A multi-device wireless charging control method and system

Abstract

The present application relates to the technical field of wireless charging, in particular to a multi-device wireless charging control method and system. The method comprises the following steps: obtaining real-time state data of each object to be wirelessly charged reported by a shared device rental cabinet and current situation data of the shared device rental cabinet; using a preset object-specific data set, the real-time state data and the current situation data to generate a charging control parameter set containing an emergency disposal strategy for each object, wherein the preset object-specific data set is constructed based on historical data and static attributes of each object to be charged; after each charging control parameter set is sent to a local control unit of the shared device rental cabinet, the local control unit is driven to control the wireless charging of multiple devices based on the charging control parameter set. The purpose of the present application is to solve the problem that the prior art cannot realize the wireless charging control of multiple devices, resulting in low charging efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless charging, in particular to a multi-device wireless charging control method and system. BACKGROUND

[0002] The shared device rental cabinet provides users with a variety of power tools supporting wireless charging. The rental cabinet provides registered users with a variety of types of power tools, such as a drill, an impact drill, an angle grinder, an electric saw, and an electric screwdriver, etc., to facilitate short-term rental on demand. The power tools all support wireless charging mode, and some tools are designed with built-in batteries, while others use detachable standardized battery packs. The battery pack itself also supports direct placement in the charging position for wireless charging. Currently, a cloud service platform is used to centrally manage information and schedule the charging process for all rental cabinets and power tools charging in the rental cabinets.

[0003] However, the types of power tools in the rental cabinet are diverse, and the specifications, battery characteristics, and charging requirements are different. The uncertainty of user behavior leads to significant differences in the state of the power tools when they are returned, such as differences in power, temperature, and running records. At the same time, the number of wireless charging stations inside the rental cabinet is limited. When multiple devices need to be charged, the existing first-come-first-serve charging strategy may result in low charging efficiency, and cannot prioritize power tools that urgently need to be charged or have reservations. In addition, the running state of the power tool itself and the external environment can affect the safety and effectiveness of the charging process. The placement posture of the power tool on the charging position can also affect the energy transfer efficiency of wireless charging. Network communication between the cloud platform and the local rental cabinet may be unstable or delayed, making it difficult to rely entirely on real-time instructions from the cloud platform for fine charging control. The local controller may not be able to effectively manage the charging process when communication is interrupted. The shared device rental cabinet cannot achieve wireless charging control for multiple types and specifications of power tools that need to be wirelessly charged, resulting in low charging efficiency. SUMMARY

[0004] The purpose of the present application is to provide a multi-device wireless charging control method and system to solve the problem of low charging efficiency caused by the inability of existing technology to achieve wireless charging control for multiple devices.

[0005] To achieve the above purpose, the technical scheme adopted by the present application is as follows: a multi-device wireless charging control method, comprising the following steps:

[0006] Obtaining real-time state data of each object to be wirelessly charged reported by a shared device rental cabinet and current scenario data of the shared device rental cabinet;

[0007] generate each charging control parameter set containing an emergency disposal strategy by using the preset object-specific data set, the real-time state data, and the current scenario data, wherein the preset object-specific data set is constructed based on historical data and static attributes of each object to be charged;

[0008] After each charging control parameter set is sent to the local control unit of the shared device rental cabinet, the local control unit controls wireless charging of multiple devices based on the charging control parameter set.

[0009] Optionally, the application further proposes that the step of generating each charging control parameter set containing an emergency disposal strategy by using the preset object-specific data set, the real-time state data, and the current scenario data comprises:

[0010] generate an initial charging control parameter set by using the preset object-specific data set, the real-time state data, and the current scenario data, wherein the current scenario data contains initial physical alignment state information between the object to be wirelessly charged and the charging position;

[0011] obtain a communication auxiliary parameter representing the quality of a communication link between the object to be wirelessly charged and the charging position corresponding to the initial physical alignment state information, and set the communication auxiliary parameter as a reference value;

[0012] collect real-time values of the communication auxiliary parameter of the object to be wirelessly charged during charging, and confirm a real-time value sequence;

[0013] determine a change trend of the real-time value sequence relative to the reference value;

[0014] when the change trend meets a preset alignment deterioration condition, adjust the initial charging control parameter set to obtain a charging control parameter set.

[0015] Optionally, the application further proposes that the step of constructing the preset object-specific data set based on historical data and static attributes of each object to be charged comprises:

[0016] when the change trend meets a preset alignment deterioration condition, generate an alignment deterioration event record containing an identifier of the object to be wirelessly charged, an identifier of the shared device rental cabinet, and the change trend;

[0017] update the initial charging control parameter set by using the alignment deterioration event record to obtain a charging control parameter set.

[0018] Optionally, the application further proposes that after the step of generating each charging control parameter set containing an emergency disposal strategy by using the preset object-specific data set, the real-time state data, and the current scenario data, the application further comprises:

[0019] generate a historical performance indicator using a preset object-specific data set, and generate an instant state indicator using real-time state data;

[0020] determine whether there is a decision conflict between a control strategy indicated by the historical performance indicator and a control strategy indicated by the instant state indicator;

[0021] in response to determining that there is the decision conflict, generate a temporary parameter set containing a monitoring trigger condition;

[0022] after the monitoring trigger condition is met, obtain a change indicator of the instant state indicator of the local control unit during execution of the temporary parameter set;

[0023] generate a charging control parameter set for subsequent charging of each object to be wirelessly charged using a degree of coincidence of the change indicator and the historical performance indicator.

[0024] Optionally, the step of generating a charging control parameter set for subsequent charging of each object to be wirelessly charged using a degree of coincidence of the change indicator and the historical performance indicator includes:

[0025] obtain running state data of at least one object in the shared device rental cabinet other than the object to be wirelessly charged;

[0026] identify an environmental disturbance event that meets a preset condition according to the running state data;

[0027] obtain a disturbance data segment affected by the environmental disturbance event based on a time correspondence relationship between the environmental disturbance event and the change indicator;

[0028] determine the degree of coincidence based on a part of the change indicator not included in the disturbance data segment and the historical performance indicator;

[0029] generate a charging control parameter set for subsequent charging of each object to be wirelessly charged according to the degree of coincidence.

[0030] Optionally, the step of identifying an environmental disturbance event that meets a preset condition according to the running state data includes:

[0031] monitor the running state data to obtain a plurality of single operation events, wherein none of the plurality of single operation events meets the preset condition;

[0032] determine a disturbance contribution value corresponding to each of the plurality of single operation events;

[0033] aggregate each of the disturbance contribution values to generate a cumulative disturbance value;

[0034] When the accumulated disturbance value meets a preset accumulated threshold condition, an environmental disturbance event meeting a preset condition is identified.

