CN117022715B - Method for supplying electric energy to inspection unmanned aerial vehicle - Google Patents
Method for supplying electric energy to inspection unmanned aerial vehicle Download PDFInfo
- Publication number
- CN117022715B CN117022715B CN202311296882.6A CN202311296882A CN117022715B CN 117022715 B CN117022715 B CN 117022715B CN 202311296882 A CN202311296882 A CN 202311296882A CN 117022715 B CN117022715 B CN 117022715B
- Authority
- CN
- China
- Prior art keywords
- electric energy
- last
- energy supply
- selsite
- station
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000007689 inspection Methods 0.000 title claims abstract description 131
- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000007726 management method Methods 0.000 claims abstract description 85
- 238000005265 energy consumption Methods 0.000 claims abstract description 27
- 238000004146 energy storage Methods 0.000 claims abstract description 24
- 230000008569 process Effects 0.000 claims abstract description 11
- 241001134453 Lista Species 0.000 claims description 45
- 241000222120 Candida <Saccharomycetales> Species 0.000 claims description 27
- 238000005457 optimization Methods 0.000 claims description 15
- 238000004364 calculation method Methods 0.000 claims description 12
- 230000009191 jumping Effects 0.000 claims description 3
- 238000012423 maintenance Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000001502 supplementing effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- B64U50/00—Propulsion; Power supply
- B64U50/30—Supply or distribution of electrical power
- B64U50/37—Charging when not in flight
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- B64U80/00—Transport or storage specially adapted for UAVs
- B64U80/20—Transport or storage specially adapted for UAVs with arrangements for servicing the UAV
- B64U80/25—Transport or storage specially adapted for UAVs with arrangements for servicing the UAV for recharging batteries; for refuelling
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- B64U2101/00—UAVs specially adapted for particular uses or applications
- B64U2101/25—UAVs specially adapted for particular uses or applications for manufacturing or servicing
- B64U2101/26—UAVs specially adapted for particular uses or applications for manufacturing or servicing for manufacturing, inspections or repairs
Abstract
The application relates to the technical field of unmanned aerial vehicle inspection, and provides an inspection unmanned aerial vehicle electric energy supply method, which comprises the following specific steps: the route planning module completes the route planning of the patrol according to the patrol station list and the starting and stopping stop positions of the unmanned aerial vehicle; the electric energy management module determines an electric energy supply station based on the principle of optimal efficiency according to instantaneous energy consumption, energy storage and electric energy supply station distribution in the unmanned aerial vehicle inspection process; the path planning adjustment module updates the routing inspection route planning based on the electric energy supply station information and the station information to be inspected; the inspection control module realizes inspection and electric energy supply control based on inspection route planning information. According to the method, the device and the system, the capacity parameters are updated periodically, then the pairing candidate set of the unmanned aerial vehicle and the charging station in the current period is dynamically constructed, the continuous iterative update of the optimal pairing result is realized, and then the optimal matching charging selection of the unmanned aerial vehicle and the charging station in the maximum limit time of the unmanned aerial vehicle power failure is realized, so that the power supply efficiency of the inspection unmanned aerial vehicle is improved.
Description
Technical Field
The application relates to the technical field of unmanned aerial vehicle inspection, in particular to an electric energy supply method for an inspection unmanned aerial vehicle.
Background
The statements in this section merely provide background information related to the present application and may not necessarily constitute prior art.
With the rapid advancement of informatization and industrialization, the penetration rate of electric equipment rapidly rises year by year, and the demand of various layers of society for power supply becomes larger and larger, so that the electric power facility becomes a key infrastructure for social development.
In order to ensure reliable and safe operation of the power transmission line, the power grid operation department needs to periodically carry out inspection and maintenance on the power grid system to ensure that faults and hidden dangers are eliminated, at present, the length of the power grid line in China is over millions of kilometers, the coverage area is extremely wide, a scheme of utilizing traditional manual inspection is difficult to succeed, most lines cannot be effectively inspected, and later, accident maintenance and periodic maintenance are adopted to make up, so that the potential safety hazard cannot be prevented in time, and negative influence is brought to social life. With technological progress, unmanned aerial vehicle patrols and becomes the effective mode that electric wire netting circuit patrolled, however, because the electric wire netting distributes extensively, the electric tower disperses in each corner, consequently, adopt unmanned aerial vehicle to patrol and examine and to meet the problem of endurance certainly, in order to deal with the problem of endurance, patrol and examine the process and need solve the electric energy supply problem, traditional round trip flight realizes charging, will be difficult to follow, in order to overcome current problem, the industry has put forward multiple scheme, including utilizing the high-voltage line to build the charging website, through solving the alignment problem of charging, realize unmanned aerial vehicle and berth to the charge station and realize the purpose of charging, in addition, the industry also put forward aerial distribution vapour ship and carry the power, unmanned aerial vehicle is through the vapour ship contact with the nearest and carrying the power of distance when not having the electricity, carry the scheme of aerial charge by the vapour ship to unmanned aerial vehicle.
