample terminal device charging capability profiles and a plurality of sample charging power output parameters corresponding thereto; performing heterogeneous division on the plurality of sample terminal device charging capability profiles to obtain a plurality of divided sample terminal charging device capability profile sets; performing mean value processing on the plurality of divided sample terminal charging device capability profile sets to obtain a plurality of template terminal charging capability profiles; aggregating the plurality of sample charging power output parameters according to the plurality of divided sample terminal charging device capability profile sets to obtain a plurality of aggregated sample charging power output parameter sets; screening the plurality of aggregated sample charging power output parameter sets to obtain a plurality of charging power output parameter templates; and performing mapping and associated storage on the plurality of template terminal charging capability profiles and the plurality of charging power output parameter templates to construct a template library; and performing matching and searching on the terminal device charging capability profile and the template terminal charging capability profiles in the template library to obtain the initial charging power output parameter template.

[0030] In the embodiment of the present application, first, the charging capability profiles of a plurality of sample terminal devices are obtained through historical collection or simulation test, each profile is composed of a plurality of dimensional parameters such as SOC, voltage, current, maximum allowed charging power, environmental temperature and thermal distribution characteristics, and the charging power output parameters adopted by the corresponding terminal in the best charging state are recorded, including target voltage, current limit and initial power setting.

[0031] Next, the charging capability portraits of the plurality of sample terminal devices are classified, i.e., the multidimensional portrait feature vectors are classified unsupervisedly based on the K-means clustering algorithm. In this process, first, all sample vectors are normalized (such as min-max normalization), and the parameter scales of different dimensions are unified, and then the samples are divided into K categories according to the principle of minimum Euclidean distance. Each category forms a charging device capability portrait set of the divided sample terminal. Through this process, a plurality of charging device capability portrait sets of the divided sample terminal are obtained.

[0032] Next, the charging capability portraits of the plurality of sample terminal devices are classified, i.e., the multidimensional portrait feature vectors are classified unsupervisedly based on the K-means clustering algorithm. In this process, first, all sample vectors are normalized (such as min-max normalization), and the parameter scales of different dimensions are unified, and then the samples are divided into K categories according to the principle of minimum Euclidean distance. Each category forms a charging device capability portrait set of the divided sample terminal. Through this process, a plurality of charging device capability portrait sets of the divided sample terminal are obtained.

[0033] Then, according to the sample charging power output parameters corresponding to each charging device capability portrait set of the divided sample terminal, an aggregation process is performed. All sample charging power output parameters in the category are collected as a whole to form an aggregated sample charging power output parameter set, which is used to reflect the typical charging strategy performance under the terminal state. Through this step, a plurality of aggregated sample charging power output parameter sets are obtained. After obtaining the plurality of aggregated sample charging power output parameter sets, an initial screening starting point is obtained by mean calculation, and based on this, a random iteration operation is performed in the set to generate a plurality of iteration screening starting points. By comparing the representative coefficient of each iteration screening starting point with the representative coefficient of the initial starting point, if the promotion condition is met, continue to iterate and update along the optimization direction, and gradually approach the output parameter subset with stronger representativeness. After a predetermined number of iterations, the selected aggregated sample set is finally selected as the charging power output parameter template, and a plurality of charging power output parameter templates are obtained.

[0034] Next, the plurality of template terminal charging capability portraits and the corresponding charging power output parameter templates are mapped and stored in association. A template library is constructed using key-value pairing, in which the template terminal charging capability portrait is used as the retrieval key and the charging power output parameter template is used as the corresponding value, to realize structured organization and fast indexing. Through this step, the charging power output parameter template library is constructed.

[0035] Finally, the terminal device charging capability portrait obtained by the current collection is input into the template matching module, and a minimum Euclidean distance matching algorithm is used to perform similarity retrieval with all template terminal charging capability portraits in the template library. The Euclidean distance between the current portrait and each template portrait is calculated, and the template corresponding to the minimum distance is selected, and the associated charging power output parameter template is extracted as the initial charging power output parameter template for the current charging control.

[0036] Further, the method provided by the application embodiment further comprises:

[0037] calculating the mean of the plurality of aggregated sample charging power output parameter sets to obtain a plurality of aggregated screening starting points; based on the plurality of aggregated screening starting points, randomly iterating in the plurality of aggregated sample charging power output parameter sets to obtain a plurality of iterative screening starting points; determining whether the representative coefficients of the plurality of iterative screening starting points are greater than or equal to the representative coefficients of the plurality of aggregated screening starting points, if yes, taking the direction from the plurality of aggregated screening starting points to the plurality of iterative screening starting points as a screening direction, and continuing to iterate the plurality of iterative screening starting points, and iterates in this way until a preset iteration number is met, and the plurality of aggregated sample charging power output parameters obtained by the last iteration are taken as the plurality of charging power output parameter templates.

