A collaborative energy management method and system for a dual-body mobile environmental processing device

Abstract

This invention relates to a collaborative energy management method and system for a dual-unit mobile environmental processing device. The method includes: acquiring first power parameters of a first mobile device and second power parameters of a second mobile device; identifying whether the current operating mode of the dual-unit device is a joint operation mode or a separate operation mode; acquiring current task load parameters of the first and second mobile devices; constructing a collaborative energy consumption prediction model based on the power parameters, task load parameters, operating mode, and historical power curves; calculating the predicted remaining operating time and optimal power ratio of the dual-unit device; and determining whether to trigger an energy balance scheduling strategy based on the predicted remaining operating time, the power difference between the two devices, and a safety threshold. This invention effectively solves the problems of energy distribution imbalance and uncontrollable range in dual-unit devices, achieving dynamic energy balance and significantly improving the overall system range, task completion rate, and energy utilization efficiency.

Description

Technical Field

[0001] This invention belongs to the technical field of intelligent service robots and indoor environmental treatment equipment, and particularly relates to a collaborative energy management method and system for a dual-body mobile environmental treatment device. Background Technology

[0002] With the continuous development of smart home devices, mobile cleaning robots and air purification equipment are gradually becoming important components of home environmental management. To improve equipment utilization efficiency and spatial adaptability, some new environmental management devices are beginning to adopt mobile or multi-functional integrated structures. However, existing technologies have the following problems: The energy consumption of multifunctional environmental equipment is constantly increasing: With the addition of functions (such as drive motors, high-power fans, compressors, etc.), the energy consumption of equipment increases significantly, placing higher demands on battery capacity and energy management capabilities.

[0003] A single battery power supply structure is insufficient to meet the requirements: when multiple modules are running simultaneously, the power is prone to rapid decline, there is a lack of energy distribution mechanism between different modules, and it is difficult to adapt to the long-term stable operation of multi-functional devices.

[0004] The lack of a collaborative energy management mechanism in dual-body equipment: Currently, the upper and lower batteries of dual-body equipment (such as mobile chassis combined with environmental treatment body) are independent of each other, and energy sharing is not possible. There is no unified energy scheduling strategy, and it is difficult to allocate tasks reasonably when the power is insufficient, which affects the overall operating efficiency.

[0005] The base station charging system lacks the ability to coordinate energy replenishment: the traditional base station charging mode has difficulty coordinating the charging sequence of the two battery systems, and cannot reasonably arrange return time or optimize energy use during mission execution.

[0006] Lack of a coordinated mechanism between task planning and energy management: Existing technologies typically handle path planning and energy management separately, which may cause equipment to interrupt tasks due to insufficient power.

[0007] In summary, it is necessary to propose a collaborative energy management method and system for dual-body mobile environmental processing equipment, which can improve the overall efficiency and endurance of the equipment by establishing a multi-battery collaborative power supply mechanism and intelligent scheduling. Summary of the Invention

[0008] The purpose of this invention is to provide a collaborative energy management method and system for a dual-body mobile environment processing device. It dynamically allocates energy based on the operating status, performs energy scheduling based on the separate status, optimizes power based on task load, and has a recombination and replenishment strategy to improve the overall endurance efficiency, thereby solving the problems of low energy utilization, unbalanced energy distribution, and lack of energy coordination between separate parts in existing dual-body structure devices.

