A monitoring method for the charging status of an unmanned aerial vehicle storage

Abstract

The present invention discloses a method for monitoring the charging state of an unmanned aerial vehicle (UAV) storage. The method includes the following steps: measuring the battery power when the UAV exits and enters the storage, calculating the actual power consumption of the UAV during the flight mission; calculating the theoretical power consumption during the UAV flight process, and calculating the natural loss of the battery during the flight process; when the UAV needs to perform the next mission and exits the storage, measuring the actual battery power of the UAV, calculating the theoretical charging amount and the actual charging amount for this charging; calculating the battery loss during this charging process; calculating the battery loss rates of the UAV in the flight state and the charging state respectively; evaluating the life of the UAV battery according to the loss rates to obtain a life index, comparing the life index with a life index threshold, and evaluating the battery life state. Starting from two perspectives, namely the loss of the battery during the UAV flight process and the loss of the battery during the charging process, the present invention obtains a relatively accurate life coefficient, and the evaluation result is more accurate and objective.

Description

Technical Field

[0001] The present invention relates to the technical field of UAV charging safety, and particularly to a method for monitoring the charging state of UAVs in a warehouse. Background Art

[0002] The intelligent UAV warehouse mainly consists of the following parts: an intelligent UAV charging cabinet, an intelligent storage cabinet, a face recognition access control system, a warehouse environment monitoring system, a monitoring system, a three-dimensional visualization operation large screen, and a server background management system. While realizing the storage function of UAVs, the intelligent UAV warehouse also has the function of charging UAVs and provides a charging place for UAVs. The existing usage experience and service life of UAVs are mostly reflected in the service life of the UAV battery. The life and state of the battery will directly affect the flight distance and flight state of the UAV. Each time a UAV executes a flight mission, it needs to be fully charged so that the next flight mission can be smoothly executed. However, the existing intelligent UAV warehouse cannot accurately and reasonably evaluate the charging state and battery life of UAVs, resulting in a poor user experience. Summary of the Invention

[0003] In view of the above deficiencies of the prior art, the present invention provides a method for monitoring the charging state of UAVs in a warehouse, which can comprehensively evaluate the battery life according to the flight state and charging state of UAVs.

[0004] To achieve the above invention objective, the technical solution adopted by the present invention is as follows:

[0005] Provide a method for monitoring the charging state of UAVs in a warehouse, which includes the following steps:

[0006] S1: Measure the battery powers d 1 and d 2 when the UAV exits and enters the warehouse, and calculate the actual power consumption d 1 and d 2 of the UAV when performing a flight mission by using d 真实 =d 1 -d 2 ;

[0007] S2: Calculate the theoretical power consumption d 理论 of the UAV according to the flight process state during the time when the UAV exits and enters the warehouse, and calculate the natural loss d 真实 of the battery during the flight process by using the actual power consumption d 理论 and the theoretical power consumption d 损耗 =d 真实 -d 理论 ;

[0008] The calculation method of the theoretical power consumption d 理论 is as follows:

[0009] S21: Calculate the mass of air m that needs to be accelerated during hovering according to the area S of the drone's propeller blades: m = ρSvt, where ρ is the density of air, v is the speed of air acceleration, and t is the hovering time;

[0010] S22: Calculate the power P that the drone does to the air during the hovering time using the mass of air m:

[0011] P = ρSgv 2 t;

[0012] S23: Calculate the output current i of the drone battery according to the power p: i = (P + P n ) / u, where u is the rated output voltage of the drone battery, and P n is the power consumed by devices other than the propeller on the drone;

[0013] S24: Calculate the power consumption d 悬停 during the hovering state according to the time t of the drone's hovering state

[0014]

[0015] S25: Statistically calculate the duration t of the drone in different flight states during flight, and calculate the theoretical power consumption d 理论 during the flight of the drone:

[0016]

[0017] where s is the different flight states of the drone during flight, t s is the duration of the drone in different flight states, and a s is the proportionality coefficient of the power consumption of the drone in different flight states to that in the hovering state;

[0018] S3: The drone enters the warehouse for charging with the power d 2 . When the drone is connected to the charging dock, it communicates with the charging dock to obtain the coordinates of the charging dock and the charging dock parameters;

[0019] S4: After the power display of the drone charging reaches 100%, the charging is completed. The charging dock disconnects from the drone to stop charging. When the drone needs to execute the next task and leave the warehouse, measure the actual power d 3 of the drone;

[0020] S5: Calculate the theoretical charging amount D 4 and the actual charging amount D 理论 of this charging using the actual power d 真实 in the brand new state of the drone battery: D 真实 = d 4 - d3 , D 理论 = d 4 -d 2 ;