[0038] In the application embodiment, first, an arithmetic mean calculation method is performed on each aggregated sample charging power output parameter set. The arithmetic mean of each parameter dimension (including target charging voltage, current limit value, and initial power setting value) of all samples in the set is calculated dimension by dimension to form a complete multi-dimensional output parameter vector as the aggregated screening starting point of the set. Through this step, a plurality of aggregated screening starting points are obtained, and each starting point represents the central tendency of an aggregated set.

[0039] Next, based on each aggregated screening starting point, a random sampling method is used to randomly select a plurality of sample charging power output parameter vectors from the corresponding aggregated sample charging power output parameter set as the iterative screening starting point of the current aggregated sample charging power output parameter set, which is used to represent the local feature area in the set. Through this step, a plurality of iterative screening starting points are obtained.

[0040] Next, to judge the centrality and representativeness of each iteration screening starting point in the aggregated sample charging power output parameter set to which it belongs, a similarity mean analysis method is used to calculate the representativeness coefficient. Specifically, for a certain iteration screening starting point, the cosine similarity of the iteration screening starting point with all sample output parameter vectors in the aggregated sample charging power output parameter set is calculated, and the arithmetic mean of all similarity values is taken to obtain the representativeness coefficient of the iteration screening starting point. The higher the representativeness coefficient, the closer the relative position of the point in the set to the majority of samples, and the stronger the representativeness. Through this step, the representativeness coefficient corresponding to each iteration screening starting point is obtained. After completing the calculation of the representativeness coefficients of all iteration screening starting points, it is judged in turn whether the representativeness coefficient of each iteration screening starting point is greater than or equal to the representativeness coefficient of the corresponding aggregated screening starting point (the coefficient is obtained by using the same similarity mean calculation method as the iteration starting point). If the representativeness coefficient of a certain iteration screening starting point is better than that of the corresponding aggregated screening starting point, the difference vector between the aggregated screening starting point and the iteration screening starting point is taken as the screening direction vector, that is, an update path pointing from the current state to a higher representativeness region is constructed. Based on the screening direction vector, the next round of sample point selection is continued in the corresponding aggregated sample charging power output parameter set using the direction iteration method. The selection of the new iteration screening starting point selects the sample point closest to the direction vector in the sample set along the screening direction. Then the representativeness coefficient of the new iteration screening starting point is recalculated, and it is judged whether to continue iteration. The screening iteration process continues to be executed until the preset iteration round threshold (such as 5 rounds) is met or the representativeness coefficient improvement amplitude of the last two rounds is less than the set convergence threshold (such as 0.001), that is, the screening process of the current sample set is terminated.

[0041] Finally, in each aggregated sample charging power output parameter set, the sample output parameter vector with the maximum or most stable representativeness coefficient obtained in the last iteration is taken as the charging power output parameter template of the set. Through this process, it is ensured that the selected template has the highest representativeness and universality in the overall sample set, thereby forming multiple charging power output parameter templates that can be used for portrait adaptation of different terminal devices.

[0042] Further, the method provided by the application embodiment further comprises:

[0043] The similarity mean of each iteration screening starting point with the corresponding aggregated sample charging power output parameter set in the plurality of aggregated sample charging power output parameter sets is calculated to obtain the representativeness coefficient of the plurality of iteration screening starting points.

[0044] In the embodiments of the present application, in order to evaluate the representativeness of the plurality of iterative screening starting points in the aggregated sample charging power supply output parameter set to which each of the plurality of iterative screening starting points belongs, similarity calculation is performed on each of the plurality of iterative screening starting points and all of the charging power supply output parameter sample vectors in the aggregated sample charging power supply output parameter set corresponding to the iterative screening starting point. Specifically, a similarity measurement method based on vector direction consistency is used to perform similarity analysis on each of the plurality of iterative screening starting points and all of the sample output parameters in the aggregated sample set one by one, and the obtained similarity results are taken as an arithmetic mean, thereby obtaining the similarity average of the iterative screening starting point in the aggregated sample charging power supply output parameter set. The similarity average is defined as the representativeness coefficient of the iterative screening starting point, and is used to measure the typicality and centrality of the point in the set. Through the above calculation, the representativeness coefficients of the plurality of iterative screening starting points are finally obtained.

[0045] Step S300: According to the initial charging power supply output parameter, the charging power supply is controlled to charge the terminal device by the management module, and the state perception module is called to continuously monitor the state of the terminal device, thereby obtaining an interactive state monitoring data sequence.

