Battery panel turbulent flow structure self-adaptive adjustment control method based on parameter analysis

Abstract

The invention discloses a parameter analysis-based battery panel turbulence structure adaptive adjustment control method, relates to the field of battery panel heat dissipation, and solves the problem that the turbulence effect of a corresponding turbulence structure of a battery panel is attenuated due to incapability of fixed-point heat dissipation when the temperature of a local area of the surface of the current battery panel is abnormal. The method comprises the following steps: detecting operation states of a battery heat dissipation plate array and battery heat dissipation plates, and obtaining abnormal state data and abnormal turbulent flow structure data of abnormal battery heat dissipation plates according to a detection result; setting a test battery heat dissipation plate and a turbulent flow structure of the test battery heat dissipation plate; adjusting a turbulent flow structure of the test battery heat dissipation plate, and judging whether the abnormal sub-region is in a normal operation state or not; adjusting the turbulent flow structure of the test battery heat dissipation plate, and then judging whether the abnormal operation state of the test battery heat dissipation plate is removed or not according to the adjusted back real-time temperature of the test battery heat dissipation plate, so that the abnormal state of the battery heat dissipation plate is eliminated by adjusting the turbulent flow structure based on the abnormal temperature.

Description

Technical Field

[0001] This invention belongs to the field of solar panel heat dissipation technology, specifically an adaptive adjustment and control method for solar panel turbulence structure based on parameter analysis. Background Technology

[0002] The turbulence structure of a solar panel refers to a collective term for structural units arranged on the back of the solar panel or in its near-wall flow area, used to actively or passively alter airflow patterns, improve heat transfer efficiency, and suppress abnormal temperature distribution. This structure does not directly generate a cold source, but rather guides natural wind or ambient airflow to form accelerated flow, shear flow, and stable vortices on the solar panel surface, weakening the thermal boundary layer attached to the panel surface and enabling more efficient heat transfer to the outside air.

[0003] In the existing technology, when there is an abnormal temperature in a local area on the surface of the battery panel of the power battery of new energy vehicle, it is difficult to dissipate heat at a fixed point. Moreover, when the environment of the battery panel changes, the turbulence effect of the original turbulence structure corresponding to the battery panel may be reduced. To address this, the present invention proposes an adaptive adjustment and control method for the solar panel disturbance structure based on parameter analysis. Summary of the Invention

[0004] The purpose of this invention is to propose an adaptive adjustment and control method for the disturbance structure of a solar panel based on parameter analysis, so as to solve the problems mentioned in the background art.

[0005] The technical problem to be solved by this invention is: How to adjust the turbulence structure based on temperature anomalies to eliminate battery heat sink malfunctions.

[0006] The objective of this invention can be achieved through the following technical solutions: An adaptive adjustment and control method for the solar panel disturbance structure based on parameter analysis, the method includes: Step S1: Detect the operating status of the battery heat sink array and the battery heat sink based on real-time battery data, and obtain abnormal state data and abnormal turbulence structure data of abnormal battery heat sinks based on the detection results. Step S2: Set the test battery heat sink and the test battery heat sink's turbulence structure according to the abnormal state data and abnormal turbulence structure data of the abnormal battery heat sink. Step S3: Adjust the turbulence structure of the test battery heat sink based on the test status data, and then determine whether the abnormal sub-region is in normal operation based on the local real-time temperature of the adjusted test battery heat sink. Step S4: Adjust the turbulence structure of the test battery heat sink based on the test status data and the real-time temperature on the back side, and then determine whether the test battery heat sink has been relieved of its abnormal operating state based on the real-time temperature on the back side of the adjusted test battery heat sink.

[0007] As a further aspect of the present invention, the turbulence structure of the battery heat sink includes turbulence columns, fins, and eddy current generator; Real-time battery data includes the real-time voltage and current values ​​of the battery heat sink array, as well as the real-time voltage and current values ​​of all battery heat sinks in the battery heat sink array.

[0008] As a further aspect of the present invention, step S1 includes the following sub-steps: Step S11: Obtain the real-time voltage and real-time current values ​​of the battery heat sink array output. Step S12: Multiply the real-time array voltage value by the real-time array current value to calculate the real-time array power of the battery heat sink array; Step S13: Subtract the standard power of the array from the real-time power of the array and take the absolute value to calculate the array power difference of the battery heat sink array. When the array power difference is greater than or equal to the power difference threshold, the battery heat sink array is determined to be in an abnormal operating state, and the process proceeds to step S14. When the power difference of the array is less than the power difference threshold, the battery heat sink array is determined to be in normal operation and no operation is performed. Step S14: Obtain the real-time battery voltage and real-time battery current values ​​of all battery heat sinks, and calculate the real-time output power of the corresponding battery heat sink by multiplying the real-time battery voltage value by the real-time battery current value. Step S15: Sum the real-time battery outputs of all battery heat sinks and take the average value to calculate the average battery power of the battery heat sink. Then, calculate the power standard deviation of the battery heat sink using the standard deviation formula. Step S16: Multiply the safety factor by the power standard deviation and add the average battery power to calculate the maximum endpoint value of the safe power range. Subtract the product of the safety factor and the power standard deviation from the average battery power to calculate the minimum endpoint value of the safe power range. Construct the safe power range of the battery heat sink using the maximum endpoint value and the minimum endpoint value. Step S17: When the real-time output power of the battery heat sink is within the safe power range, the operating state of the corresponding battery heat sink is determined to be normal operation, and no operation is performed. When the real-time output power of the battery heat sink is not within the safe power range, the operating state of the corresponding battery heat sink is determined to be an abnormal operating state, and the corresponding battery heat sink is recorded as an abnormal battery heat sink, and the process proceeds to step S18. Step S18: Collect abnormal status data of the abnormal battery heat sink; Step S19: Collect abnormal turbulence structure data of the abnormal battery heat sink.

