Multi-device wireless charging control method and system

Abstract

The invention 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: acquiring real-time state data of each to-be-wirelessly charged object reported by a shared equipment leasing cabinet and current scene data of the shared equipment leasing cabinet; a preset object exclusive data set, the real-time state data and the current scene data are utilized to generate each charging control parameter set containing an emergency disposal strategy, and the preset object exclusive data set is constructed based on historical data and static attributes of each to-be-charged object; and after each charging control parameter set is issued to a local control unit of the shared equipment leasing cabinet, the local control unit is driven to control wireless charging of multiple devices based on the charging control parameter sets. The objective of the invention is to solve the problem of low charging efficiency caused by incapability of realizing wireless charging control of multiple devices in the prior art.

Description

Technical Field

[0001] The present invention relates to the field of wireless charging technology, and in particular to a multi-device wireless charging control method and system. Background Art

[0002] Shared equipment rental cabinets offer users a variety of power tools that support wireless charging. Registered users can rent a variety of power tools, such as hand drills, impact drills, angle grinders, electric saws, and electric screwdrivers, for short-term, on-demand rental. All power tools support wireless charging. Some have built-in batteries, while others utilize removable, standardized battery packs that can be placed directly into a charging station for wireless charging. A cloud service platform is currently used to centrally manage information and schedule charging processes for all rental cabinets and the power tools charging within them.

[0003] However, rental cabinets contain a wide variety of power tools, each with varying specifications, battery characteristics, and charging requirements. Uncertainty in user behavior leads to significant variations in the status of returned power tools, such as differences in battery level, temperature, and operating history. Furthermore, the number of wireless charging stations within the rental cabinets is limited. When multiple devices require charging, the existing first-come, first-served charging strategy can result in low charging efficiency and fail to prioritize power tools that urgently need charging or have reservations. Furthermore, the power tool's own operating status and external environment can affect the safety and effectiveness of the charging process. The placement of the power tool on the charging station can also affect the energy transfer efficiency of wireless charging. Network communication between the cloud platform and the local rental cabinet can be unstable or delayed, making it difficult to rely solely on real-time cloud platform instructions for precise charging control. Local controllers may also be unable to effectively manage the charging process if communication is interrupted. Shared equipment rental cabinets are unable to implement wireless charging control for multiple types and specifications of power tools awaiting wireless charging, resulting in low charging efficiency. Summary of the Invention

[0004] The object of the present invention is to provide a multi-device wireless charging control method and system to solve the problem that the existing technology cannot realize wireless charging control of multiple devices, resulting in low charging efficiency.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a multi-device wireless charging control method, comprising the following steps: Acquire the real-time status data of each wireless charging object reported by the shared equipment rental cabinet and the current scenario data of the shared equipment rental cabinet; generating a charging control parameter set including each emergency response strategy using a preset object-specific data set, the real-time status 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; After each of the charging control parameter sets is sent 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.

[0006] Optionally, the present application further proposes that the step of generating each charging control parameter set including an emergency response strategy by using a preset object-specific data set, the real-time status data, and the current scenario data includes: Generate an initial charging control parameter set using a preset object-specific data set, the real-time status data, and the current scenario data; wherein the current scenario data includes initial physical alignment status information between the object to be wirelessly charged and the charging position; Acquire a communication auxiliary parameter corresponding to the initial physical alignment state information and representing the quality of the communication link between the object to be wirelessly charged and the charging position, and set the communication auxiliary parameter as a reference value; collecting real-time values ​​of the communication auxiliary parameters of the wireless charging object during charging, and confirming a real-time value sequence; Determining a change trend of the real-time value sequence relative to the reference value; When the change trend meets a preset alignment deterioration condition, the initial charging control parameter set is adjusted to obtain a charging control parameter set.

[0007] Optionally, the present application further proposes that the steps of constructing the preset object-specific data set based on the historical data and static attributes of each object to be charged include: When the change trend meets the preset alignment deterioration condition, generating an alignment deterioration event record including the identifier of the object to be wirelessly charged, the identifier of the shared equipment rental cabinet, and the change trend; The initial charging control parameter set is updated by using the alignment deterioration event record to obtain a charging control parameter set.

[0008] Optionally, the present application further proposes that after the step of generating each charging control parameter set including an emergency response strategy using the preset object-specific data set, the real-time status data, and the current scenario data, the step further includes: Generate historical performance indicators using pre-set object-specific data sets and generate immediate status indicators using real-time status data; determining whether there is a decision conflict between the control strategy indicated by the historical performance indicator and the control strategy indicated by the immediate status indicator; In response to determining that the decision conflict exists, generating a temporary parameter set including a monitoring trigger condition; After the monitoring trigger condition is met, obtaining a change indicator of the instantaneous status indicator during execution of the temporary parameter set by the local control unit; A charging control parameter set for subsequent charging of each object to be wirelessly charged is generated using the degree of conformity between the change indicator and the historical performance indicator.

[0009] Optionally, the present application further proposes that the steps of generating a charging control parameter set for subsequent charging of each wirelessly charged object using the degree of conformity between the change indicator and the historical performance indicator include: Acquire operating status data of at least one object other than the object to be wirelessly charged in the shared equipment rental cabinet; Identifying environmental disturbance events that meet preset conditions based on the operating status data; Based on the time correspondence between the environmental disturbance event and the change index, a disturbance data segment affected by the environmental disturbance event is obtained; determining a degree of compliance based on a portion of the change indicator not included in the disturbance data segment and the historical performance indicator; A charging control parameter set for subsequent charging of each object to be wirelessly charged is generated based on the compliance.

[0010] Optionally, the present application further proposes that the step of identifying an environmental disturbance event that meets preset conditions based on the operating status data includes: Monitoring the operating status data to obtain a plurality of single operation events, wherein none of the plurality of single operation events satisfies a preset condition; Determining disturbance contribution values ​​corresponding to each of the plurality of single operation events; Aggregating each of the disturbance contribution values ​​to generate a cumulative disturbance value; When the accumulated disturbance value meets a preset accumulation threshold condition, an environmental disturbance event meeting the preset condition is identified.