[0046] In the embodiments of the present application, after the initial charging power supply output parameter is determined, the management module is called to start the charging control process. The management module controls the charging power supply to perform actual charging operation on the currently connected terminal device according to the target voltage, current limit and power setting value in the initial charging power supply output parameter through the output control unit in the management module. At the same time, the state perception module is called in parallel to continuously monitor the running state of the terminal device in the charging process. The process continuously communicates with the battery management system (BMS) in the terminal device to collect key state parameters in the charging process in real time, including the current state of charge (SOC), the real-time updated maximum allowed charging power and the battery temperature state. These parameter data are packaged into a unified structure data unit and form an interactive state monitoring data sequence at a set time interval.

[0047] Step S400: Iterative fluctuation identification is performed on the interactive state monitoring data sequence to determine a terminal device charging stability coefficient.

[0048] In the embodiment of the present application, when the interaction state monitoring data sequence is iteratively identified, first, the near-neighbor difference of the interaction state monitoring data sequence is calculated to obtain the near-neighbor difference sequence of the interaction state monitoring data reflecting the charging state change rate; then, the extreme value points are extracted from the near-neighbor difference sequence of the interaction state monitoring data, and the time interval between adjacent extreme values is calculated to form an extreme value interval window set. The maximum value in the extreme value interval window set is taken as the first iterative fluctuation identification scale, and the minimum value is taken as the second iterative fluctuation identification scale, and based on the two scales, the difference sequence is analyzed for multiple rounds of fluctuation to identify the fluctuation characteristics at each time scale. Finally, the identification result is processed by mean value to obtain the charging stability coefficient of the terminal device under the current charging parameter control.

[0049] Further, the method provided by the embodiment of the present application further comprises:

[0050] The near-neighbor difference of the interaction state monitoring data sequence is calculated to obtain the near-neighbor difference sequence of the interaction state monitoring data; the extreme value in the near-neighbor difference sequence of the interaction state monitoring data is extracted, and the interval window of adjacent two extreme values is determined to obtain an extreme value interval window set; the first iterative fluctuation identification scale and the second iterative fluctuation identification scale are determined based on the extreme value interval window set; the near-neighbor difference sequence of the interaction state monitoring data is iteratively identified based on the first iterative fluctuation identification scale and the second iterative fluctuation identification scale, and the identification result is processed by mean value to obtain the charging stability coefficient of the terminal device.

[0051] Further, the method provided by the embodiment of the present application further comprises:

[0052] The maximum value in the extreme value interval window set is taken as the first iterative fluctuation identification scale, and the minimum value in the extreme value interval window set is taken as the second iterative fluctuation identification scale.

[0053] In the embodiment of the present application, first, the near-neighbor difference of the interaction state monitoring data sequence is calculated. Specifically, the same dimension data items (including the battery state of charge SOC, the maximum allowed charging power, and the battery temperature state) between two consecutive sampling points in the time sequence are differentiated item by item, the sliding window difference method is used to calculate the change value of each pair of adjacent points on each parameter, and a new time sequence is formed by merging, which is called the near-neighbor difference sequence of the interaction state monitoring data.

[0054] Subsequently, the local maximum and minimum values in the near-neighbor difference sequence of the interaction state monitoring data are extracted by using the fixed window extreme value identification method. Specifically, whether the current point is greater than or less than all other points in the fixed length sliding window is identified to identify the extreme value point. Then, the interval of the adjacent two extreme value points in the time index is recorded to generate an extreme value interval window set.

[0055] Next, the maximum and minimum values are extracted from the extreme value interval window set by using the maximum and minimum value extraction method, as the time scale for subsequent fluctuation identification, wherein the maximum value is used as the first iteration fluctuation identification scale, and the minimum value is used as the second iteration fluctuation identification scale.

[0056] Finally, the near-neighbor difference sequence of the interaction state monitoring data is iteratively identified by using the fixed scale sliding window method based on the first iteration fluctuation identification scale and the second iteration fluctuation identification scale. The first iteration fluctuation identification scale and the second iteration fluctuation identification scale are used as the window length, and the sliding window traversal is performed on the difference sequence. The maximum fluctuation amplitude in each window is calculated to quantify the fluctuation intensity in the window, and the fluctuation feature sequences under two scales are formed. The arithmetic average method is performed on the fluctuation feature sequences under the two scales to obtain the average values. The average values are averaged to obtain the final terminal device charging stability coefficient.

[0057] Step S500: The voltage sampling sequence and the current sampling sequence of the charging power supply are obtained by interaction, and the output error is identified based on the initial charging power supply output parameter to obtain a steady-state output error.

[0058] In the embodiment of the present application, first, the voltage sampling sequence and the current sampling sequence of the charging power supply are obtained by data interaction with the control interface of the charging power supply, that is, the output voltage values and the output current values at multiple time points are continuously read in a preset sampling period to form the voltage sampling sequence and the current sampling sequence.

