Forked mobile robot power distribution method with omnidirectional state-awareness warning

Abstract

This invention discloses a power distribution method for a forklift mobile robot with integrated multi-dimensional state perception and early warning, belonging to the field of power distribution technology. It collects continuous temperature trajectory values, continuous current trajectory values, and corresponding time scale information of the forklift mobile robot during heavy-load operation, forming a continuous change sequence. Within this sequence, it identifies segments where the temperature continuously rises and continues to operate below a preset temperature threshold, marking these segments as advancement intervals. This invention achieves early identification of the continuous temperature rise process by constructing a continuous change sequence and an extended heat accumulation criterion, thereby detecting potential thermal risks before the threshold is reached. Furthermore, it dynamically adjusts power release through forward control and progressive convergence control, restoring power intensity in an orderly manner during periods of slowing temperature change, thus balancing operational efficiency and safety stability.

Description

Technical Field

[0001] This invention relates to the field of power distribution technology, and more specifically to a power distribution method for a fork-type mobile robot that integrates full-dimensional state perception and early warning. Background Technology

[0002] Forklift mobile robots are automated material handling equipment that integrates a forklift mechanism onto a mobile robot chassis. They can lift, move, and precisely place pallets in warehousing or production line environments. Their operation relies on battery power and is characterized by high-frequency start-stop and parallel operation of multiple actuators. Power distribution for forklift mobile robots involves dividing and controlling the battery input according to the voltage level and power requirements of different loads within the vehicle's power distribution unit. This includes implementing power path regulation and on / off control for the drive system, controller, sensors, and actuators, thus forming a multi-circuit collaborative power supply system. Power distribution with comprehensive status perception and early warning simultaneously collects operating parameters such as voltage, current, and temperature during the above distribution process. Through real-time monitoring and threshold judgment, the operating status of each power supply circuit is dynamically identified. Before or at the initial stage of abnormalities such as overcurrent, short circuit, or overtemperature, it triggers early disconnection or current limiting regulation. Combined with the onboard control unit and cloud platform, it achieves status reporting and remote response, thus completing an integrated control process of risk warning and safety protection while distributing power.

[0003] The existing technology has the following shortcomings: When a forklift robot operates under heavy load continuously, its temperature will show a continuous and slow upward trend. Because the temperature rise is relatively gradual, it is difficult to cross the preset threshold boundary within a considerable period. The system will maintain the current power distribution state without timely intervention. During this continuous operation, heat will gradually accumulate in local power supply paths, forming a hidden heating zone. This zone is difficult to effectively identify using fixed threshold judgment methods, easily leading to delayed risk assessment. As heat continues to accumulate and gradually approaches the material's tolerance critical point, the local insulation performance will rapidly decline, triggering insulation breakdown in a short time. This causes the corresponding power supply path to fail, further inducing overall power distribution abnormalities, ultimately resulting in irreversible damage.

[0004] For example: A forklift mobile robot operates on a rated 48V battery system. Under heavy-load handling conditions, the drive motor continuously draws approximately 85A. Since the equivalent resistance of the power supply path, including the power distribution busbar and connection terminals, is 3mΩ, the corresponding heat dissipation power is approximately P=I. 2 R=85 2×0.003≈21.7W. This heat continues to accumulate in the enclosed electrical compartment. If the heat dissipation conditions are not good, the temperature may rise slowly at a rate of 0.3°C per minute, from 40°C to 76°C within 2 hours.

[0005] Because the system's over-temperature protection threshold was set at 85℃, the protection mechanism was not triggered during prolonged operation. However, the actual hot spot temperature of the local connection terminals may have approached the insulation material's tolerance threshold of 80℃, significantly accelerating insulation aging. When the current surged to 110A during a heavy-load start-up, the local temperature rapidly exceeded the tolerance limit, leading to insulation breakdown and ultimately a short circuit failure in the power supply circuit. This process involved gradual heat accumulation rather than instantaneous overload, making it difficult for traditional fixed-threshold protection mechanisms to identify and intervene in a timely manner.

[0006] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this invention is to provide a power distribution method for fork-type mobile robots that integrates full-dimensional state perception and early warning. By constructing a continuously changing sequence and an extended heat accumulation criterion, it can identify the process of continuous temperature rise in advance, thereby discovering potential thermal risks before the threshold is reached. Furthermore, by dynamically adjusting power release through forward regulation and progressive convergence control, it can orderly restore power supply intensity when the temperature change slows down by combining trend judgment, thereby balancing operational efficiency and safety stability, and solving the problems in the aforementioned background technology.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a power distribution method for a fork-type mobile robot with integrated multi-dimensional state perception and early warning, comprising the following steps: The temperature trajectory value, current trajectory value, and corresponding time scale information of the forklift mobile robot are collected during the heavy-load operation phase to form a continuous change sequence. In the continuous change sequence, the section where the temperature rises continuously and continues to operate below the preset temperature threshold is identified and marked as the propulsion section. The temperature increment and corresponding duration per unit time are extracted around the propulsion interval. The temperature increment and duration are continuously superimposed in one direction with the starting time scale information of the propulsion interval as zero point. An extended heat accumulation criterion without using a sliding time window is constructed. The propulsion interval is segmented according to the continuous expansion trend of the extended heat accumulation criterion on the time scale information to determine the implicit heating section. Based on the implicit heating section, the current power distribution rhythm is adjusted forward. Within the implicit heating section, the output amplitude is gradually reduced and the high power duration is shortened. The voltage drop action is triggered only when the extended heat accumulation criterion shows a continuous increasing trend and the temperature change slope is positive. Under the operating conditions of voltage drop output amplitude and shortened high power duration, the temperature change slope is continuously acquired, and the temperature change slope is coupled with the extended heat accumulation criterion for judgment. When the temperature change slope is still on an upward trend and the extended heat accumulation criterion has not entered the convergence zone, the convergence power release rhythm is further advanced. The dynamic intervention range is defined by combining the power release rhythm after convergence. When the slope of temperature change enters the flat section and the extended heat accumulation criterion enters the decline section, the power supply distribution intensity is gradually restored according to the change amplitude of the extended heat accumulation criterion. During the restoration process, the implicit temperature rise section is monitored in advance based on the heat accumulation trend predicted in the section on the future time scale. When the expansion risk is predicted, the restoration action is suspended.