[0009] This invention provides a collaborative energy management method for a dual-body mobile environmental processing device, comprising the following steps: Step 1: Obtain the first battery parameter E1 of the first mobile device and the second battery parameter E2 of the second mobile device, respectively; Step 2: Identify whether the current operating mode of the dual-unit equipment is joint operation mode or separate operation mode; Step 3: Obtain the current task load parameters L1 and L2 of the first mobile device and the second mobile device respectively; Step 4: Based on the power parameters, task load parameters, operating mode and historical power curve, construct a collaborative energy consumption prediction model to calculate the predicted remaining operating time and optimal power ratio of the dual-body equipment; Step 5: Determine whether to trigger the energy balance scheduling strategy based on the predicted remaining running time, the power difference between the two devices, and the safety threshold. In split operation mode: When a single unit has insufficient remaining operating time, another unit will take over part of the task, with the former prioritizing returning to base or operating at reduced power to ensure mission continuity. When the power difference exceeds the threshold, the power allocation ratio between the first and second mobile devices is dynamically adjusted, and the remaining running time prediction values ​​of the two devices are recalculated. When the battery level of any device falls below a preset safety threshold, a reconfiguration or return-to-home control strategy is triggered. Under joint operation mode: When the power replenishment conditions are met, one device supplies power to another device through an electrical connection structure; the power replenishment conditions include: the power of any device is lower than the power replenishment threshold, and the power of the other device is higher than the shared threshold; the power transmission direction is automatically determined based on the power difference between the first mobile device and the second mobile device. When the battery level of any device falls below a preset safety threshold, the split-operation control strategy is triggered.

[0010] Furthermore, the collaborative energy consumption prediction model includes the following functional relationships: , where M represents the operating mode parameter.

[0011] Furthermore, the power allocation ratio is determined as follows: , ,in, , These are variable weighting coefficients.

[0012] Furthermore, the remaining running time prediction is dynamically corrected based on historical running data.

[0013] Furthermore, when the predicted remaining running time is less than the preset task completion time, the reorganization path is planned in advance.

[0014] Furthermore, the method also includes: In the base-coordinated charging scheduling, the base receives status data, determines the charging target, and controls interface switching, supporting synchronous or sequential charging.

[0015] The present invention also provides a collaborative energy management system for a dual-body mobile environmental processing device, comprising: A power monitoring module is used to detect the power parameters of the first mobile device and the second mobile device respectively; The pattern recognition module is used to identify the current operating mode; The task load identification module is used to obtain task load parameters; The energy consumption prediction module is used to calculate the predicted value of the remaining running time; The collaborative scheduling module is used to execute energy balance scheduling strategies; The power control module is used to dynamically adjust the output power of the device; The safety control module is used to trigger reassembly, return to home, or prohibit split operation control strategies when the battery level is below the safety threshold.

[0016] Furthermore, the system also includes an energy-sharing control module for controlling bidirectional power transmission in joint operation mode.

[0017] Furthermore, the first mobile device and the second mobile device are electrically connected in joint operation mode through a bidirectional DC-DC conversion module; the energy sharing control module realizes bidirectional power transmission by controlling the bidirectional DC-DC conversion module; the energy sharing control module includes a current direction control unit, a voltage matching unit, and a protection unit.

[0018] The present invention also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the collaborative energy management method of the dual-body mobile environment processing device.

[0019] By employing the above-described scheme, the collaborative energy management method and system for dual-body mobile environmental processing equipment achieves the following technical effects: 1) Achieve dynamic energy balance of dual-body equipment: Through bidirectional energy sharing control and dynamic power regulation, the power consumption of the two bodies tends to be balanced, significantly extending the overall effective operating time.

[0020] 2) Avoid premature depletion of individual units: By combining task load identification and energy consumption prediction, high-load equipment can be intervened in advance to reduce downtime and improve task completion rate.

[0021] 3) Support bidirectional energy sharing: Set up bidirectional DC-DC conversion and current direction control to improve the overall energy utilization rate and avoid power waste.

[0022] 4) Implement forward-looking energy management: Build an energy consumption prediction model, which has predictive and risk assessment capabilities compared with simple strategies, and improve the intelligent level.

[0023] 5) Improve safety and reduce maintenance costs: Set multiple safety thresholds and protection mechanisms to reduce the risks of deep discharge and thermal runaway; at the same time, reduce the number of charging times to extend the battery life.