[0059] Subsequently, the initial charging power supply output parameter recorded in the management module is called to extract the target voltage value and the current limit value set in this stage as the reference benchmark for error identification. On this basis, the point-by-point difference calculation method is used to perform difference calculation on each actual voltage value in the voltage sampling sequence and the target voltage value, and the same operation is performed on each actual current value in the current sampling sequence and the target current value to obtain the voltage error sequence and the current error sequence. Then, the two error sequences are subjected to mean statistical processing, that is, the arithmetic average of the error values at all sampling time points is performed to obtain the voltage average error and the current average error. The two average error values are combined as the output performance index of this stage, which is defined as the corresponding steady-state output error.

[0060] Step S600: adjusting the initial charging power supply output parameter based on the charging stability coefficient and the steady-state output error to obtain an adjusted charging power supply output parameter, and transmitting the adjusted charging power supply output parameter to a management module for charging power supply management.

[0061] In the embodiment of the present application, when the initial charging power supply output parameter is adjusted based on the charging stability coefficient and the steady-state output error, a parameter adjustment module is first pre-constructed, the parameter adjustment module is called, the current charging stability coefficient and the initial charging power supply output parameter are read, a new set of initial optimization parameters is generated according to the stability coefficient and the distribution of the current voltage, current, power and other set values by using a rule mapping identification method, and a first-stage adjusted charging power supply output parameter is formed. Then, according to the specific value of the steady-state output error, a plurality of random adjustment methods based on perturbation are performed on the first-stage parameter in a controllable range, such as adjusting the voltage set value ± 0.2V, the current limit value ± 0.5A, etc., to generate a plurality of update-stage adjusted charging power supply output parameters.

[0062] Then, an update similarity calculation method is used to calculate the similarity between each set of update-stage adjusted charging power supply output parameters and the first-stage adjusted parameter, and the set of update parameters with the maximum similarity is selected as the adjusted charging power supply output parameter of the current optimization completion.

[0063] Finally, the adjusted charging power supply output parameter is transmitted to the management module through the communication interface, the control parameter of the current charging power supply is updated by the management module, and the charging process is driven by the new parameter in the next charging period, so as to realize closed-loop charging control based on actual feedback and improve the stability, safety and energy efficiency of the charging process.

[0064] Further, in the method provided by the embodiment of the present application, the initial charging power supply output parameter is adjusted based on the charging stability coefficient and the steady-state output error to obtain an adjusted charging power supply output parameter, and the method further comprises:

[0065] a parameter adjustment module is pre-constructed; the charging stability coefficient and the initial charging power supply output parameter are identified by using the parameter adjustment module to obtain a first-stage adjusted charging power supply output parameter; the first-stage adjusted charging power supply output parameter is adjusted according to a preset adjustment mode based on the size of the steady-state output error to obtain a plurality of update-stage adjusted charging power supply output parameters; and the update similarity between the plurality of update-stage adjusted charging power supply output parameters and the first-stage adjusted charging power supply output parameter is iteratively calculated, and the update-stage adjusted charging power supply output parameter corresponding to the maximum update similarity is taken as the adjusted charging power supply output parameter.

[0066] Further, the method provided by the application embodiment further comprises:

[0067] The preset adjustment mode is to randomly increase or decrease a parameter in the first stage adjustment charging power supply output parameter according to a preset scale, wherein the preset scale is determined according to the steady-state output error.

[0068] In the application embodiment, first, a parameter adjustment module is pre-constructed, which is established by using a parameter configuration initialization method, that is, the interface format and the adjustable field range of the input and output parameters are preset in the initialization stage, including the voltage set value, the current limit value and the power set value, etc., to ensure that the module can receive the charging stability coefficient and the initial charging power supply output parameter as input, and to provide a basis for subsequent identification and adjustment. Through this step, the initialization construction of the parameter adjustment module is completed. Then, the parameter adjustment module is called, and a rule mapping identification method is used to analyze and process the input charging stability coefficient and the initial charging power supply output parameter. Whether the current charging process is stable is determined according to the numerical range of the stability coefficient, and each field value in the initial output parameter is matched and processed, for example, when the stability coefficient is lower than the preset threshold and the current limit value is higher, the current set will be adjusted downward according to the preset mapping relationship, and then a set of optimized output parameters is generated as the first stage adjustment charging power supply output parameter.

[0069] Next, according to the size of the steady-state output error in the current stage, an error magnitude matching method is used to determine the corresponding preset adjustment mode. According to the preset interval (such as less than 1%, 1% to 5%, greater than 5%) in which the steady-state output error falls, different preset adjustment scales (such as voltage step ±0.1V, current step ±0.2A) are assigned, and multiple random disturbance operations are performed accordingly. Specifically, in each round of disturbance, one or more parameters are selected from the first stage adjustment charging power supply output parameter, and are randomly increased or decreased by the corresponding preset adjustment scale, so as to generate a new set of output parameters, and multiple updated stage adjustment charging power supply output parameters are obtained.