[0009] Preferably, the propulsion interval is identified, and the specific steps are as follows: The temperature, current and time scale information of the forklift mobile robot during heavy-load operation are obtained to form a raw data set. Based on the original dataset, temperature and current values ​​are bound together to form data units, and a continuous change sequence is constructed. By using a continuous change sequence to select continuous acquisition points, temperature values ​​are compared point by point, and combined with current values ​​within the heavy load operating range to form an effective segment. Based on the time scale information recorded in the effective segment, the advancement interval is marked to form an advancement interval. The range of the advancement interval is extended by combining the newly added data to achieve advancement interval identification.

[0010] Preferably, the implicit heating zone is determined, and the specific steps are as follows: Extract the temperature value changes of adjacent time scales within the propulsion interval to form the temperature increment per unit time, and record the corresponding duration. The temperature increment and duration are reset to zero according to the starting time scale of the advancement interval, and then continuously superimposed in one direction to form a temperature accumulation sequence and a cumulative duration sequence. The temperature accumulation sequence and the cumulative duration sequence are combined to form an extended heat accumulation criterion, and the cumulative change trend is continuously analyzed along the time scale. The propulsion interval is divided into several sub-segments based on the continuity of temperature cumulative change, and the start and end time scales and corresponding cumulative values ​​of each sub-segment are recorded. The sub-segments are selected from those that show a continuous increase in temperature accumulation without exceeding a preset threshold and marked to form hidden temperature rise segments.

[0011] Preferably, in the step of forming the extended heat accumulation criterion, the temperature increment of each unit time slice is accumulated one by one in chronological order and the corresponding cumulative duration is recorded to ensure that each time scale position obtains a temperature accumulation value that continuously increases from zero point, thereby completely recording the continuous process of temperature gradually changing with time within the advancement interval.

[0012] Preferably, the current power supply distribution rhythm is adjusted forward, and the specific steps are as follows: Based on the implicit heating segment, the corresponding time scale information is read, the temperature value is extracted and compared with the cumulative temperature value point by point to determine the direction of temperature change and the cumulative temperature increase relationship, thus forming the trigger segment; By utilizing the start time scale information of the trigger segment, the output amplitude is gradually decreased and the high power duration is shortened, forming a continuous control sequence in combination with the trigger segment; By continuously comparing newly added temperature values ​​with accumulated temperature values ​​read around the continuous control sequence, the trigger segment can be extended or the continuous control sequence state can be maintained, thereby realizing the forward control of power distribution rhythm.

[0013] Preferably, the triggering segment is determined by the time range within which the temperature change direction continues to rise and the cumulative temperature value continues to increase within a continuous time scale.

[0014] The preferred method is to progressively converge to a higher power release rhythm, with the following specific steps: Collect temperature values ​​at the corresponding time scale information of the operating status, and compare them point by point to form a temperature change slope sequence; By combining the temperature change slope sequence to read the cumulative temperature value and the cumulative duration, a corresponding relationship is formed to determine the time segment for coupling judgment; Based on the coupling judgment time segment, the output amplitude is continuously reduced and the high power duration is continuously compressed, forming a progressive convergence power release rhythm. By combining the newly added temperature change slope with the extended temperature cumulative value to determine the time segment, or by maintaining the current power release rhythm, the progressive convergence control of the power release rhythm can be achieved.

[0015] Preferably, during the formation of the temperature change slope sequence, the temperature values ​​at adjacent time scales are compared point by point for marking, and the temperature change slope is bound to the corresponding time scale information for recording, so as to maintain the continuity of the temperature change trend.

[0016] Preferably, the dynamic intervention interval is defined based on the power release rhythm after convergence. The specific steps are as follows: The system acquires time scale information corresponding to output amplitude, high power duration, temperature value and temperature accumulation value, forms operating status data in time sequence, selects analysis sections to determine the slope of temperature change to enter the flat section and the extended heat accumulation criterion to enter the fall section, and determines the dynamic intervention range. Based on the starting time scale of the dynamic intervention interval, the power distribution intensity is restored, the output amplitude and high power duration are adjusted, and the recovery rhythm is formed by combining the temperature accumulation value change amplitude. Continue the recovery rhythm by selecting future time scale prediction segments, associate the temperature change slope sequence and the temperature cumulative value change trajectory, generate the predicted temperature change slope and the predicted temperature cumulative value, and mark the extended risk segment. Combined with the power distribution intensity restoration control of the extended risk section, the restoration action is paused or started to complete the dynamic intervention interval delineated after the power release rhythm is converged.

[0017] Preferably, in the process of selecting future time scale prediction segments to continue the recovery rhythm, the temperature change slope corresponding to each time scale is continuously correlated with the temperature cumulative value change trajectory. The segments where the predicted temperature change slope remains positive and the predicted temperature cumulative value continues to increase are marked as extended risk segments for use in pausing or starting control of the recovery action.

[0018] The technical effects and advantages provided by the present invention in the above technical solution are as follows: Beneficial Effect 1: This invention, by constructing a continuous change sequence and introducing an extended heat accumulation criterion, transforms the temperature change process from a single threshold judgment to a continuous accumulation identification based on the time dimension. This allows the continuous temperature rise process before reaching a preset threshold to be detected in advance, thereby achieving accurate identification of hidden heating sections. Through continuous superposition of temperature increments and durations, the dynamic process of gradual heat accumulation can be fully reflected, enabling potential thermal risks in the power supply path to be captured at an early stage. This effectively avoids the problem of insulation performance degradation caused by long-term temperature accumulation, giving the power distribution process a forward-looking perception capability and improving overall operational safety.