[0035] Optionally, the application further provides a method for identifying an environmental disturbance event meeting a preset condition, comprising:

[0036] For each single operation event in the plurality of single operation events, a current running stage of the wireless charging object is obtained;

[0037] A basic disturbance contribution value of the single operation event is determined;

[0038] The basic disturbance contribution value is adjusted by using the current running stage, and a disturbance contribution value corresponding to each single operation event is determined.

[0039] Optionally, the application further provides that the step of aggregating each disturbance contribution value to generate an accumulated disturbance value comprises:

[0040] A time weight corresponding to each disturbance contribution value is obtained;

[0041] Each disturbance contribution value is multiplied by the time weight corresponding thereto to obtain all weighted disturbance contribution values;

[0042] All the weighted disturbance contribution values are summed to generate the accumulated disturbance value.

[0043] Optionally, the application further provides that the step of obtaining real-time state data of each wireless charging object reported by the shared equipment rental cabinet and current situation data of the shared equipment rental cabinet comprises:

[0044] Real-time state data of each wireless charging object reported by the shared equipment rental cabinet, containing environmental information and reservation information, and current situation data of the shared equipment rental cabinet, containing tool placement information, are obtained.

[0045] The application further provides a multi-device wireless charging control system, comprising:

[0046] An obtaining module is configured to obtain real-time state data of each wireless charging object reported by the shared equipment rental cabinet and current situation data of the shared equipment rental cabinet;

[0047] A parameter set generation module is configured to generate, by using a preset object-specific data set, the real-time state data, and the current situation data, a charging control parameter set containing an emergency disposal strategy for each wireless charging object, wherein the preset object-specific data set is constructed based on historical data and static attributes of each wireless charging object;

[0048] The control module is configured to, after the control parameter set is sent to the local control unit of the shared device rental cabinet, drive the local control unit to control wireless charging of the multiple devices based on the control parameter set.

[0049] Compared with the prior art, the multi-device wireless charging control method and system has the following advantages:

[0050] The present application can obtain the real-time state data of each object to be wirelessly charged and the current situation data of the shared device rental cabinet, and can master the instant health condition of the object to be charged, the power level and the current state of the charging environment. In combination with the preset object-specific data set, a customized charging control parameter set is generated for each object to be wirelessly charged. The parameter set not only contains parameters for guiding normal charging process, but also contains emergency disposal strategies for potential abnormal situations. In the execution of the charging process by the local control unit, the real-time cloud instruction is not needed, and the sudden conditions such as temperature abnormality and poor connection can be coped with. The charging control parameter set is sent to the local control unit of the shared device rental cabinet. After the local control unit receives the parameter set, the wireless charging hardware is driven based on the instructions and strategies in the parameter set to perform wireless charging on the multiple devices in the cabinet. The charging control decision is more intelligent, and the charging efficiency, battery life and safety can be improved. By embedding the emergency strategy in the parameter set, the robustness of the system in unstable network communication is enhanced. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the specific embodiments of the present application, the drawings needed in the specific embodiments will be briefly introduced below. In all the drawings, the elements or parts are not necessarily drawn according to the actual proportions.

[0052] Figure 1 The flow chart of the multi-device wireless charging control method of the present application.

[0053] Figure 2 The structural block diagram of the multi-device wireless charging control system of the present application.

[0054] In the figure: 210, acquisition module; 220, parameter set generation module; 230, control module.

[0055] The implementation and advantages of the present application will be further described with reference to the embodiments and the drawings. DETAILED DESCRIPTION

[0056] The embodiments of the present application will be described below with reference to drawings. Numerous specific details will be set forth in the following description in order to provide a thorough understanding of the application. However, it will be appreciated that the application can be practiced without these specific details. In other instances, well-known methods have not been described in detail in order not to unnecessarily obscure the application. The specific details recited below are illustrative of the present application, but are not intended to limit the present application.

[0057] It should be noted that all directional directions (such as up, down, left, right, front, back, etc.) described herein are only used to explain relative positions between components, movement conditions, etc. in a certain specific posture (as shown in the drawings), and if the specific posture changes, the directional directions will also change accordingly.

[0058] In addition, the descriptions such as "first", "second" and the like in the present application are only for the purpose of description, and are not intended to specifically indicate the order or sequence, nor to limit the present application. They are merely used to distinguish components or operations described by the same technical terms, and cannot be understood as indicating or implying the relative importance of the indicated technical features or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first", "second" can be explicitly or implicitly included at least one of the features. In addition, the technical solutions of each embodiment can be combined with each other, but it must be based on the realization of ordinary skilled in the art. When the combination of technical solutions contradicts each other or cannot be realized, it should be considered that the combination of technical solutions does not exist, nor within the scope of protection required by the present application.

[0059] The conventional prior art has technical challenges in managing, improving charging efficiency, allocating limited resources, and responding to environmental changes and communication interruptions when facing different types, specifications, and states of objects to be charged in a shared device rental cabinet. It affects the ability of power tools to quickly recover to a usable state and the user experience. For example, a shared device rental cabinet is deployed outdoors, where the ambient temperature is high. Multiple different models of power tools are returned by users, and these tools have different battery levels, internal temperatures, and last use intensities. The number of wireless charging sites in the cabinet is limited, and some tools may be placed off-center by users, resulting in reduced wireless charging energy transfer efficiency. At the same time, the network connection of the rental cabinet is unstable. The conventional prior art only starts charging according to the return order or the power threshold of each power tool, without considering the influence of tool temperature, battery history, placement alignment, or external environment on the charging process. This results in some tools interrupting charging due to temperature rise, tools placed off-center taking longer to charge and occupying charging sites, and affecting other tools from obtaining charging services in a timely manner. The conventional prior art cannot achieve wireless charging control of multiple devices, resulting in low charging efficiency.

[0060] In order to further understand the content, characteristics and effects of the present application, the following examples are given below, and the details are described as follows with reference to the drawings.

[0061] Please refer to Figure 1 The present application provides a multi-device wireless charging control method, comprising the following steps:

[0062] S100, obtain the real-time state data of each object to be wirelessly charged reported by the shared device rental cabinet and the current situation data of the shared device rental cabinet. Wherein, the real-time state data is the current running state information of each object to be wirelessly charged reported by the shared device rental cabinet, which can be obtained by sensor collection or internal register reading, such as battery capacity, battery temperature, tool internal temperature, error code, etc., which is mainly to obtain the instant situation of the object to be charged, and to provide basis for dynamically adjusting the charging strategy. The current situation data is the overall environmental information of the shared device rental cabinet reported by the shared device rental cabinet, which can be obtained by environmental sensor collection, cabinet state monitoring, etc., such as cabinet environmental temperature, humidity, charging position occupation situation, tool placement position information, etc., which is mainly to obtain the external environment and resource allocation situation when charging occurs, and to provide basis for formulating global or local charging strategy.