[0070] Then, a Euclidean distance calculation method is used to evaluate the difference between the multiple updated stage adjustment charging power supply output parameters and the original first stage adjustment charging power supply output parameter. By performing Euclidean distance operation on the same dimension numerical vectors composed of each set of updated parameters and the first stage parameters, the distance between the two in the parameter space is quantified, and the value is taken as the update similarity. This method can judge the aggregation degree of each disturbance result near the original strategy, which helps to avoid deviating from the reasonable control range.

[0071] Finally, a maximum similarity selection method is used to traverse all the generated updated stage parameter groups, select the parameter group with the maximum update similarity with the first stage parameter group, and take it as the final adjustment charging power supply output parameter.

[0072] In the embodiments of the present application, based on the above, the embodiments of the present application have at least the following technical effects:

[0073] After the charging power supply is connected to the terminal device, the state sensing module is activated to sense the state of the terminal device and obtain a charging capability profile of the terminal device. Based on the charging capability profile of the terminal device, the output parameter template of the charging power supply is matched to obtain an initial output parameter of the charging power supply. Through the management module, the charging power supply is controlled to charge the terminal device according to the initial output parameter of the charging power supply, and the state sensing module is called to continuously monitor the state of the terminal device to obtain an interaction state monitoring data sequence. The interaction state monitoring data sequence is iteratively identified to determine a charging stability coefficient of the terminal device. The voltage sampling sequence and the current sampling sequence of the charging power supply are obtained, and the output error is identified based on the initial output parameter of the charging power supply to obtain a steady-state output error. Based on the charging stability coefficient and the steady-state output error, the initial output parameter of the charging power supply is adjusted to obtain an adjusted output parameter of the charging power supply, and the adjusted output parameter of the charging power supply is transmitted to the management module for charging power supply management. The present application solves the technical problems of fixed charging power supply output parameters in the prior art, which are difficult to adapt to the charging capability and state changes of different terminal devices, resulting in low charging efficiency and poor stability. By constructing a charging capability profile of the terminal device and dynamically adjusting the charging parameters based on the charging stability coefficient and the steady-state output error, the technical effects of improving the charging efficiency and stability are achieved.

[0074] In the embodiments of the present application, based on the above, the embodiments of the present application have at least the following technical effects: Figure 2 As shown in the above embodiment, the present application provides a power adaptive adjustment charging power supply management system, and the system and method embodiments in the embodiments of the present application are based on the same inventive concept. The system comprises:

[0075] The state sensing module 11 is configured to activate the state sensing module to sense the state of the terminal device and obtain a charging capability profile of the terminal device when the charging power supply is connected to the terminal device. The matching module 12 is configured to match the output parameter template of the charging power supply based on the charging capability profile of the terminal device to obtain an initial output parameter of the charging power supply. The state monitoring module 13 is configured to control the charging power supply to charge the terminal device according to the initial output parameter of the charging power supply through the management module, and continuously monitor the state of the terminal device by calling the state sensing module to obtain an interaction state monitoring data sequence. The fluctuation identification module 14 is configured to identify the iteration fluctuation of the interaction state monitoring data sequence to determine a charging stability coefficient of the terminal device. The error identification module 15 is configured to obtain a voltage sampling sequence and a current sampling sequence of the charging power supply, and identify the output error in combination with the initial output parameter of the charging power supply to obtain a steady-state output error. The charging management module 16 is configured to adjust the initial output parameter of the charging power supply based on the charging stability coefficient and the steady-state output error to obtain an adjusted output parameter of the charging power supply, and transmit the adjusted output parameter of the charging power supply to the management module for charging power supply management.

[0076] Further, the system is also used to implement the following functions:

[0077] The load identification unit of the called state sensing module communicates with the BMS to collect the state of charge (SOC), voltage, current and maximum allowable charging power of the terminal device. The temperature control sensing unit of the called state sensing module collects the ambient temperature and the thermal distribution map of the charging interface. Based on the state of charge (SOC), voltage, current and maximum allowable charging power, and the ambient temperature and the thermal distribution map of the charging interface, the charging capability profile of the terminal device is constructed.

[0078] Further, the system is also used to implement the following functions:

[0079] Obtaining a plurality of sample terminal device charging capability portraits and corresponding a plurality of sample charging power output parameters; performing heterogeneous division on the plurality of sample terminal device charging capability portraits to obtain a plurality of divided sample terminal charging device capability portrait sets; performing mean value processing on the plurality of divided sample terminal charging device capability portrait sets to obtain a plurality of template terminal charging capability portraits; performing aggregation on the plurality of sample charging power output parameters according to the plurality of divided sample terminal charging device capability portrait sets to obtain a plurality of aggregated sample charging power output parameter sets; performing screening on the plurality of aggregated sample charging power output parameter sets to obtain a plurality of charging power output parameter templates; performing mapping and association storage on the plurality of template terminal charging capability portraits and the plurality of charging power output parameter templates to construct a template library; performing matching and searching on the terminal device charging capability portrait and the template terminal charging capability portrait in the template library to obtain the initial charging power output parameter template.