Disclosure of Invention
In order to solve the problems, the application provides an inspection unmanned aerial vehicle electric energy supply method, capacity parameters are updated periodically, then a pairing candidate set of an unmanned aerial vehicle and a charging station in the current period is dynamically constructed, continuous iterative updating of an optimized pairing result is achieved, optimal matching charging selection of the unmanned aerial vehicle and the charging station in the maximum limit time of unmanned aerial vehicle electric energy failure is achieved, and accordingly inspection unmanned aerial vehicle electric energy supply efficiency is improved.
The application provides an inspection unmanned aerial vehicle electric energy supply method, based on an electric energy supply device composed of a line planning module, an electric energy management module, a path planning and adjusting module and an inspection control module, comprising the following specific steps:
step 1, a line planning module completes the routing inspection line planning according to an inspection station list and the starting and stopping stop positions of the unmanned aerial vehicle;
step 2, the electric energy management module determines an electric energy supply station based on the efficiency optimization principle according to instantaneous energy consumption, energy storage and electric energy supply station distribution in the unmanned aerial vehicle inspection process;
step 3, the path planning and adjusting module updates the routing inspection route planning based on the electric energy supply station information and the station information to be inspected;
and step 4, the inspection control module realizes inspection and electric energy supply control based on the inspection route planning information.
Preferably, in the step 1, the routing method adopts a shortest path planning.
Preferably, in the step 2, the specific steps of determining the electric energy recharging station by the electric energy management module are:
step 2.1, the electric energy management module updates a current instantaneous energy consumption value CurrentInstantPerCost according to a preset period P, wherein the calculation method of the current instantaneous energy consumption value CurrentInstantPerCost comprises the following steps: calculating the energy consumption PeriodEnergyCost (m) generated in the mth period divided by the sailing distance PeriodDistance (m) in the mth period to obtain an instantaneous energy consumption value InstantPerCost (m) in the mth period, and selecting one with the maximum energy consumption value from the instantaneous energy consumption values in the last N periods as a currentInstantPerCost, wherein P, N is completed through configuration;
step 2.2, the electric energy management module divides the current energy storage value CurrentEnergyStorage of the unmanned aerial vehicle by the current instantaneous energy consumption value CurrentInstantPerCost to obtain a residual sailing distance SurplunsDistance, then judging whether the SurplunsDistance is larger than the residual inspection line length, if so, determining that the number of electric energy supply stations is zero, and if not, jumping to step 2.3;
step 2.3, the electric energy management module takes the current position of the unmanned aerial vehicle as a center, takes Surplus distance as a radius, and determines charging stations existing in the radius as candidate charging stations to form a candidate charging station list Candida atesiiteList;
Step 2.4, the electric energy management module performs candidate path planning by combining with a candidate charging site list Candida parapsilosist, and outputs a candidate path list Candida parapsilosist;
2.5, the electric energy management module calculates SurplusNumSite (K) of the remaining inspection towers when the electric energy supply inspection is performed according to each candidate path K in the candidateplist, wherein the value of K is 1 and the number of the elements in the candidateplist list is K;
and 2.6, the power management module stores the patrol route with the value of 0 in SurplusNumSite (k) into a queue ListA, stores the patrol route with the value of not 0 into a queue ListB, and then determines the power supply station from the ListA or ListB based on the optimal efficiency principle.
Preferably, in the step 2.4, the specific method for outputting the candidateplathlist by the power management module is as follows:
step 2.4.1, the electric energy management module judges whether the Candida parapsiloside is empty or not, if yes, the step 2.4.4 is skipped, if no, a site Q is selected from the Candida parapsiloside, and the Q is deleted from the Candida parapsiloside;
step 2.4.2, the electric energy management module forms a patrol target set by the station Q and the electric tower to be patrol;
step 2.4.3, the electric energy management module performs shortest inspection path planning on the inspection target set, and places the inspection target set into a queue candidateplathlist and then jumps to step 2.4.1;
Step 2.4.4, outputting a Candida atthlist.
