Multifunctional integrated AC / DC charging device with 3D printing function

Abstract

This invention provides a multi-functional integrated AC / DC charging device with 3D printing capabilities, belonging to the technical field of AC / DC charging devices. The AC / DC charging device is configured to: acquire historical AC / DC charging data for different charging objects, perform cluster analysis based on charging performance changes to form object charging performance change characteristic data; acquire current AC / DC charging performance information of the target charging object, and combine it with the object charging performance change characteristic data to perform charging guidance analysis to form current charging basic information; collect charging demand information, and combine it with the current charging basic information to perform AC / DC charging guidance analysis to form current charging guidance information. This device provides a more reasonable AC / DC interactive charging service through the analysis of interactive charging big data, not only efficiently ensuring the charging service but also improving the battery performance of the charging object.

Description

Technical Field

[0001] This invention relates to the field of AC / DC charging equipment technology, and more specifically, to a 3D-printed multifunctional integrated AC / DC charging device. Background Technology

[0002] With the development of 3D technology, it is gradually being applied to more fields. The use of 3D printing in charging equipment is currently a cutting-edge application of 3D printing technology. Because 3D printing technology offers greater control over materials than traditional material manufacturing and processing, charging equipment produced using 3D printing technology has superior charging performance, significantly improving charging efficiency.

[0003] Currently, the demand for alternating AC and DC charging is increasing. AC charging is slower but has less impact on battery performance, while DC charging is faster but has a greater impact on battery performance. Modern 3D-printed AC / DC integrated charging devices offer better alternating AC and DC charging performance, necessitating proper control over the charging service provided to the devices to ensure optimal battery performance.

[0004] Therefore, designing a multifunctional integrated AC / DC charging device with 3D printing capabilities, and providing more reasonable AC / DC interactive charging services based on the analysis of interactive charging big data, is an urgent problem to be solved. This not only ensures the efficient operation of the charging service but also improves the battery performance of the charging device. Summary of the Invention

[0005] The purpose of this invention is to provide a 3D-printed multifunctional integrated AC / DC charging device. By acquiring charging data information of the charging objects served by the AC / DC charging device, reasonable AC / DC charging interaction data for different charging objects under different battery usage conditions is extracted. This provides guidance data for the AC / DC charging device to provide more reasonable and efficient AC and DC charging interaction services to the charging objects. At the same time, based on the charging needs of the charging objects, a more reasonable AC / DC charging service mode is formed to meet different charging needs. On the one hand, it can ensure that the AC / DC charging device can efficiently and energy-savingly meet the charging needs of the charging objects, and on the other hand, it can also reasonably improve the battery performance of the charging objects.

[0006] In a first aspect, the present invention provides a 3D-printed multifunctional integrated AC / DC charging device, configured to: acquire historical AC / DC charging data of different charging objects, perform cluster analysis based on changes in charging performance to form object charging performance change characteristic data; acquire current AC / DC charging performance information of the target charging object, and combine it with the object charging performance change characteristic data to perform charging guidance analysis to form current charging basic information; collect charging demand information, and combine it with the current charging basic information to perform AC / DC charging guidance analysis to form current charging guidance information.

[0007] In this invention, the device extracts reasonable AC / DC charging interaction data for different charging objects under different battery usage conditions by acquiring charging data information of the charging objects served by the AC / DC charging equipment. This provides guidance data for the AC / DC charging equipment to provide more reasonable and efficient AC and DC charging interaction services to the charging objects. At the same time, based on the charging needs of the charging objects, a more reasonable AC / DC charging service mode is formed to meet different charging needs. On the one hand, it can ensure that the AC / DC charging equipment can meet the charging needs of the charging objects efficiently and energy-savingly. On the other hand, it can also reasonably improve the battery performance of the charging objects.

[0008] One possible approach is to acquire historical AC / DC charging data for different charging objects, perform cluster analysis based on changes in charging performance, and generate object charging performance change characteristic data. This includes: clustering historical AC / DC charging data based on different charging objects to generate object-clustered AC / DC charging historical data; collecting battery lifespan and charging duration information for each charging object from the different object-clustered AC / DC charging historical data, performing performance comparison analysis based on lifespan, and generating object charging performance comparison information; extracting features based on stable battery lifespan from the object charging performance comparison information for different charging objects, and generating object charging performance characteristic information; and extracting historical sub-item charging information for each charging object from the different object-clustered AC / DC charging historical data, and combining this with the object charging performance characteristic information to perform interactive charging optimization feature analysis, and generating object charging performance change characteristic data.

[0009] In this invention, for AC / DC charging equipment, different charging objects have different batteries and charging performance, resulting in different charging methods. Therefore, to enable AC / DC charging equipment to more accurately and reasonably serve different charging objects and meet their personalized charging needs, it is necessary to perform clustering of historical AC / DC charging data based on different charging objects during big data analysis. After completing the segmentation of historical charging data for different charging objects, considering that even for the same charging object, the battery status may vary, leading to significant differences in AC / DC interactive charging services, further clustering based on the charging object's battery lifespan is required. After completing these two data clusterings, reasonable AC / DC interactive charging feature information can be extracted from the clustered data, helping to form more accurate and reasonable AC / DC charging interactive feature information. It should be noted that for the same object, clustering based on battery lifespan can also be combined with actual charging conditions and the charging object's energy usage performance to achieve clustering beyond just battery lifespan factors.

[0010] As one possible implementation, historical AC / DC charging data for different objects is clustered, and battery lifespan and charging duration information for each charging object are collected. Performance comparison analysis based on lifespan is then performed to form object charging performance comparison information. This includes: setting a similarity tolerance value for battery lifespan; obtaining the current battery lifespan of each charging object from the historical AC / DC charging data for different objects; and clustering charging objects based on similar lifespans according to the similarity tolerance value to form historical charging data with similar lifespans for different objects under the clustered AC / DC charging data; and obtaining the current battery lifespan of each charging object from the historical charging data with similar lifespans for different objects. 'm' represents the ID of the charging object in the AC / DC charging history data of different object clusters within the similar lifespan charging history data; for the similar lifespan charging history data, the total charging time for each charging object is obtained. And based on the corresponding current battery lifespan Determine the total effective charging time rate of the lifespan. ,in, ; Obtain the total AC charging time for each charging object based on its similar lifespan charging history data. And based on the corresponding current battery lifespan Determine the total effective AC charging time rate of the lifespan. ,in, ; Obtain the total DC charging time for each charging object based on its similar lifespan charging history data. And based on the corresponding current battery lifespan Determine the total effective DC charging time rate of the lifetime. ,in, Based on the effective total AC charging time rate of the lifespan and lifespan effective DC charging total time rate Determine the AC / DC charging interaction time ratio for each charging object. ,in, Based on the effective total charging time rate corresponding to the lifespan of each charging object. Compared to AC / DC charging interaction time Determine the high-efficiency charging comparison factor ,in, , This indicates that the total charging time affects the weighting factor. This indicates the weighting factor for the impact of interactive charging duration; and the efficient charging comparison factor for each charging object. The charging objects in the charging history data of similar lifespan are sorted to form ordered similar object sequence information; the charging history data of similar lifespan is then organized based on the order of the charging objects in the ordered similar object sequence information to form object charging performance comparison information.