[0080] Further, the system is also used to implement the following functions:

[0081] Calculating the mean value of the plurality of aggregated sample charging power output parameter sets to obtain a plurality of aggregated screening starting points; based on the plurality of aggregated screening starting points, randomly iterating in the plurality of aggregated sample charging power output parameter sets to obtain a plurality of iterative screening starting points; judging whether the representative coefficients of the plurality of iterative screening starting points are greater than or equal to the representative coefficients of the plurality of aggregated screening starting points, if yes, taking the direction from the plurality of aggregated screening starting points to the plurality of iterative screening starting points as the screening direction, continuing to iterate on the plurality of iterative screening starting points, and so on until the preset iteration number is met, and taking the plurality of aggregated sample charging power output parameters obtained by the last iteration as the plurality of charging power output parameter templates.

[0082] Further, the system is also used to implement the following functions:

[0083] Calculating the mean value of the plurality of iterative screening starting points respectively with the corresponding aggregated sample charging power output parameter sets in the plurality of aggregated sample charging power output parameter sets to obtain the representative coefficients of the plurality of iterative screening starting points.

[0084] Further, the system is also used to implement the following functions:

[0085] The near neighbor difference calculation is performed on the interaction state monitoring data sequence to obtain a near neighbor difference sequence of the interaction state monitoring data; extreme values in the near neighbor difference sequence of the interaction state monitoring data are extracted, and an interval window of adjacent two extreme values is determined to obtain an extreme value interval window set; a first iteration fluctuation recognition scale and a second iteration fluctuation recognition scale are determined based on the extreme value interval window set; the near neighbor difference sequence of the interaction state monitoring data is subjected to iteration fluctuation recognition based on the first iteration fluctuation recognition scale and the second iteration fluctuation recognition scale, and the recognition result is subjected to mean value processing to obtain a terminal device charging stability coefficient.

[0086] Further, the system is further configured to implement the following functions:

[0087] The maximum value in the extreme value interval window set is taken as the first iteration fluctuation recognition scale, and the minimum value in the extreme value interval window set is taken as the second iteration fluctuation recognition scale.

[0088] Further, the system is further configured to implement the following functions:

[0089] The parameter adjustment module is pre-constructed; the charging stability coefficient and the initial charging power supply output parameter are identified by using the parameter adjustment module to obtain a first stage adjustment charging power supply output parameter; the first stage adjustment charging power supply output parameter is subjected to multiple random adjustments according to a preset adjustment mode according to the size of the steady state output error to obtain multiple updated stage adjustment charging power supply output parameters; the update similarity of the multiple updated stage adjustment charging power supply output parameters and the first stage adjustment charging power supply output parameter is calculated iteratively, and the updated stage adjustment charging power supply output parameter corresponding to the maximum update similarity is taken as the adjustment charging power supply output parameter.

[0090] Further, the system is further configured to implement the following functions:

[0091] The preset adjustment mode is to randomly increase or decrease the parameters in the first stage adjustment charging power supply output parameter according to a preset scale, wherein the preset scale is determined according to the steady state output error.

[0092] It should be noted that the above sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The above describes a specific embodiment of the present application. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0093] The above description is only the preferred embodiment of the present application, and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0094] The specification and drawings are only exemplary and illustrative of the present application and are considered to cover any and all modifications, variations, combinations or equivalents that are within the scope of the present application. Obviously, various modifications and changes can be made to the present application by those skilled in the art without departing from the scope of the present application. Thus, it is intended that the present application cover the modifications and changes as they come within the scope of the application, and that the scope of the application be limited only by the claims.