[0063] S200, using the preset object exclusive data set, the real-time state data and the current situation data, generate a charging control parameter set containing an emergency disposal strategy for each object, wherein the preset object exclusive data set is constructed based on the historical data and static attributes of each object to be charged. Specifically, the preset object exclusive data set is a data set constructed based on the historical data and static attributes of each object to be charged, which can be realized by database storage, file storage, etc., such as tool model, battery type, rated capacity, maximum charging power, historical charging cycle number, typical use time and historical fault record, etc., which is mainly to provide the inherent characteristics and long-term behavior mode information of each object to be charged, and to provide the basis for generating personalized and optimized charging control parameters. The charging control parameter set is a parameter set containing an emergency disposal strategy generated for each object to be wirelessly charged, which can be represented in the form of data structure and configuration file, such as target charging current, target charging voltage, charging cutoff condition, temperature protection threshold and abnormal processing rule, etc., which is mainly to guide the local control unit to execute the specific charging process, and to perform safety processing in abnormal situation. The emergency disposal strategy is contained in the charging control parameter set, which is a rule or instruction for taking measures in abnormal situation during the charging process, which can be realized by conditional judgment logic and preset action sequence, such as reducing the charging power when the temperature is too high, suspending the charging when the communication quality is low, etc., which is mainly to ensure the safety of the charging process and the reliability of the device.

[0064] S300, after each of the charging control parameter sets is issued to the local control unit of the shared device rental cabinet, the local control unit is driven to control the wireless charging of multiple devices based on the charging control parameter set. The local control unit is a hardware or software module inside the shared device rental cabinet responsible for executing the charging control parameter set and directly controlling the wireless charging process. It can be implemented by an embedded microcontroller or an industrial control board, etc. Its main purpose is to receive cloud instructions and drive the wireless charging hardware locally to achieve specific charging control of multiple devices.

[0065] In this embodiment, the cloud service platform acts as the central processing entity and receives data from each shared device rental cabinet through the network. Each rental cabinet is equipped with sensors to collect real-time state data and current situation data of the tool to be charged, such as battery voltage, current, temperature, tool identification information on the charging position, and cabinet environment temperature, and package and report these data. The cloud platform maintains a database to store the static attributes of each tool model (such as battery type, capacity, and maximum charging power) and object-specific data sets constructed based on historical charging records, usage duration, etc. When receiving new reported data, the cloud platform runs existing decision algorithms based on these data and object-specific data sets. The algorithm comprehensively evaluates the tool's power demand, battery health, current temperature, cabinet environment temperature, charging position availability, and historical performance to generate a charging control parameter set containing specific charging parameters and emergency rules, where specific charging parameters such as initial charging power, power adjustment curve, or temperature threshold, and emergency rules such as reducing power to a certain proportion when temperature exceeds threshold, attempting small power charging or stopping charging when charging position is not well aligned. The parameter set is in the form of structured data, such as JSON format. It is issued to the local control unit of the target rental cabinet through the network. The local control unit, like an embedded controller, parses the received parameter set and controls the output power of the wireless charging module according to the instructions in it. During the charging process, the local control unit continuously monitors the tool's battery temperature and other real-time states. Once the emergency rules defined in the parameter set are triggered (e.g., temperature exceeds the set threshold), the local control unit immediately performs the corresponding emergency action, such as reducing the charging power, without waiting for further instructions from the cloud platform. When the charging is completed or other events occur, the local control unit reports the charging results and key events during the process to the cloud platform.

[0066] The scheme of the present application obtains the real-time state data of each object to be wirelessly charged reported by the shared device rental cabinet and the current situation data of the shared device rental cabinet, thereby grasping the instant health condition, power level of the object to be charged, and the current state of the charging environment. Meanwhile, in combination with the preset object-specific data set, which is constructed based on the historical data and static attributes of each object to be charged, the long-term characteristics and behavior patterns of each object are provided. Further, a customized charging control parameter set can be generated for each object to be wirelessly charged by using the preset algorithm model. This parameter set not only includes parameters for guiding the normal charging process, such as recommended charging power or current curve, but also includes emergency handling strategies for potential abnormal situations. The strategies are pre-set according to the characteristics, current state and environment of the object, and in the execution of the charging process by the local control unit, the sudden conditions such as temperature abnormality and poor connection can be coped with without relying on real-time cloud instructions. Subsequently, these generated charging control parameter sets are issued to the local control unit of the shared device rental cabinet. After the local control unit receives the parameter set, the wireless charging hardware is driven based on the instructions and strategies in the parameter set to perform wireless charging on multiple devices in the cabinet. This way makes the charging control decision more intelligent. At the same time, it can realize the improvement of charging efficiency, battery life and safety, and by embedding the emergency strategy in the issued parameter set, the robustness of the system when the network communication is unstable is enhanced.

[0067] In some embodiments of the above-mentioned embodiments of the present application, the present application further proposes that the step of generating each charging control parameter set containing an emergency handling strategy by using the preset object-specific data set, the real-time state data and the current situation data comprises:

[0068] An initial charging control parameter set is generated by using the preset object-specific data set, the real-time state data and the current situation data; wherein the current situation data includes initial physical alignment state information between the object to be wirelessly charged and the charging position. The initial charging control parameter set is a preliminary charging strategy parameter set generated based on available information before the start of the charging process, which can be implemented by using a data structure containing charging power, charging time or charging mode, etc. The purpose is to provide an initial charging scheme.

[0069] obtaining a communication auxiliary parameter representing a quality of a communication link between the wireless charging object and the charging position corresponding to the initial physical alignment state information, and setting the communication auxiliary parameter as a reference value. The initial physical alignment state information is initial position and attitude information of the wireless charging object when placed on the charging position, which can be obtained by visual recognition, position sensor or near field communication signal strength, and is used to evaluate the physical alignment state at the beginning of charging. The communication auxiliary parameter is a technical index reflecting the quality of the wireless communication link between the wireless charging object and the charging position, which can be realized by signal strength (RSSI), signal-to-noise ratio (SNR) or bit error rate (BER), and is used to indirectly represent the influence of the physical alignment state on communication. The reference value is the value of the communication auxiliary parameter obtained according to the initial physical alignment state information at the beginning of the charging process, which can be realized by recording the initial acquisition value, and is used to provide a reference point for subsequent real-time monitoring.

[0070] obtaining a real-time value of the communication auxiliary parameter of the wireless charging object during charging, and confirming a real-time value sequence. Specifically, the real-time value sequence is a data sequence composed of the values of the communication auxiliary parameter continuously collected during wireless charging, which can be realized by time stamp sequence data, and is used to record the change process of the communication link quality over time.