[0011] Optionally, the present application further proposes that the step of determining the disturbance contribution values ​​corresponding to each of the multiple single operation events includes: For each of the multiple single operation events, obtaining a current operation stage of the object to be wirelessly charged; determining a basic disturbance contribution value of the single operation event; The basic disturbance contribution value is adjusted using the current operating stage to determine disturbance contribution values ​​corresponding to respective single operating events.

[0012] Optionally, the present application further proposes that the step of aggregating each disturbance contribution value to generate a cumulative disturbance value includes: Get 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; All the weighted disturbance contribution values ​​are summed to generate the cumulative disturbance value.

[0013] Optionally, the present application further proposes that the step of obtaining the real-time status data of each wireless charging object reported by the shared equipment rental cabinet and the current scenario data of the shared equipment rental cabinet includes: Real-time status data including environmental information and reservation information of each object to be wirelessly charged reported by the shared equipment rental cabinet and current scenario data including tool placement information of the shared equipment rental cabinet are obtained.

[0014] The present application also provides a multi-device wireless charging control system, the system comprising: An acquisition module, configured to acquire real-time status data of each wireless charging object reported by a shared equipment rental cabinet and current scenario data of the shared equipment rental cabinet; a parameter set generation module, configured to generate a charging control parameter set including each emergency response strategy using a preset object-specific data set, the real-time status 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; The control module is used to send each of the charging control parameter sets to the local control unit of the shared device rental cabinet, and then drive the local control unit to control the wireless charging of multiple devices based on the charging control parameter set.

[0015] Compared with the prior art, the multi-device wireless charging control method and system of the present invention has the following advantages: The present invention obtains the real-time status data of each wireless charging object reported by the shared equipment rental cabinet and the current scenario data of the shared equipment rental cabinet, thereby understanding the immediate health status, power level, and current state of the charging environment of the object to be charged. Combined with a preset object-specific data set, a customized charging control parameter set is generated for each wireless charging object. This set not only contains parameters to guide the normal charging process, but also includes emergency response strategies for potential abnormal situations. During the charging process, the local control unit can respond to emergencies such as abnormal temperatures and poor connections without relying on real-time cloud instructions. The charging control parameter set is sent to the local control unit of the shared equipment rental cabinet. After receiving the parameter set, the local control unit drives the wireless charging hardware based on the instructions and strategies therein to wirelessly charge multiple devices in the cabinet. This makes charging control decisions more intelligent, can achieve improvements in charging efficiency, battery life, and safety, and by integrating emergency strategies into the sent parameter set, the robustness of the system is enhanced when network communication is unstable. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments of the present invention, the following briefly introduces the drawings required for use in the specific embodiments. In all the drawings, each element or part is not necessarily drawn according to the actual scale.

[0017] Figure 1 This is a flow chart of a multi-device wireless charging control method of the present invention.

[0018] Figure 2 This is a structural block diagram of a multi-device wireless charging control system of the present invention.

[0019] In the figure: 210, acquisition module; 220, parameter set generation module; 230, control module.

[0020] The implementation and advantages of the functions of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] The following diagrams illustrate various embodiments of the present invention. For clarity, many practical details are included in the following description. However, it should be understood that these practical details are not intended to limit the present invention. In other words, in some embodiments of the present invention, these practical details are not essential. Furthermore, to simplify the drawings, some commonly used structures and components are depicted in simplified schematic form.

[0022] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0023] In addition, in the present invention, descriptions such as "first" and "second" are only used for descriptive purposes and do not specifically refer to the order or sequence, nor are they used to limit the present invention. They are only used to distinguish components or operations described with the same technical terms, and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0024] Traditional existing technologies face technical challenges in managing the diverse types, specifications, and status of charging objects in shared equipment rental cabinets, improving charging efficiency, allocating limited resources, and coping with environmental changes and communication interruptions. This impacts the ability of power tools to quickly restore to a usable state and the user experience. For example, a shared equipment rental cabinet is deployed outdoors in high ambient temperatures. Multiple power tools of different models are returned by users, with varying battery levels, internal temperatures, and usage intensity. The cabinet has a limited number of wireless charging spots, and some tools may be misplaced due to user placement, resulting in reduced wireless charging energy transmission efficiency. Furthermore, the rental cabinet's network connection is unstable. Traditional existing technologies only initiate charging based on the order in which each power tool is returned or the charge threshold, failing to consider the impact of tool temperature, battery history, placement, or the external environment on the charging process. This can cause charging interruptions for some tools due to elevated temperatures, and misplaced tools can take up charging spots and hinder timely charging for other tools. Traditional existing technologies are unable to control wireless charging for multiple devices, resulting in low charging efficiency.

[0025] In order to further understand the content, features and effects of the present invention, the following embodiments are given as examples and described in detail with reference to the accompanying drawings: See also Figure 1 The present invention provides a multi-device wireless charging control method, comprising the following steps: S100, obtain the real-time status data of each object to be wirelessly charged reported by the shared equipment rental cabinet and the current scenario data of the shared equipment rental cabinet. Among them, the real-time status data is the current operating status information of each object to be wirelessly charged reported by the shared equipment rental cabinet, which can be obtained by sensor collection or internal register reading, such as battery power, battery temperature, tool internal temperature and error code, etc., which is mainly to obtain the real-time situation of the object to be charged and provide a basis for dynamically adjusting the charging strategy. The current scenario data is the overall environmental information of the shared equipment rental cabinet reported by the shared equipment rental cabinet, which can be obtained by environmental sensor collection, cabinet status monitoring, etc., such as the ambient temperature and humidity inside the cabinet, charging position occupancy, tool placement location information, etc., which is mainly to obtain the external environment and resource allocation when charging occurs, and provide a basis for formulating global or local charging strategies.