Claims

1. A power adaptive regulation charging power management method, characterized in that, The method comprises: When the charging power supply is connected to the terminal device, activate the state sensing module to sense the state of the terminal device, and obtain the charging capability profile of the terminal device; Based on the charging capability profile of the terminal device, perform charging power supply output parameter template matching to obtain initial charging power supply output parameters; Through the management module, control the charging power supply to charge the terminal device according to the initial charging power supply output parameters, and call the state sensing module to continuously monitor the state of the terminal device to obtain interactive state monitoring data sequences; Iterative fluctuation identification is performed on the interactive state monitoring data sequences to determine the charging stability coefficient of the terminal device; Interactively obtain the voltage sampling sequence and the current sampling sequence of the charging power supply, perform output error identification in combination with the initial charging power supply output parameters to obtain a steady-state output error; Based on the charging stability coefficient and the steady-state output error, adjust the initial charging power supply output parameters to obtain adjusted charging power supply output parameters, and transmit the adjusted charging power supply output parameters to the management module for charging power supply management; Based on the charging capability profile of the terminal device, perform charging power supply output parameter template matching to obtain initial charging power supply output parameters, comprising: Obtain a plurality of sample terminal device charging capability profiles and a plurality of corresponding sample charging power supply output parameters; Classify the plurality of sample terminal device charging capability profiles to obtain a plurality of divided sample terminal charging device capability profile sets, wherein the plurality of sample terminal device charging capability profiles are classified based on a K-means clustering algorithm to perform unsupervised classification on a multi-dimensional profile feature vector; Perform mean value processing on the plurality of divided sample terminal charging device capability profile sets, that is, use the dimension-by-dimension mean value method to perform arithmetic averaging on all charging capability profiles in each parameter dimension in the plurality of divided sample terminal charging device capability profile sets to obtain a plurality of template terminal charging capability profiles; Based on the plurality of divided sample terminal charging device capability profile sets, aggregate the plurality of sample charging power supply output parameters to obtain a plurality of aggregated sample charging power supply output parameter sets, filter the plurality of aggregated sample charging power supply output parameter sets to obtain a plurality of charging power supply output parameter templates, after obtaining the plurality of aggregated sample charging power supply output parameter sets, obtain an initial filtering starting point through mean value calculation, and based on the initial filtering starting point, perform a random iteration operation in the set to generate a plurality of iteration filtering starting points, compare the representative coefficient of each iteration filtering starting point with the representative coefficient of the initial starting point, if the improvement condition is met, continue to iterate and update along the optimization direction, gradually approach the output parameter subset with strong representation, and after a preset number of iterations, the finally selected aggregated sample set is used as the charging power supply output parameter template to obtain a plurality of charging power supply output parameter templates; Map and store the plurality of template terminal charging capability profiles and the plurality of charging power supply output parameter templates to construct a template library; The terminal equipment charging capability image is matched with the template terminal charging capability image in the template library to obtain the initial charging power supply output parameter template; The multiple aggregated sample charging power supply output parameter sets are screened to obtain multiple charging power supply output parameter templates, including: The mean value of the multiple aggregated sample charging power supply output parameter sets is calculated, and the arithmetic mean of each parameter dimension, including the target charging voltage, current limit value and initial power setting value, of all samples in the set is calculated dimension by dimension to form a complete multi-dimensional output parameter vector, and multiple aggregated screening starting points are obtained, each of which represents the central tendency of an aggregated set; Based on the multiple aggregated screening starting points, random iteration is performed in the multiple aggregated sample charging power supply output parameter sets to obtain multiple iterative screening starting points, and a random sampling method is used to randomly select multiple sample charging power supply output parameter vectors from the aggregated sample charging power supply output parameter sets as the iterative screening starting points of the current aggregated sample charging power supply output parameter set, which are used to represent the local feature region in the set; It is judged whether the representative coefficients of the multiple iterative screening starting points are greater than or equal to the representative coefficients of the multiple aggregated screening starting points. For a certain iterative screening starting point, the cosine similarity of all sample output parameter vectors in the aggregated sample charging power supply output parameter set is calculated, and the arithmetic mean of all similarity values is obtained to obtain the representative coefficient of the iterative screening starting point. The higher the representative coefficient is, the closer the relative position of the point in the set to the majority of samples is, and the stronger the representative ability is. If yes, the direction from the multiple aggregated screening starting points to the multiple iterative screening starting points is taken as the screening direction, and iteration is continued on the multiple iterative screening starting points. In this way, the multiple aggregated sample charging power supply output parameters obtained by the last iteration are taken as the multiple charging power supply output parameter templates. The similarity mean values of the multiple iterative screening starting points and the corresponding aggregated sample charging power supply output parameter sets in the multiple aggregated sample charging power supply output parameter sets are calculated to obtain the representative coefficients of the multiple iterative screening starting points. A similarity measurement method based on vector direction consistency is used to analyze the similarity of each iterative screening starting point and all sample output parameters in the aggregated sample set one by one, and the arithmetic mean of the obtained similarity results is taken to obtain the similarity mean value of the iterative screening starting point in the aggregated sample charging power supply output parameter set. The similarity mean value is defined as the representative coefficient of the iterative screening starting point, which is used to measure the typicality and centrality of the point in the set.

2. The power adaptive regulation charging power management method of claim 1, wherein, It includes: The load identification unit of the state perception module is called to communicate with the BMS to collect the state of charge (SOC), voltage, current and maximum allowable charging power of the terminal equipment; The temperature control perception unit of the state perception module is called to collect the ambient temperature and charging interface heat distribution map; Based on the state of charge (SOC), voltage, current and maximum allowable charging power, and the ambient temperature and charging interface heat distribution map, the terminal equipment charging capability image is constructed.