[0011] In this invention, the extraction of AC / DC interactive charging feature information based on battery lifespan performance mainly involves identifying parameters associated with the AC / DC interactive charging method, and then extracting the relationship between these parameters and AC / DC interactive charging. This provides reference and comparison data for subsequent AC / DC interactive charging services. Considering AC / DC charging, it is crucial to focus on the total charging time and the time relationship between AC and DC charging within that total charging time. Because the extracted data is clustered based on battery lifespan, the analysis and extraction of feature information must take into account the relationship between the extracted data and battery lifespan. Of course, it's understandable that AC / DC intermodal charging devices can perform both AC and DC charging. AC charging typically takes longer but has less impact on battery life, while DC charging is shorter but has a greater impact on battery life. In today's efficiency-driven world, AC / DC intermodal charging aims to improve battery performance by combining DC charging with AC charging while maintaining the efficiency of DC charging. Therefore, when considering a suitable charging method, both the total charging time and the ratio of DC charging time to AC charging time need to be considered simultaneously. Simply considering charging time alone, while the total charging time may be long, it doesn't guarantee efficient and fast charging every time. Conversely, considering only charging efficiency, while DC charging may have a high proportion, it can significantly impact battery performance. Therefore, when extracting efficient charging data, analyzing the total charging time and the ratio of AC to DC charging time based on weights makes the data more reasonable. The weighting factors can be determined based on actual conditions or big data analysis. Similarly, the battery lifespan similarity tolerance value is a reference for dividing battery lifespan into stages. It is the basis for completing the data clustering of the same charging object in different battery lifespan stages. It can be set according to actual conditions or determined based on big data analysis.

[0012] As one possible implementation, based on the comparison information of charging performance of different charging objects, feature extraction based on stable battery life is performed to form object charging performance feature information. This includes: setting a corresponding high-efficiency charging feature extraction limit value for each object charging performance comparison information; determining charging objects whose high-efficiency charging comparison factor is not less than the high-efficiency charging feature extraction limit value in the corresponding object charging performance comparison information, identifying them as high-efficiency charging objects, and extracting the charging history data corresponding to the high-efficiency charging objects to form high-efficiency charging object performance comparison information; extracting high-efficiency charging feature information for each high-efficiency charging object performance comparison information to form corresponding high-efficiency charging feature information; combining different high-efficiency charging feature information corresponding to the same charging object to form object high-efficiency charging feature information; and combining object high-efficiency charging feature information corresponding to different charging objects to form object charging performance feature information.

[0013] In this invention, after rationally clustering and sorting the charging data, it is necessary to extract feature information from this data based on the high-efficiency characteristics of AC / DC interactive charging. This mainly involves defining the data of charging objects corresponding to high-efficiency charging under the given order, thereby providing a more reasonable data partitioning for subsequent feature information extraction and analysis. Of course, whether charging data belongs to high-efficiency and reasonable charging data needs to be analyzed and judged in conjunction with the battery's lifespan and historical charging conditions. Therefore, the feature extraction limit values ​​for high-efficiency charging can be set according to actual conditions or determined based on big data analysis.

[0014] As one possible implementation, high-efficiency charging feature information is extracted from the performance comparison information of each high-efficiency charging object to form corresponding high-efficiency charging feature information, including: obtaining the total effective charging time rate for each high-efficiency charging object based on its performance comparison information. and AC / DC charging interaction time ratio 'n' represents the ordered number of different high-efficiency charging objects in the performance comparison information; based on the total effective charging time over lifetime. As the dependent variable, the corresponding AC / DC charging interaction time ratio Using the total effective charging time rate over lifetime as the independent variable, a nonlinear fitting is performed relative to the AC / DC charging interaction time ratio to form a high-efficiency charging characteristic variation function. .

[0015] In this invention, the extraction of efficient charging feature information mainly serves as a reference for determining the AC charging duration and DC charging duration when the charging object undergoes AC / DC alternating charging. Therefore, feature extraction analysis involves correlation analysis between the total charging time and battery lifespan, as well as the ratio of total DC charging time to total AC charging time. It's worth noting that efficient charging should be understood as the longest DC charging time achieved under the current battery lifespan condition, while minimizing the impact on battery lifespan changes. When performing a fitting analysis of the relationship between the effective total charging time rate and the AC / DC alternating charging time ratio, both data are considered to be related to battery lifespan, which reflects battery performance. Therefore, the fitting is non-linear; that is, the power of the resulting power function should be greater than the power of the curve function showing battery lifespan changing over time.

[0016] As one possible implementation, historical AC / DC charging data for different objects is clustered, historical sub-item charging information for each charging object is extracted, and interactive charging optimization feature analysis is performed in conjunction with object charging performance feature information to form object charging performance change feature data. This includes: determining the corresponding average interactive charging change value for each high-efficiency charging feature information of each different charging object under each different object charging performance feature information. ,in: , , This represents the AC / DC charging interaction time ratio of the i-th charging session for the efficient charging object numbered n, based on the time-dimension sequence. This represents the AC / DC charging interaction change value of the high-efficiency charging object numbered n relative to the number of charging cycles; it also represents the object interaction change characteristic data by combining different average interaction charging change values ​​under the same charging object; and it represents the object charging performance change characteristic data by combining all object interaction change characteristic data of different charging objects.

[0017] In this invention, the total charging time, DC total charging time, and AC total charging time are all extracted from the overall analysis of the reasonable charging situation of the charging object at a specific stage of battery life. However, the state changes of battery life are also affected by the different AC and DC charging times and proportions each time. Therefore, based on the efficient feature information extraction, the AC and DC interactive charging feature information of the charging object based on the number of charging times is extracted again to form a data adjustment reference for reasonable interactive charging from another dimension.