[0019] Benefit 2: This invention implements forward control of power distribution rhythm within the implicit heating zone, and combines temperature change slope and heat accumulation trend for progressive convergence control. This allows the power release process to dynamically adjust with temperature changes, gradually reducing output intensity while the temperature is still rising, thereby suppressing further heat accumulation. Simultaneously, a dynamic recovery adjustment mechanism is introduced during the temperature slowdown phase, and the recovery process is constrained by future time-scale trend judgments. This ensures the controllability and continuity of power supply intensity recovery, thereby preventing repeated thermal risks while maintaining operational efficiency and improving the stability and reliability of the vehicle's power distribution. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0021] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0022] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0023] This invention provides, for example Figure 1 The power distribution method for a forklift mobile robot with integrated full-dimensional state perception and early warning, as shown, includes the following steps: The temperature trajectory value, current trajectory value, and corresponding time scale information of the forklift mobile robot are collected during the heavy-load operation phase to form a continuous change sequence. In the continuous change sequence, the section where the temperature rises continuously and continues to operate below the preset temperature threshold is identified and marked as the propulsion section. In a continuously changing sequence, identify the segments where the temperature rises continuously and remains below a preset temperature threshold, and mark them as advancement intervals. The specific steps are as follows: After the forklift mobile robot enters the heavy-load operation phase, the operation process is continuously recorded according to a pre-set time sampling interval, for example, with a sampling cycle of 0.5 seconds. In each sampling cycle, the temperature and current values ​​corresponding to that moment are acquired simultaneously, and a unique time scale identifier is assigned to this set of data. The time scale identifier is recorded incrementally starting from the start of the heavy-load operation. Specifically, the time scale corresponding to the first sampling point is 0.5 seconds, the time scale corresponding to the second sampling point is 1.0 seconds, and so on, continuously increasing. This sampling process is continuously executed throughout the entire heavy-load operation phase. The temperature, current, and time scale information obtained in each sampling cycle are written into the storage sequence one by one in chronological order, so that the temperature and current values ​​correspond point by point in the time dimension and the sampling interval remains consistent, thereby forming a raw data set covering the entire heavy-load operation phase. The temperature value is reflected as a continuous trajectory that changes gradually over time, the current value is reflected as the continuous output state under the driving load, and the time scale information is reflected as the sequential relationship between each data point.

[0024] It should be noted that: During operation, the system comprehensively judges the multi-dimensional operating parameters of the forklift mobile robot to identify whether it has entered the heavy-load operation stage. Specifically, it continuously collects the driving current value, the change of travel speed, and the load execution status. When the driving current is stably maintained at more than 70% of the rated operating current in multiple consecutive sampling cycles, the travel speed decreases compared to the no-load operation state and remains in the set low speed range, and the forklift mechanism is in the lifting or carrying pallet state and continuously outputs power, it is determined that the forklift mobile robot has entered the heavy-load operation stage.

[0025] The above judgment process is based on time continuity. The heavy load operation stage indicator is triggered only when the above conditions are met simultaneously within the preset duration. This avoids misjudgment caused by instantaneous load changes or short-term current fluctuations, and enables the identification results to accurately reflect the actual operating state of the forklift mobile robot under continuous load and outputting large power.

[0026] After continuous data acquisition, the raw data set is organized according to the time scale information. The temperature and current values ​​corresponding to each time scale are bound into a unified data unit and arranged in ascending order of time scale to form a continuous change sequence.

[0027] In this continuously changing sequence, each nth data unit contains clear time scale information, the corresponding temperature value, and the corresponding current value, and the time interval between adjacent data units remains at a fixed sampling period, so that the entire sequence is uniformly distributed in the time dimension.

[0028] Furthermore, the original numerical differences between adjacent data units are preserved during the arrangement process, so that the continuous change sequence can fully reflect the gradual change of temperature over time and the continuous output of current during heavy-load operation. At the same time, it ensures that data within any continuous time period can be directly extracted for subsequent segment identification processing.

[0029] After forming a continuous change sequence, the temperature values ​​are analyzed and processed segment by segment along the time scale. Starting from the beginning of the continuous change sequence, at least 5 consecutive sampling points are selected to form an initial judgment interval. The temperature value changes between adjacent sampling points in the interval are compared in turn. When the temperature value of the next sampling point is greater than the temperature value of the previous sampling point, the interval is identified as a candidate interval for the continuous temperature rise segment.

[0030] Then, based on the candidate interval, the time scale is extended backward to include subsequent collection points one by one. During each extension, it is simultaneously determined whether the temperature value of the newly added collection point continues to be greater than the temperature value of the previous collection point. At the same time, the temperature values ​​of all collection points in the interval are compared with the preset temperature threshold point by point. When the temperature value of any collection point in the interval reaches or exceeds the preset temperature threshold, the extension is stopped and the parts that do not meet the conditions are removed.

[0031] During the entire interval identification process, it is simultaneously checked whether the corresponding current value within that time range is continuously within the heavy load operating range, for example, maintained above 70% of the rated current, in order to eliminate short-term temperature changes caused by load fluctuations, thereby obtaining an effective segment that satisfies both continuous temperature rise and always remains below the preset temperature threshold, while the corresponding current remains within the heavy load range.

[0032] After obtaining the above effective segments, the start and end time scales of the segments in the continuous change sequence are recorded, and the temperature, current and time scale information of all the collection points in the segments are extracted as a whole. The segments are then marked and defined as the advance interval.