[0009] As a further aspect of the present invention, the process for collecting the abnormal state data is as follows: Step S1801: Divide the back of the abnormal battery heat sink into a fixed number of back sub-regions, obtain the local real-time temperature corresponding to the center of each back sub-region, sum all the local real-time temperatures and take the average value to calculate the abnormal temperature of the back of the abnormal battery heat sink. Step S1802: Divide the front of the abnormal battery heat sink into a fixed number of front sub-regions, obtain the light intensity received by all front sub-regions, sum the light intensity of all front sub-regions and take the average value to calculate the real-time light intensity of the abnormal battery heat sink. Step S1803: Obtain the pitch angle and horizontal rotation angle of the abnormal battery heat sink. Step S1804: Construct a two-dimensional coordinate system for the abnormal battery heat sink, using any vertex of the abnormal battery heat sink as the origin. Step S1805: Install the anemometers on the back of the abnormal battery heat sink at the four corresponding vertices, and obtain the wind speed and direction measured by each anemometer. Step S1806: Convert the wind speed of all vertices into a horizontal wind speed vector and a vertical wind speed vector; Step S1807: The average lateral wind speed is calculated by summing the lateral wind speed vectors of all vertices and taking the average value. At the same time, the average longitudinal wind speed is calculated by summing the longitudinal wind speed vectors of all vertices and taking the average value. Step S1808: Calculate the actual wind direction at the location of the abnormal battery heat sink. Step S1809: The abnormal temperature on the back of the abnormal battery heat sink in the abnormal operating state, real-time light intensity, pitch angle, horizontal rotation angle, actual wind direction, and the corresponding local real-time temperature of all sub-regions of the abnormal battery heat sink are merged and summarized into the abnormal state data of the abnormal battery heat sink.

[0010] As a further aspect of the present invention, the process for acquiring the abnormal disturbance structure data is as follows: Step S1901: Using any vertex of the turbulence structure as the origin, construct a two-dimensional coordinate system for the turbulence structure, and then obtain the coordinates of all turbulence columns within the turbulence structure, as well as the height and spacing of the turbulence columns. Step S1902: Obtain the rib height, rib spacing, and rib angle of all ribs within the turbulence structure; Step S1903: Obtain the generator coordinates of the vortex generator inside the vortex generator through the two-dimensional coordinate system of the vortex generator, and at the same time obtain the generator angle of the vortex generator. Step S1904: The data obtained in steps S1901 to S1903 are merged and summarized into abnormal turbulence structure data of abnormal battery heat sink.

[0011] As a further aspect of the present invention, step S2 includes the following sub-steps: Step S21: Randomly select one battery heat sink from the same batch of battery heat sinks as the test battery heat sink. Step S22: Set the turbulence structure on the back of the test battery heat sink according to the abnormal turbulence structure data; Step S23: Adjust the angle of the test battery heat sink according to the pitch angle and horizontal rotation angle of the abnormal battery heat sink. Step S24: Set the light intensity received on the back of the test battery heat sink to the real-time light intensity of the abnormal battery heat sink when it is in an abnormal operating state. Step S25: Divide the back of the test battery heat sink into a fixed number of back sub-regions, obtain the local real-time temperature corresponding to the center of each back sub-region on the test battery heat sink, sum all the local real-time temperatures and take the average value to calculate the real-time temperature of the back of the test battery heat sink. When the real-time temperature of the back of the test battery heat sink is not equal to the abnormal temperature of the back of the abnormal battery heat sink, the real-time temperature of the back of the test battery heat sink is set to the abnormal temperature of the back of the abnormal battery heat sink, and the process proceeds to step S26. When the real-time temperature of the back of the test battery heat sink is equal to the abnormal temperature of the back of the abnormal battery heat sink, proceed to step S26. Step S26: Set the actual wind direction at the location of the test battery heat sink.

[0012] As a further aspect of the present invention, step S2 further includes the following sub-steps: Step S27: Collect the test status data of the test battery heat sink according to the abnormal state data corresponding to the abnormal state data of the abnormal battery heat sink. Step S28: Compare the real-time local temperature of all the back sub-regions of the test battery heat sink with the normal temperature of the sub-region; if any real-time local temperature is greater than the normal temperature of the sub-region, the corresponding sub-region is determined to be an abnormal sub-region and proceed to step S3; if all real-time local temperatures are less than or equal to the normal temperature of the sub-region, compare the real-time temperature of the back of the test battery heat sink with the safe temperature. Step S29: When the real-time temperature on the back is equal to the safe temperature, the test battery heat sink is determined to be non-temperature abnormal and no operation is performed; when the real-time temperature on the back is greater than the safe temperature, proceed to step S4.