[0071] determining the change trend of the real-time value sequence relative to the reference value. The change trend is the change direction and amplitude of the real-time value sequence relative to the reference value, which can be realized by calculating the slope, comparing the average value or judging the continuous change direction, and is used to identify whether the communication link quality is deteriorating.

[0072] when the change trend meets a preset alignment deterioration condition, adjusting the initial charging control parameter set to obtain a charging control parameter set. The preset alignment deterioration condition is a technical standard or threshold set for judging whether the physical alignment state is deteriorating, which can be realized by conditions such as continuous decrease of the communication auxiliary parameter exceeding a certain threshold, decrease rate exceeding a certain value or continuous increase of the bit error rate reaching a certain level, and is used to determine when the charging strategy needs to be adjusted. The charging control parameter set is the final charging strategy parameter set obtained by adjusting the initial charging control parameter set after determining the alignment deterioration, which can be realized by updating the initial parameter set, and is used to optimize the charging process to cope with poor alignment.

[0073] Specifically, after generating the initial charging control parameter set by using the preset object-specific data set, real-time state data and current situation data, the initial placement position information of the object to be wirelessly charged on the charging position can be obtained through image recognition or sensor detection. Then, the communication auxiliary parameter corresponding to the initial placement position information can be obtained, for example, the initial signal strength (RSSI) value between the wireless charging modules is obtained, and the initial RSSI value is set as a reference value. During the charging of the object to be wirelessly charged, the system can continuously collect real-time values of RSSI to form a sequence of real-time values of RSSI. Then, the change trend of the sequence of real-time values of RSSI relative to the reference value can be determined, for example, whether the RSSI value presents a continuous downward trend. When the downward trend meets a preset alignment deterioration condition, for example, when the RSSI value decreases by more than 5 dBm within 30 seconds, the system can adjust the initial charging control parameter set, for example, reduce the initial set charging power by 20%, or trigger a prompt of a repositioning tool, so as to obtain the charging control parameter set for the current charging process. The application can monitor the change of the physical alignment state between the object to be wirelessly charged and the charging position in real time, and dynamically adjust the charging control parameter according to the alignment deterioration trend, effectively cope with the problem of charging efficiency reduction caused by poor physical alignment, improve the energy transmission efficiency, and improve the charging effect.

[0074] In some embodiments of the above-mentioned embodiments of the application, the preset object-specific data set is constructed based on the historical data and static attributes of each object to be charged.

[0075] When the change trend meets the preset alignment deterioration condition, an alignment deterioration event record containing the identification of the object to be wirelessly charged, the identification of the shared device rental cabinet and the change trend is generated. The alignment deterioration event record is a data structure containing the identification of the object to be wirelessly charged, the identification of the shared device rental cabinet and the change trend, which can be a data entry or a structured data packet, and is used to capture and record specific events indicating the deterioration of the physical alignment state between the object to be wirelessly charged and the charging position during the charging process.

[0076] The initial charging control parameter set is updated by using the alignment deterioration event record to obtain a charging control parameter set. In this embodiment, the initial charging control parameter set is updated by using the alignment deterioration event record to modify or adjust the initial charging control parameter set generated previously. Specifically, the adjustment range or direction can be determined by consulting historical alignment deterioration event data related to the to-be-wirelessly-charged object identifier or the shared equipment rental cabinet identifier, or according to the severity of the recorded change trend, so that the alignment deterioration abnormality is fed back to the current charging control strategy, and the parameter set can better adapt to the actual alignment state, or trigger a corresponding emergency disposal strategy.

[0077] Specifically, when the communication auxiliary parameter, such as the wireless signal strength or the energy transmission efficiency index, is monitored to have a downward trend relative to a reference value that meets a preset alignment deterioration condition (for example, a continuous decrease exceeding a certain threshold or a decrease rate exceeding a certain threshold), the system immediately generates an alignment deterioration event record. The record contains the unique identifier of the to-be-wirelessly-charged object currently being charged (for example, the tool serial number), the identifier of the shared equipment rental cabinet where it is located (for example, the cabinet number), and the specific change trend data of the monitored communication auxiliary parameter. Subsequently, the newly generated alignment deterioration event record is used to update the initial charging control parameter set generated for the to-be-wirelessly-charged object. The updating process can include dynamically adjusting the upper limit of the charging current, the target value of the charging voltage, or the preset value of the charging time length in the initial parameter set according to the severity of the recorded change trend. Or according to the recorded to-be-wirelessly-charged object identifier and the shared equipment rental cabinet identifier, historical alignment deterioration handling experience data related to the object or the location is retrieved from the preset object-specific data set, and the initial parameter set is modified according to these experience data. If the historical data shows that a certain model of tool is prone to alignment problems at a certain charging position of a certain cabinet, and historical handling experience shows that reducing the charging power can alleviate the problem, then when alignment deterioration occurs this time, the system will use the record to trigger a power reduction strategy in the parameter set. Thus, a charging control parameter set modified by the alignment deterioration event information is obtained to guide the subsequent charging process.

[0078] The application can generate an event record containing specific situational information when a misalignment is detected, and use the record to adjust the charging control parameter set. In this way, the abnormal event information of misalignment can be effectively fed back to the charging control strategy, making the parameter adjustment more targeted and enabling the charging problem caused by misalignment to be addressed more effectively, thereby improving the stability and success rate of the charging process. At the same time, by accumulating these event records, a data basis can be provided for the continuous optimization of the preset object-specific data set, enabling the system to learn and adapt to the alignment characteristics of different objects and positions, further improving the intelligent level of charging control.

[0079] In some embodiments of the above-mentioned embodiments of the application, the application further comprises, after the step of generating each charging control parameter set containing an emergency handling strategy using the preset object-specific data set, the real-time state data and the current situational data:

[0080] A historical performance indicator is generated using the preset object-specific data set, and an instant state indicator is generated using the real-time state data. The historical performance indicator is a quantitative representation of the charging behavior, efficiency and safety boundary of the object under typical or historical conditions, which is obtained based on statistical analysis of the preset object-specific data set, and serves as a reference baseline based on long-term experience. The instant state indicator is a quantitative representation of the current physical state, operating environment and other characteristics of the object, which is obtained based on real-time state data, and serves to provide information on the actual situation of the object.

[0081] It is determined whether there is a decision conflict between the control strategy indicated by the historical performance indicator and the control strategy indicated by the instant state indicator. The decision conflict is an inconsistency or potential risk between the control recommendations derived based on the historical performance indicator and the control recommendations derived based on the instant state indicator, and serves to identify situations that require special handling.