[0033] During the marking process, a unique identifier is assigned to the advancement interval and associated with its position in the continuous change sequence, enabling the advancement interval to be directly located during subsequent operation. Subsequently, as the forklift mobile robot continues to run, new temperature values, current values, and time scale information are continuously acquired according to the same sampling period, and the new data is appended to the end of the continuous change sequence. At the same time, it is determined whether the newly added data is consistent with the end data of the marked advancement interval in terms of temperature change trend. If it meets the condition of continuous increase and has not reached the preset temperature threshold, the end time scale of the advancement interval is extended backward, and the newly added data is included in the scope of the advancement interval. This achieves continuous recording of the slow temperature rise process, so that the advancement interval fully covers the entire process of gradual temperature accumulation.

[0034] The temperature increment and corresponding duration per unit time are extracted around the propulsion interval. The temperature increment and duration are continuously superimposed in one direction with the starting time scale information of the propulsion interval as zero point. An extended heat accumulation criterion without using a sliding time window is constructed. Based on the continuous expansion trend of the extended heat accumulation criterion on the time scale information, the propulsion interval is segmented to determine the implicit heating section.

[0035] Based on the continuous expansion trend of the extended heat accumulation criterion on the time scale information, the advancement interval is segmented to determine the implicit heating section. The specific steps are as follows: After the advance interval has been clearly marked, the temperature changes between adjacent time points are extracted one by one, following the time scale information corresponding to each collection point within the advance interval. For example, between 0 seconds and 0.5 seconds, the change is recorded by subtracting the temperature at 0 seconds from the temperature at 0.5 seconds, and this change is taken as the temperature increment per unit time. Simultaneously, the duration between 0 seconds and 0.5 seconds is recorded as the duration corresponding to this temperature increment. This process is then repeated for the interval from 0.5 seconds to 1 second. Temperature changes between 0.0 seconds and 1.0 to 1.5 seconds are processed in the same way, and this process is repeated until the end of the time interval. This ensures that each adjacent time interval corresponds to a specific temperature increment and a defined duration. These data are then arranged in ascending order of the time scale to form a complete sequence of temperature increments and durations. Each data unit corresponds to a specific time range. For example, the first data unit corresponds to the interval between 0 and 0.5 seconds, the second data unit corresponds to the interval between 0 and 1.0 seconds, and so on.

[0036] After obtaining the temperature increment sequence and duration sequence, the starting time scale information of the advancement interval is uniformly reset to zero. Using this zero point as the time reference benchmark, all time scales within the advancement interval are recalibrated. For example, for an advancement interval with an original time scale of 120 seconds to 180 seconds, after resetting, 120 seconds will correspond to 0 seconds, 120.5 seconds to 0.5 seconds, 121 seconds to 1.0 seconds, and so on until the end time scale of the advancement interval.

[0037] After resetting the time scale, the temperature increment corresponding to each unit time slice is accumulated one by one according to the new time order. Starting from zero, the temperature increment of the first unit time slice is recorded as the initial accumulated value. Then, the temperature increment of the second unit time slice is superimposed on the initial accumulated value to obtain the accumulated temperature value corresponding to the second time scale. The temperature increment of the third unit time slice is then superimposed on the accumulated temperature value of the previous moment. This process continues until the end of the advance interval, so that each time scale corresponds to a temperature accumulated value that continuously increases from zero.

[0038] At the same time, the duration of each unit time slice is gradually accumulated in the same order. For example, the first time scale corresponds to a cumulative duration of 0.5 seconds, the second time scale corresponds to a cumulative duration of 1.0 seconds, and the third time scale corresponds to a cumulative duration of 1.5 seconds, thus forming a cumulative duration sequence that corresponds one-to-one with the cumulative temperature value.

[0039] After the synchronous construction of the accumulated temperature value and the accumulated duration is completed, the two are combined to form a continuous corresponding data relationship. This data relationship serves as the specific manifestation of the extended heat accumulation criterion. At any given time scale position, a clear accumulated temperature value and corresponding accumulated duration can be obtained. The accumulated temperature value always increases continuously based on the previous moment and will not be recalculated after any fixed time range ends. This ensures that the temperature accumulation process remains continuously recorded throughout the entire advancement interval. Within the entire advancement interval, a continuously increasing temperature accumulation trajectory is formed from the zero point to the end time scale. This trajectory has a unique correspondence with the corresponding accumulated duration at each time scale position, allowing the temperature accumulation process over time to be fully presented and avoiding data truncation under fixed time length division conditions.

[0040] After forming the extended heat accumulation criterion, the changes in the accumulated temperature value are analyzed step by step from zero along the time scale information. The continuous time scale is divided into several continuous segments. For example, the first analysis segment is from 0 seconds to 5 seconds, and the second analysis segment is from 5 seconds to 10 seconds. During the division process, the changes in the accumulated temperature value between adjacent time scales in each segment are compared one by one. When the accumulated temperature value continues to increase in a certain time period and the incremental changes between adjacent time scales show a continuous relationship, the time period is classified into the same continuous segment.

[0041] When the temperature cumulative value changes between adjacent time scales at a certain time scale position, that time scale is used as a segment division point to separate the preceding and following time ranges, thereby forming multiple sub-segments arranged in chronological order within the entire advancement interval. Each sub-segment contains a clear start time scale, end time scale, corresponding temperature cumulative value change trajectory, and cumulative duration change trajectory.

[0042] After completing the above segmentation, each sub-segment is screened one by one. Sub-segments in which the cumulative temperature value increases continuously over a long period of time and the temperature value at each time scale in the entire segment does not reach the preset temperature threshold are extracted and defined as hidden temperature rise segments.