Preferably, in the step 2.5, the specific method for the power management module to calculate SurplusNumSite (k) is as follows:
step 2.5.1, setting k equal to 1 by the electric energy management module, and clearing SurplunmSite (k);
step 2.5.2, the electric energy management module judges whether K is greater than K, if yes, jump to step 2.5.6, if no, take CandidatePathList (K) out of Candida nathList, and jump to step 2.5.3;
step 2.5.3, the electric energy management module calculates a distance DisttanceTmp from the current position of the unmanned aerial vehicle to the electric energy supply station according to a planning path corresponding to CandidatePathList (k), calculates a current energy storage-DisttanceTmp, obtains electric energy storage site remained by the unmanned aerial vehicle reaching the electric energy supply station according to a planning line CandidatePathList (k) by using a current energy InstantPercost, jumps to step 2.5.4 if the electric energy storage site is greater than or equal to 0, assigns SurplusNumSite (k) as the total station number of the inspection operation if the electric energy storage site is less than 0, assigns k+1 to k, and jumps to step 2.5.2;
step 2.5.4, the electric energy management module inquires the amount of charge energy supply provided by the current electric energy supply station, and then takes min (energy storage ArriveSite+ EnergySupply, maxEnergyStorage) as the electric quantity energy supply after the unmanned aerial vehicle finishes electric energy supply, wherein min (A, B) is a smaller value in the value A, B, and the MaxEnergyStorage is the maximum energy storage value of the unmanned aerial vehicle;
Step 2.5.5, power management Module calculation
The energy aftersupply/currentlnstantpercost obtains a patrol distance after electric energy supply, then determines the last electric tower SiteLast capable of completing patrol after electric energy supply according to a patrol route, determines the number of electric towers positioned behind SiteLast on the patrol route CandidatePathList (k) as SurplusNumSite (k), assigns (k+1) to k, and jumps to step 2.5.2;
step 2.5.6, output SurplusNumSite (k).
Preferably, in the step 2.6, the efficiency optimization principle specifically includes:
optimum principle of efficacy a: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to the shortest route of the remaining routing inspection line is selected from ListB to serve as an electric energy supply station to be selected, the length of the shortest route of the routing inspection line is assigned to G1, G2 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, selecting an electric energy supply station corresponding to the shortest line from the ListA as an electric energy supply station to be selected, wherein the length of the shortest line is assigned to G1, G2 and G3 are set to be empty, the Type is set to be A, and the electric energy supply station to be selected is assigned to SelSite;
Optimum efficiency principle B: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to the shortest route of the remaining routing inspection line is selected from ListB to serve as an electric energy supply station to be selected, the length of the shortest route of the routing inspection line is assigned with G1, G2 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, selecting an electric energy supply station corresponding to a line with the highest residual electric energy of the electric energy supply station after electric energy supply from the ListA as an electric energy supply station to be selected, assigning the residual electric energy after the selected electric energy supply station finishes supplying to G2, setting G1 and G3 as null, setting Type as A, and assigning the electric energy supply station to be selected to SelSite;
optimum principle of efficacy C: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to the shortest route of the remaining routing inspection line is selected from ListB to serve as an electric energy supply station to be selected, the length of the shortest route of the routing inspection line is assigned with G1, G2 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, calculating the total power supply amount TotalSupplySiteInListA (y) of power supply of each power supply station SiteInListA (y) in the ListA in a preset history period T_range, calculating the residual power SurplusEnergySiteInListA (y) of each station after the current power supply is completed, obtaining the margin coefficient Coefficient (y) of each station through calculation SurplusEnergySiteInListA (y)/TotalSupplySiteInListA (y), selecting the power supply station with the maximum margin coefficient as the power supply station to be selected, assigning the maximum margin coefficient to G3, setting G1 and G2 to be null, setting Type to be A, and assigning the power supply station to be selected to SelSite, wherein the T_range is completed through configuration;
Optimum principle of efficacy D: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to a line with the largest residual electric energy of the electric energy supply station after electric energy supply is selected from ListB to serve as an electric energy supply station to be selected, the residual electric energy after the electric energy supply station to be selected is assigned to G2, G1 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, selecting an electric energy supply station corresponding to the shortest line from the ListA as an electric energy supply station to be selected, wherein the length of the shortest line is assigned to G1, G2 and G3 are set to be empty, the Type is set to be A, and the electric energy supply station to be selected is assigned to SelSite;