[0013] As a further aspect of the present invention, step S3 includes the following sub-steps: Step S31: Obtain the vertex coordinates corresponding to the four vertices of the abnormal sub-region. Construct the x-coordinate interval of the abnormal sub-region using the maximum and minimum x-coordinate values ​​of the vertex coordinates, and construct the y-coordinate interval of the abnormal sub-region using the maximum and minimum y-coordinate values ​​of the vertex coordinates. Step S32: Obtain the actual wind direction of the test battery heat sink; If the actual wind direction is opposite to the positive direction of the horizontal axis in the two-dimensional coordinate system of the turbulence structure, then select the turbulence column and vortex generator whose horizontal coordinate is equal to the maximum value of the horizontal coordinate. If the actual wind direction is the same as the positive direction of the horizontal axis in the two-dimensional coordinate system of the turbulence structure, then select a turbulence column and a vortex generator whose horizontal coordinate is equal to the minimum value of the horizontal coordinate. Step S33: Increase the height of the turbulence column by a fixed height, and at the same time increase the spacing between adjacent turbulence columns by a fixed distance. Then, obtain the local real-time temperature of the abnormal sub-region after each adjustment of the turbulence structure. When the local real-time temperature is still not equal to the normal temperature of the sub-region, the height of the turbulence column is increased by a fixed amount again, and the distance between adjacent turbulence columns is increased by a fixed amount until the height of the turbulence column is equal to the maximum height of the turbulence column, the distance between adjacent turbulence columns is equal to the maximum distance, or the local real-time temperature is equal to the normal temperature of the sub-region, then the adjustment of the turbulence structure is stopped. Step S34: If the height of the turbulence column is equal to the maximum height of the turbulence column or the spacing between adjacent turbulence columns is equal to the maximum spacing, stop adjusting the turbulence structure and proceed to step S35. If the local real-time temperature equals the normal temperature of the sub-region, stop adjusting the perturbation structure and proceed to step S37.

[0014] As a further aspect of the present invention, step S3 further includes the following sub-steps: Step S35: Obtain the generator angle of the eddy current generator, reduce the fixed angle based on the current generator angle, and then obtain the local real-time temperature of the abnormal sub-region after the generator angle is adjusted. If the local real-time temperature is not equal to the normal temperature of the sub-region, then reduce the fixed angle again until the local real-time temperature is equal to the normal temperature of the sub-region or the generator angle is equal to zero, then stop reducing the generator angle. Step S36: When the local real-time temperature equals the normal temperature of the sub-region, proceed to step S37. When the generator angle is zero and the local real-time temperature is still not equal to the normal temperature of the sub-region, the abnormal sub-region is determined to be a mechanical fault, and a repair signal is issued. Step S37: Obtain all local real-time temperatures of the test battery heat sink again; when all local real-time temperatures of the test battery heat sink are equal to the normal temperature of the sub-region, determine that the abnormal sub-region is in normal operating condition, and proceed to step S4.

[0015] As a further aspect of the present invention, step S4 includes the following sub-steps: Step S41: If the actual wind direction is opposite to the positive direction of the horizontal axis in the two-dimensional coordinate system of the turbulence structure, then select the rib and vortex generator whose horizontal coordinate is equal to the maximum value of the horizontal coordinate. If the actual wind direction is the same as the positive direction of the horizontal axis in the two-dimensional coordinate system of the turbulence structure, then select a rib and a vortex generator whose horizontal coordinate is equal to the minimum value of the horizontal coordinate. Step S42: Increase the height of the fins by a fixed height, increase the spacing between adjacent fins by a fixed distance, and decrease the fixed angle based on the current generator angle. Then, obtain the real-time temperature of the back of the battery heat sink after the turbulence structure adjustment. If the real-time temperature on the back side is still not equal to the safe temperature, then the rib height is increased by a fixed height again, the rib spacing between adjacent ribs is increased by a fixed distance, and the generator angle of the eddy current generator is decreased by a fixed angle, and then proceed to step S43. If the real-time temperature on the back is equal to the safe temperature, then the abnormal operating state of the test battery heat sink is determined to be resolved. Step S43: Obtain the real-time temperature of the back of the battery heat sink after each adjustment of the turbulence structure. If any of the following conditions are met: the real-time temperature on the back side is not equal to the safe temperature, the fin height is equal to the maximum height, the fin spacing between adjacent fins is equal to the maximum fin spacing, or the generator angle of the eddy current generator is equal to zero, the heat sink of the test battery is determined to be mechanically faulty, and a repair signal is issued. When the real-time temperature on the back side equals the safe temperature, the abnormal operating state of the test battery heat sink is determined to be resolved.

[0016] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. This invention detects the operating status of the battery heat sink array and the battery heat sink based on real-time battery data, obtains abnormal state data and abnormal turbulence structure data of abnormal battery heat sinks based on the detection results, and sets the test battery heat sink and the turbulence structure of the test battery heat sink based on the abnormal state data and abnormal turbulence structure data of the abnormal battery heat sink. 2. This invention adjusts the turbulence structure of the test battery heat sink based on test status data, and then determines whether the abnormal sub-region is in normal operation based on the local real-time temperature of the adjusted test battery heat sink, thereby achieving accurate analysis of local temperature anomalies of the battery panel. 2. This invention adjusts the turbulence structure of the test battery heat sink based on test status data and real-time temperature on the back side, and then determines whether the test battery heat sink has been cleared of abnormal operation based on the real-time temperature on the back side of the adjusted test battery heat sink. The abnormal situation of the battery panel is intelligently cleared by adjusting the turbulence structure. Attached Figure Description

[0017] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0018] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is an example diagram of the back sub-region of the test battery heat sink in this invention; Figure 3 This is a schematic diagram of the computer device in this invention. Detailed Implementation