[0026] S200: Generate a charging control parameter set, each containing an emergency response strategy, 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. Specifically, the preset object-specific dataset is a data set constructed based on the historical data and static attributes of each object to be charged. This dataset can be implemented using database storage or file storage, and includes information such as tool model, battery type, rated capacity, maximum charging power, historical number of charging cycles, typical usage duration, and historical fault records. This dataset primarily provides information on the inherent characteristics and long-term behavior patterns of each object to be charged, providing a foundation for generating personalized and optimized charging control parameters. The charging control parameter set is a parameter set generated for each wirelessly charged object, containing an emergency response strategy. This parameter set can be represented using a data structure or configuration file, and includes information such as target charging current, target charging voltage, charging cutoff conditions, temperature protection thresholds, and exception handling rules. This parameter set primarily guides the local control unit in executing a specific charging process and enabling safe handling in abnormal situations. The emergency response strategy is included in the charging control parameter set, and is used to define rules or instructions for taking countermeasures when abnormal situations occur during the charging process. It can be implemented using conditional judgment logic and preset action sequences. For example, it can reduce the charging power when the temperature is too high, suspend charging when the communication quality deteriorates, etc. Its main purpose is to ensure the safety of the charging process and the reliability of the equipment.

[0027] S300: After each charging control parameter set is sent to the local control unit of the shared equipment rental cabinet, the local control unit is driven to control wireless charging of multiple devices based on the charging control parameter set. The local control unit is a hardware or software module within the shared equipment rental cabinet responsible for executing the charging control parameter set and directly controlling the wireless charging process. It can be implemented using an embedded microcontroller or industrial control board, etc. Its primary function is to receive cloud commands and locally drive the wireless charging hardware to achieve specific charging control of multiple devices.

[0028] In this embodiment, a cloud service platform acts as a central processing entity, receiving data from various shared equipment rental cabinets over the network. Each rental cabinet is equipped with sensors that collect real-time status data and current contextual data, including battery voltage, current, temperature, tool identification information on the charging station, and ambient temperature within the cabinet. These data are then packaged and reported. The cloud platform maintains a database that stores static attributes for each tool model (such as battery type, capacity, and maximum charging power), as well as object-specific datasets based on historical charging records and usage duration. When new reported data is received, the cloud platform runs an existing decision-making algorithm based on this data and the object-specific dataset. This algorithm comprehensively evaluates the tool's power requirements, battery health, current temperature, ambient temperature within the cabinet, charging station availability, and historical tool performance, generating a set of charging control parameters and emergency rules. Specific charging parameters include initial charging power, power adjustment curves, or temperature thresholds. Emergency rules include reducing power to a certain percentage when the temperature exceeds a threshold, attempting low-power charging, or terminating charging when the charging station is misaligned. The parameter set is distributed over the network to the local control unit of the target rental cabinet in the form of structured data, such as JSON. The local control unit, such as an embedded controller, parses the received parameter set and controls the output power of the wireless charging module according to the instructions contained therein. During the charging process, the local control unit continuously monitors the tool's real-time status, such as battery temperature. Once an emergency rule defined in the parameter set is triggered (for example, if the temperature exceeds a set threshold), the local control unit immediately executes the corresponding emergency action, such as reducing the charging power, without waiting for further instructions from the cloud platform. When 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.

[0029] The solution of this application obtains real-time status data for each wirelessly charged object reported by a shared equipment rental cabinet, as well as the cabinet's current contextual data. This provides insights into the current health status, charge level, and charging environment of each object. Furthermore, combined with a pre-defined object-specific dataset built from each object's historical data and static attributes, it provides insights into each object's long-term characteristics and behavior patterns. Furthermore, a pre-defined algorithm model is used to generate a customized charging control parameter set for each wirelessly charged object. This parameter set not only includes parameters that guide the normal charging process, such as recommended charging power or current curves, but also includes emergency response strategies for potential abnormal situations. These strategies are pre-defined based on the object's characteristics, current status, and environment. During the charging process, the local control unit can handle unexpected situations such as temperature anomalies and poor connectivity without relying on real-time cloud-based instructions. These generated charging control parameter sets are then distributed to the local control unit of the shared equipment rental cabinet. Upon receiving the parameter set, the local control unit uses the instructions and strategies contained in the parameter set to drive the wireless charging hardware and wirelessly charge multiple devices within the cabinet. This approach makes charging control decisions more intelligent. At the same time, it can improve charging efficiency, battery life and safety, and by building emergency strategies into the distributed parameter set, it enhances the robustness of the system when network communication is unstable.

[0030] In some of the above embodiments of the present application, the present application further proposes that the step of generating each charging control parameter set including an emergency response strategy by using the preset object-specific data set, 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; the current scenario data includes information about the initial physical alignment between the object to be wirelessly charged and the charging station. The initial charging control parameter set is a preliminary set of charging strategy parameters generated based on available information before the charging process begins. This parameter set can be implemented using a data structure containing parameters such as charging power, charging duration, or charging mode, with the goal of providing an initial charging plan.

[0031] Acquire communication auxiliary parameters corresponding to the initial physical alignment status information, indicating the quality of the communication link between the object to be wirelessly charged and the charging station, and set the communication auxiliary parameters as baseline values. The initial physical alignment status information refers to the initial position and posture of the object to be wirelessly charged when placed on the charging station. This information can be obtained using data acquired through methods such as visual recognition, a position sensor, or near-field communication signal strength. Its purpose is to assess the physical alignment at the start of charging. The communication auxiliary parameters are technical indicators that reflect the quality of the wireless communication link between the object to be wirelessly charged and the charging station. These parameters can be acquired using parameters such as signal strength (RSSI), signal-to-noise ratio (SNR), or bit error rate (BER). Their purpose is to indirectly indicate the impact of the physical alignment status on communication. The baseline value is the value of the communication auxiliary parameter acquired based on the initial physical alignment status information at the start of the charging process. This information can be acquired by recording the initial acquired value to provide a reference point for subsequent real-time monitoring.

[0032] The real-time values ​​of the communication auxiliary parameters of the wireless charging object during charging are collected to determine a real-time value sequence. Specifically, the real-time value sequence is a data sequence consisting of the communication auxiliary parameter values ​​continuously collected during wireless charging. This can be implemented as time-stamped sequence data, and its purpose is to record the changes in communication link quality over time.