optimum principle of efficacy E: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to a line with the largest residual electric energy of the electric energy supply station after electric energy supply is selected from ListB to serve as an electric energy supply station to be selected, the residual electric energy after the electric energy supply station to be selected is assigned to G2, G1 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, selecting an electric energy supply station corresponding to the line with the highest residual electric energy of the electric energy supply station after electric energy supply from the ListA as an electric energy supply station to be selected, assigning the residual electric energy after the electric energy supply station to be selected is completed to G2, setting G1 and G3 as null, setting Type as A, and assigning the electric energy supply station to be selected to SelSite;
Optimum principle F of efficacy: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to a line with the largest residual electric energy of the electric energy supply station after electric energy supply is selected from ListB to serve as an electric energy supply station to be selected, the residual electric energy after the electric energy supply station to be selected is assigned to G2, G1 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, calculating the total power supply amount TotalSupplySiteInListA (y) of power supply of each power supply station SiteInListA (y) in the ListA in a preset history period, calculating the residual power SurplusEnergySiteInListA (y) of each station after the current power supply is completed, obtaining the margin coefficient Coefficient (y) of each station through calculation SurplusEnergySiteInListA (y)/TotalSupplySiteInListA (y), selecting the power supply station with the largest margin coefficient as the power supply station to be selected, assigning the maximum margin coefficient to G3, setting G1 and G2 as null, setting Type as A, and assigning the power supply station to be selected to SelSite, wherein T_random is completed through configuration;
the values of G1, G2, G3, type, selSite, G1_last, G2_last, G3_last, type_last, selSite_last are the efficacy reference parameters, and the initial values are all set to be null.
Preferably, in step 2.6, the power management module performs the iterative updating according to the period P and then determines the current charging station CurrestSite according to the optimal principle, and updates the states of g1_last, g2_last, g3_last, type_last, selsite_last, and the specific method is as follows:
2.6.1, if SelSite_last is empty, sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last, and determining SelSite as a current charging station CurestSite;
2.6.2 if SelSite _ last is not empty,
2.6.2.1 if the type_last value is A, the Type value is A
2.6.2.1.1, optimum efficacy principle a or D: if G1 is smaller than G1_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
2.6.2.1.2, optimum efficacy principle B or E: if G2 is greater than G2_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
2.6.2.1.3, optimum efficacy principle C or F: if G3 is greater than G3_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
2.6.2.2 if the type_last is A and the Type is B, determining the SelSite_last as the current charging station CurrestSite;
2.6.2.3 if the type_last is B and the Type is A, determining the SelSite as the current charging station CurrestSite, and sequentially assigning the SelSite, G1, G2, G3 and Type to the SelSite_last, the G1_last, the G2_last, the G3_last and the type_last;
2.6.2.4 if the type_last value is B, the Type value is B;
2.6.2.4.1, optimum efficacy principle a or B or C: if G1 is smaller than G1_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
2.6.2.4.2, optimum efficiency principle D or E or F: if G2 is greater than G2_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, selsite_last is determined as the current charging site CurrestSite.
Preferably, in step 4, the inspection control module implements inspection and electric energy supply control based on inspection route planning information, and when the unmanned aerial vehicle adopts CurrestSite to charge, all selsite_last, g1_last, g2_last, g3_last, and type_last are set to be empty.
Preferably, in the step 2 and the step 3, the electric energy supply station performs iterative updating based on the method in the step 2 according to the period P, and adjusts the electric energy supply inspection route in the inspection process according to the iterative updating result.
Preferably, in the step 3, the path planning adjustment module iteratively updates the inspection route according to a minimum path planning principle based on the replenishment station information and the station information to be inspected.
Compared with the prior art, the beneficial effects of this application are:
according to the method, the capacity parameters are updated periodically, the pairing candidate set of the unmanned aerial vehicle and the charging station in the current period is dynamically built, the unmanned aerial vehicle and the charging station in the current period pairing candidate set are paired and optimally selected based on the efficiency optimal principle, finally, the continuous iterative updating of the optimal pairing result is realized by comparing the efficiency difference of the current pairing optimal selection result and the historical non-execution optimal pairing selection result, and the optimal matching charging selection of the unmanned aerial vehicle and the charging station in the maximum limit time of the unmanned aerial vehicle electric energy failure is realized, so that the energy supply efficiency of the inspection unmanned aerial vehicle is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application.