[0018] One possible approach is to acquire the current AC / DC charging performance information of the target charging object and combine it with the object's charging performance change characteristic data to perform charging guidance analysis, forming the current basic charging information. This includes: acquiring the target charging object's real-time battery lifespan, real-time total charging time, real-time total AC charging time, and real-time total DC charging time; and determining the real-time lifetime effective total charging time rate based on the real-time battery lifespan and real-time total charging time. Real-time AC / DC charging interaction time ratio Based on real-time battery lifespan, determine the efficient charging characteristic change function of the target charging object corresponding to the same charging object in the object's charging performance characteristic information. The calibration is based on the real-time selection of high-efficiency charging characteristic change function. Based on the real-time selection of high-efficiency charging characteristic change function And combined with the real-time lifetime effective total charging time rate of the target charging object Compared with real-time AC / DC charging interaction time We conduct charging performance stability analysis to generate current basic charging information for the target charging object.

[0019] In this invention, after acquiring feature data from large datasets, it is necessary to design a reasonable AC / DC interactive charging method based on the actual battery performance of the target object during charging. By using an efficient charging feature change function and combining it with the current charging information of the target object, a reasonable charging data design can be performed, providing charging data references for the AC / DC interactive charging of the target object.

[0020] As one possible implementation, the high-efficiency charging characteristic change function is selected in real time. And combined with the real-time lifetime effective total charging time rate of the target charging object Compared with real-time AC / DC charging interaction time The system performs charging performance stability analysis to generate current basic charging information for the target charging object, including: setting the interactive charging deviation γ, and selecting a high-efficiency charging characteristic change function in real time. Real-time lifespan and effective total charging time rate and the real-time AC / DC charging interaction time ratio The following analysis and judgment are made: If the high-efficiency charging characteristic change function is selected in real time... and real-time lifetime effective total charging time rate The determined AC / DC charging interaction time ratio belongs to [ , If the target charging object is determined to be an object with stable interactive charging performance, then the total real-time charging time and the ratio of real-time AC / DC charging interaction time of the target charging object are combined. This forms the current stable basic information for charging; if based on the real-time selection of the high-efficiency charging characteristic change function... and real-time lifetime effective total charging time rate The determined AC / DC charging interaction time ratio does not belong to [ , If the target charging object is determined to be a non-interactive charging stable object, the historical charging information of the target charging object is collected to form the current unstable basic information of charging.

[0021] In this invention, the charging performance stability analysis based on the extracted AC / DC interactive charging feature information mainly considers whether the target charging object is in a reasonable charging state under the current battery life data. If the AC / DC charging interaction time ratio formed by the efficient charging feature change function is within the reasonable range defined by the efficient charging feature information, then the charging state of the target object is considered to be stable and in the efficient charging state provided by the big data; otherwise, the charging state of the target charging object is considered to be unstable.

[0022] One possible approach is to collect charging demand information and combine it with current charging baseline information to perform AC / DC charging guidance analysis, thereby generating current charging guidance information. This includes: obtaining the target charging duration for the target charging object, and determining the effective total charging time rate based on the real-time total charging duration of the target charging object and the battery life. Based on the effective total charging time rate of the pilot life. In conjunction with the current basic charging information, AC / DC charging guidance analysis is performed to generate current charging guidance information.

[0023] In this invention, both the feature information obtained from big data and the charging stability analysis based on big data feature information serve to guide the AC / DC alternating charging of the target charging object for the next charging cycle. Therefore, based on the upcoming charging demand information of the target charging object, considering that the duration of a single charging cycle is negligible compared to the total charging duration, it is assumed that a single charging cycle will not cause a jump in battery lifespan. Thus, the feature information extracted from big data can be directly used for prediction.

[0024] As one possible implementation, based on the effective total charging time rate of the boot lifetime. Based on the current charging infrastructure information, AC / DC charging guidance analysis is performed to generate current charging guidance information, including: when the target charging object is an object with stable interactive charging performance, the effective total charging time rate is based on the guidance lifetime. and real-time selection of efficient charging characteristic change function Determine the ratio of AC / DC charging interaction time. In conjunction with the target charging duration, the maximum DC charging time is determined to satisfy the guide AC / DC charging interaction time ratio. The guided AC charging duration and guided DC charging duration; when the target charging object is a non-interactive charging stable object, the real-time AC / DC charging interaction change value of the target charging object is determined based on the historical charging information of the target charging object. Based on the corresponding average interactive charging change value The following comparative analysis will be conducted: If > Then As the guiding AC / DC charging interaction time ratio, and based on the target charging duration, the guiding AC charging duration and guiding DC charging duration that maximize the DC charging time and satisfy the guiding AC / DC charging interaction time ratio are determined; if ≤ Then As the ratio of AC to DC charging interaction time, and based on the target charging duration, the guiding AC charging duration and guiding DC charging duration that maximize the DC charging time and satisfy the guiding AC to DC charging interaction time ratio are determined.

[0025] In this invention, the charging information guidance varies depending on whether the target object is a stable charging object. For a target object with stable interactive charging performance, the AC / DC charging interaction time ratio can be directly determined using a real-time high-efficiency charging characteristic change function. Based on this, the required charging time is divided according to the maximum DC charging time. If the target object is not a stable interactive charging object, its charging performance has deviated from the feature information extracted from big data. In this case, the characteristics of this charging need to be considered, and the average ratio of AC / DC charging time for each charge is used to determine the AC / DC charging time. It is understandable that as battery performance declines, the AC charging time will increase if charging aims to maintain battery performance as much as possible. This is a parameter that gradually increases as battery performance declines. > It is believed that the current charging distribution of the target charging object is below a reasonable average level, therefore... As a guide for charging duration, conversely, it is assumed that the current charging allocation of the target object is at or above a reasonable average level, and therefore... This serves as a guide for charging time.