[0019] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Example 1, please refer to Figure 1 and Figure 2 As shown, the technical solution provided by the present invention is: an adaptive adjustment and control method for the disturbance structure of a battery panel based on parameter analysis. This method is used to adjust the disturbance structure of the battery panel in a new energy vehicle to achieve heat dissipation in a local area or the entire battery panel. In this embodiment, the method is as follows: Step S1: Detect the operating status of the battery heat sink array and the battery heat sink based on real-time battery data, and obtain abnormal state data and abnormal turbulence structure data of abnormal battery heat sinks based on the detection results. Specifically, the battery heat sink is a plate-like structure used to house the power battery in a new energy vehicle. The airflow-damping structure of the battery heat sink includes baffle columns, fins, and vortex generators. Real-time battery data includes the real-time voltage and current values ​​of the battery heat sink array, as well as the real-time voltage and current values ​​of all battery heat sinks in the array. The current values ​​of the battery heat sink array and individual battery heat sinks can be obtained using an ammeter and a voltmeter. During operation, the baffle structure installed on the back of the battery heat sink provides heat dissipation. The baffle columns disrupt the airflow, improving convective heat transfer. The fins guide and divide the airflow path, increasing the contact area between the air and the back of the battery heat sink. The vortex generator actively generates vortex airflow, continuously improving the heat exchange efficiency between the baffle structure and the back of the battery heat sink. In this embodiment, step S1 includes the following sub-steps: Step S11: Obtain the real-time voltage and real-time current values ​​of the battery heat sink array output. It should be noted that adjacent battery heat sinks are connected in series, and multiple series-connected battery heat sinks form a battery heat sink sequence. The battery heat sink sequences are connected in parallel, and multiple battery heat sink sequences form a battery heat sink array. Step S12: Multiply the real-time array voltage value by the real-time array current value to calculate the real-time array power of the battery heat sink array; Step S13: Subtract the standard power of the array from the real-time power of the array and take the absolute value to calculate the array power difference of the battery heat sink array. When the array power difference is greater than or equal to the power difference threshold, the battery heat sink array is determined to be in an abnormal operating state, and the process proceeds to step S14. When the power difference of the array is less than the power difference threshold, the battery heat sink array is determined to be in normal operation and no operation is performed. Among them, the array standard power and power difference threshold are existing data that can be obtained from the database; Step S14: Obtain the real-time battery voltage and real-time battery current values ​​of all battery heat sinks, and calculate the real-time output power of the corresponding battery heat sink by multiplying the real-time battery voltage value by the real-time battery current value. Step S15: Sum the real-time battery outputs of all battery heat sinks and take the average value to calculate the average battery power of the battery heat sink. Then, calculate the power standard deviation of the battery heat sink using the standard deviation formula. Step S16: Multiply the safety factor by the power standard deviation and add the average battery power to calculate the maximum endpoint value of the safe power range. Subtract the product of the safety factor and the power standard deviation from the average battery power to calculate the minimum endpoint value of the safe power range. Construct the safe power range of the battery heat sink using the maximum endpoint value and the minimum endpoint value. The safety factor is used to adjust the coverage range of the safe power range. In actual calculations, the safety factor is equal to three. Step S17: When the real-time output power of the battery heat sink is within the safe power range, the operating state of the corresponding battery heat sink is determined to be normal operation, and no operation is performed. When the real-time output power of the battery heat sink is not within the safe power range, the operating state of the corresponding battery heat sink is determined to be an abnormal operating state, and the corresponding battery heat sink is recorded as an abnormal battery heat sink, and the process proceeds to step S18. Step S18: Collect abnormal status data of the abnormal battery heat sink. The specific collection process is as follows: Step S1801: Divide the back of the abnormal battery heat sink into a fixed number of back sub-regions, obtain the local real-time temperature corresponding to the center of each back sub-region, sum all the local real-time temperatures and take the average value to calculate the abnormal temperature of the back of the abnormal battery heat sink. It should be specifically noted that the back of the abnormal battery heat sink is the side of the battery heat sink that is opposite to the ground. Step S1802: Construct a two-dimensional coordinate system for the abnormal battery heat sink, using any vertex of the abnormal battery heat sink as the origin. Step S1803: Install the wind speed sensor on the back of the abnormal battery heat sink at the four corresponding vertices, and obtain the wind speed Vi and wind direction θi measured by each wind speed sensor, where i is the number of the wind speed sensor, i=1, 2, 3, 4. Step S1804: Convert the wind speed at all vertices into a horizontal wind speed vector Vxi and a vertical wind speed vector Vyi using the following formula: Vxi = Vi·cos(θi); Vyi = Vi·sin(θi; Step S1805: The average lateral wind speed PVx is calculated by summing the lateral wind speed vectors of all vertices and taking the average value. At the same time, the average longitudinal wind speed PVy is calculated by summing the longitudinal wind speed vectors of all vertices and taking the average value. Step S1806: Calculate the actual wind direction ZS at the location of the abnormal battery heat sink using the following formula: ZS = arctan(PVy / PYx); Among them, the actual wind direction is the actual airflow direction at the location of the abnormal battery heat sink, which is the vector synthesis result of the airflow direction measured by the anemometer. Step S1807: The abnormal temperature and actual airflow direction on the back of the abnormal battery heat sink in abnormal operating state, as well as the local real-time temperature corresponding to all sub-regions of the abnormal battery heat sink, are merged and summarized into the abnormal state data of the abnormal battery heat sink. Step S19: Collect abnormal turbulence structure data of the abnormal battery heat sink. The specific collection process is as follows: Step S1901: Using any vertex of the turbulence structure as the origin, construct a two-dimensional coordinate system for the turbulence structure, and then obtain the coordinates of all turbulence columns within the turbulence structure, as well as the height and spacing of the turbulence columns. In practice, the height and spacing of the turbulence columns can be obtained using a laser rangefinder; the two-dimensional coordinate system of the abnormal battery heat sink is the same as that of the turbulence structure. Step S1902: Obtain the rib height, rib spacing, and rib angle of all ribs within the turbulence structure; Among them, the rib height and rib spacing can be obtained by a laser rangefinder, and the rib angle can be obtained by an tilt sensor. Step S1903: Obtain the generator coordinates of the vortex generator inside the vortex generator through the two-dimensional coordinate system of the vortex generator, and at the same time obtain the generator angle of the vortex generator. Specifically, the generator angle can be obtained through a tilt sensor; Step S1904: The data obtained in steps S1901 to S1903 are merged and summarized into abnormal turbulence structure data of abnormal battery heat sink.