[0024] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly and implement it according to the content of the specification, the following takes the preferred embodiments of the present invention and combines with the drawings to describe in detail as follows. Brief Description of the Drawings

[0025] Figure 1 is a flowchart of a collaborative energy management method for a dual-body mobile environment processing device of the present invention; Figure 2 is a collaborative energy consumption prediction model of the present invention; Figure 3 is an energy balance control logic diagram for the split operation mode of the present invention; Figure 4 is a low-power safety control mechanism of the present invention; Figure 5 is an energy sharing control logic diagram under the combined operation mode of the present invention; Figure 6 is a schematic diagram of the overall structure of a dual-body mobile environment processing device of the present invention; Figure 7 is a structural block diagram of the collaborative energy management of a dual-body mobile environment processing device of the present invention; Figure 8 is a schematic diagram of the energy sharing interface structure of the present invention; Figure 9 is a structural block diagram of bidirectional power transmission of the present invention; Detailed Description of the Preferred Embodiments

[0026] The following combines the drawings and embodiments to further describe in detail the specific implementation manners of the present invention. The following embodiments are used to illustrate the present invention, but are not used to limit the scope of the present invention.

[0027] Refer Figure 1As shown, this embodiment provides a collaborative energy management method for a dual-body mobile environmental processing device. The device, applicable to home or indoor environments, includes a mobile chassis for ground movement and cleaning operations, and an environmental processing unit for air environment treatment. These two components form a dual-body collaborative system via a mechanical connection structure and can operate in combination or separately according to task requirements. The environmental processing unit can integrate one or more environmental processing functions such as air purification, air circulation, humidification, dehumidification, and air disinfection. The mobile chassis can perform floor cleaning functions such as sweeping, vacuuming, and mopping. The device is powered by a built-in battery system and can be charged or recharged by a base station. Data exchange between the two components is achieved through wired contacts or wireless communication.

[0028] The method includes the following steps: Step S1: Obtain the first battery parameter E1 of the first mobile device and the second battery parameter E2 of the second mobile device.

[0029] Step S2: Identify whether the current operating mode of the dual-unit equipment is joint operation mode or separate operation mode.

[0030] Step S3: Obtain the current task load parameters L1 and L2 of the first mobile device and the second mobile device, respectively.

[0031] Step S4: Based on the power parameters, task load parameters, operating mode, and historical power curves, construct a collaborative energy consumption prediction model to calculate the predicted remaining operating time and optimal power ratio of the dual-unit equipment. Figure 2 As shown.

[0032] Step S5: Determine whether to trigger the energy balance scheduling strategy based on the predicted remaining running time, the power difference between the two devices, and the safety threshold. In split operation mode: When a single unit's remaining operating time is insufficient, the other unit will take over some tasks, with the former prioritizing return to base or operating at reduced power to ensure mission continuity. During the dual-unit separation operation, location and estimated remaining time are shared wirelessly. (See reference...) Figure 3 As shown.

[0033] When the power difference exceeds the threshold, the power allocation ratio between the first and second mobile devices is dynamically adjusted, and the remaining operating time prediction values ​​of the two devices are recalculated.

[0034] When the battery level of any device falls below a preset safety threshold, a reconfiguration or return-to-home control strategy is triggered. (See reference...) Figure 4 As shown.

[0035] Under joint operation mode: When the energy replenishment condition is met, power is supplied from one device to another through the electrical connection structure; the energy replenishment condition includes: the power of any one device is lower than the energy replenishment threshold, and the power of the other device is higher than the sharing threshold; the power transmission direction is automatically determined according to the power difference between the first mobile device and the second mobile device. Refer to Figure 5 as shown.

[0036] When the power of any one device is lower than the preset safety threshold, the control strategy of prohibiting split operation is triggered. Refer to Figure 4 as shown.

[0037] This collaborative energy management method effectively solves the problems of unbalanced energy distribution and uncontrollable endurance of dual-body devices, achieves dynamic balance of dual-body energy, and significantly improves the overall endurance, task completion rate and energy utilization efficiency of the system.

[0038] In this embodiment, the collaborative energy consumption prediction model includes the following functional relationships: , where M represents the operation mode parameter.

[0039] In this embodiment, the power distribution ratio is determined as follows: , , where , are variable weight coefficients.

[0040] In this embodiment, the predicted remaining operation time value is dynamically corrected based on historical operation data.

[0041] In this embodiment, when the predicted remaining operation time is less than the preset task completion time, a reconfiguration path is planned in advance.