[0026] The beneficial effects of the 3D-printed multifunctional integrated AC / DC charging device provided by this invention are as follows: This device extracts reasonable AC / DC charging interaction data for different charging objects under different battery usage conditions by acquiring charging data information of the charging objects served by AC / DC charging equipment. This provides guidance data for AC / DC charging equipment to provide more reasonable and efficient AC and DC charging interaction services to charging objects. At the same time, based on the charging needs of charging objects, it forms a more reasonable AC / DC charging service mode to meet different charging needs. On the one hand, it can ensure that AC / DC charging equipment can efficiently and energy-savingly meet the charging needs of charging objects, and on the other hand, it can also reasonably improve the battery performance of charging objects. Attached Figure Description

[0027] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 A flowchart illustrating the steps of a 3D-printed multifunctional integrated AC / DC charging device provided in an embodiment of the present invention. Detailed Implementation

[0029] The technical solutions of the present invention will now be described with reference to the accompanying drawings in the embodiments of the present invention.

[0030] With the development of 3D technology, it is gradually being applied to more fields. The use of 3D printing in charging equipment is currently a cutting-edge application of 3D printing technology. Because 3D printing technology offers greater control over materials than traditional material manufacturing and processing, charging equipment produced using 3D printing technology has superior charging performance, significantly improving charging efficiency.

[0031] Currently, the demand for alternating AC and DC charging is increasing. AC charging is slower but has less impact on battery performance, while DC charging is faster but has a greater impact on battery performance. Modern 3D-printed AC / DC integrated charging devices offer better alternating AC and DC charging performance, necessitating proper control over the charging service provided to the devices to ensure optimal battery performance.

[0032] refer to Figure 1 This invention provides a 3D-printed multifunctional integrated AC / DC charging device. This device extracts reasonable AC / DC charging interaction data for different charging objects under different battery usage conditions by acquiring charging data information of the charging objects served by the AC / DC charging device. This provides guidance data for the AC / DC charging device to provide more reasonable and efficient AC and DC charging interaction services to the charging objects. Simultaneously, based on the charging needs of the charging objects, it forms a more reasonable AC / DC charging service mode that meets different charging needs. On the one hand, it ensures that the AC / DC charging device efficiently and energy-savingly meets the charging needs of the charging objects; on the other hand, it can also reasonably improve the battery performance of the charging objects.

[0033] The 3D printing multi-functional integrated AC / DC charging device is specifically configured as follows: S1: Obtain historical AC / DC charging data for different charging objects, perform cluster analysis based on changes in charging performance, and generate characteristic data of object charging performance changes.

[0034] Historical AC / DC charging data for different charging objects is acquired, and cluster analysis based on charging performance changes is performed to form object charging performance change characteristic data. This includes: clustering historical AC / DC charging data based on different charging objects to form object-clustered AC / DC charging historical data; collecting battery lifespan and charging duration information for each charging object from the different object-clustered AC / DC charging historical data, and performing performance comparison analysis based on lifespan to form object charging performance comparison information; extracting features based on stable battery lifespan from the object charging performance comparison information for different charging objects to form object charging performance characteristic information; and extracting historical sub-item charging information for each charging object from the different object-clustered AC / DC charging historical data, and combining this with the object charging performance characteristic information to perform interactive charging optimization feature analysis to form object charging performance change characteristic data.

[0035] For AC / DC charging equipment, different charging objects have different batteries and charging performance, resulting in different charging methods. Therefore, to enable AC / DC charging equipment to more accurately and reasonably serve different charging objects and meet their personalized charging needs, it is necessary to perform clustering of historical AC / DC charging data based on different charging objects during big data analysis. After completing the historical charging data segmentation for different charging objects, considering that even for the same charging object, the battery state may vary, leading to significant differences in AC / DC interactive charging services, further clustering based on the charging object's battery lifespan is required. After completing these two data clustering segments, reasonable AC / DC interactive charging feature information can be extracted from the clustered data, helping to form more accurate and reasonable AC / DC charging interaction feature information. It should be noted that for the same object, clustering based on battery lifespan can also be combined with actual charging conditions and the charging object's energy usage performance to achieve clustering beyond just battery lifespan factors.

[0036] For AC / DC charging history data clustered across different objects, battery lifespan and charging duration information are collected for each charging object. Performance comparison analysis based on lifespan is then performed to generate object charging performance comparison information. This includes: setting a similarity tolerance value for battery lifespan; obtaining the current battery lifespan of each charging object from the AC / DC charging history data clustered across different objects; and clustering charging objects based on similar lifespans according to the similarity tolerance value to form charging history data with similar lifespans for different objects under the clustered AC / DC charging history data; and obtaining the current battery lifespan of each charging object from the charging history data with similar lifespans for different objects. 'm' represents the ID of the charging object in the AC / DC charging history data of different object clusters within the similar lifespan charging history data; for the similar lifespan charging history data, the total charging time for each charging object is obtained. And based on the corresponding current battery lifespan Determine the total effective charging time rate of the lifespan. ,in, ; Obtain the total AC charging time for each charging object based on its similar lifespan charging history data. And based on the corresponding current battery lifespan Determine the total effective AC charging time rate of the lifespan. ,in, ; Obtain the total DC charging time for each charging object based on its similar lifespan charging history data. And based on the corresponding current battery lifespan Determine the total effective DC charging time rate of the lifetime. ,in, Based on the effective total AC charging time rate of the lifespan and lifespan effective DC charging total time rate Determine the AC / DC charging interaction time ratio for each charging object. ,in, Based on the effective total charging time rate corresponding to the lifespan of each charging object. Compared to AC / DC charging interaction time Determine the high-efficiency charging comparison factor ,in, , This indicates that the total charging time affects the weighting factor. This indicates the weighting factor for the impact of interactive charging duration; and the efficient charging comparison factor for each charging object. The charging objects in the charging history data of similar lifespan are sorted to form ordered similar object sequence information; the charging history data of similar lifespan is then organized based on the order of the charging objects in the ordered similar object sequence information to form object charging performance comparison information.