[0021] Step S2: Set the test battery heat sink and the test battery heat sink's turbulence structure according to the abnormal state data and abnormal turbulence structure data of the abnormal battery heat sink. In this embodiment, step S2 includes the following sub-steps: Step S21: Randomly select one battery heat sink from the same batch of battery heat sinks as the test battery heat sink. Step S22: Set the turbulence structure on the back of the test battery heat sink according to the abnormal turbulence structure data; Step S23: Divide the back of the test battery heat sink into a fixed number of back sub-regions, obtain the local real-time temperature corresponding to the center of each back sub-region on the test battery heat sink, sum all the local real-time temperatures and take the average value to calculate the real-time temperature of the back of the test battery heat sink. When the real-time temperature of the back of the test battery heat sink is not equal to the abnormal temperature of the back of the abnormal battery heat sink, the real-time temperature of the back of the test battery heat sink is set to the abnormal temperature of the back of the abnormal battery heat sink, and the process proceeds to step S26. When the real-time temperature of the back of the test battery heat sink is equal to the abnormal temperature of the back of the abnormal battery heat sink, proceed to step S26. It should be noted that the real-time temperature of the back of the test battery heat sink can be adjusted through the turbulence structure. Step S24: Set the actual wind direction at the location of the test battery heat sink. In practice, blowers can be set up in four directions of the test battery heat sink to simulate the actual wind direction at the location of the abnormal battery heat sink. Step S25: Collect the test status data of the test battery heat sink according to the abnormal status data of the abnormal battery heat sink. The data required for testing the battery heat sink is the same as the data required for testing the abnormal state of the abnormal battery heat sink. Step S26: Compare the real-time local temperature of all back sub-regions of the test battery heat sink with the normal temperature of the sub-regions. If any local real-time temperature is greater than the normal temperature of the sub-region, the corresponding sub-region is determined to be an abnormal sub-region, and the process proceeds to step S3. If all local real-time temperatures are less than or equal to the normal temperature of the sub-region, then the real-time temperature of the back of the test battery heat sink is compared with the safe temperature. Step S27: When the real-time temperature on the back is equal to the safe temperature, the heat sink of the test battery is determined to be non-temperature abnormal, and no operation is performed. When the real-time temperature on the back side is greater than the safe temperature, proceed to step S4; The normal temperature of the sub-region corresponding to the back of the test battery heat sink and the safe temperature of the test battery heat sink can be obtained from the database; in reality, the normal temperature of the sub-region is greater than the safe temperature; since the turbulence structure is used to dissipate heat from the battery heat sink, this embodiment only detects and analyzes the case where the temperature of the battery heat sink is greater than the threshold.

[0022] Step S3: Adjust the turbulence structure of the test battery heat sink based on the test status data, and then determine whether the abnormal sub-region is in normal operation based on the local real-time temperature of the adjusted test battery heat sink. In this embodiment, step S3 includes the following sub-steps: Step S31: Obtain the vertex coordinates corresponding to the four vertices of the abnormal sub-region. Construct the x-coordinate interval of the abnormal sub-region using the maximum and minimum x-coordinate values ​​of the vertex coordinates, and construct the y-coordinate interval of the abnormal sub-region using the maximum and minimum y-coordinate values ​​of the vertex coordinates. Step S32, as follows Figure 2 As shown, the actual airflow direction of the test battery heat sink is obtained; If the actual wind direction is opposite to the positive direction of the horizontal axis in the two-dimensional coordinate system of the turbulence structure, then select the turbulence column and vortex generator whose horizontal coordinate is equal to the maximum value of the horizontal coordinate. If the actual wind direction is the same as the positive direction of the horizontal axis in the two-dimensional coordinate system of the turbulence structure, then select a turbulence column and a vortex generator whose horizontal coordinate is equal to the minimum value of the horizontal coordinate. It should be specifically noted that when natural wind flows through the test battery heat sink through the real wind direction, a turbulence column and vortex generator with an abscissa equal to the maximum value of the abscissa are selected to change the local real-time temperature of the abnormal sub-region behind the turbulence column and vortex generator. Step S33: Increase the height of the turbulence column by a fixed height, and at the same time increase the spacing between adjacent turbulence columns by a fixed distance. Then, obtain the local real-time temperature of the abnormal sub-region after each adjustment of the turbulence structure. When the local real-time temperature is still not equal to the normal temperature of the sub-region, the height of the turbulence column is increased by a fixed amount again, and the distance between adjacent turbulence columns is increased by a fixed amount until the height of the turbulence column is equal to the maximum height of the turbulence column, the distance between adjacent turbulence columns is equal to the maximum distance, or the local real-time temperature is equal to the normal temperature of the sub-region, then the adjustment of the turbulence structure is stopped. The fixed height is a fixed percentage of the maximum height of the spoiler column; the fixed reduction in distance between adjacent spoiler columns is calculated by multiplying the current spacing between spoiler columns by the fixed percentage; in practice, the fixed percentage can be 10%. Step S34: If the height of the turbulence column is equal to the maximum height of the turbulence column or the spacing between adjacent turbulence columns is equal to the maximum spacing, stop adjusting the turbulence structure and proceed to step S35. If the local real-time temperature equals the normal temperature of the sub-region, stop adjusting the perturbation structure and proceed to step S37. The fixed height is a fixed percentage of the maximum height of the spoiler column; the fixed reduction in distance between adjacent spoiler columns is calculated by multiplying the current spacing between spoiler columns by the fixed percentage; in practice, the fixed percentage can be 10%. Step S35: Obtain the generator angle of the eddy current generator, reduce the fixed angle based on the current generator angle, and then obtain the local real-time temperature of the abnormal sub-region after the generator angle is adjusted. If the local real-time temperature is not equal to the normal temperature of the sub-region, then reduce the fixed angle again until the local real-time temperature is equal to the normal temperature of the sub-region or the generator angle is equal to zero, then stop reducing the generator angle. Step S36: When the local real-time temperature equals the normal temperature of the sub-region, proceed to step S37. When the generator angle is zero and the local real-time temperature is still not equal to the normal temperature of the sub-region, the abnormal sub-region is determined to be a mechanical fault, and a repair signal is issued. Step S37: Obtain all local real-time temperatures of the test battery heat sink again; When the real-time temperature of all local areas of the test battery heat sink is equal to the normal temperature of the sub-region, the abnormal sub-region is determined to be in normal operating condition, and the process proceeds to step S4.