[0033] Determine the trend of change of the real-time value sequence relative to the reference value. The trend is the direction and magnitude of change of the real-time value sequence relative to the reference value. This can be achieved by calculating the slope, comparing the average value, or determining the direction of continuous change. The purpose is to identify whether the communication link quality is deteriorating.

[0034] When the change trend meets the preset alignment deterioration condition, the initial charging control parameter set is adjusted to obtain a charging control parameter set. The preset alignment deterioration condition is a technical standard or threshold set for determining whether the physical alignment state has deteriorated. This can be achieved by conditions such as a continuous decrease in a communication auxiliary parameter exceeding a specific threshold, a decrease rate exceeding a specific value, or a continuous increase in the bit error rate reaching a specific level. The purpose is 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 alignment deterioration. This can be achieved by updating the initial parameter set. The purpose is to optimize the charging process to cope with poor alignment.

[0035] Specifically, after generating an initial charging control parameter set using a preset object-specific dataset, real-time status data, and current scenario data (the current scenario data may include initial placement information of the wirelessly charged object on the charging station, obtained through image recognition or sensor detection), the system can then obtain communication auxiliary parameters corresponding to this initial placement information, such as the initial RSSI value between wireless charging modules, and set this initial RSSI value as a baseline value. While the wireless charging object is charging, the system can continuously collect real-time RSSI values ​​to form a sequence of real-time RSSI values. The system can then determine the trend of this sequence of real-time RSSI values ​​relative to the baseline value, for example, determining whether the RSSI value exhibits a continuously decreasing trend. If this downward trend meets a preset alignment deterioration condition, for example, if the RSSI value decreases by more than 5dBm for 30 consecutive seconds, the system can adjust the initial charging control parameter set, for example, by reducing the initially set charging power by 20% or triggering a prompt to reposition the tool, thereby obtaining the charging control parameter set for the current charging process. This application can monitor the changes in the physical alignment status between the object to be wirelessly charged and the charging position in real time, and dynamically adjust the charging control parameters according to the trend of alignment deterioration, effectively addressing the problem of reduced charging efficiency caused by poor physical alignment, improving energy transmission efficiency, and improving charging effects.

[0036] In some of the above embodiments of the present application, the present application further proposes that the steps of constructing the preset object-specific data set based on the historical data and static attributes of each object to be charged include: When the change trend meets the preset alignment deterioration condition, an alignment deterioration event record is generated, including the identifier of the wireless charging object, the shared equipment rental cabinet identifier, and the change trend. The alignment deterioration event record is a data structure containing the identifier of the wireless charging object, the shared equipment rental cabinet identifier, and the change trend. Specifically, it can be a data entry or a structured data packet, and is intended to capture and record specific events during the charging process that indicate a deterioration in the physical alignment between the wireless charging object and the charging station.

[0037] The initial charging control parameter set is updated using the alignment deterioration event record to obtain the charging control parameter set. In this embodiment, updating the initial charging control parameter set using the alignment deterioration event record is to modify or adjust the previously generated initial charging control parameter set based on the information contained in the alignment deterioration event record. Specifically, the magnitude or direction of the parameter adjustment can be determined by consulting historical alignment deterioration event data related to the identifier of the object to be wirelessly charged or the identifier of the shared equipment rental cabinet, or based on the severity of the recorded change trend. The purpose is to feed back the abnormal situation of alignment deterioration to the current charging control strategy, so that the parameter set can better adapt to the current actual alignment state, or trigger a corresponding emergency response strategy.

[0038] Specifically, when a monitored communication auxiliary parameter, such as wireless signal strength or energy transmission efficiency, shows a downward trend relative to a baseline value that meets a preset alignment deterioration condition (e.g., a continuous decrease exceeding a certain threshold or a rate of decrease exceeding a certain threshold), the system immediately generates an alignment deterioration event record. This record contains the unique identifier of the wireless charging target (e.g., the tool serial number), the identifier of the shared equipment rental cabinet (e.g., the cabinet number), and the specific change trend data of the monitored communication auxiliary parameter. This newly generated alignment deterioration event record is then used to update the initial charging control parameter set currently generated for the wireless charging target. The update process may include dynamically adjusting the upper limit of charging current, target charging voltage, or preset charging duration in the initial parameter set based on the severity of the recorded change trend. Alternatively, based on the recorded wireless charging target identifier and shared equipment rental cabinet identifier, historical alignment deterioration management experience data related to the target object or location is retrieved from a preset object-specific dataset and modified based on this experience. If historical data indicates that a particular tool model is prone to misalignment issues at a specific charging station in a specific cabinet, and historical experience indicates that reducing the charging power can alleviate the problem, the system will use this record to trigger the power reduction strategy in the parameter set when misalignment deteriorates. This results in a charging control parameter set that has been corrected based on the misalignment event information and is used to guide subsequent charging processes.

[0039] This application can generate an event record containing specific context information when alignment deterioration is detected, and use this record to adjust the charging control parameter set. As a result, the abnormal event information of alignment deterioration can be effectively fed back into the charging control strategy, making parameter adjustments more targeted and more effective in dealing with charging problems caused by poor alignment, thereby improving the stability and success rate of the charging process. At the same time, by accumulating these event records, it can provide a data foundation for the continuous optimization of the preset object-specific data set, allowing the system to learn and adapt to the alignment characteristics of different objects and positions, further improving the intelligent level of charging control.

[0040] In some of the above embodiments of the present application, the present application further proposes that after the step of generating each charging control parameter set including an emergency response strategy using the preset object-specific data set, the real-time status data, and the current scenario data, the following steps are further included: Historical performance indicators are generated using a preset object-specific dataset, and immediate status indicators are generated using real-time status data. Historical performance indicators are quantitative representations of the object's charging behavior, efficiency, and safety margins under typical or historical conditions, derived from statistical analysis of the preset object-specific dataset. These quantitative representations provide a reference baseline based on long-term experience. Instant status indicators are quantitative representations of the object's current physical state, operating environment, and other characteristics, derived from real-time status data. These quantitative representations provide information about the object's current actual situation.