[0043] During the determination process, the start and end time scales of each implicit heating segment are recorded, and all temperature increment data, cumulative temperature values, and cumulative duration data within the segment are retained. This ensures that the implicit heating segment can fully reflect the entire process of temperature accumulation under the condition that the preset temperature threshold is not reached, and the segment is marked in the continuous change sequence, thereby completing the specific determination and recording of the implicit heating segment.

[0044] Based on the implicit heating section, the current power distribution rhythm is adjusted forward. Within the implicit heating section, the output amplitude is gradually reduced and the high power duration is shortened. The voltage drop action is triggered only when the extended heat accumulation criterion shows a continuous increasing trend and the temperature change slope is positive. Within the implicit heating range, the output amplitude is gradually reduced and the duration of high power is shortened. The specific steps are as follows: After the implicit heating segment has been marked and has clear start and end time scales, starting from the start time scale of the implicit heating segment, the corresponding original temperature value, cumulative temperature value, and cumulative duration are read point by point according to the time scale information. A point-by-point comparison is performed between each adjacent time scale. For example, between the time scale of 0 seconds and 0.5 seconds, the temperature values ​​corresponding to 0 seconds and 0.5 seconds are read and compared. If the temperature value corresponding to 0.5 seconds is higher than the temperature value corresponding to 0 seconds, the temperature change direction for this time period is recorded as upward. Then, the same processing is performed on the temperature values ​​between 0.5 seconds and 1.0 seconds, and between 1.0 seconds and 1.5 seconds, so that each time slice in the entire implicit heating segment has a clear temperature change direction mark.

[0045] While marking the direction of temperature change, the cumulative temperature values ​​corresponding to each time scale are continuously compared. For example, the cumulative temperature value corresponding to 0.5 seconds is compared with the cumulative temperature value corresponding to 0 seconds. If the latter is greater than the former, the time point is recorded as meeting the cumulative increase condition, and the same process is continued for subsequent time scales. This forms a continuous time range within the entire implicit heating zone that simultaneously satisfies the continuous upward direction of temperature change and the gradual increase of the cumulative temperature value. The start and end time scales of this continuous time range are recorded, making this time range the trigger segment for subsequent power distribution rhythm advance control.

[0046] After the triggering zone is determined, the starting time scale of the triggering zone is used as the starting point for adjustment. The output amplitude and high power duration in the current power distribution rhythm are adjusted synchronously. In the specific execution process, the output amplitude is gradually reduced according to a fixed time scale. For example, at the starting time scale position of the triggering zone, the output amplitude is adjusted from the original operating value to 95%, at the next time scale position to 90%, and then at the next time scale position to 85%, and continues to decrease at the same time interval until the preset minimum output amplitude value is reached.

[0047] Meanwhile, the duration of high power is gradually shortened within the triggering zone. For example, at the beginning of the triggering zone, the high power output, which was originally maintained for 10 seconds, is adjusted to 8 seconds. At subsequent time points, it is adjusted to 6 seconds and 4 seconds, and then continues to decrease according to the same time scale as the time progresses, so that the duration of high power is continuously shortened throughout the entire triggering zone. During the above adjustment process, the reduction of output amplitude and the shortening of high power duration are synchronized with the time scale information, so that the power supply distribution rhythm forms a continuous adjustment trajectory in the time dimension, and the temperature accumulation process is intervened in advance in the implicit heating zone.

[0048] After the power supply distribution rhythm has been adjusted and continuously executed, the system continues to collect new temperature values, cumulative temperature values, and cumulative duration along the time scale. The new data is then sequentially connected with the existing data in the trigger segment. At each new time scale position, the system repeatedly performs the temperature change direction judgment and temperature cumulative value comparison processing. When the temperature change direction is still upward and the temperature cumulative value increases point by point in multiple consecutive time scales, the output amplitude continues to decrease according to the predetermined step size, and the high power duration continues to shorten according to the predetermined time scale. At the same time, the control range is extended backward along the time scale.

[0049] When the temperature value at a certain time scale position is the same as or lower than the previous time scale position, or when the cumulative temperature value does not continue to increase between adjacent time scale positions, the output amplitude will stop decreasing further at that time scale position, and the current output amplitude and high power duration will remain unchanged, so that the power supply distribution rhythm enters a stable state. This ensures that the entire forward control process is always consistent with the temperature change trend within the implicit heating section, and completes the entire process of forward control of the power supply distribution rhythm based on the implicit heating section.

[0050] Under the operating conditions of voltage drop output amplitude and shortened high power duration, the temperature change slope is continuously acquired, and the temperature change slope is coupled with the extended heat accumulation criterion for judgment. When the temperature change slope is still on an upward trend and the extended heat accumulation criterion has not entered the convergence zone, the convergence power release rhythm is further advanced. When the temperature change slope is still trending upwards and the extended heat accumulation criterion has not yet entered the convergence zone, the convergence power release rhythm is further accelerated. The specific steps are as follows: After the current operating state has seen a gradual decrease in output amplitude and a shortening of high-power duration according to the time scale, new temperature values ​​are continuously collected along the time scale. Each adjacent time scale is processed point-by-point, comparing the temperature value of the next time scale with that of the previous time scale. When the temperature value of the next time scale is greater than that of the previous time scale, the temperature change slope corresponding to that time period is marked as positive, and this marking result is bound and recorded with the corresponding time scale information. Throughout the entire operation, this process is performed on all consecutive time scales, ensuring that each time slice has a clear temperature change slope identifier. A continuous sequence of temperature change slopes is formed according to the time scale order. Simultaneously, this temperature change slope sequence is synchronously recorded with the currently executed output amplitude voltage drop state and high-power duration shortening state, establishing a correspondence between the temperature change trend and the power supply distribution rhythm in the time dimension.

[0051] After constructing the temperature change slope sequence, the cumulative temperature value and cumulative duration are read point by point along the time scale information. The temperature change slope is then associated point by point with the cumulative temperature value in the extended heat accumulation criterion, so that each time scale position forms a correspondence composed of the temperature change slope, the cumulative temperature value, and the cumulative duration.