[0023] Step S4: Adjust the turbulence structure of the test battery heat sink based on the test status data and the real-time temperature on the back. Then, determine whether the test battery heat sink has been deactivated based on the real-time temperature on the back of the adjusted test battery heat sink. In this embodiment, step S4 includes the following sub-steps: Step S41: If the actual wind direction is opposite to the positive direction of the horizontal axis in the two-dimensional coordinate system of the turbulence structure, then select the rib and vortex generator whose horizontal coordinate is equal to the maximum value of the horizontal coordinate. If the actual wind direction is the same as the positive direction of the horizontal axis in the two-dimensional coordinate system of the turbulence structure, then select a rib and a vortex generator whose horizontal coordinate is equal to the minimum value of the horizontal coordinate. Step S42: Increase the height of the fins by a fixed height, increase the spacing between adjacent fins by a fixed distance, and decrease the fixed angle based on the current generator angle. Then, obtain the real-time temperature of the back of the battery heat sink after the turbulence structure adjustment. If the real-time temperature on the back side is still not equal to the safe temperature, then the rib height is increased by a fixed height again, the rib spacing between adjacent ribs is increased by a fixed distance, and the generator angle of the eddy current generator is decreased by a fixed angle, and then proceed to step S43. If the real-time temperature on the back is equal to the safe temperature, then the abnormal operating state of the test battery heat sink is determined to be resolved. Step S43: Obtain the real-time temperature of the back of the battery heat sink after each adjustment of the turbulence structure. If any of the following conditions are met: the real-time temperature on the back side is not equal to the safe temperature, the fin height is equal to the maximum height, the fin spacing between adjacent fins is equal to the maximum fin spacing, or the generator angle of the eddy current generator is equal to zero, the heat sink of the test battery is determined to be mechanically faulty, and a repair signal is issued. When the real-time temperature on the back side equals the safe temperature, the abnormal operating state of the test battery heat sink is determined to be resolved.

[0024] Example 2: This embodiment of the invention also provides a computer device for running the aforementioned adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis; see also... Figure 3 The schematic diagram of a computer device provided by the embodiment of the present invention shown above includes a memory and a processor. The memory is used to store one or more computer instructions, and the one or more computer instructions are executed by the processor to realize the above-mentioned adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis. Furthermore, Figure 3 The computer device shown also includes a system bus and a communication interface, with the processor, communication interface, and memory connected via the communication bus; The memory may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The system bus can be an ISA bus, PCI bus, or EISA bus, etc. The system bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The symbol is represented by only one bidirectional arrow, but this does not mean that there is only one communication bus or one type of system bus. The processor may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above methods can be completed by integrated logic circuits in the processor's hardware or by software instructions. The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

[0025] Example 3: This embodiment of the invention also provides a computer storage medium storing computer-executable instructions. When these computer-executable instructions are called and executed by a processor, they cause the processor to implement the above-mentioned adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis. For specific implementation, please refer to the method embodiment, which will not be repeated here. The computer program product of the adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis provided in this embodiment of the invention includes a computer storage medium storing program code. The instructions included in the program code can be used to execute the methods in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0026] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and / or device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0027] Furthermore, in the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0028] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0029] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis, characterized in that, The methods include: Step S1: Detect the operating status of the battery heat sink array and the battery heat sink based on real-time battery data, and obtain abnormal state data and abnormal turbulence structure data of abnormal battery heat sinks based on the detection results. Step S2: Set the test battery heat sink and the test battery heat sink's turbulence structure according to the abnormal state data and abnormal turbulence structure data of the abnormal battery heat sink. Step S3: Adjust the turbulence structure of the test battery heat sink based on the test status data, and then determine whether the abnormal sub-region is in normal operation based on the local real-time temperature of the adjusted test battery heat sink. Step S4: Adjust the turbulence structure of the test battery heat sink based on the test status data and the real-time temperature on the back side, and then determine whether the test battery heat sink has been relieved of its abnormal operating state based on the real-time temperature on the back side of the adjusted test battery heat sink.

2. The adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis according to claim 1, characterized in that, The turbulence structure of the battery heat sink includes turbulence columns, fins, and eddy current generators; Real-time battery data includes the real-time voltage and current values ​​of the battery heat sink array, as well as the real-time voltage and current values ​​of all battery heat sinks in the battery heat sink array.