[0041] Determine whether there is a decision conflict between the control strategy indicated by the historical performance indicator and the control strategy indicated by the current status indicator. A decision conflict is an inconsistency or potential risk between a control recommendation derived from the historical performance indicator and a control recommendation derived from the current status indicator, thereby identifying situations requiring special treatment.

[0042] In response to determining that a decision conflict exists, a temporary parameter set containing monitoring trigger conditions is generated. The monitoring trigger conditions are conditions that initiate execution of the temporary parameter set and data collection, such as reaching a certain charging stage, temperature threshold, or time interval, to verify the strategy at a specific time. A temporary parameter set is a set of charging control parameters temporarily generated to verify or adjust the control strategy after determining that a decision conflict exists, and is intended to test the effectiveness of different strategies in actual operation.

[0043] After the monitoring trigger condition is met, a change index of the immediate state indicator during execution of the temporary parameter set by the local control unit is obtained. The change index is a quantitative representation of how the immediate state indicator changes over time or over the charging process during execution of the temporary parameter set, and its purpose is to reflect the impact of the temporary policy on the object state.

[0044] The degree of conformity between the change indicator and the historical performance indicator is used to generate a set of charging control parameters for each subsequent wireless charging target. Conformity refers to the degree of match between the target behavior or state change trend reflected by the change indicator and the typical or expected behavior reflected by the historical performance indicator. This is used to assess the effectiveness of the temporary strategy.

[0045] Specifically, when a power tool is returned to a shared equipment rental locker and is ready for wireless charging, the system first obtains the tool's real-time status data (e.g., battery temperature of 40°C, remaining charge of 20%), as well as the locker's current context data (e.g., ambient temperature of 35°C). The system also utilizes the tool's pre-set, object-specific dataset, which may include historical charging curves, safe temperature ranges, and temperature rise data at different charging currents for this battery model, to generate historical performance indicators. For example, historical data shows that when the ambient temperature exceeds 30°C and the charging current exceeds 0.8°C, the battery temperature rises significantly faster, easily triggering overtemperature protection. Based on the real-time status data, a current status indicator is generated, e.g., the current battery temperature is 40°C, which is already at a high level. At this point, a decision conflict is determined between the control strategy indicated by the historical performance indicators (e.g., when the battery is low, a higher current is generally recommended to shorten charging time) and the control strategy indicated by the current status indicator (e.g., the current temperature is too high, so high current charging is not recommended). In response to determining a decision conflict, the system generates a temporary parameter set that includes monitoring trigger conditions. For example, it sets the charging current cap to 0.5C and sets the monitoring trigger condition to monitor the battery temperature every 5 minutes for 30 minutes after charging begins. The local control unit begins executing this temporary parameter set, charging at a current of 0.5C. After the monitoring trigger condition is met, the system obtains the change indicator of the local control unit's current status indicator during the execution of the temporary parameter set. For example, it records that the battery temperature rose from 40°C to 43°C in 30 minutes at a current of 0.5C. Finally, the system uses the consistency of this change indicator (temperature rise rate) with historical performance indicators (historical temperature rise data) to generate a charging control parameter set for subsequent charging. For example, the system compares the temperature rise rate at the current current of 0.5C with the temperature rise rate at a current of 0.5C in historical data, as well as the temperature rise rate at a current of 0.8C or higher in historical data. If it is found that the current temperature rise rate is basically consistent with the temperature rise rate at 0.5C current in the historical data, and is much lower than the temperature rise rate at high current in the historical data, then the 0.5C current is considered to be a relatively safe strategy, which can be used as a parameter set for subsequent charging, or the current can be further fine-tuned 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, and avoid blindly executing strategies that may cause device overheating or low charging efficiency. By introducing a temporary parameter set for dynamic monitoring and verification, and adjusting it according to the degree of conformity between the actual monitoring results and historical experience, the generated charging control parameter set is more adaptable and robust, and can better cope with complex situations and uncertainties in actual operation, thereby improving the safety, efficiency and reliability of wireless charging of multiple devices.

[0046] In some of the above-mentioned embodiments of the present application, the present application further proposes that the steps of generating a charging control parameter set for subsequent charging of each wireless charging object using the degree of conformity between the change indicator and the historical performance indicator include: Obtaining operating status data of at least one object in the shared equipment rental cabinet other than the object to be wirelessly charged. Specifically, the operating status data of the at least one object is operating or status information of the non-charging object related to environmental changes inside or outside the shared equipment rental cabinet. This data can be implemented using cabinet door switch status, other charging position occupancy status, cabinet temperature sensor data, humidity sensor data, light sensor data, sound sensor data, or other data such as the temperature and power level of other non-charging tools. The purpose is to obtain information about external or internal non-charging factors that may affect the charging environment or the status of the object to be charged.

[0047] Based on the operating status data, environmental disturbance events that meet preset conditions are identified. The preset conditions are rules or threshold sets used to determine whether an environmental disturbance event has occurred. They can be implemented using a single threshold, a combination of multiple indicators, or a model judgment rule based on historical data training. The purpose is to set standards for identifying environmental disturbance events. Environmental disturbance events are unexpected or non-charging related events that occur in the environment where the shared equipment rental cabinet is located and may affect the wireless charging process or the state of the object to be charged. They are implemented by events such as the cabinet door being opened, other tools being stored or taken out, the ambient temperature or humidity changing drastically, or the cabinet being subjected to external impact. The purpose is to identify external interference that may cause distortion of the change indicator.

[0048] Based on the temporal correspondence between the environmental disturbance event and the change index, a disturbance data segment affected by the environmental disturbance event is derived. The temporal correspondence is the association between the time point or time period at which the environmental disturbance event occurs and the time point or time period at which the change index is recorded. This is achieved using methods such as timestamp matching, time window overlap judgment, or causal relationship analysis, and aims to determine which parts of the change index may have occurred simultaneously with or been affected by a specific environmental disturbance event. The disturbance data segment is a subset of data within the time period of the change index that is determined to be affected by the environmental disturbance event. This is achieved using change index data recorded during or within a specific period of time after the environmental disturbance event, and aims to separate the disturbed data from the change index.

[0049] A degree of compliance is determined based on a portion of the change indicator that is not included in the disturbance data segment and the historical performance indicator.