[0052] Subsequently, the correspondence is continuously analyzed according to the time scale. Within multiple consecutive time scales, when the temperature change slope remains positive and the cumulative temperature value continues to increase between adjacent time scales, this continuous time range is recorded as the time segment that meets the coupling judgment condition. Within this time segment, the change of the cumulative temperature value with the cumulative duration is observed. When the cumulative temperature value continues to increase during the time progression and does not remain unchanged between consecutive time scales, this time segment is identified as the extended heat accumulation criterion not entering the convergence segment, thus completing the coupling judgment process of the temperature change slope and the extended heat accumulation criterion.

[0053] After the aforementioned coupling judgment segment is determined, the starting time scale of this time segment is used as the new control starting point. Based on the output amplitude voltage drop state and the high power duration shortening state that have already been executed, the power release rhythm is further progressively converged. Specifically, the output amplitude is adjusted point by point along the time scale information, so that the output amplitude decreases continuously with a denser time scale on the basis of the original gradual decrease. For example, an amplitude reduction operation is performed between adjacent time scales, and the output amplitude after each reduction and the corresponding time scale are recorded, so that the output amplitude forms a change sequence of continuous decrease with the progress of time.

[0054] Meanwhile, regarding the duration of high power, the already shortened duration is further compressed in subsequent time scales, so that the high power duration corresponding to each time scale is less than the duration corresponding to the previous time scale. This duration change is then bound and recorded point by point with the time scale, so that the high power duration forms a change sequence that gradually decreases over time, thereby making the power release rhythm continuously tighten in the time dimension.

[0055] After completing the adjustment of the progressive convergence power release rhythm, the subsequent operation process continues to be recorded along the time scale information. The temperature change slope, cumulative temperature value, and cumulative duration corresponding to the new time scale are sequentially connected with the existing data. At each new time scale position, the temperature change slope judgment and cumulative temperature value change analysis are repeated. When the temperature change slope remains positive and the cumulative temperature value continues to increase on the basis of the previous time scale in subsequent consecutive time scales, the progressive convergence power release rhythm is maintained and the adjustment process is continuously extended along the time scale direction.

[0056] When the slope of temperature change is no longer positive at a certain time scale position, or when the cumulative temperature value remains unchanged between adjacent time scale positions, the further reduction of output amplitude and compression of high power duration operation will stop at that time scale position, and the current power release rhythm will remain unchanged. This ensures that the entire control process remains consistent with the temperature change trend and the extended heat accumulation criterion throughout the time progression, thereby completing the full-process control of the progressive convergence power release rhythm.

[0057] The dynamic intervention range is defined by combining the power release rhythm after convergence. When the slope of temperature change enters the flat section and the extended heat accumulation criterion enters the falling section, the power supply distribution intensity is gradually restored according to the change amplitude of the extended heat accumulation criterion. During the restoration process, the implicit temperature rise section is monitored in advance based on the predicted heat accumulation trend in the section on the future time scale. When the predicted expansion risk exists, the restoration action is suspended. The dynamic intervention interval is determined based on the power release rhythm after convergence. The specific steps are as follows: With the progressive convergence power release rhythm already stably executed, the output amplitude, high power duration, temperature value, and cumulative temperature value corresponding to each time scale are continuously recorded along the time scale information, and organized point by point in chronological order so that each time scale corresponds to complete operating status data. Then, starting from the current time scale, at least ten consecutive time scales are selected as the analysis segment. Within the analysis segment, the temperature value difference between adjacent time scales is compared point by point. The temperature value of the previous time scale is subtracted from the temperature value of the later time scale, and the change of the difference between consecutive time scales is recorded. When the difference is always positive and gradually decreases within multiple consecutive time scales, and the change amplitude remains consistent between at least three consecutive time scales, the continuous time range is marked as the temperature change slope entering the flat segment.

[0058] Within the same analysis segment, the cumulative temperature values ​​are compared point by point. When the cumulative temperature value continues to increase within a continuous time scale, but the increase between adjacent time scales gradually decreases, and the cumulative temperature value corresponding to the current time scale is less than the cumulative temperature value corresponding to the previous time scale in at least two subsequent time scales, this time range is marked as an extended heat accumulation criterion and enters the decline segment. The time range that simultaneously meets the above two conditions is determined as the dynamic intervention interval. At the same time, the start and end time scales of the dynamic intervention interval are recorded, so that the subsequent control process has clear time boundaries.

[0059] To fully understand how this process is implemented, the following examples will further illustrate the details: Assume that in 11 consecutive sampling points from time scale t0 to t10, the temperature values ​​are 60℃, 62℃, 63.5℃, 64.5℃, 65.2℃, 65.7℃, 66.1℃, 66.4℃, 66.6℃, 66.7℃, and 66.75℃, respectively. The corresponding adjacent differences are 2℃, 1.5℃, 1.0℃, 0.7℃, 0.5℃, 0.4℃, 0.3℃, 0.2℃, 0.1℃, and 0.05℃, all of which are positive and gradually decrease. Furthermore, from t6 to t8, the differences remain between 0.3℃ and 0.2℃, exhibiting a consistent range of variation. The temperature change slope can be determined to be flattened from t0 to t10. The corresponding cumulative temperature values ​​are 0, 2, 3.5, 4.5, 5.2, 5.7, 6.1, 6.4, 6.6, 6.65, and 6.63. The cumulative temperature increases continuously from t0 to t8, but the increment gradually decreases from 2 to 0.2. At t9 and t10, the cumulative temperature drops from 6.65 to 6.63, which meets the criteria for the extended heat accumulation to enter the decline zone. Therefore, the entire period from t0 to t10 is defined as the dynamic intervention interval, with t0 as the starting time scale and t10 as the ending time scale.