[0082] In response to determining that there is a decision conflict, a temporary parameter set containing a monitoring trigger condition is generated. The monitoring trigger condition is a condition for starting the execution of the temporary parameter set and data collection, such as reaching a certain charging stage, temperature threshold or time interval, and serves to verify the strategy at a specific time. The temporary parameter set is a set of charging control parameters temporarily generated for verifying or adjusting the control strategy after determining that there is a decision conflict, and serves to test the effect of different strategies in actual operation.

[0083] After the monitoring trigger condition is met, a change indicator of the instant state indicator during execution of the temporary parameter set by the local control unit is obtained. The change indicator is a quantitative representation of the change of the instant state indicator over time or the charging process during execution of the temporary parameter set, and its purpose is to reflect the impact of the temporary strategy on the state of the object.

[0084] generate a set of charging control parameters for each of the subsequent objects to be wirelessly charged, according to the degree of coincidence between the change indicator and the historical performance indicator. The degree of coincidence is the matching degree between the change trend of the behavior or state of the object reflected by the change indicator and the typical or expected behavior reflected by the historical performance indicator, and is used to evaluate the effectiveness of the temporary strategy.

[0085] Specifically, when an electric power tool is returned to a shared device rental cabinet and is ready for wireless charging, first, real-time state data of the tool is acquired, such as battery temperature of 40℃ and remaining power of 20%, and current situational data of the rental cabinet is acquired, such as ambient temperature of 35℃. At the same time, a preset object-specific data set of the tool is utilized, which may contain historical charging curves of the battery of this model, safe temperature range, temperature rise data under different charging currents, etc., to generate historical performance indicators, such as historical data showing that the battery temperature rises significantly faster and is prone to trigger over-temperature protection when the ambient temperature is above 30℃ and the charging current exceeds 0.8C. Instant state indicators are generated based on real-time state data, such as the current battery temperature of 40℃, which is already at a high level. At this time, it is determined that there is a decision conflict between the control strategy indicated by the historical performance indicators (such as usually recommending higher current charging to shorten the time when the power is low) and the control strategy indicated by the instant state indicators (such as the current temperature being too high, and high current charging is not suitable). In response to the determination that there is a decision conflict, the system generates a temporary parameter set containing a monitoring trigger condition, such as setting the upper limit of the charging current to 0.5C, and setting the monitoring trigger condition as: monitoring the battery temperature every 5 minutes after the start of charging for 30 minutes. The local control unit starts to execute the temporary parameter set to charge at a current of 0.5C. After the monitoring trigger condition is met, the system acquires the change indicators of the instant state indicators during the execution of the temporary parameter set by the local control unit, such as recording that the battery temperature rises from 40℃ to 43℃ within 30 minutes under the current of 0.5C. Finally, the degree of coincidence between the change indicators (temperature rise speed) and the historical performance indicators (historical temperature rise data) is utilized to generate a charging control parameter set for subsequent charging. For example, the temperature rise speed under the current of 0.5C is compared with the temperature rise speed under the current of 0.5C in the historical data, and with the temperature rise speed under the current of 0.8C or higher in the historical data. If it is found that the current temperature rise speed is basically consistent with the temperature rise speed under the current of 0.5C in the historical data, and is far lower than the temperature rise speed under the high current in the historical data, then 0.5C current is considered to be a relatively safe strategy, which can be used as the parameter set for subsequent charging, or the current can be further adjusted according to the temperature rise trend. The present application can identify and handle potential conflicts between charging control strategies generated based on historical data and real-time data, avoiding blindly executing strategies that may cause device overheating or low charging efficiency. By introducing temporary parameter sets for dynamic monitoring and verification, and adjusting according to the degree of coincidence between actual monitoring results and historical experience, the generated charging control parameter set is more adaptive and robust, and can better cope with complex situations and uncertainties in actual operation, thereby improving the safety, efficiency and reliability of multi-device wireless charging.

[0086] In some embodiments of the above-mentioned embodiments of the present application, the step of generating a set of charging control parameters for subsequent charging of each to-be-wirelessly-charged object using the degree of coincidence between the change indicator and the historical performance indicator comprises:

[0087] Obtaining running state data of at least one object in the shared device rental cabinet other than the to-be-wirelessly-charged object. Specifically, the running state data of at least one object is running or state information of non-to-be-charged objects inside or outside the shared device rental cabinet related to environmental changes, which can be implemented by using cabinet door opening and closing state, other charging position occupancy state, cabinet internal temperature sensor data, humidity sensor data, illumination sensor data, sound sensor data, or other non-to-be-charged tool temperature, power, etc. data, in order to obtain external or internal non-charging factor information that may affect the charging environment or the state of the to-be-charged object.

[0088] According to the running state data, an environmental disturbance event meeting a preset condition is identified. The preset condition is a rule or threshold set for judging whether an environmental disturbance event occurs, which can be implemented by using a single threshold, a combination rule of multiple indicators, or a model judgment rule trained based on historical data, in order to set the standard for identifying environmental disturbance events. The environmental disturbance event is an unexpected or non-charging-related event occurring in the environment of the shared device rental cabinet, which may affect the wireless charging process or the state of the to-be-charged object, which can be implemented by using events such as the cabinet door being opened, other tools being stored or taken out, environmental temperature or humidity changing sharply, or the cabinet body being impacted from outside, in order to identify external disturbances that may cause distortion of the change indicator.

[0089] Based on the time correspondence relationship between the environmental disturbance event and the change indicator, a disturbance data segment affected by the environmental disturbance event is obtained. The time correspondence relationship is the association between the time point or time period of the environmental disturbance event and the time point or time period recorded by the change indicator, which can be implemented by using time stamp matching, time window overlap judgment, or causal relationship analysis, in order to determine which part of the change indicator may occur at the same time as or be affected by a specific environmental disturbance event. The disturbance data segment is a data subset in the change indicator within the time period determined to be affected by the environmental disturbance event, which can be implemented by using the change indicator data recorded during the occurrence of the environmental disturbance event or a specific period of time thereafter, in order to separate the disturbed data from the change indicator.

[0090] Based on the part of the change indicator not included in the disturbance data segment and the historical performance indicator, the degree of coincidence is determined.

[0091] According to the degree of coincidence, a set of charging control parameters for subsequent charging of each to-be-wirelessly-charged object is generated.