[0050] A charging control parameter set for subsequent charging of each object to be wirelessly charged is generated based on the compliance.

[0051] In this embodiment, data from the cabinet's internal temperature sensor, humidity sensor data, cabinet door switch sensor data, and the temperature and power data of tools at other charging stations are collected as operational status data for at least one object in the shared equipment rental cabinet, other than the object to be wirelessly charged. Preset conditions can be set as: the cabinet temperature rises by more than 5 degrees Celsius in a short period of time, the cabinet door is open for more than 10 seconds, or a tool is deposited or withdrawn. When these conditions are detected, they can be identified as environmental disturbance events that meet the preset conditions. For example, if the cabinet door is detected to be open within a certain time period (e.g., 1 minute), the data for a variation indicator (e.g., the battery temperature change rate of the object to be charged) within that time period and a subsequent buffer period (e.g., 30 seconds) can be marked as a disturbance data segment. When determining compliance, data from the variation indicator not marked as a disturbance data segment is extracted and compared with historical performance indicators for the object to be charged (e.g., a typical temperature change curve for that type of battery during normal charging). A correlation coefficient is calculated as the compliance level. When generating a charging control parameter set based on compliance, if the compliance is high, such as a correlation coefficient greater than 0.8, the current state is considered to be consistent with historical experience, and an optimization strategy generated based on historical performance indicators is adopted. If the compliance is low, a more conservative charging strategy needs to be adopted or further diagnosis needs to be triggered. This application makes the calculation of compliance more accurate by identifying and eliminating the impact of environmental disturbances on change indicators, thereby generating a more reliable and effective charging control parameter set. This improves the adaptability and robustness of the charging strategy, avoids the reduction in charging efficiency or safety risks caused by environmental interference, and improves the overall performance and stability of wireless charging of multiple devices.

[0052] In some of the above embodiments of the present application, the present application further proposes that the steps of identifying an environmental disturbance event that meets preset conditions based on the operating status data include: The operating status data is monitored to obtain multiple single operation events, wherein none of the multiple single operation events meet a preset condition. A single operation event is a discrete occurrence or change in the operating status data, each of which does not meet a preset condition. It can be manifested by a brief temperature fluctuation, a slight drop in signal strength, or a single slight vibration, etc. The purpose is to capture events that are not sufficient to trigger an alarm individually but may have a cumulative impact.

[0053] Determine a disturbance contribution value corresponding to each of the plurality of single operational events. The disturbance contribution value is a quantitative value assigned to each single operational event, representing the potential impact or contribution of the event to the environmental disturbance. The disturbance contribution value can be implemented using a numerical value calculated based on the event type, magnitude, or duration, and is intended to quantify the impact of different events.

[0054] Aggregate each of the disturbance contribution values ​​to generate a cumulative disturbance value. Aggregation is the process of combining multiple individual values ​​into a single representative value. This can be achieved through summation, weighted averaging, or integration, and is intended to comprehensively assess the cumulative impact of multiple events. The cumulative disturbance value is the result of aggregating the disturbance contribution values ​​of multiple single operational events. It represents the combined impact of these smaller events and provides an indicator reflecting the cumulative effect.

[0055] 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 using a numerical threshold or a rate of change threshold, etc., to determine whether the cumulative impact has reached a significant level.

[0056] Specifically, the system monitors the operating status data of wirelessly charged objects in shared equipment rental cabinets, such as battery temperature, charging current, charging station vibration sensor data, and communication signal strength between the charging station and the tool. Assume that the preset conditions are: an instantaneous battery temperature increase of no more than 2°C, an instantaneous charging current decrease of no more than 10%, a vibration amplitude of no more than 0.1g, and an instantaneous communication signal strength decrease of no more than 3dBm. If a series of events are detected, such as three battery temperature increases of 1°C within 5 minutes, four charging current decreases of 5% within 10 minutes, or multiple communication signal strength decreases of 2dBm within a short period of time, none of these individual operational events meet the preset conditions for directly triggering an environmental disturbance event. A basic disturbance contribution value can be set for each type of single operational event, for example, a 1°C temperature fluctuation contribution value of 1, a 5% current decrease contribution value of 0.5, and a 2dBm signal strength decrease contribution value of 0.8. The basic contribution value is then adjusted based on the time of occurrence, duration, or current charging stage of the event to obtain a disturbance contribution value for each single operational event. For example, the contribution value of an event that occurs during a critical charging stage 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 so that the cumulative disturbance value reaches 10. When the cumulative disturbance value exceeds 10, the system identifies environmental disturbance events that meet the preset conditions, such as determining that a continuous slight environmental disturbance has occurred or the stability of the charging position has decreased. The present application can effectively aggregate and analyze multiple single operation events with relatively small impacts, and identify environmental disturbance events that have a significant impact on the wireless charging process due to the accumulation of these scattered events. This method overcomes the problem that traditional methods may miss disturbances due to single data not reaching the threshold, and improves the accuracy and sensitivity of environmental disturbance event identification, so that the factors affecting the charging process can be more comprehensively grasped, providing a more reliable basis for subsequent charging control decisions.

[0057] In some of the above embodiments of the present application, the present application further proposes that the step of determining the disturbance contribution value corresponding to each of the multiple single operation events includes: For each of the multiple single operation events, a current operation stage of the wirelessly charged object is obtained. The current operation stage of the wirelessly charged object is a specific state or period of the wirelessly charged object during the entire charging or standby cycle, such as an initial charging stage, a mid-charging stage, a final charging stage, a standby state, and a fault state, and is determined based on parameters such as a charge level, a charging current, a battery temperature, and a charging duration of the wirelessly charged object.

[0058] Determine a basic disturbance contribution value for the single operational event. The basic disturbance contribution value is a preliminary quantitative assessment of the inherent disturbance level of the single operational event, and is determined based on preset parameters or models such as the type, intensity, and duration of the single operational event.