[0060] After the starting time scale of the dynamic intervention interval is determined, the power distribution intensity recovery process is executed from that time scale. During the recovery process, the output amplitude and high power duration are adjusted point by point along the time scale information, so that the output amplitude increases by a fixed percentage compared to the previous time scale at each time scale, and the high power duration is extended by a fixed duration compared to the previous time scale at each time scale. At the same time, the change in the cumulative temperature value corresponding to each time scale is used as the basis for adjusting the recovery rhythm. When the decrease in the cumulative temperature value corresponding to a certain time scale compared to the previous time scale reaches the maximum value within three consecutive time scales, the output amplitude is increased by a fixed percentage at that time scale position, and the high power duration is extended by a fixed duration simultaneously.

[0061] When the decrease in the cumulative temperature value corresponding to a certain time scale compared to the previous time scale is the minimum among three consecutive time scales, the increase in output amplitude and the extension of high power duration remain unchanged at that time scale position. This ensures that the power distribution intensity recovery process corresponds to the change in the amplitude of the extended heat accumulation criterion, thereby making the recovery rhythm gradually advance over time.

[0062] During the power distribution intensity restoration process, at least five consecutive time scales are selected forward from the current time scale as the future time scale prediction segment. Within this prediction segment, based on the temperature change slope sequence and temperature cumulative value change trajectory already recorded before the current time scale, the temperature change slope and temperature cumulative value corresponding to each time scale in the prediction segment are continuously extended and recorded, so that each time scale in the prediction segment corresponds to a predicted temperature change slope and a predicted temperature cumulative value.

[0063] Within the prediction segment, the slope of the predicted temperature change between adjacent time scales is compared point by point. When the slope of the predicted temperature change is positive for three or more consecutive time scales and the corresponding cumulative value of the predicted temperature shows an increasing relationship between adjacent time scales, the prediction segment is marked as a segment with a risk of expansion. The marking result is then bound and recorded with the time scale of the current recovery process, so that the recovery process and the prediction result have a corresponding relationship in the time dimension.

[0064] After the predicted segment marking is completed, the marking results within the predicted segment are synchronously associated with the current recovery process. When the predicted segment corresponding to the current time scale is marked as having an expansion risk, the output amplitude is immediately stopped from increasing further at that time scale position, and the high power duration is stopped from being extended further, so that the current power supply distribution intensity remains unchanged at the state corresponding to that time scale. At the same time, the subsequent operating status continues to be recorded along the time scale information.

[0065] When the predicted temperature change slope of multiple consecutive time scales no longer shows a positive value and the cumulative predicted temperature value no longer shows an increasing relationship in the predicted segment reselected in the subsequent time scale, the process of gradually increasing the output amplitude and gradually extending the high power duration is restarted from that time scale position, so that the power supply distribution intensity continues to recover in the subsequent time scale, thereby completing the whole process of defining the dynamic intervention interval and performing forward monitoring and recovery control in combination with the converged power release rhythm.

[0066] By constructing a continuous change sequence and introducing an extended heat accumulation criterion, the temperature change process is transformed from a single threshold judgment to a continuous accumulation identification based on the time dimension. This allows the continuous rise in temperature before reaching a preset threshold to be detected in advance, thus achieving accurate identification of latent heating sections. Through continuous superposition of temperature increments and durations, the dynamic process of gradual heat accumulation can be fully reflected, enabling potential thermal risks in the power supply path to be captured at an early stage. This effectively avoids insulation performance degradation caused by long-term temperature accumulation, giving the power distribution process proactive awareness and improving overall operational safety. By implementing forward control of the power distribution rhythm within the latent heating section and combining the temperature change slope with the heat accumulation trend for progressive convergence control, the power release process can be dynamically adjusted according to temperature changes. While the temperature is still rising, the output intensity is gradually reduced, thereby suppressing further heat accumulation. Meanwhile, a dynamic recovery adjustment mechanism is introduced during the temperature change slowing down phase, and the recovery process is constrained by the trend judgment of future time scale, so that the power supply strength recovery is controllable and continuous, thereby ensuring operating efficiency while avoiding repeated thermal risks and improving the stability and reliability of the vehicle power distribution.

[0067] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A power distribution method for a forklift mobile robot integrating full-dimensional state perception and early warning, characterized in that, Includes the following steps: The temperature trajectory value, current trajectory value, and corresponding time scale information of the forklift mobile robot are collected during the heavy-load operation phase to form a continuous change sequence. In the continuous change sequence, the section where the temperature rises continuously and continues to operate below the preset temperature threshold is identified and marked as the propulsion section. The temperature increment and corresponding duration per unit time are extracted around the propulsion interval. The temperature increment and duration are continuously superimposed in one direction with the starting time scale information of the propulsion interval as zero point. An extended heat accumulation criterion without using a sliding time window is constructed. The propulsion interval is segmented according to the continuous expansion trend of the extended heat accumulation criterion on the time scale information to determine the implicit heating section. Based on the implicit heating section, the current power distribution rhythm is adjusted forward. Within the implicit heating section, the output amplitude is gradually reduced and the high power duration is shortened. The voltage drop action is triggered only when the extended heat accumulation criterion shows a continuous increasing trend and the temperature change slope is positive. Under the operating conditions of voltage drop output amplitude and shortened high power duration, the temperature change slope is continuously acquired, and the temperature change slope is coupled with the extended heat accumulation criterion for judgment. When the temperature change slope is still on an upward trend and the extended heat accumulation criterion has not entered the convergence zone, the convergence power release rhythm is progressively accelerated. The dynamic intervention range is defined by combining the power release rhythm after convergence. When the slope of temperature change enters the flat section and the extended heat accumulation criterion enters the decline section, the power supply distribution intensity is gradually restored according to the change amplitude of the extended heat accumulation criterion. During the restoration process, the implicit temperature rise section is monitored in advance based on the heat accumulation trend predicted in the section on the future time scale. When the expansion risk is predicted, the restoration action is suspended.

