A method and system for coordinated energy management of a twin body mobile environment treatment apparatus

Abstract

The application relates to a kind of synergic energy management method and system of twin mobile environment treatment equipment, the method includes respectively obtaining the first electric quantity parameter of first mobile equipment and the second electric quantity parameter of second mobile equipment;Identify the current running mode of twin equipment as joint operation mode or split operation mode;Respectively obtain the current task load parameter of first mobile equipment and second mobile equipment;Synergic energy consumption prediction model is constructed based on the electric quantity parameter, task load parameter, running mode and historical power curve, the remaining running time prediction value of twin equipment and optimal power ratio are calculated;According to the remaining running time prediction value, the electric quantity difference of twin equipment and safety threshold, judge whether to trigger energy balance scheduling strategy.The application effectively solves the problem of unbalanced energy distribution and uncontrollable endurance of twin equipment, realizes the dynamic balance of twin energy, significantly improves the overall endurance, task completion rate and energy utilization efficiency of system.

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: Bidirectional DC-DC conversion and current direction control are provided to improve the overall energy utilization rate and avoid power waste.

[0022] 4) Implement proactive energy management: An energy consumption prediction model is constructed, which has predictive and risk assessment capabilities compared with simple strategies, and improves the intelligence level.

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

[0024] The above description is only an overview of the technical solutions of the present invention. In order to understand the technical means of the present invention more clearly and implement them according to the content of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. Brief Description of the Drawings

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

[0026] The specific embodiments of the present invention are further described in detail below with reference to the accompanying drawings and embodiments. The following embodiments are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0027] Ref 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 that the power level of any device is lower than the energy replenishment threshold, and the power level 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. See Figure 5 as shown in.

[0036] When the power level of any device is lower than the preset safety threshold, the split operation prohibition control strategy is triggered. See Figure 4 as shown in.

[0037] This collaborative energy management method effectively solves the problems of unbalanced energy distribution and uncontrollable endurance of the dual-body device, realizes 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 relationship: , where M denotes the operation mode parameter.

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

[0040] In this embodiment, the predicted remaining operation time 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, the reorganization path is planned in advance.

[0042] In this embodiment, the method further comprises: In the base collaborative charging scheduling, the base receives status data, determines the charging object and controls interface switching, supporting synchronous or sequential charging. For example, the smart base detects the dual-body SOC and temperature; if the SOC difference is large, the low-power body is charged preferentially, if the SOC levels are close, the two bodies are charged synchronously, and if the temperature is high, slow charging is adopted, so as to improve efficiency and protect the battery.

[0043] See Figure 6 , Figure 7 as shown, this embodiment further provides a collaborative energy management system 104 for a dual-body mobile environment processing device, comprising: A power monitoring module 201, configured to respectively detect power parameters of the first mobile device and the second mobile device; A mode recognition module 202, configured to recognize the current operation mode; A task load recognition module 203, configured to acquire task load parameters; The energy consumption prediction module 204 is configured to calculate a predicted remaining operation time value; The collaborative scheduling module 205 is configured to execute an energy balance scheduling strategy; The power control module 206 is configured to dynamically adjust the output power of the device; The safety control module 207 is configured to trigger a control strategy of recombination, return voyage or prohibiting split operation when the electric quantity is lower than a safety threshold.

[0044] The energy sharing control module 208 is configured to control bidirectional electric energy transmission in the joint operation mode.

[0045] Ref Figure 8 As shown, the energy sharing interface 103 includes conductive contacts (positive contact 301, negative contact 302), a signal contact 303, an elastic crimping assembly 304, and an insulation isolation structure 305.

[0046] Ref Figure 9 As shown, the first mobile device and the second mobile device are electrically connected through the bidirectional DC-DC conversion module 403 in the joint operation mode; the energy sharing control module realizes bidirectional electric energy 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. During energy replenishment, the conductive contact of the first mobile device is electrically connected to the docking terminal of the second mobile device through the crimping connection area.

[0047] This 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 performs split operation to reduce load concentration, so as to ensure system safety.

[0048] Energy-path linkage optimization: Evaluate the estimated energy consumption of the current path planning. If the energy consumption exceeds the limit, add an "energy cost weight" for re-planning to reduce invalid movement and realize double closed-loop optimization.

[0049] Emergency protection for abnormal states: When a sudden drop in electric quantity or communication abnormality occurs, the system automatically enters the emergency low-power mode and returns to the nearby home point. In the split state, the operation of the main body with higher electric quantity is preferentially guaranteed, so as to improve the system robustness.

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

[0051] Short-term energy transfer: When in the recombination state and the structure supports, if the electric quantity difference is too large, start short-term electric energy transfer to balance the electric quantity to the set range, so as 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. A collaborative energy management system for a dual-body mobile environmental processing device, used to execute the method of claim 1, 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.

7. The collaborative energy management system for the dual-body mobile environmental processing device according to claim 6, characterized in that, It also includes an energy sharing control module for controlling bidirectional power transmission in joint operation mode.

8. The collaborative energy management system for the dual-body mobile environmental processing device according to claim 7, 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.

9. 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 5.

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