[0059] The basic disturbance contribution value is adjusted using the current operating stage to determine disturbance contribution values ​​corresponding to each of the multiple single operation events. Specifically, adjusting the basic disturbance contribution value using the current operating stage is to correct or weight the basic disturbance contribution value of the single operation event based on the current operating stage of the wirelessly charged object. This can be achieved using a preset adjustment coefficient, a lookup table, or a machine learning model, and is intended to more accurately reflect the actual impact of the operation event on the wireless charging environment in the current operating stage.

[0060] The present application first obtains the current operating stage of the object to be wirelessly charged for each single operating event among multiple single operating events. This is because the same operating event may have different disturbance effects on the environment when the object to be wirelessly charged is in different operating stages. Next, the basic disturbance contribution value of the single operating event is determined, which is a preliminary quantification of the degree of disturbance of the operating event itself. The basic disturbance contribution value is adjusted using the current operating stage to determine the disturbance contribution value corresponding to each of the multiple single operating events. It is precisely because the specific operating stage of the object to be wirelessly charged is taken into consideration and the basic disturbance contribution value is corrected based on this that the disturbance contribution value finally obtained can more accurately reflect the actual impact of the operating event on the wireless charging environment in the current specific situation. These adjusted disturbance contribution values ​​are then used for aggregation to generate cumulative disturbance values, thereby identifying environmental disturbance events that meet the preset conditions. This method overcomes the limitations of simply assigning fixed contribution values ​​to all single operating events and improves the accuracy of environmental disturbance event identification. More accurate identification of environmental disturbance events provides a more reliable basis for subsequent charging control decisions. For example, after identifying an environmental disturbance event, charging parameters can be adjusted or emergency strategies can be triggered more promptly, thereby improving the robustness and effectiveness of the entire multi-device wireless charging control method.

[0061] In some of the above embodiments of the present application, the present application further proposes that the step of aggregating each of the disturbance contribution values ​​to generate a cumulative disturbance value includes: Get the time weight corresponding to each disturbance contribution value. The time weight is a coefficient used to measure the decay or cumulative effect of the disturbance contribution value over time. It can be determined based on the time distance between the disturbance event and the current moment. For example, the closer the disturbance event is to the current moment, the greater the time weight, and vice versa.

[0062] Multiply each disturbance contribution value by its corresponding time weight to obtain the total weighted disturbance contribution value. The weighted disturbance contribution value is the value obtained by multiplying the disturbance contribution value by the corresponding time weight. It reflects the actual contribution of the single operation event to the current cumulative disturbance after considering the time factor.

[0063] All the weighted disturbance contribution values ​​are summed to generate the cumulative disturbance value. The cumulative disturbance value is the sum of all the weighted disturbance contribution values, which comprehensively reflects the overall impact of multiple single operation events on the current environmental disturbance level after considering time decay or cumulative effects.

[0064] In this embodiment, by obtaining the time weight corresponding to each disturbance contribution value, multiplying each disturbance contribution value by its 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 time factors is introduced into the process of aggregating disturbance contribution values. It is precisely because of the consideration of time factors that the impact of disturbance events that occurred recently on the cumulative disturbance value is greater, while the impact of events that occurred earlier gradually weakens. This is more in line with the law that the impact of disturbances in real environments decays over time. Through this weighted summation method, the generated cumulative disturbance value can more accurately reflect the actual impact level of the environmental disturbance event at the current moment. This more accurate cumulative disturbance value, combined with the steps in the previous scheme of obtaining multiple single operation events by monitoring operating status data, determining their respective disturbance contribution values, and simply summing them to generate a cumulative disturbance value, together achieves more accurate identification of environmental disturbance events. In this way, the errors that may be caused by simple summation can be effectively avoided, and the accuracy of environmental disturbance event identification is improved.

[0065] In some of the above embodiments of the present application, the present application further proposes that the step of obtaining the real-time status data of each wireless charging object reported by the shared equipment rental cabinet and the current scenario data of the shared equipment rental cabinet includes: Real-time status data including environmental information and reservation information of each object to be wirelessly charged reported by the shared equipment rental cabinet and current scenario data including tool placement information of the shared equipment rental cabinet are obtained.

[0066] The solution of the present application provides richer and more targeted information input for subsequent charging control by obtaining real-time status data including environmental information and reservation information, as well as current scenario data including tool placement information. Since the environmental information is obtained, it is possible to understand the temperature and humidity conditions of the charging object, so that when generating the charging control parameter set, the impact of environmental factors on the battery charging characteristics and safety can be considered, such as appropriately reducing the charging power in a high temperature environment to avoid overheating. Since the reservation information is obtained, the system can know the user's usage requirements and time constraints for specific tools, so that when scheduling charging tasks, it can give priority to allocating charging resources or adjusting the charging strategy for tools with reservations to ensure that the required power is reached before the reservation time. Since the tool placement information is obtained, it is possible to determine whether the object to be charged is correctly aligned with the charging position, so that potential charging efficiency is low or charging cannot be achieved, and the alignment status is considered when generating the parameter set, and even trigger a prompt to the user to re-place or adjust the charging strategy. Therefore, through this more detailed data acquisition method, the method of the present application can more comprehensively grasp the key factors affecting the charging process, laying the foundation for the subsequent generation of a more accurate and optimized charging control parameter set based on these data, thereby improving the overall charging efficiency, safety and user experience.

[0067] For a multi-device wireless charging control method based on any of the above embodiments, please refer to Figure 2 The present application also provides a multi-device wireless charging control system, which includes an acquisition module 210, a parameter set generation module 220 and a control module 230.

[0068] The acquisition module 210 is used to acquire the real-time status data of each object to be wirelessly charged reported by the shared equipment rental cabinet and the current context data of the shared equipment rental cabinet.

[0069] The parameter set generation module 220 is configured to generate a charging control parameter set including each emergency response strategy using a preset object-specific data set, the real-time status 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; The control module 230 is configured to send each of the charging control parameter sets to the local control unit of the shared device rental cabinet, and then drive the local control unit to control wireless charging of multiple devices based on the charging control parameter set.