[0037] The extraction of AC / DC interactive charging feature information based on battery lifespan performance mainly involves identifying parameters associated with AC / DC interactive charging methods, and then extracting the relationship between these parameters and AC / DC interactive charging. This provides reference and comparative data for subsequent AC / DC interactive charging services. Considering AC / DC charging, it is crucial to focus on the total charging time and the time relationship between AC and DC charging within that total charging time. Since the extracted data is clustered based on battery lifespan, the analysis and extraction of feature information must take into account the relationship between the extracted data and battery lifespan. Of course, it's understandable that AC / DC intermodal charging devices can perform both AC and DC charging. AC charging typically takes longer but has less impact on battery life, while DC charging is shorter but has a greater impact on battery life. In today's efficiency-driven world, AC / DC intermodal charging aims to improve battery performance by combining DC charging with AC charging while maintaining the efficiency of DC charging. Therefore, when considering a suitable charging method, both the total charging time and the ratio of DC charging time to AC charging time need to be considered simultaneously. Simply considering charging time alone, while the total charging time may be long, it doesn't guarantee efficient and fast charging every time. Conversely, considering only charging efficiency, while DC charging may have a high proportion, it can significantly impact battery performance. Therefore, when extracting efficient charging data, analyzing the total charging time and the ratio of AC to DC charging time based on weights makes the data more reasonable. The weighting factors can be determined based on actual conditions or big data analysis. Similarly, the battery lifespan similarity tolerance value is a reference for dividing battery lifespan into stages. It is the basis for completing the data clustering of the same charging object in different battery lifespan stages. It can be set according to actual conditions or determined based on big data analysis.

[0038] Based on the comparison of charging performance of different charging objects, feature extraction based on stable battery life is performed to form object charging performance feature information. This includes: setting a corresponding high-efficiency charging feature extraction limit value for each object charging performance comparison information; determining charging objects whose high-efficiency charging comparison factor is not less than the high-efficiency charging feature extraction limit value in the corresponding object charging performance comparison information, identifying them as high-efficiency charging objects, and extracting the charging history data corresponding to the high-efficiency charging objects to form high-efficiency charging object performance comparison information; extracting high-efficiency charging feature information for each high-efficiency charging object performance comparison information to form corresponding high-efficiency charging feature information; combining different high-efficiency charging feature information corresponding to the same charging object to form object high-efficiency charging feature information; and combining object high-efficiency charging feature information corresponding to different charging objects to form object charging performance feature information.

[0039] After reasonably clustering and sorting the charging data, it is necessary to extract feature information from this data based on the high-efficiency characteristics of AC / DC interactive charging. This mainly involves defining the data of charging objects that correspond to high-efficiency charging within the sorted order, thus providing a more reasonable data partitioning for subsequent feature extraction and analysis. Of course, whether charging data qualifies as high-efficiency needs to be analyzed and judged in conjunction with battery lifespan and historical charging data. Therefore, the feature extraction limits for high-efficiency charging can be set according to actual conditions or determined based on big data analysis.

[0040] For each high-efficiency charging object's performance comparison information, high-efficiency charging feature information is extracted to form corresponding high-efficiency charging feature information, including: obtaining the total effective charging time rate for each high-efficiency charging object's lifetime based on its performance comparison information. and AC / DC charging interaction time ratio 'n' represents the ordered number of different high-efficiency charging objects in the performance comparison information; based on the total effective charging time over lifetime. As the dependent variable, the corresponding AC / DC charging interaction time ratio Using the total effective charging time rate over lifetime as the independent variable, a nonlinear fitting is performed relative to the AC / DC charging interaction time ratio to form a high-efficiency charging characteristic variation function.

[0041] The extraction of efficient charging characteristic information primarily serves as a reference for determining the AC and DC charging durations when performing AC / DC alternating charging on the target battery. Therefore, feature extraction analysis involves correlation analysis between the total charging time and battery lifespan, as well as the ratio of total DC charging time to total AC charging time. It's worth noting that efficient charging should be understood as the longest DC charging time achieved under the current battery lifespan, while minimizing the impact on battery lifespan changes. When fitting the relationship between the effective total charging time rate and the AC / DC alternating charging time ratio, both data points are considered to be related to battery lifespan, which reflects battery performance. Therefore, the fitting is non-linear; the resulting power function must have a power greater than the power of the curve function showing battery lifespan changing over time.

[0042] For different object clustering AC / DC charging history data, historical sub-item charging information for each charging object is extracted, and interactive charging optimization feature analysis is performed in combination with object charging performance feature information to form object charging performance change feature data, including: for each high-efficiency charging feature information of each different charging object under each different object charging performance feature information, the corresponding average interactive charging change value is determined. ,in: , , This represents the AC / DC charging interaction time ratio of the i-th charging session for the efficient charging object numbered n, based on the time-dimension sequence. This represents the AC / DC charging interaction change value of the high-efficiency charging object numbered n relative to the number of charging cycles; it also represents the object interaction change characteristic data by combining different average interaction charging change values ​​under the same charging object; and it represents the object charging performance change characteristic data by combining all object interaction change characteristic data of different charging objects.

[0043] Of course, the total charging time, DC total charging time, and AC total charging time are all analyses and extractions of the reasonable charging situation for charging objects in a specific stage of battery life. However, changes in battery life can also be affected by the different AC and DC charging times and proportions each time. Therefore, based on the efficient feature information extraction, AC and DC interactive charging feature information of the charging object based on the number of charging cycles is extracted again to form a data adjustment reference for reasonable interactive charging from another dimension.

[0044] S2: Obtain the current AC / DC charging performance information of the target charging object, and combine it with the object's charging performance change characteristic data to perform charging guidance analysis and form the current basic charging information. The system acquires the current AC / DC charging performance information of the target charging object and, combined with the object's charging performance change characteristic data, performs charging guidance analysis to form the current basic charging information. This includes: acquiring the target charging object's real-time battery lifespan, real-time total charging time, real-time total AC charging time, and real-time total DC charging time. Based on the real-time battery lifespan and real-time total charging time, the system determines the real-time lifetime effective total charging time rate. Real-time AC / DC charging interaction time ratio Based on real-time battery lifespan, determine the efficient charging characteristic change function of the target charging object corresponding to the same charging object in the object's charging performance characteristic information. The calibration is based on the real-time selection of high-efficiency charging characteristic change function. Based on the real-time selection of high-efficiency charging characteristic change function And combined with the real-time lifetime effective total charging time rate of the target charging object Compared with real-time AC / DC charging interaction time We conduct charging performance stability analysis to generate current basic charging information for the target charging object.

[0045] After acquiring the feature data formed by big data, it is necessary to design a reasonable AC / DC alternating charging method based on the actual battery performance of the target object. By using an efficient charging feature change function and combining it with the current charging information of the target object, a reasonable charging data design can be carried out, providing charging data reference for the AC / DC alternating charging of the target object.