3. The adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis according to claim 2, characterized in that, Step S1 includes the following sub-steps: Step S11: Obtain the real-time voltage and real-time current values ​​of the battery heat sink array output. Step S12: Multiply the real-time array voltage value by the real-time array current value to calculate the real-time array power of the battery heat sink array; Step S13: Subtract the standard power of the array from the real-time power of the array and take the absolute value to calculate the array power difference of the battery heat sink array. When the array power difference is greater than or equal to the power difference threshold, the battery heat sink array is determined to be in an abnormal operating state, and the process proceeds to step S14. When the power difference of the array is less than the power difference threshold, the battery heat sink array is determined to be in normal operation and no operation is performed. Step S14: Obtain the real-time battery voltage and real-time battery current values ​​of all battery heat sinks, and calculate the real-time output power of the corresponding battery heat sink by multiplying the real-time battery voltage value by the real-time battery current value. Step S15: Sum the real-time battery outputs of all battery heat sinks and take the average value to calculate the average battery power of the battery heat sink. Then, calculate the power standard deviation of the battery heat sink using the standard deviation formula. Step S16: Multiply the safety factor by the power standard deviation and add the average battery power to calculate the maximum endpoint value of the safe power range. Subtract the product of the safety factor and the power standard deviation from the average battery power to calculate the minimum endpoint value of the safe power range. Construct the safe power range of the battery heat sink using the maximum endpoint value and the minimum endpoint value. Step S17: When the real-time output power of the battery heat sink is within the safe power range, the operating state of the corresponding battery heat sink is determined to be normal operation, and no operation is performed. When the real-time output power of the battery heat sink is not within the safe power range, the operating state of the corresponding battery heat sink is determined to be an abnormal operating state, and the corresponding battery heat sink is recorded as an abnormal battery heat sink, and the process proceeds to step S18. Step S18: Collect abnormal status data of the abnormal battery heat sink; Step S19: Collect abnormal turbulence structure data of the abnormal battery heat sink.

4. The adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis according to claim 3, characterized in that, The specific process for collecting the abnormal status data is as follows: Step S1801: Divide the back of the abnormal battery heat sink into a fixed number of back sub-regions, obtain the local real-time temperature corresponding to the center of each back sub-region, sum all the local real-time temperatures and take the average value to calculate the abnormal temperature of the back of the abnormal battery heat sink. Step S1802: Divide the front of the abnormal battery heat sink into a fixed number of front sub-regions, obtain the light intensity received by all front sub-regions, sum the light intensity of all front sub-regions and take the average value to calculate the real-time light intensity of the abnormal battery heat sink. Step S1803: Obtain the pitch angle and horizontal rotation angle of the abnormal battery heat sink. Step S1804: Construct a two-dimensional coordinate system for the abnormal battery heat sink, using any vertex of the abnormal battery heat sink as the origin. Step S1805: Install the anemometers on the back of the abnormal battery heat sink at the four corresponding vertices, and obtain the wind speed and direction measured by each anemometer. Step S1806: Convert the wind speed of all vertices into a horizontal wind speed vector and a vertical wind speed vector; Step S1807: The average lateral wind speed is calculated by summing the lateral wind speed vectors of all vertices and taking the average value. At the same time, the average longitudinal wind speed is calculated by summing the longitudinal wind speed vectors of all vertices and taking the average value. Step S1808: Calculate the actual wind direction at the location of the abnormal battery heat sink. Step S1809: The abnormal temperature on the back of the abnormal battery heat sink in the abnormal operating state, real-time light intensity, pitch angle, horizontal rotation angle, actual wind direction, and the corresponding local real-time temperature of all sub-regions of the abnormal battery heat sink are merged and summarized into the abnormal state data of the abnormal battery heat sink.

5. The adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis according to claim 3, characterized in that, The specific process for collecting the abnormal disturbance structure data is as follows: Step S1901: Using any vertex of the turbulence structure as the origin, construct a two-dimensional coordinate system for the turbulence structure, and then obtain the coordinates of all turbulence columns within the turbulence structure, as well as the height and spacing of the turbulence columns. Step S1902: Obtain the rib height, rib spacing, and rib angle of all ribs within the turbulence structure; Step S1903: Obtain the generator coordinates of the vortex generator inside the vortex generator through the two-dimensional coordinate system of the vortex generator, and at the same time obtain the generator angle of the vortex generator. Step S1904: The data obtained in steps S1901 to S1903 are merged and summarized into abnormal turbulence structure data of abnormal battery heat sink.

6. The adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis according to claim 3, characterized in that, Step S2 includes the following sub-steps: Step S21: Randomly select one battery heat sink from the same batch of battery heat sinks as the test battery heat sink. Step S22: Set the turbulence structure on the back of the test battery heat sink according to the abnormal turbulence structure data; Step S23: Adjust the angle of the test battery heat sink according to the pitch angle and horizontal rotation angle of the abnormal battery heat sink. Step S24: Set the light intensity received on the back of the test battery heat sink to the real-time light intensity of the abnormal battery heat sink when it is in an abnormal operating state. Step S25: Divide the back of the test battery heat sink into a fixed number of back sub-regions, obtain the local real-time temperature corresponding to the center of each back sub-region on the test battery heat sink, sum all the local real-time temperatures and take the average value to calculate the real-time temperature of the back of the test battery heat sink. When the real-time temperature of the back of the test battery heat sink is not equal to the abnormal temperature of the back of the abnormal battery heat sink, the real-time temperature of the back of the test battery heat sink is set to the abnormal temperature of the back of the abnormal battery heat sink, and the process proceeds to step S26. When the real-time temperature of the back of the test battery heat sink is equal to the abnormal temperature of the back of the abnormal battery heat sink, proceed to step S26. Step S26: Set the actual wind direction at the location of the test battery heat sink.