[0021] S6: Calculate the battery loss D during this charging process 损耗 : D 损耗 = D 理论 -D 真实 ;

[0022] S7: According to the flight duration t of the UAV execution 1 and the charging duration t 2 calculate the loss rate d of the UAV battery in the flight state respectively 损耗率 and the loss rate D of the battery in the charging state 损耗率 :

[0023]

[0024] S8: Evaluate the life of the UAV battery according to the loss rates D 损耗率 and d 损耗率 calculate the life index f of the UAV battery during this flight cycle:

[0025] f = ln(a) + z 1 ln(d 损耗 ) + z 2 ln(D 损耗 )

[0026] where a is the attenuation rate of the chemical components in the UAV battery, z 1 is the influence coefficient of the loss rate in the flight state on the life of the UAV battery, z 2 is the influence coefficient of the loss rate in the charging state on the life of the UAV battery;

[0027] S9: Compare the life index f with the life index threshold f(threshold):

[0028] If f > f(threshold), it is determined that the battery life in the UAV is insufficient, intercept the UAV when it is out of the warehouse this time to prevent the UAV from going out of the warehouse to continue the flight mission, and send the model of the UAV to the UAV warehouse to remind the staff to replace the battery of the UAV;

[0029] If f ≤ f(threshold), it is determined that the battery life in the UAV is sufficient, and the UAV can go out of the warehouse smoothly.

[0030] Furthermore, different flight states of the UAV include one or more of ascending flight, descending flight, horizontal acceleration flight, horizontal deceleration flight, and hovering flight.

[0031] Furthermore, it also includes:

[0032] S10: After the power display of the UAV charging reaches 100% in step S4, the charging time t of the UAV this time is counted 3 , and the actual charging amount D 真实 is used to calculate the charging efficiency D of the UAV this time 效率 :

[0033]

[0034] S11: Subtract the rated charging efficiency D 效率 from the charging efficiency D 额定效率 to obtain the fluctuation value D of the charging efficiency 波动 : D 波动 = D 额定效率 - D 效率 ;

[0035] S12: Compare the fluctuation value D 波动 with the fluctuation threshold D 波动阈值 :

[0036] If D 波动 > D 波动阈值 , it is determined that the charging station is faulty, and the staff checks the corresponding charging station according to the coordinates and parameters of the charging station. If the charging station is in normal condition, the UAV battery has been damaged;

[0037] If D 波动 ≤ D 波动阈值 , it is determined that the charging status is normal this time

[0038] The beneficial effects of the present invention are as follows: The present invention effectively improves the intelligent performance of the UAV storage, making the UAV storage no longer just a place for simply storing and accommodating UAVs. The proposed solution of the present invention enables the UAV storage to monitor the status of the UAV battery, evaluate according to the life of the UAV battery, and control whether the UAV goes out of the warehouse according to the evaluation results, so as to more reasonably manage the UAVs, avoid the UAVs performing tasks with problems, and thus cause the crash of the UAVs and unnecessary emergency losses

[0039] Starting from two aspects of the battery loss during the UAV flight and the battery loss during the charging process, the present invention accurately calculates the battery loss of the UAV battery in two states, and on this basis, evaluates the battery life of the UAV, can obtain a relatively accurate life coefficient as a reference for life evaluation, and the evaluation results are more accurate and objective Description of the Drawings

[0040] Figure 1 is a flowchart of the method for monitoring the charging status of the UAV storage Detailed Embodiments

[0041] The specific implementation manners of the present invention will be described below to facilitate those skilled in the art of this technology to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation manners. For those of ordinary skill in the art of this technology, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are within the scope of protection.

[0042] As Figure 1 shown, the monitoring method for the charging state of the unmanned aerial vehicle (UAV) storage in this solution includes the following steps:

[0043] S1: Measure the battery power d 1 and d 2 when the UAV exits and enters the warehouse, and calculate the actual power consumption d 1 and d 2 of the UAV during the flight mission by using the battery power d 真实 = d 1 - d 2 ;

[0044] S2: Calculate the theoretical power consumption d 理论 of the UAV according to the flight process state during the time when the UAV exits and enters the warehouse, and calculate the natural loss d 真实 of the battery during the flight process by using the actual power consumption d 理论 and the theoretical power consumption d 损耗 = d 真实 - d 理论 ;

[0045] The calculation method of the theoretical power consumption d 理论 is as follows:

[0046] S21: Calculate the mass of air m that needs to be accelerated during hovering according to the area S of the UAV propeller blades: m = ρSvt, where ρ is the density of air, v is the air acceleration speed, and t is the hovering time;