Figure 1 is a schematic flow chart of a method according to one embodiment of the present application,
figure 2 is a schematic diagram of the system components of an embodiment of the present application,
FIG. 3 is a schematic illustration of an implementation of an embodiment of the present application.
Detailed Description
The present application is further described below with reference to the drawings and examples.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments in accordance with the present disclosure. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
In the present disclosure, terms such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "side", "bottom", and the like indicate an azimuth or a positional relationship based on the azimuth or the positional relationship shown in the drawings, are merely relational terms determined for convenience in describing structural relationships of the various components or elements of the present disclosure, and do not denote any one of the components or elements of the present disclosure, and are not to be construed as limiting the present disclosure.
Example 1
As shown in fig. 1 to 3, the present application provides an inspection unmanned aerial vehicle electric energy supply device, which is composed of a line planning module, an electric energy management module, a path planning adjustment module and an inspection control module, wherein the functions of each module are as follows:
the line planning module is used for completing the routing inspection route planning according to the inspection site list;
the electric energy management module is used for determining an electric energy supply station based on the efficiency optimization principle according to instantaneous energy consumption, energy storage and electric energy supply station distribution in the unmanned aerial vehicle inspection process;
the path planning adjustment module is used for updating the routing inspection route planning based on the information of the supply station and the information of the station to be inspected;
the inspection control module is used for realizing inspection and electric energy supply control based on inspection route planning information.
Based on the inspection robot electric energy supply device, the application also provides an inspection unmanned aerial vehicle electric energy supply method, which comprises the following specific steps:
step 1, a line planning module completes the routing inspection line planning according to an inspection station list and the starting and stopping stop positions of the unmanned aerial vehicle;
step 2, the electric energy management module determines an electric energy supply station based on the efficiency optimization principle according to instantaneous energy consumption, energy storage and electric energy supply station distribution in the unmanned aerial vehicle inspection process;
Step 3, the path planning and adjusting module updates the routing inspection route planning based on the electric energy supply station information and the station information to be inspected;
and step 4, the inspection control module realizes inspection and electric energy supply control based on the inspection route planning information.
Specifically, in the step 1, the routing inspection route planning method adopts shortest path planning.
Specifically, the shortest path planning method takes a starting point of the unmanned aerial vehicle as a starting point, and sequentially connects the inspection stations closest to the starting point until the last inspection station is connected.
Preferably, in the step 2, the specific steps of determining the electric energy recharging station by the electric energy management module are:
step 2.1, the electric energy management module updates a current instantaneous energy consumption value CurrentInstantPerCost according to a preset period P, wherein the calculation method of the current instantaneous energy consumption value CurrentInstantPerCost comprises the following steps: calculating the energy consumption PeriodEnergyCost (m) generated in the mth period divided by the sailing distance PeriodDistance (m) in the mth period to obtain an instantaneous energy consumption value InstantPerCost (m) in the mth period, and selecting one with the maximum energy consumption value from the instantaneous energy consumption values in the last N periods as a currentInstantPerCost, wherein P, N is completed through configuration;
Step 2.2, the electric energy management module divides the current energy storage value CurrentEnergyStorage of the unmanned aerial vehicle by the current instantaneous energy consumption value CurrentInstantPerCost to obtain a residual sailing distance SurplunsDistance, then judging whether the SurplunsDistance is larger than the residual inspection line length, if so, determining that the number of electric energy supply stations is zero, and if not, jumping to step 2.3;
step 2.3, the electric energy management module takes the current position of the unmanned aerial vehicle as a center, takes Surplus distance as a radius, and determines charging stations existing in the radius as candidate charging stations to form a candidate charging station list Candida atesiiteList;
step 2.4, the electric energy management module performs candidate path planning by combining with a candidate charging site list Candida parapsilosist, and outputs a candidate path list Candida parapsilosist;
2.5, the electric energy management module calculates SurplusNumSite (K) of the remaining inspection towers when the electric energy supply inspection is performed according to each candidate path K in the candidateplist, wherein the value of K is 1 and the number of the elements in the candidateplist list is K;
and 2.6, the power management module stores the patrol route with the value of 0 in SurplusNumSite (k) into a queue ListA, stores the patrol route with the value of not 0 into a queue ListB, and then determines the power supply station from the ListA or ListB based on the optimal efficiency principle.