[0046] Based on the real-time selection of high-efficiency charging characteristic change function And combined with the real-time lifetime effective total charging time rate of the target charging object Compared with real-time AC / DC charging interaction time The system performs charging performance stability analysis to generate current basic charging information for the target charging object, including: setting the interactive charging deviation γ, and selecting a high-efficiency charging characteristic change function in real time. Real-time lifespan and effective total charging time rate and the real-time AC / DC charging interaction time ratio The following analysis and judgment are made: If the high-efficiency charging characteristic change function is selected in real time... and real-time lifetime effective total charging time rate The determined AC / DC charging interaction time ratio belongs to [ , If the target charging object is determined to be an object with stable interactive charging performance, then the total real-time charging time and the ratio of real-time AC / DC charging interaction time of the target charging object are combined. This forms the current stable basic information for charging; if based on the real-time selection of the high-efficiency charging characteristic change function... and real-time lifetime effective total charging time rate The determined AC / DC charging interaction time ratio does not belong to [ , If the target charging object is determined to be a non-interactive charging stable object, the historical charging information of the target charging object is collected to form the current unstable basic information of charging.

[0047] The stability analysis of charging performance based on the extracted AC / DC interactive charging feature information mainly considers whether the target charging object is in a reasonable charging state under the current battery life data. If the AC / DC charging interaction time ratio formed by the efficient charging feature change function is within the reasonable range defined by the efficient charging feature information, then the charging state of the target object is considered to be stable and in the efficient charging state provided by the big data. Otherwise, the charging state of the target charging object is considered to be unstable.

[0048] S3: Collect charging demand information and combine it with the current basic charging information to perform AC / DC charging guidance analysis and form the current charging guidance information.

[0049] Collect charging demand information and combine it with current charging infrastructure information to perform AC / DC charging guidance analysis, forming current charging guidance information, including: obtaining the target charging duration for the target charging object, and determining the effective total charging time rate based on the real-time total charging duration of the target charging object and the battery life. Based on the effective total charging time rate of the pilot life. In conjunction with the current basic charging information, AC / DC charging guidance analysis is performed to generate current charging guidance information.

[0050] Of course, both the feature information obtained from big data and the charging stability analysis based on big data feature information guide the AC / DC alternating charging of the target charging object for the next charging. Therefore, based on the charging demand information of the target charging object, considering that the duration of a single charging session is negligible compared to the total charging time, it is assumed that a single charging session will not cause a jump in battery life, so the feature information extracted from big data can be directly used for prediction.

[0051] Based on the effective total charging time rate of the pilot life Based on the current charging infrastructure information, AC / DC charging guidance analysis is performed to generate current charging guidance information, including: when the target charging object is an object with stable interactive charging performance, the effective total charging time rate is based on the guidance lifetime. and real-time selection of efficient charging characteristic change function Determine the ratio of AC / DC charging interaction time. In conjunction with the target charging duration, the maximum DC charging time is determined to satisfy the guide AC / DC charging interaction time ratio. The guided AC charging duration and guided DC charging duration; when the target charging object is a non-interactive charging stable object, the real-time AC / DC charging interaction change value of the target charging object is determined based on the historical charging information of the target charging object. Based on the corresponding average interactive charging change value The following comparative analysis will be conducted: If > Then As the guiding AC / DC charging interaction time ratio, and based on the target charging duration, the guiding AC charging duration and guiding DC charging duration that maximize the DC charging time and satisfy the guiding AC / DC charging interaction time ratio are determined; if ≤ Then As the ratio of AC to DC charging interaction time, and based on the target charging duration, the guiding AC charging duration and guiding DC charging duration that maximize the DC charging time and satisfy the guiding AC to DC charging interaction time ratio are determined.

[0052] Of course, different charging information will guide the process depending on whether the target object is a stable charging object. For a target object with stable interactive charging performance, the AC / DC charging interaction time ratio can be determined directly using the real-time selection of the efficient charging characteristic change function. Based on this, the required charging time is divided according to the maximum DC charging time. If the target object is not a stable interactive charging object, its charging performance has already deviated from the feature information extracted from big data. In this case, the characteristics of this charging need to be considered, and therefore the average ratio of AC / DC charging time for each charge is used to determine the AC / DC charging time. It is understandable that as battery performance declines, the AC charging time will increase if charging aims to maintain battery performance as much as possible. This is a parameter that gradually increases as battery performance declines. > It is believed that the current charging distribution of the target charging object is below a reasonable average level, therefore... As a guide for charging duration, conversely, it is assumed that the current charging allocation of the target object is at or above a reasonable average level, and therefore... This serves as a guide for charging time.

[0053] In summary, the beneficial effects of the 3D-printed multifunctional integrated AC / DC charging device provided by the embodiments of the present invention are as follows: This device extracts reasonable AC / DC charging interaction data for different charging objects under different battery usage conditions by acquiring charging data information of the charging objects served by AC / DC charging equipment. This provides guidance data for AC / DC charging equipment to provide more reasonable and efficient AC and DC charging interaction services to charging objects. At the same time, based on the charging needs of charging objects, it forms a more reasonable AC / DC charging service mode to meet different charging needs. On the one hand, it can ensure that AC / DC charging equipment can efficiently and energy-savingly meet the charging needs of charging objects, and on the other hand, it can also reasonably improve the battery performance of charging objects.

[0054] In the embodiments of this application, "instruction" can include direct and indirect instructions, as well as explicit and implicit instructions. The information indicated by a certain piece of information is called the information to be instructed. In the specific implementation process, there are many ways to instruct the information to be instructed, such as, but not limited to, directly instructing the information to be instructed, such as the information to be instructed itself or its index. It can also indirectly instruct the information to be instructed by instructing other information, where there is a relationship between the other information and the information to be instructed. It can also instruct only a part of the information to be instructed, while the other parts are known or pre-agreed upon. For example, the instruction of specific information can be achieved by using a pre-agreed (e.g., protocol-defined) arrangement of various pieces of information, thereby reducing instruction overhead to some extent. At the same time, common parts of various pieces of information can be identified and uniformly indicated to reduce the instruction overhead caused by individually indicating the same information.

[0055] Furthermore, the specific indication method can also be any existing indication method, such as, but not limited to, the above-mentioned indication methods and their various combinations. Specific details of various indication methods can be found in existing technologies, and will not be repeated here. As described above, for example, when multiple pieces of information of the same type need to be indicated, the indication methods for different pieces of information may differ. In the specific implementation process, the required indication method can be selected according to specific needs. This application embodiment does not limit the selected indication method; therefore, the indication methods involved in this application embodiment should be understood to cover various methods that enable the party to be indicated to obtain the information to be indicated.