[0047] S22: Calculate the power P that the UAV does to the air during the hovering time by using the mass of air m:

[0048] P = ρSgv 2 t;

[0049] S23: Calculate the output current i of the UAV battery according to the power p: i = (P + P n ) / u, where u is the rated output voltage of the UAV battery, and P n is the power consumed by devices other than the propeller on the UAV;

[0050] S24: Calculate the power consumption d 悬停:

[0051]

[0052] S25: Statistically analyze the duration t of the drone in different flight states during flight, and calculate the theoretical power consumption d of the drone during flight 理论 :

[0053]

[0054] Among them, s represents different flight states of the drone during flight, and t s represents the duration of different flight states of the drone, and a s is the proportionality coefficient of the power consumption of the drone in different flight states compared to the hovering state; different flight states of the drone include one or more of ascending flight, descending flight, horizontal acceleration flight, horizontal deceleration flight, and hovering flight.

[0055] S3: The drone enters the warehouse for charging with a power level of d 2 When the drone connects to the charging dock, it communicates with the charging dock to obtain the coordinates and parameters of the charging dock;

[0056] S4: After the power display of the drone during charging reaches 100%, the charging is completed. The charging dock disconnects from the drone to stop charging. When the drone needs to execute the next task and leave the warehouse, measure the actual power level d of the drone 3 ;

[0057] S5: Use the actual power level d of the drone in a brand-new battery state 4 to calculate the theoretical charging amount D 理论 and the actual charging amount D 真实 : D 真实 = d 4 - d 3 、D 理论 = d 4 - d 2 ;

[0058] S6: Calculate the battery loss D during this charging process 损耗 : D 损耗 = D 理论 - D 真实 ;

[0059] S7: Calculate the loss rate d of the drone in the flight state and the loss rate D of the battery in the charging state based on the flight duration t 1 and the charging duration t 2 of the drone: 损耗率 损耗率 :

[0060] ​

[0061] S8: Evaluate the life of the UAV battery according to the loss rates D 损耗率 and d 损耗率 and calculate the life index f of the UAV battery during this flight cycle:

[0062] f = ln(a) + z 1 ln(d 损耗 ) + z 2 ln(D 损耗 )

[0063] where a is the attenuation rate of the chemical components in the UAV battery, and z 1 is the influence coefficient of the loss rate in the flight state on the life of the UAV battery, and z 2 is the influence coefficient of the loss rate in the charging state on the life of the UAV battery;

[0064] S9: Compare the life index f with the life index threshold f(threshold):

[0065] If f > f(threshold), it is determined that the battery life in the UAV is insufficient. Intercept the UAV when it leaves the warehouse this time to prevent the UAV from leaving the warehouse to continue the flight mission, and send the model of the UAV to the UAV warehouse to remind the staff to replace the battery of the UAV;

[0066] If f ≤ f(threshold), it is determined that the battery life in the UAV is sufficient, and the UAV can leave the warehouse smoothly.

[0067] It also includes:

[0068] S10: After the power display of the UAV charging reaches 100% in step S4, count the charging time t of the UAV this time 3 , and use the actual charging amount D 真实 to calculate the charging efficiency D of the UAV this time 效率 :

[0069]

[0070] S11: Subtract the rated charging efficiency D 效率 from the charging efficiency D 额定效率 to obtain the fluctuation value D of the charging efficiency 波动 : D 波动 = D 额定效率 - D 效率 ;

[0071] S12: Compare the fluctuation value D 波动 with the fluctuation threshold D 波动阈值 :

[0072] If D 波动>D 波动阈值 , it is determined that the charging stand has a fault. The staff checks the corresponding charging stand according to the coordinates and parameters of the charging stand. If the charging stand is in normal condition, the drone battery has been damaged;

[0073] If D 波动 ≤D 波动阈值 , it is determined that the current charging status is normal.

[0074] The present invention effectively improves the intelligent performance of the drone storage. It makes the drone storage no longer just a place for simply storing and accommodating drones. The proposed solution of the present invention enables the drone storage to monitor the state of the drone battery, evaluate according to the life of the drone battery, and control whether the drone goes out of the warehouse according to the evaluation result, so as to more reasonably manage the drones, avoid the drones performing tasks with problems, and thus cause the crash of the drones and unnecessary emergency losses.

[0075] Starting from two aspects, namely the battery loss during the flight process of the drone and the battery loss during the charging process, the present invention accurately calculates the battery loss of the drone battery in the two states, and based on this, evaluates the battery life of the drone, can obtain a relatively accurate life coefficient as a reference for life evaluation, and the evaluation result is more accurate and objective.