2. The power distribution method for a fork-type mobile robot with integrated full-dimensional state perception and early warning as described in claim 1, characterized in that, The specific steps for identifying the propulsion zone are as follows: The temperature, current and time scale information of the forklift mobile robot during heavy-load operation are obtained to form a raw data set. Based on the original dataset, temperature and current values ​​are bound together to form data units, and a continuous change sequence is constructed. By using a continuous change sequence to select continuous acquisition points, temperature values ​​are compared point by point, and combined with current values ​​within the heavy load operating range to form an effective segment. Based on the time scale information recorded in the effective segment, the advancement interval is marked to form an advancement interval. The range of the advancement interval is extended by combining the newly added data to achieve advancement interval identification.

3. The power distribution method for a fork-type mobile robot with integrated full-dimensional state perception and early warning as described in claim 2, characterized in that, The specific steps to identify the latent warming zone are as follows: Extract the temperature value changes of adjacent time scales within the propulsion interval to form the temperature increment per unit time, and record the corresponding duration. The temperature increment and duration are reset to zero according to the starting time scale of the advancement interval, and then continuously superimposed in one direction to form a temperature accumulation sequence and a cumulative duration sequence. The temperature accumulation sequence and the cumulative duration sequence are combined to form an extended heat accumulation criterion, and the cumulative change trend is continuously analyzed along the time scale. The propulsion interval is divided into several sub-segments based on the continuity of temperature cumulative change, and the start and end time scales and corresponding cumulative values ​​of each sub-segment are recorded. The sub-segments are selected from those that show a continuous increase in temperature accumulation without exceeding a preset threshold and marked to form hidden temperature rise segments.

4. The power distribution method for a fork-type mobile robot with integrated full-dimensional state perception and early warning as described in claim 3, characterized in that, In the step of forming the extended heat accumulation criterion, the temperature increment of each unit time slice is accumulated one by one in chronological order and the corresponding cumulative duration is added to ensure that each time scale position obtains a temperature accumulation value that has been continuously increasing since zero.

5. The power distribution method for a fork-type mobile robot with integrated full-dimensional state perception and early warning as described in claim 3, characterized in that, The specific steps for adjusting the current power distribution rhythm in advance are as follows: Based on the implicit heating segment, the corresponding time scale information is read, the temperature value is extracted and compared with the cumulative temperature value point by point to determine the direction of temperature change and the cumulative temperature increase relationship, thus forming the trigger segment; By utilizing the start time scale information of the trigger segment, the output amplitude is gradually decreased and the high power duration is shortened, forming a continuous control sequence in combination with the trigger segment; By continuously comparing newly added temperature values ​​with accumulated temperature values ​​read around the continuous control sequence, the trigger segment can be extended or the continuous control sequence state can be maintained, thereby realizing the forward control of power distribution rhythm.

6. The power distribution method for a fork-type mobile robot with integrated full-dimensional state perception and early warning as described in claim 5, characterized in that, The trigger zone is determined by the time range within which the temperature change direction continues to rise and the cumulative temperature value continues to increase within a continuous time scale.

7. The power distribution method for a fork-type mobile robot with integrated full-dimensional state perception and early warning as described in claim 5, characterized in that, The progressive convergence power release rhythm follows these steps: Collect temperature values ​​at the corresponding time scale information of the operating status, and compare them point by point to form a temperature change slope sequence; By combining the temperature change slope sequence to read the cumulative temperature value and the cumulative duration, a corresponding relationship is formed to determine the time segment for coupling judgment; Based on the coupling judgment time segment, the output amplitude is continuously reduced and the high power duration is continuously compressed, forming a progressive convergence power release rhythm. By combining the newly added temperature change slope with the extended temperature cumulative value to determine the time segment, or by maintaining the current power release rhythm, the progressive convergence control of the power release rhythm can be achieved.

8. The power distribution method for a fork-type mobile robot with integrated full-dimensional state perception and early warning as described in claim 7, characterized in that, In the process of forming the temperature change slope sequence, the temperature values ​​of adjacent time scales are compared point by point for marking, and the temperature change slope is bound and recorded with the corresponding time scale information.

9. The power distribution method for a fork-type mobile robot with integrated full-dimensional state perception and early warning as described in claim 7, characterized in that, The dynamic intervention interval is determined based on the power release rhythm after convergence. The specific steps are as follows: The system acquires time scale information corresponding to output amplitude, high power duration, temperature value and temperature accumulation value, forms operating status data in time sequence, selects analysis sections to determine the slope of temperature change to enter the flat section and the extended heat accumulation criterion to enter the fall section, and determines the dynamic intervention range. Based on the starting time scale of the dynamic intervention interval, the power distribution intensity is restored, the output amplitude and high power duration are adjusted, and the recovery rhythm is formed by combining the temperature accumulation value change amplitude. Continue the recovery rhythm by selecting future time scale prediction segments, associate the temperature change slope sequence and the temperature cumulative value change trajectory, generate the predicted temperature change slope and the predicted temperature cumulative value, and mark the extended risk segment. Combined with the power distribution intensity restoration control of the extended risk section, the restoration action is paused or started to complete the dynamic intervention interval delineated after the power release rhythm is converged.

10. The power distribution method for a fork-type mobile robot with integrated full-dimensional state perception and early warning as described in claim 9, characterized in that, In the process of selecting future time scale prediction segments to continue the recovery rhythm, the temperature change slope corresponding to each time scale is continuously correlated with the temperature cumulative value change trajectory. Segments where the predicted temperature change slope remains positive and the predicted temperature cumulative value continues to increase are marked as extended risk segments.

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