7. The adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis according to claim 6, characterized in that, Step S2 further includes the following sub-steps: Step S27: Collect the test status data of the test battery heat sink according to the abnormal state data corresponding to the abnormal state data of the abnormal battery heat sink. Step S28: Compare the real-time local temperature of all the back sub-regions of the test battery heat sink with the normal temperature of the sub-region; if any real-time local temperature is greater than the normal temperature of the sub-region, the corresponding sub-region is determined to be an abnormal sub-region and proceed to step S3; if all real-time local temperatures are less than or equal to the normal temperature of the sub-region, compare the real-time temperature of the back of the test battery heat sink with the safe temperature. Step S29: When the real-time temperature on the back is equal to the safe temperature, the test battery heat sink is determined to be non-temperature abnormal and no operation is performed; when the real-time temperature on the back is greater than the safe temperature, proceed to step S4.

8. The adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis according to claim 7, characterized in that, Step S3 includes the following sub-steps: Step S31: Obtain the vertex coordinates corresponding to the four vertices of the abnormal sub-region. Construct the x-coordinate interval of the abnormal sub-region using the maximum and minimum x-coordinate values ​​of the vertex coordinates, and construct the y-coordinate interval of the abnormal sub-region using the maximum and minimum y-coordinate values ​​of the vertex coordinates. Step S32: Obtain the actual wind direction of the test battery heat sink; If the actual wind direction is opposite to the positive direction of the horizontal axis in the two-dimensional coordinate system of the turbulence structure, then select the turbulence column and vortex generator whose horizontal coordinate is equal to the maximum value of the horizontal coordinate. If the actual wind direction is the same as the positive direction of the horizontal axis in the two-dimensional coordinate system of the turbulence structure, then select a turbulence column and a vortex generator whose horizontal coordinate is equal to the minimum value of the horizontal coordinate. Step S33: Increase the height of the turbulence column by a fixed height, and at the same time increase the spacing between adjacent turbulence columns by a fixed distance. Then, obtain the local real-time temperature of the abnormal sub-region after each adjustment of the turbulence structure. When the local real-time temperature is still not equal to the normal temperature of the sub-region, the height of the turbulence column is increased by a fixed amount again, and the distance between adjacent turbulence columns is increased by a fixed amount until the height of the turbulence column is equal to the maximum height of the turbulence column, the distance between adjacent turbulence columns is equal to the maximum distance, or the local real-time temperature is equal to the normal temperature of the sub-region, then the adjustment of the turbulence structure is stopped. Step S34: If the height of the turbulence column is equal to the maximum height of the turbulence column or the spacing between adjacent turbulence columns is equal to the maximum spacing, stop adjusting the turbulence structure and proceed to step S35. If the local real-time temperature equals the normal temperature of the sub-region, stop adjusting the perturbation structure and proceed to step S37.

9. The adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis according to claim 8, characterized in that, Step S3 further includes the following sub-steps: Step S35: Obtain the generator angle of the eddy current generator, reduce the fixed angle based on the current generator angle, and then obtain the local real-time temperature of the abnormal sub-region after the generator angle is adjusted. If the local real-time temperature is not equal to the normal temperature of the sub-region, then reduce the fixed angle again until the local real-time temperature is equal to the normal temperature of the sub-region or the generator angle is equal to zero, then stop reducing the generator angle. Step S36: When the local real-time temperature equals the normal temperature of the sub-region, proceed to step S37. When the generator angle is zero and the local real-time temperature is still not equal to the normal temperature of the sub-region, the abnormal sub-region is determined to be a mechanical fault, and a repair signal is issued. Step S37: Obtain all local real-time temperatures of the test battery heat sink again; when all local real-time temperatures of the test battery heat sink are equal to the normal temperature of the sub-region, determine that the abnormal sub-region is in normal operating condition, and proceed to step S4.

10. The adaptive adjustment and control method for solar panel disturbance structure based on parameter analysis according to claim 9, characterized in that, Step S4 includes the following sub-steps: Step S41: If the actual wind direction is opposite to the positive direction of the horizontal axis in the two-dimensional coordinate system of the turbulence structure, then select the rib and vortex generator whose horizontal coordinate is equal to the maximum value of the horizontal coordinate. If the actual wind direction is the same as the positive direction of the horizontal axis in the two-dimensional coordinate system of the turbulence structure, then select a rib and a vortex generator whose horizontal coordinate is equal to the minimum value of the horizontal coordinate. Step S42: Increase the height of the fins by a fixed height, increase the spacing between adjacent fins by a fixed distance, and decrease the fixed angle based on the current generator angle. Then, obtain the real-time temperature of the back of the battery heat sink after the turbulence structure adjustment. If the real-time temperature on the back side is still not equal to the safe temperature, then the rib height is increased by a fixed height again, the rib spacing between adjacent ribs is increased by a fixed distance, and the generator angle of the eddy current generator is decreased by a fixed angle, and then proceed to step S43. If the real-time temperature on the back is equal to the safe temperature, then the abnormal operating state of the test battery heat sink is determined to be resolved. Step S43: Obtain the real-time temperature of the back of the battery heat sink after each adjustment of the turbulence structure. If any of the following conditions are met: the real-time temperature on the back side is not equal to the safe temperature, the fin height is equal to the maximum height, the fin spacing between adjacent fins is equal to the maximum fin spacing, or the generator angle of the eddy current generator is equal to zero, the heat sink of the test battery is determined to be mechanically faulty, and a repair signal is issued. When the real-time temperature on the back side equals the safe temperature, the abnormal operating state of the test battery heat sink is determined to be resolved.

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