3. The power adaptive regulation charging power management method of claim 1, wherein, The interactive state monitoring data sequence is subjected to iterative fluctuation recognition to determine a terminal device charging stability coefficient, comprising: The interactive state monitoring data sequence is subjected to near-neighbor difference calculation to obtain an interactive state monitoring data near-neighbor difference sequence; Extrema in the interactive state monitoring data near-neighbor difference sequence are extracted, and an interval window of adjacent two extrema is determined to obtain an extrema interval window set; Based on the extrema interval window set, a first iterative fluctuation recognition scale and a second iterative fluctuation recognition scale are determined, and the maximum-minimum value extraction method is used to process the extrema interval window set to extract a maximum value and a minimum value from the extrema interval window set as time scales for subsequent fluctuation recognition, wherein the maximum value is the first iterative fluctuation recognition scale, and the minimum value is the second iterative fluctuation recognition scale; Based on the first iterative fluctuation recognition scale and the second iterative fluctuation recognition scale, the interactive state monitoring data near-neighbor difference sequence is subjected to iterative fluctuation recognition, a sliding window traversal is performed on the difference sequence with the first iterative fluctuation recognition scale and the second iterative fluctuation recognition scale as window lengths, a maximum fluctuation amplitude is calculated in each window for quantifying fluctuation intensity in the window, a fluctuation feature sequence under two scales is formed, and the recognition results are subjected to mean value processing, i.e., the fluctuation intensity values of all windows under each scale are averaged, two average values are obtained, and then an average of the two average values is obtained to obtain the terminal device charging stability coefficient.

4. The power adaptive regulation charging power management method of claim 3, wherein, The maximum value in the extrema interval window set is taken as the first iterative fluctuation recognition scale, and the minimum value in the extrema interval window set is taken as the second iterative fluctuation recognition scale.

5. The power adaptive regulation charging power management method of claim 1, wherein, Based on the charging stability coefficient and the steady-state output error, the initial charging power supply output parameter is adjusted to obtain an adjusted charging power supply output parameter, comprising: A pre-constructed parameter adjustment module; The charging stability coefficient and the initial charging power supply output parameter are recognized by using the parameter adjustment module to obtain a first-stage adjusted charging power supply output parameter; According to the size of the steady-state output error, the first-stage adjusted charging power supply output parameter is subjected to multiple random adjustments according to a preset adjustment mode, different preset adjustment scales are assigned according to a preset interval into which the steady-state output error falls, and multiple random disturbance operations are performed according to the preset adjustment scales, in each round of disturbance, one or more parameters are selected from the first-stage adjusted charging power supply output parameter to be randomly increased or decreased by a corresponding preset adjustment scale, thereby generating a new set of output parameters to obtain multiple update-stage adjusted charging power supply output parameters; The update similarity of the charging power supply output parameter adjusted in each of the plurality of update stages to the first stage adjustment of the charging power supply output parameter is calculated. The difference between the charging power supply output parameter adjusted in each of the plurality of update stages and the original first stage adjustment of the charging power supply output parameter is evaluated by using the Euclidean distance calculation method. The Euclidean distance between each set of update parameters and the first stage parameters is calculated to quantify the distance between them in the parameter space, and the quantified distance is used as the update similarity. The update similarity is used to determine the update stage adjustment of the charging power supply output parameter.

6. The power adaptive regulation charging power management method of claim 5, wherein, The preset adjustment method is to randomly increase or decrease the parameters in the first stage adjustment of the charging power supply output parameter according to a preset scale. The preset scale is determined according to the steady-state output error. The error magnitude matching method is used to determine the corresponding preset adjustment method according to the size of the steady-state output error in the current stage.

7. A power adaptive regulated charging power management system, characterized by, The system is used to perform the power adaptive adjustment method of the charging power supply management method according to any one of claims 1-6. The system comprises: The state sensing module is used to activate the state sensing module to sense the state of the terminal device when the charging power supply is connected to the terminal device, and obtain the charging capability profile of the terminal device. The matching module is used to match the charging power supply output parameter template based on the charging capability profile of the terminal device, and obtain the initial charging power supply output parameter. The state monitoring module is used to control the charging power supply to charge the terminal device according to the initial charging power supply output parameter through the management module, and continuously monitor the state of the terminal device through the state sensing module to obtain the interactive state monitoring data sequence. The fluctuation identification module is used to identify the fluctuation of the interactive state monitoring data sequence iteratively to determine the charging stability coefficient of the terminal device. The error identification module is used to obtain the voltage sampling sequence and the current sampling sequence of the charging power supply, and identify the output error based on the initial charging power supply output parameter to obtain the steady-state output error. The charging management module is used to adjust the initial charging power supply output parameter based on the charging stability coefficient and the steady-state output error to obtain the adjusted charging power supply output parameter, and transmit the adjusted charging power supply output parameter to the management module for charging power supply management.

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