[0092] In this embodiment, the temperature sensor data, humidity sensor data, cabinet door switch sensor data, and other charging site tool temperature and power data are obtained as the running state data of at least one object in the shared device rental cabinet other than the wireless charging object. The preset condition can be set as: the cabinet temperature rises by more than 5 degrees Celsius in a short time, or the cabinet door is opened for more than 10 seconds, or a tool is stored / taken out. When these conditions are monitored, it can be identified that the environmental disturbance event meets the preset condition. For example, if it is identified that the cabinet door is opened within a certain time period (e.g., 1 minute), the data of the change index (e.g., the battery temperature change rate of the charging object) within the time period and a buffer time (e.g., 30 seconds) thereafter can be marked as a disturbance data segment. In determining the degree of compliance, the data in the change index that is not marked as a disturbance data segment is extracted and compared with the historical performance index of the type of object (e.g., the typical temperature change curve of the type of battery during normal charging) to calculate the correlation coefficient as the degree of compliance. When generating the charging control parameter set according to the degree of compliance, if the degree of compliance is high, such as a correlation coefficient greater than 0.8, it is considered that the current state is consistent with historical experience, and the optimization strategy based on historical performance index is adopted. If the degree of compliance is low, a more conservative charging strategy needs to be adopted or further diagnosis needs to be triggered. The present application identifies and excludes the influence of environmental disturbance on the change index, so that the calculation of the degree of compliance is more accurate, thereby generating more reliable and effective charging control parameter sets. This improves the adaptability and robustness of the charging strategy, avoids the decline in charging efficiency or safety risks caused by environmental interference, and improves the overall performance and stability of multi-device wireless charging.

[0093] In some embodiments of the above-mentioned embodiments of the present application, the present application further proposes that the step of identifying an environmental disturbance event that meets the preset condition according to the running state data comprises:

[0094] The running state data is monitored to obtain a plurality of single operation events, wherein none of the plurality of single operation events meets the preset condition. Wherein, a single operation event is a discrete occurrence or change in the running state data, each of which does not meet the preset condition, which can be embodied by a short temperature fluctuation, a slight signal strength drop or a single slight vibration, in order to capture those events that are not enough to trigger an alarm alone but may have an impact when accumulated.

[0095] The disturbance contribution value corresponding to each of the plurality of single operation events is determined. Wherein, the disturbance contribution value is a quantitative value assigned to each single operation event, which represents the potential influence or contribution of the event to the environmental disturbance, which can be realized by a numerical value calculated based on the event type, amplitude or duration, in order to quantify the influence of different events.

[0096] The disturbance contribution values are aggregated to generate a cumulative disturbance value. Aggregation is a process of combining multiple individual values into a single representative value, which can be implemented in the form of summation, weighted average or integration, etc., in order to comprehensively evaluate the cumulative impact of multiple events. The cumulative disturbance value is the result of aggregating the disturbance contribution values of multiple single operation events, which represents the comprehensive impact of these smaller events, in order to provide an indicator reflecting the cumulative effect.

[0097] When the cumulative disturbance value meets a preset cumulative threshold condition, an environmental disturbance event meeting the preset condition is identified. The preset cumulative threshold condition is a predefined standard applied to the cumulative disturbance value, which can be implemented in the form of a numerical threshold or a change rate threshold, etc., in order to determine whether the cumulative impact reaches a significant degree.

[0098] Specifically, by monitoring the operating state data of the wireless charging object in the shared device rental cabinet, such as battery temperature, charging current, charging vibration sensor data, and communication signal strength between the charging site and the tool. Assuming that the preset condition is set as: the instantaneous increase of battery temperature does not exceed 2℃, the instantaneous decrease of charging current does not exceed 10%, the vibration amplitude does not exceed 0.1g, and the instantaneous decrease of communication signal strength does not exceed 3dBm. When a series of events are monitored, such as the battery temperature fluctuating three times by 1℃ within 5 minutes, the charging current fluctuating four times by 5% within 10 minutes, or the communication signal strength fluctuating multiple times by 2dBm within a short period of time, none of these single operation events individually meets the preset condition of directly triggering the environmental disturbance event. A basic disturbance contribution value can be set for each type of single operation event, for example, the contribution value of temperature fluctuation 1℃ is set to 1, the contribution value of current decrease 5% is set to 0.5, and the contribution value of signal strength decrease 2dBm is set to 0.8. Then, the basic contribution value is adjusted according to the time, duration or current charging phase of the event to obtain the disturbance contribution value of each single operation event. For example, the contribution value of an event occurring in a critical charging phase can be amplified. Then, these disturbance contribution values can be accumulated within a certain time window to generate a cumulative disturbance value. For example, the sum of all disturbance contribution values in the past 15 minutes. The preset cumulative threshold condition can be set as the cumulative disturbance value reaching 10. When the cumulative disturbance value exceeds 10, the system identifies an environmental disturbance event that meets the preset condition, for example, determines that a continuous slight environmental disturbance or a decrease in the stability of the charging site has occurred. The present application can effectively aggregate and analyze multiple single operation events that individually have a small impact, and identify environmental disturbance events that are cumulatively formed by these scattered events and have a significant impact on the wireless charging process. This method overcomes the problem of missed disturbance reporting in traditional methods due to single data not reaching the threshold, improves the accuracy and sensitivity of environmental disturbance event identification, and thus can more comprehensively grasp the factors affecting the charging process, providing a more reliable basis for subsequent charging control decisions.

[0099] In some embodiments of the above-mentioned embodiments of the present application, the step of determining the disturbance contribution value corresponding to each of the plurality of single operation events comprises:

[0100] For each single operation event in the plurality of single operation events, the current operating phase of the wireless charging object is obtained. The current operating phase of the wireless charging object is a specific state or period of the wireless charging object in the entire charging or standby cycle, such as the initial charging period, the middle charging period, the final charging period, the standby state, and the fault state, which is determined according to the parameters such as the power of the wireless charging object, the charging current, the battery temperature, and the charging duration.

[0101] determine a base disturbance contribution value of the single operation event. The base disturbance contribution value is a preliminary quantitative evaluation of the disturbance degree inherent to the single operation event, and is determined based on preset parameters or models of the type, intensity, and duration of the single operation event.

[0102] adjust the base disturbance contribution value using the current operating phase to determine a disturbance contribution value corresponding to each of the plurality of single operation events. Specifically, the adjustment of the base disturbance contribution value using the current operating phase is a correction or weighting process of the base disturbance contribution value of the single operation event according to the current operating phase of the object to be wirelessly charged. The adjustment can be achieved by using a preset adjustment coefficient, a lookup table, or a machine learning model, and the like, so as to more accurately reflect the actual influence of the operation event on the wireless charging environment in the current operating phase.