[0056] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information messages sent separately, and the sending period and / or timing of these sub-information messages can be the same or different. The specific sending method is not limited in this application embodiment. The sending period and / or timing of these sub-information messages can be predefined, for example, according to a protocol, or configured by the sending device by sending configuration information to the receiving device.

[0057] "Predefined" or "pre-configured" can be achieved by pre-saving corresponding codes, tables, or other means that can be used to indicate relevant information in the device. This application does not limit the specific implementation method. "Saving" can refer to saving in one or more memories. These memories can be separate installations or integrated into the encoder, decoder, processor, or communication device. Alternatively, some memories can be separately installed, while others are integrated into the decoder, processor, or communication device. The type of memory can be any form of storage medium, and this application does not limit this.

[0058] The “protocol” mentioned in this application embodiment may refer to a protocol family in the field of communication, a standard protocol with a similar protocol family frame structure, or a related protocol applied to future communication systems. This application embodiment does not specifically limit this.

[0059] In the embodiments of this application, descriptions such as "when," "under the circumstances," "if," and "if" all refer to the device making corresponding processing under certain objective circumstances, and are not limited to a specific time. They do not require the device to make a judgment action during implementation, nor do they imply any other limitations.

[0060] In the description of the embodiments of this application, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can represent A or B. "And / or" in the embodiments of this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Furthermore, in the description of the embodiments of this application, unless otherwise stated, "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. Additionally, to facilitate a clear description of the technical solutions of the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first," "second," etc., do not limit the quantity or order of execution, and that "first," "second," etc., are not necessarily different. Furthermore, in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate that something is being used as an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner for ease of understanding.

[0061] It should be understood that the processor in the embodiments of this application can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0062] It should also be understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0063] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0064] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0065] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0066] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0067] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0068] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0069] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0070] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0071] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0072] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0073] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. Evaluation Warning: The document was created with Spire.Doc for Python. A multi-functional integrated AC / DC charging device with 3D printing capabilities, characterized in that... Configured as: Acquire historical AC / DC charging data for different charging objects, perform cluster analysis based on changes in charging performance, and generate characteristic data on changes in the charging performance of the objects. Obtain the current AC / DC charging performance information of the target charging object, and combine it with the charging performance change characteristic data of the object to perform charging guidance analysis and form the current charging basic information; Collect charging demand information and combine it with the current basic charging information to perform AC / DC charging guidance analysis to form current charging guidance information.

2. The 3D printing multifunctional integrated AC / DC charging device according to claim 1, characterized in that, The process of acquiring historical AC / DC charging data for different charging objects, performing cluster analysis based on changes in charging performance, and forming characteristic data of object charging performance changes includes: The AC / DC charging history data is clustered based on different charging objects to form object clustering AC / DC charging history data; For different objects, cluster AC / DC charging history data, collect battery lifespan information and charging duration information for each charging object, perform performance comparison analysis based on lifespan, and form object charging performance comparison information; Based on the comparison information of the charging performance of different charging objects, feature extraction based on stable battery life is performed to form object charging performance feature information; For different clusters of AC / DC charging history data of the objects, extract the historical sub-item charging information of each charging object, and combine it with the charging performance characteristic information of the objects to perform interactive charging optimization feature analysis to form the charging performance change characteristic data of the objects.

3. The 3D printing multifunctional integrated AC / DC charging device according to claim 2, characterized in that, The method involves clustering AC / DC charging history data for different objects, collecting battery lifespan information and charging duration information for each charging object, performing performance comparison analysis based on lifespan, and forming object charging performance comparison information, including: Set a similarity tolerance value for battery lifespan, cluster AC / DC charging history data for different objects, obtain the current battery lifespan of each charging object, and perform similar lifespan clustering of the charging objects according to the similarity tolerance value for battery lifespan to form different object similar lifespan charging history data under the object clustering AC / DC charging history data; For different similar lifespan charging history data of the objects, obtain the current battery lifespan Linowm of each charging object, where m represents the number of the charging object in the AC / DC charging history data of different objects in the similar lifespan charging history data of the objects; For the similar lifespan charging history data of the objects, obtain the total charging time Tallm for each of the charging objects, and determine the effective total charging time rate Rallm based on the corresponding current battery lifespan Linowm, where Rallm = TallmLnowm; For the similar lifespan charging history data of the objects, obtain the total AC charging time Tallaltm for each of the charging objects, and determine the effective AC charging time rate Rallaltm based on the corresponding current battery lifespan Lnowm, where Rallaltm = TallaltmLnowm; For the similar lifespan charging history data of the objects, obtain the total DC charging time Talldrtm for each of the charging objects, and determine the effective DC charging time rate Ralldrtm based on the corresponding current battery lifespan Lnowm, where Ralldrtm = TalldrtmLnowm; Based on the lifetime effective AC charging total time rate Rallaltm and the lifetime effective DC charging total time rate Ralldrtm, the AC / DC charging interaction time ratio Rintm for each of the charging objects is determined, where Rintm = RalldrtmRallaltm; Based on the total effective charging time rate Rallm and the AC / DC charging interaction time ratio Rintm corresponding to each charging object, the high-efficiency charging comparison factor Fm is determined, where Fm = α1Rallm + α2Rintm, α1 represents the weighting factor of the total charging time, and α2 represents the weighting factor of the interaction charging time. Based on the high-efficiency charging comparison factor Fm corresponding to each charging object, the charging objects in the charging history data of similar lifespan are sorted to form ordered similar object sequence information; Based on the order of the charging objects in the ordered similar object sequence information, the charging history data of the objects with similar lifespans are organized on an object-based basis to form the charging performance comparison information of the objects.

4. The 3D printing multifunctional integrated AC / DC charging device according to claim 3, characterized in that, The step of extracting features based on stable battery lifespan to form object charging performance feature information, according to the object charging performance comparison information of different charging objects, includes: For each object charging performance comparison information, a corresponding high-efficiency charging feature extraction limit value is set, and based on the high-efficiency charging feature extraction limit value, the charging objects whose high-efficiency charging comparison factor in the corresponding object charging performance comparison information is not less than the high-efficiency charging feature extraction limit value are determined as high-efficiency charging objects, and the charging history data corresponding to the high-efficiency charging objects is extracted to form high-efficiency charging object performance comparison information. For each of the high-efficiency charging objects, high-efficiency charging feature information is extracted to form corresponding high-efficiency charging feature information. Collect the different high-efficiency charging feature information corresponding to the same charging object to form object high-efficiency charging feature information; The efficient charging characteristic information of the object corresponding to different charging objects is collected to form the charging performance characteristic information of the object.