[0042] In this embodiment, the method further includes: In the base collaborative charging scheduling, the base receives the status data, determines the charging object and controls the interface switching to support synchronous or sequential charging. For example, the intelligent base detects the SOC and temperature of the dual body. If the SOC difference is large, it preferentially charges the low-power body. If they are close, it charges synchronously. If the temperature is high, it charges slowly to improve efficiency and protect the battery.

[0043] Refer to Figure 6 , Figure 7 As shown, this embodiment also provides a collaborative energy management system 104 for a dual-body mobile environment processing device, including: The power monitoring module 201 is used to detect the power parameters of the first mobile device and the second mobile device respectively; The mode recognition module 202 is used to recognize the current operation mode; The task load recognition module 203 is used to obtain the task load parameters; The energy consumption prediction module 204 is used to calculate the predicted value of the remaining running time; The collaborative scheduling module 205 is used to execute the energy balance scheduling strategy; The power control module 206 is used to dynamically adjust the output power of the device; The safety control module 207 is used to trigger the reorganization, return flight or prohibit the split operation control strategy when the power is lower than the safety threshold.

[0044] The energy sharing control module 208 is used to control the bidirectional power transmission in the combined operation mode.

[0045] Parameter Figure 8 As shown, the energy sharing interface 103 includes conductive contacts (positive electrode contact 301, negative electrode contact 302), signal contacts 303, elastic crimping components 304, and insulation isolation structures 305.

[0046] Parameter Figure 9 As shown, the first mobile device and the second mobile device are electrically connected through a bidirectional DC-DC conversion module 403 in the combined operation mode; the energy sharing control module realizes bidirectional power transmission by controlling the bidirectional DC-DC conversion module; the energy sharing control module includes a current direction control unit 404, a voltage matching unit 405, and a protection unit 406. When replenishing energy, the conductive contacts of the first mobile device are electrically connected to the docking terminals of the second mobile device through the crimping connection area.

[0047] The collaborative energy management system also has the following functions: Dynamic load reduction in high-load scenarios: In high-pollution and high-frequency mobile scenarios, when the total power exceeds the limit or the temperature rises, the system automatically reduces the fan gear, reduces movement or separation operation to reduce the load concentration, and ensures system safety.

[0048] Energy-path linkage optimization: Evaluate the predicted energy consumption of the current path planning. If it exceeds the limit, increase the "energy cost weight" and re-plan to shorten the ineffective movement and achieve double-loop optimization.

[0049] Emergency protection for abnormal states: When there is a sudden drop in power or communication anomaly, automatically enter the emergency low-power mode and return to the base nearby. In the split state, prioritize ensuring the operation of the high-power main body to enhance the system robustness.

[0050] Historical learning optimization: Long-term record the task energy consumption and load consumption model data, dynamically update the prediction function parameters, and improve the prediction accuracy.

[0051] Short-term energy transfer: In the reorganization state and when the structure supports, if the power difference is too large, start short-term power transfer to balance to the set range to improve the overall utilization rate.

[0052] Tiered operation mode: The system supports multiple modes such as collaborative balancing, high performance, and energy saving priority. Different energy scheduling weights are automatically matched in different modes to meet the needs of multiple scenarios.

[0053] The present invention also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the collaborative energy management method of the dual-body mobile environment processing device.

[0054] The present invention has the following technical effects: 1) Achieve dynamic energy balance of dual-body equipment: Through bidirectional energy sharing control and dynamic power regulation, the power consumption of the two bodies tends to be balanced, significantly extending the overall effective operating time.

[0055] 2) Avoid premature depletion of individual units: By combining task load identification and energy consumption prediction, high-load equipment can be intervened in advance to reduce downtime and improve task completion rate.

[0056] 3) Supports bidirectional energy sharing: It sets up bidirectional DC-DC conversion and current direction control to improve the overall energy utilization rate and avoid power waste.

[0057] 4) Achieve forward-looking energy management: Build an energy consumption prediction model, which has predictive and risk assessment capabilities compared to simple strategies, and improves the level of intelligence.