[0103] The present application first obtains the current operating phase of the object to be wirelessly charged for each of the plurality of single operation events. This is because the disturbance influence of the same operation event on the environment may be different when the object to be wirelessly charged is in different operating phases. Then, the base disturbance contribution value of the single operation event is determined, which is a preliminary quantitative evaluation of the disturbance degree of the operation event itself. The base disturbance contribution value is adjusted using the current operating phase to determine a disturbance contribution value corresponding to each of the plurality of single operation events. Since the specific operating phase of the object to be wirelessly charged is considered and the base disturbance contribution value is corrected based thereon, the final disturbance contribution value can more accurately reflect the actual influence of the operation event on the wireless charging environment in the current specific situation. These adjusted disturbance contribution values are then aggregated to generate a cumulative disturbance value, and an environmental disturbance event satisfying a preset condition is identified. This method overcomes the limitations of simply assigning fixed contribution values to all single operation events, and improves the accuracy of environmental disturbance event identification. More accurate environmental disturbance event identification provides a more reliable basis for subsequent charging control decisions, such as adjusting charging parameters or triggering emergency strategies more timely after identifying an environmental disturbance event, thereby improving the robustness and effectiveness of the entire multi-device wireless charging control method.

[0104] In some embodiments of the above-mentioned embodiments of the present application, the step of aggregating each of the disturbance contribution values to generate a cumulative disturbance value comprises:

[0105] obtaining a time weight corresponding to each disturbance contribution value. The time weight is a coefficient for measuring the decay or accumulation effect of the disturbance contribution value over time, and can be determined according to the distance of the time of the disturbance event from the current time. For example, the closer the time of the disturbance event to the current time, the greater the time weight, and vice versa.

[0106] The disturbance contribution value is multiplied by the corresponding time weight to obtain all weighted disturbance contribution values. The weighted disturbance contribution value is a value obtained by multiplying the disturbance contribution value by the corresponding time weight, and reflects the actual contribution of the single operation event to the current cumulative disturbance after considering the time factor.

[0107] The weighted disturbance contribution values are summed to generate the cumulative disturbance value. The cumulative disturbance value is the sum of all weighted disturbance contribution values, and comprehensively reflects the overall influence of multiple single operation events on the current environmental disturbance level after considering the time decay or accumulation effect.

[0108] In the embodiment, by obtaining the time weight corresponding to each disturbance contribution value, multiplying each disturbance contribution value by the corresponding time weight to obtain a weighted disturbance contribution value, and summing all weighted disturbance contribution values to generate a cumulative disturbance value, the influence of the time factor is introduced in the process of aggregating the disturbance contribution values. Due to the consideration of the time factor, the influence of the disturbance event occurring recently on the cumulative disturbance value is greater, and the influence of the event occurring earlier gradually decreases, which is more consistent with the law of disturbance influence decay over time in the actual environment. Through this weighted summation method, the generated cumulative disturbance value can more accurately reflect the real influence level of the environmental disturbance event at the current time. This more accurate cumulative disturbance value, combined with the steps of acquiring multiple single operation events, determining their disturbance contribution values and simply summing to generate a cumulative disturbance value in the prior scheme by monitoring the running state data, together realizes more accurate identification of environmental disturbance events. In this way, errors that may be caused by simple summation can be effectively avoided, and the accuracy of environmental disturbance event identification is improved.

[0109] In some embodiments of the application described above, the application further proposes that the step of acquiring real-time state data of each object to be wirelessly charged reported by the shared equipment rental cabinet and current situational data of the shared equipment rental cabinet comprises:

[0110] Acquiring real-time state data of each object to be wirelessly charged reported by the shared equipment rental cabinet, which contains environmental information and reservation information, and current situational data of the shared equipment rental cabinet, which contains tool placement information.

[0111] The scheme of the present application provides more abundant and targeted information input for subsequent charging control by obtaining real-time state data containing environmental information and reservation information, and current scene data containing tool placement information. As environmental information is obtained, the temperature and humidity conditions where the charging object is located can be understood, so that when generating the charging control parameter set, the influence of environmental factors on the charging characteristics and safety of the battery can be considered, such as appropriately reducing the charging power in a high-temperature environment to avoid overheating. As reservation information is obtained, the system can know the user's use demand and time constraint for a specific tool, so that when scheduling the charging task, the charging resource can be allocated to the tool with reservation or the charging strategy can be adjusted to ensure that the required power is reached before the reservation time. As tool placement information is obtained, it can be determined whether the to-be-charged object is correctly aligned with the charging position, so that potential low charging efficiency or charging failure can be identified, and the alignment state can be considered when generating the parameter set, or even the user is prompted to reposition or adjust the charging strategy. Therefore, through this more detailed data acquisition method, the method of the present application can more comprehensively master the key factors affecting the charging process, lay a foundation for generating more accurate and optimized charging control parameter sets based on these data in the future, and thus improve the overall charging efficiency, safety and user experience.

[0112] Based on any one of the multi-device wireless charging control methods in the above embodiments, please refer to Figure 2 The present application also provides a multi-device wireless charging control system, which comprises an acquisition module 210, a parameter set generation module 220 and a control module 230.

[0113] The acquisition module 210 is used to acquire real-time state data of each to-be-wirelessly-charged object reported by a shared device rental cabinet and current scene data of the shared device rental cabinet.

[0114] The parameter set generation module 220 is used to generate a charging control parameter set containing an emergency disposal strategy for each to-be-charged object by using a preset object-specific data set, the real-time state data and the current scene data, wherein the preset object-specific data set is constructed based on historical data and static attributes of each to-be-charged object.

[0115] The control module 230 is used to drive the local control unit of the shared device rental cabinet to control the wireless charging of the multi-device based on the charging control parameter set after each charging control parameter set is issued to the local control unit of the shared device rental cabinet.

[0116] In this embodiment, the acquisition module 210 receives data from the shared device rental cabinet, including real-time state data of each object to be wirelessly charged and current situational data of the shared device rental cabinet. This provides basic information for subsequent charging decisions, such as the power level, temperature of the object to be charged, and environmental conditions of the rental cabinet. The parameter set generation module 220 receives the data provided by the acquisition module and combines a pre-set object-specific data set, which is constructed based on historical data and static attributes of the object to be charged, to generate individualized charging control parameter sets for different objects. The parameter set not only contains regular charging instructions, but also integrates emergency handling strategies to ensure timely response in abnormal situations. The control module 230 receives the charging control parameter sets output by the parameter set generation module and issues them to the local control unit of the shared device rental cabinet. After receiving the parameter set, the local control unit drives the wireless charging process of multiple devices according to the instructions in the parameter set. This design enables the system to dynamically adjust the charging strategy based on real-time data, historical information, and environmental factors, extending the intelligent decision-making capabilities of the cloud platform to the local execution level. In this way, the system can effectively manage the charging process of different types and states of objects to be charged in a limited charging position, optimize charging efficiency, ensure charging safety, and respond to possible emergency situations. The system can obtain real-time state of the object to be charged and situational data of the rental cabinet, generate charging control parameter sets containing emergency strategies based on historical and static attributes, and issue the parameter sets to the local control unit to drive charging. This enables the system to dynamically adjust the charging strategy according to the specific situation, improves the level of refinement of multi-device wireless charging management and the ability to respond to emergency situations, and thus optimizes charging efficiency and safety.