Claims

1. A method for monitoring the charging status of an unmanned aerial vehicle (UAV) storage warehouse, characterized in that, it includes the following steps: S1: Measure the power d when the drone exits and enters the warehouse 1 and d 2 , and use the power d 1 and d 2 to calculate the actual power consumption d of the drone when performing flight missions 真实 = d 1 - d 2 ; S2: Calculate the theoretical power consumption d of the UAV based on the flight process status during the UAV's outbound and inbound times 理论 , and use the actual power consumption d 真实 and the theoretical power consumption d 理论 to calculate the natural loss amount d of the battery during the flight process 损耗 = d 真实 - d 理论 ; The theoretical power consumption d 理论 is calculated as follows: S21: Calculate the mass of air m required for acceleration during hovering according to the area S of the UAV propeller blades: m = ρSvt, where ρ is the density of air, v is the air acceleration speed, and t is the hovering time; S22: Calculate the power P exerted by the UAV on the air during the hovering time using the mass of air m; P = ρSgv 2 t; S23: Calculate the output current i of the UAV battery according to the power p: i = (P + P n ) / u, where u is the rated output voltage of the UAV battery, and P n is the power consumed by each device on the UAV except the propellers; S24: Calculate the power consumption d during the hovering state based on the time t of the UAV's hovering state 悬停 : S25: Statistically calculate the duration t of the drone in different flight states during flight, and calculate the theoretical power consumption d of the drone during flight 理论 : Among them, s represents different flight states during the flight of the UAV, and t s represents the duration of different flight states of the UAV, and a s is the proportionality coefficient of the power consumption of the UAV in different flight states to that in the hovering state; S3: The drone enters the warehouse for charging with a battery level of d 2 When the drone enters the warehouse for charging and connects to the charging dock, it communicates with the charging dock to obtain the coordinates and parameters of the charging dock. S4: After the power display of the drone charging reaches 100%, the charging is completed, the charging dock disconnects from the drone and stops charging. When the drone needs to execute the next task and leave the warehouse, measure the true power d of the drone 3 ; S5: Use the actual battery level d of the brand-new UAV battery 4 to calculate the theoretical charging amount D for this charging 理论 and the actual charging amount D 真实 : D 真实 = d 4 - d 3 、D 理论 = d 4 - d 2 ; S6: Calculate the battery loss D during this charging process 损耗 : D 损耗 = D 理论 - D 真实 ; S7: According to the flight duration t of the drone 1 and the charging duration t 2 calculate the loss rate d of the drone in the flight state 损耗率 and the loss rate D of the battery in the charging state 损耗率 : S8: According to the loss rate D 损耗率 and d 损耗率 evaluate the life of the UAV battery, and calculate the life index f of the UAV battery during this flight cycle: f = ln(a) + z 1 ln(d 损耗 ) + z 2 ln(D 损耗 ) where a is the attenuation rate of the chemical components in the UAV battery, z 1 is the influence coefficient of the loss rate in the flight state on the UAV battery life, z 2 is the influence coefficient of the loss rate in the charging state on the UAV battery life; S9: Compare the life index f with the life index threshold f(threshold): If f > f(threshold), it is determined that the battery life of the UAV is insufficient, and the UAV is intercepted during this outbound operation to prevent the UAV from leaving the warehouse and continuing to perform flight tasks, and the model of the UAV is sent to the UAV storage warehouse to remind the staff to replace the battery of the UAV; If f ≤ f(threshold), it is determined that the battery life of the UAV is sufficient, and the UAV can leave the warehouse smoothly.

2. The method for monitoring the charging status of an UAV storage warehouse according to claim 1, characterized in that, the different flight states of the UAV include one or more of ascending flight, descending flight, horizontal accelerating flight, horizontal decelerating flight, and hovering flight.

3. The method for monitoring the charging status of an UAV storage warehouse according to claim 1, characterized in that, it further includes: S10: After the power display of the drone charging reaches 100% in step S4, the charging time t of the drone this time is counted 3 , and the actual charging amount D 真实 is used to calculate the charging efficiency D of the drone this time 效率 : S11: Subtract the charging efficiency D 效率 from the rated charging efficiency D 额定效率 to obtain the fluctuation value D 波动 of the charging efficiency: D 波动 = D 额定效率 - D 效率 ; S12: Compare the fluctuation value D 波动 with the fluctuation threshold D 波动阈值 as follows: If D 波动 > D 波动阈值 , it is determined that the charging stand has a fault. The staff checks the corresponding charging stand according to the coordinates and parameters of the charging stand. If the charging stand is in normal condition, the drone battery has been damaged; If D 波动 ≤ D 波动阈值 , it is determined that the current charging status is normal.

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