[0070] In this embodiment, the acquisition module 210 receives data from the shared equipment rental cabinet. This data includes the real-time status of each device to be wirelessly charged, as well as the current context of the shared equipment rental cabinet. This data provides essential information for subsequent charging decisions, such as the device's power level, temperature, and the cabinet's environmental conditions. The parameter set generation module 220 receives the data provided by the acquisition module and combines it with a preset object-specific dataset, constructed based on the device's historical data and static attributes, to generate personalized charging control parameter sets for each device. These parameter sets not only include general charging instructions but also integrate emergency response strategies to ensure timely response in abnormal situations. The control module 230 receives the charging control parameter set output by the parameter set generation module and sends it to the local control unit of the shared equipment rental cabinet. After receiving the parameter set, the local control unit drives the wireless charging process for multiple devices based on the instructions contained therein. This design enables the system to dynamically adjust charging strategies based on real-time data, historical information, and environmental factors, extending the cloud platform's intelligent decision-making capabilities to the local execution level. In this way, the system can effectively manage the charging process of different types and states of charging objects at limited charging stations, optimize charging efficiency, ensure charging safety, and respond to possible emergencies. The system can obtain the real-time status of the charging objects and the contextual data of the rental cabinets, combine historical and static attributes to generate a charging control parameter set containing emergency strategies, and then send the parameter set to the local control unit to drive charging. This enables the system to dynamically adjust charging strategies based on specific circumstances, improving the level of refinement of multi-device wireless charging management and the ability to respond to emergencies, thereby optimizing charging efficiency and safety.

[0071] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the present invention specification.

Claims

1. A multi-device wireless charging control method, characterized in that: The following steps are involved: Acquire the real-time status data of each wireless charging object reported by the shared equipment rental cabinet and the current scenario data of the shared equipment rental cabinet; generating a charging control parameter set including each emergency response strategy using a preset object-specific data set, the real-time status 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; After each of the charging control parameter sets is sent 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.

2. A multi-device wireless charging control method according to claim 1, characterized in that: The step of generating each charging control parameter set including an emergency response strategy by using a preset object-specific data set, the real-time status data, and the current scenario data includes: Generate an initial charging control parameter set using a preset object-specific data set, the real-time status data, and the current scenario data; wherein the current scenario data includes initial physical alignment status information between the object to be wirelessly charged and the charging position; Acquire a communication auxiliary parameter corresponding to the initial physical alignment state information and representing the quality of the communication link between the object to be wirelessly charged and the charging position, and set the communication auxiliary parameter as a reference value; collecting real-time values ​​of the communication auxiliary parameters of the wireless charging object during charging, and confirming a real-time value sequence; Determining a change trend of the real-time value sequence relative to the reference value; When the change trend meets a preset alignment deterioration condition, the initial charging control parameter set is adjusted to obtain a charging control parameter set.

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

4. The multi-device wireless charging control method according to claim 1, characterized in that: After the step of generating each charging control parameter set including an emergency response strategy by using the preset object-specific data set, the real-time status data, and the current scenario data, the method further includes: Generate historical performance indicators using pre-set object-specific data sets and generate immediate status indicators using real-time status data; determining whether there is a decision conflict between the control strategy indicated by the historical performance indicator and the control strategy indicated by the immediate status indicator; In response to determining that the decision conflict exists, generating a temporary parameter set including a monitoring trigger condition; After the monitoring trigger condition is met, obtaining a change indicator of the instantaneous status indicator during execution of the temporary parameter set by the local control unit; A charging control parameter set for subsequent charging of each object to be wirelessly charged is generated using the degree of conformity between the change indicator and the historical performance indicator.

5. The multi-device wireless charging control method according to claim 4, characterized in that: The step of generating a charging control parameter set for subsequent charging of each wirelessly charged object by using the degree of conformity between the change indicator and the historical performance indicator includes: Acquire operating status data of at least one object other than the object to be wirelessly charged in the shared equipment rental cabinet; Identifying environmental disturbance events that meet preset conditions based on the operating status data; Based on the time correspondence between the environmental disturbance event and the change index, a disturbance data segment affected by the environmental disturbance event is obtained; determining a degree of compliance based on a portion of the change indicator not included in the disturbance data segment and the historical performance indicator; A charging control parameter set for subsequent charging of each object to be wirelessly charged is generated based on the compliance.

6. The multi-device wireless charging control method according to claim 5, characterized in that: The step of identifying an environmental disturbance event that meets a preset condition based on the operating status data includes: Monitoring the operating status data to obtain a plurality of single operation events, wherein none of the plurality of single operation events satisfies a preset condition; Determining disturbance contribution values ​​corresponding to each of the plurality of single operation events; Aggregating each of the disturbance contribution values ​​to generate a cumulative disturbance value; When the accumulated disturbance value meets a preset accumulation threshold condition, an environmental disturbance event meeting the preset condition is identified.

7. The multi-device wireless charging control method according to claim 6, characterized in that: The step of determining the disturbance contribution values ​​corresponding to each of the plurality of single operation events comprises: For each of the multiple single operation events, obtaining a current operation stage of the object to be wirelessly charged; determining a basic disturbance contribution value of the single operation event; The basic disturbance contribution value is adjusted using the current operating stage to determine disturbance contribution values ​​corresponding to respective single operating events.

8. The 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: Get 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; All the weighted disturbance contribution values ​​are summed to generate the cumulative disturbance value.

9. The multi-device wireless charging control method according to claim 1, characterized in that: The step of obtaining the real-time status data of each wireless charging object reported by the shared equipment rental cabinet and the current scenario data of the shared equipment rental cabinet includes: Real-time status data including environmental information and reservation information of each object to be wirelessly charged reported by the shared equipment rental cabinet and current scenario data including tool placement information of the shared equipment rental cabinet are obtained.

10. A multi-device wireless charging control system, characterized in that: The system includes: An acquisition module, configured to acquire real-time status data of each object to be wirelessly charged reported by a shared equipment rental cabinet and current scenario data of the shared equipment rental cabinet; a parameter set generation module, configured to generate a charging control parameter set including each emergency response strategy using a preset object-specific data set, the real-time status 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; The control module is used to send each of the charging control parameter sets to the local control unit of the shared device rental cabinet, and then drive the local control unit to control the wireless charging of multiple devices based on the charging control parameter set.

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