[0117] The above embodiments are only used to illustrate the technical solutions of the present application, rather than limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or make equivalent replacements for some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application, and they should be covered in the scope of the present application.

Claims

1. A method for controlling wireless charging of multiple devices, characterized in that, Includes the following steps: Obtain real-time status data of each object to be wirelessly charged reported by the shared equipment rental cabinet, as well as the current scenario data of the shared equipment rental cabinet; Using a preset object-specific dataset, the real-time status data, and the current scenario data, a charging control parameter set containing an emergency response strategy is generated. The preset object-specific dataset is constructed based on the historical data and static attributes of each object to be charged. After each set of charging control parameters is sent to the local control unit of the shared equipment rental cabinet, the local control unit is driven to control the wireless charging of multiple devices based on the set of charging control parameters. After the step of generating each charging control parameter set containing an emergency response strategy using a preset object-specific dataset, the real-time status data, and the current scenario data, the method further includes: Historical performance metrics are generated using a pre-defined object-specific dataset, and instantaneous status metrics are generated using real-time status data. Determine whether there is a decision conflict between the control strategy indicated by the historical performance indicators and the control strategy indicated by the real-time status indicators; In response to the determination that a decision conflict exists, a temporary parameter set containing the monitoring trigger conditions is generated; After the monitoring triggering condition is met, the change index of the real-time status index of the local control unit during the execution of the temporary parameter set is obtained; By utilizing the degree of conformity between the change index and the historical performance index, a set of charging control parameters is generated for each subsequent wireless charging object.

2. The multi-device wireless charging control method according to claim 1, characterized in that, The step of generating each charging control parameter set containing an emergency response strategy using a preset object-specific dataset, the real-time status data, and the current scenario data includes: An initial charging control parameter set is generated using a preset object-specific dataset, the real-time status data, and the current scenario data; wherein, the current scenario data includes the initial physical alignment status information between the object to be wirelessly charged and the charging position; Obtain communication auxiliary parameters that characterize the quality of the communication link between the object to be wirelessly charged and the charging position, corresponding to the initial physical alignment state information, and set the communication auxiliary parameters as a reference value; Collect the real-time values ​​of the communication auxiliary parameters of the wireless charging object during charging, and confirm the real-time value sequence; Determine the trend of the real-time value sequence relative to the baseline value; When the changing trend meets the preset alignment deterioration condition, the initial charging control parameter set is adjusted to obtain the charging control parameter set.

3. The multi-device wireless charging control method according to claim 2, characterized in that, in, The steps involved in constructing the preset object-specific dataset based on the historical data and static attributes of each object to be charged include: When the trend of change meets the preset alignment deterioration condition, an alignment deterioration event record is generated, which includes the identifier of the object to be wirelessly charged, the identifier of the shared equipment rental cabinet, and the trend of change. The initial charging control parameter set is updated using the alignment deterioration event record to obtain the charging control parameter set.

4. The multi-device wireless charging control method according to claim 1, characterized in that, The step of generating a set of charging control parameters for each subsequent wireless charging object by utilizing the conformity between the change index and the historical performance index includes: Obtain the operating status data of at least one object in the shared equipment rental cabinet, excluding the object to be wirelessly charged; Based on the operational status data, environmental disturbance events that meet preset conditions are identified; Based on the time correspondence between the environmental disturbance events and the change indicators, the disturbance data segments affected by the environmental disturbance events are derived. Based on the portion of the change indicators not included in the disturbance data segment and the historical performance indicators, the degree of conformity is determined; Based on the compliance score, a set of charging control parameters is generated for each subsequent wireless charging object.

5. The multi-device wireless charging control method according to claim 4, characterized in that, The steps for identifying environmental disturbance events that meet preset conditions based on the operational status data include: The operation status data is monitored to obtain multiple individual operation events, wherein none of the multiple individual operation events meet the preset conditions; Determine the disturbance contribution value corresponding to each of the plurality of individual operational events; Each of the aforementioned disturbance contribution values ​​is aggregated to generate a cumulative disturbance value; When the cumulative disturbance value meets the preset cumulative threshold condition, an environmental disturbance event that meets the preset condition is identified.

6. The multi-device wireless charging control method according to claim 5, characterized in that, The step of determining the disturbance contribution value corresponding to each of the plurality of individual operational events includes: For each of the plurality of single operation events, obtain the current operating stage of the object to be wirelessly charged; Determine the basic disturbance contribution value of the single operational event; The basic disturbance contribution value is adjusted using the current operating phase to determine the disturbance contribution value corresponding to each of the multiple individual operation events.

7. A multi-device wireless charging control method according to claim 6, characterized in that, The step of aggregating each of the disturbance contribution values ​​to generate a cumulative disturbance value includes: Obtain the time weight corresponding to each disturbance contribution value; Multiply each disturbance contribution value by its corresponding time weight to obtain all weighted disturbance contribution values; The cumulative disturbance value is generated by summing all the weighted disturbance contribution values.

8. The multi-device wireless charging control method according to claim 1, characterized in that, The steps of obtaining real-time status data of each wireless charging object reported by the shared device rental cabinet and the current situation data of the shared device rental cabinet include: Obtain real-time status data, including environmental and reservation information, for each wireless charging target reported by the shared equipment rental cabinet, as well as current scenario data, including tool placement information, from the shared equipment rental cabinet.

9. A multi-device wireless charging control system, characterized in that, The system includes: The acquisition module is used to acquire real-time status data of each wireless charging object reported by the shared equipment rental cabinet and the current situation data of the shared equipment rental cabinet; The parameter set generation module is used to generate each charging control parameter set containing an emergency response strategy by using a preset object-specific dataset, the real-time status data and the current scenario data. The preset object-specific dataset is constructed based on the historical data and static attributes of each object to be charged. The control module is used to send each set of charging control parameters to the local control unit of the shared equipment rental cabinet, and then drive the local control unit to control the wireless charging of multiple devices based on the set of charging control parameters. It is also used to generate historical performance metrics using a pre-defined object-specific dataset, and to generate instantaneous status metrics using real-time status data. Determine whether there is a decision conflict between the control strategy indicated by the historical performance indicators and the control strategy indicated by the real-time status indicators; In response to the determination that a decision conflict exists, a temporary parameter set containing the monitoring trigger conditions is generated; After the monitoring triggering condition is met, the change index of the real-time status index of the local control unit during the execution of the temporary parameter set is obtained; By utilizing the degree of conformity between the change index and the historical performance index, a set of charging control parameters is generated for each subsequent wireless charging object.

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