5. The 3D printing multifunctional integrated AC / DC charging device according to claim 4, characterized in that, The process of extracting high-efficiency charging feature information from the performance comparison information of each of the high-efficiency charging objects to form corresponding high-efficiency charging feature information includes: For each high-efficiency charging object performance comparison information, obtain the lifetime effective total charging time rate Rallm and the AC / DC charging interaction time ratio Rintn corresponding to each high-efficiency charging object, where n represents the ordered number of different high-efficiency charging objects in the high-efficiency charging object performance comparison information; Using the total effective charging time rate Rallm as the dependent variable and the corresponding AC / DC charging interaction time ratio Rintn as the independent variable, a nonlinear fitting of the total effective charging time rate relative to the AC / DC charging interaction time ratio is performed to form an efficient charging characteristic change function R(r).

6. The 3D printing multifunctional integrated AC / DC charging device according to claim 5, characterized in that, The method involves clustering AC / DC charging history data for different objects, extracting historical sub-item charging information for each charging object, and combining this with the object's charging performance characteristic information to perform interactive charging optimization feature analysis, thereby forming object charging performance change characteristic data, including: For each high-efficiency charging characteristic of each different charging object under each different charging performance characteristic information of the object, determine the corresponding average interactive charging change value Ck, where: Ck=1n(En)n,En=1i(iRintni)i,Rintni represents the AC / DC charging interaction time ratio of the i-th charging of the high-efficiency charging object numbered n based on the time dimension sequence, and En represents the AC / DC charging interaction change value of the high-efficiency charging object numbered n relative to the number of charging times. Collect the different average interactive charging change values ​​under the same charging object to form object interactive change feature data; Collect all the interaction change feature data of the different charging objects to form the object charging performance change feature data.

7. The 3D printing multifunctional integrated AC / DC charging device according to claim 6, characterized in that, The process involves acquiring the current AC / DC charging performance information of the target charging object, and combining this information with the object's charging performance change characteristic data to perform charging guidance analysis, thereby forming current basic charging information, including: The real-time battery life, real-time total charging time, real-time AC charging time, and real-time DC charging time of the target charging object are obtained, and the real-time effective total charging time rate Rall0 and the real-time AC-DC charging interaction time ratio Rint0 are determined based on the real-time battery life and the real-time total charging time. Based on the real-time battery lifespan, the efficient charging characteristic change function R(r) of the charging object that is the same as the target charging object in the object charging performance characteristic information is determined and calibrated as the efficient charging characteristic change function R(r) selected in real time; Based on the real-time selected high-efficiency charging characteristic change function R(r), and combined with the real-time lifetime effective total charging time rate Rall0 and the real-time AC / DC charging interaction time ratio Rint0 of the target charging object, a charging performance stability analysis is performed to form the current charging basic information of the target charging object.

8. The 3D printing multifunctional integrated AC / DC charging device according to claim 7, characterized in that, The step involves performing a charging performance stability analysis based on the real-time selected high-efficiency charging characteristic change function R(r), combined with the real-time lifetime effective total charging time rate Rall0 and the real-time AC / DC charging interaction time ratio Rint0 of the target charging object, to form the current charging basic information of the target charging object, including: Set the interactive charging deviation γ, and perform the following analysis and judgment based on the real-time selected high-efficiency charging characteristic change function R(r), the real-time lifetime effective total charging time rate Rall0, and the real-time AC / DC charging interaction time ratio Rint0: If the AC / DC charging interaction time ratio determined by the real-time selected high-efficiency charging characteristic change function R(r) and the real-time lifetime effective charging total time rate Rall0 belongs to [Rint0γ, Rint0+γ], then the target charging object is determined to be an object with stable interactive charging performance, and the real-time total charging time and the real-time AC / DC charging interaction time ratio Rint0 of the target charging object are combined to form the current charging stability basic information; If the AC / DC charging interaction time ratio determined by the real-time selected high-efficiency charging characteristic change function R(r) and the real-time lifetime effective charging total time rate Rall0 does not belong to [Rint0γ, Rint0+γ], then the target charging object is determined to be a non-interactive charging performance stable object, and the historical sub-item charging information of the target charging object is collected to form the current charging unstable basic information.

9. The 3D printing multifunctional integrated AC / DC charging device according to claim 8, characterized in that, The process involves collecting charging demand information and combining it with the current basic charging information to perform AC / DC charging guidance analysis, thereby generating current charging guidance information, including: The target charging time of the target charging object is obtained, and the Rallwill effective total charging time rate is determined based on the real-time total charging time of the target charging object and the battery life. Based on the RallWill effective total charging time rate during the guided lifetime and combined with the current charging basic information, AC / DC charging guidance analysis is performed to form the current charging guidance information.

10. The 3D printing multifunctional integrated AC / DC charging device according to claim 9, characterized in that, The step involves performing AC / DC charging guidance analysis based on the effective total charging time rate Rall0 of the guided lifetime and in conjunction with the current charging baseline information to form the current charging guidance information, including: When the target charging object is an object with stable interactive charging performance, the guided AC / DC charging interaction time ratio Rintwill is determined based on the guided lifetime effective total charging time rate RallWill and the real-time selected high-efficiency charging characteristic change function R(r). Combined with the target charging duration, the guided AC charging duration and guided DC charging duration that maximize the DC charging time and satisfy the guided AC / DC charging interaction time ratio Rintwill are determined. When the target charging object is a non-interactive charging performance stable object, based on the historical charging information of the target charging object, the real-time AC / DC charging interaction change value E0 of the target charging object is determined, and the following comparative analysis is performed based on the corresponding average interaction charging change value Ck: If E0 > Ck, then 1Ck is used as the guiding AC / DC charging interaction time ratio, and based on the target charging time, the guiding AC charging time and guiding DC charging time that maximize the DC charging time and satisfy the guiding AC / DC charging interaction time ratio are determined. If E0≤Ck, then 1E0 is used as the guiding AC-DC charging interaction time ratio, and based on the target charging time, the guiding AC charging time and guiding DC charging time that maximize the DC charging time and satisfy the guiding AC-DC charging interaction time ratio are determined.

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