[0058] 5) Improve safety and reduce maintenance costs: Set multiple safety thresholds and protection mechanisms to reduce the risk of deep discharge and thermal runaway; at the same time, reduce the number of charging cycles to extend battery life.

[0059] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A collaborative energy management method for a dual-body mobile environmental processing device, characterized in that, Includes the following steps: Step 1: Obtain the first battery parameter E1 of the first mobile device and the second battery parameter E2 of the second mobile device, respectively; Step 2: Identify whether the current operating mode of the dual-unit equipment is joint operation mode or separate operation mode; Step 3: Obtain the current task load parameters L1 and L2 of the first mobile device and the second mobile device respectively; Step 4: Based on the power parameters, task load parameters, operating mode and historical power curve, construct a collaborative energy consumption prediction model to calculate the predicted remaining operating time and optimal power ratio of the dual-body equipment; Step 5: Determine whether to trigger the energy balance scheduling strategy based on the predicted remaining running time, the power difference between the two devices, and the safety threshold. In split operation mode: When a single unit has insufficient remaining operating time, another unit will take over part of the task, with the former prioritizing returning to base or operating at reduced power to ensure mission continuity. When the power difference exceeds the threshold, the power allocation ratio between the first and second mobile devices is dynamically adjusted, and the remaining running time prediction values ​​of the two devices are recalculated. When the battery level of any device falls below a preset safety threshold, a reconfiguration or return-to-home control strategy is triggered. Under joint operation mode: When the power replenishment conditions are met, one device supplies power to another device through an electrical connection structure; the power replenishment conditions include: the power of any device is lower than the power replenishment threshold, and the power of the other device is higher than the shared threshold; the power transmission direction is automatically determined based on the power difference between the first mobile device and the second mobile device. When the battery level of any device falls below a preset safety threshold, the split-operation control strategy is triggered.

2. The collaborative energy management method for a dual-body mobile environmental processing device according to claim 1, characterized in that, The collaborative energy consumption prediction model includes the following functional relationships: , where M represents the operating mode parameter.

3. The collaborative energy management method for a dual-body mobile environmental processing device according to claim 1, characterized in that, The power allocation ratio is determined as follows: , ,in, , These are variable weighting coefficients.

4. The collaborative energy management method for a dual-body mobile environmental processing device according to claim 1, characterized in that, The remaining running time prediction is dynamically adjusted based on historical running data.

5. The collaborative energy management method for a dual-body mobile environmental processing device according to claim 1, characterized in that, If the predicted remaining running time is less than the preset task completion time, the reorganization path is planned in advance.

6. The collaborative energy management method for a dual-body mobile environmental processing device according to claim 1, characterized in that, Also includes: In the base-coordinated charging scheduling, the base receives status data, determines the charging target, and controls interface switching, supporting synchronous or sequential charging.

7. A collaborative energy management system for a dual-body mobile environmental processing device, characterized in that, include: A power monitoring module is used to detect the power parameters of the first mobile device and the second mobile device respectively; The pattern recognition module is used to identify the current operating mode; The task load identification module is used to obtain task load parameters; The energy consumption prediction module is used to calculate the predicted value of the remaining running time; The collaborative scheduling module is used to execute energy balance scheduling strategies; The power control module is used to dynamically adjust the output power of the device; The safety control module is used to trigger reassembly, return to home, or prohibit split operation control strategies when the battery level is below the safety threshold.

8. The collaborative energy management system for the dual-body mobile environmental processing device according to claim 7, characterized in that, It also includes an energy sharing control module for controlling bidirectional power transmission in joint operation mode.

9. The collaborative energy management system for the dual-body mobile environmental processing device according to claim 8, characterized in that, The first mobile device and the second mobile device are electrically connected in joint operation mode through a bidirectional DC-DC conversion module; the energy sharing control module realizes bidirectional power transmission by controlling the bidirectional DC-DC conversion module; the energy sharing control module includes a current direction control unit, a voltage matching unit and a protection unit.

10. A storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the collaborative energy management method of the dual-body mobile environment processing device according to any one of claims 1 to 6.

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