Specifically, in the step 2.4, the specific method for outputting the candidateplathlist by the electric energy management module is as follows:
step 2.4.1, the electric energy management module judges whether the Candida parapsiloside is empty or not, if yes, the step 2.4.4 is skipped, if no, a site Q is selected from the Candida parapsiloside, and the Q is deleted from the Candida parapsiloside;
step 2.4.2, the electric energy management module forms a patrol target set by the station Q and the electric tower to be patrol;
step 2.4.3, the electric energy management module performs shortest inspection path planning on the inspection target set, and places the inspection target set into a queue candidateplathlist and then jumps to step 2.4.1;
step 2.4.4, outputting a Candida atthlist.
Specifically, in the step 2.5, the specific method for the power management module to calculate SurplusNumSite (k) is as follows:
step 2.5.1, setting k equal to 1 by the electric energy management module, and clearing SurplunmSite (k);
step 2.5.2, the electric energy management module judges whether K is greater than K, if yes, jump to step 2.5.6, if no, take CandidatePathList (K) out of Candida nathList, and jump to step 2.5.3;
step 2.5.3, the electric energy management module calculates a distance DisttanceTmp from the current position of the unmanned aerial vehicle to the electric energy supply station according to a planning path corresponding to CandidatePathList (k), calculates a current energy storage-DisttanceTmp, obtains electric energy storage site remained by the unmanned aerial vehicle reaching the electric energy supply station according to a planning line CandidatePathList (k) by using a current energy InstantPercost, jumps to step 2.5.4 if the electric energy storage site is greater than or equal to 0, assigns SurplusNumSite (k) as the total station number of the inspection operation if the electric energy storage site is less than 0, assigns k+1 to k, and jumps to step 2.5.2;
Step 2.5.4, the electric energy management module inquires the amount of charge energy supply provided by the current electric energy supply station, and then takes min (energy storage ArriveSite+ EnergySupply, maxEnergyStorage) as the electric quantity energy supply after the unmanned aerial vehicle finishes electric energy supply, wherein min (A, B) is a smaller value in the value A, B, and the MaxEnergyStorage is the maximum energy storage value of the unmanned aerial vehicle;
step 2.5.5, power management Module calculation
The energy aftersupply/currentlnstantpercost obtains a patrol distance after electric energy supply, then determines the last electric tower SiteLast capable of completing patrol after electric energy supply according to a patrol route, determines the number of electric towers positioned behind SiteLast on the patrol route CandidatePathList (k) as SurplusNumSite (k), assigns (k+1) to k, and jumps to step 2.5.2;
step 2.5.6, output SurplusNumSite (k).
Specifically, in the step 2.6, the efficiency optimization principle specifically includes:
optimum principle of efficacy a: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to the shortest route of the remaining routing inspection line is selected from ListB to serve as an electric energy supply station to be selected, the length of the shortest route of the routing inspection line is assigned to G1, G2 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, selecting an electric energy supply station corresponding to the shortest line from the ListA as an electric energy supply station to be selected, wherein the length of the shortest line is assigned to G1, G2 and G3 are set to be empty, the Type is set to be A, and the electric energy supply station to be selected is assigned to SelSite;
Optimum efficiency principle B: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to the shortest route of the remaining routing inspection line is selected from ListB to serve as an electric energy supply station to be selected, the length of the shortest route of the routing inspection line is assigned with G1, G2 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, selecting an electric energy supply station corresponding to a line with the highest residual electric energy of the electric energy supply station after electric energy supply from the ListA as an electric energy supply station to be selected, assigning the residual electric energy after the selected electric energy supply station finishes supplying to G2, setting G1 and G3 as null, setting Type as A, and assigning the electric energy supply station to be selected to SelSite;
optimum principle of efficacy C: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to the shortest route of the remaining routing inspection line is selected from ListB to serve as an electric energy supply station to be selected, the length of the shortest route of the routing inspection line is assigned with G1, G2 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, calculating the total power supply amount TotalSupplySiteInListA (y) of power supply of each power supply station SiteInListA (y) in the ListA in a preset history period T_range, calculating the residual power SurplusEnergySiteInListA (y) of each station after the current power supply is completed, obtaining the margin coefficient Coefficient (y) of each station through calculation SurplusEnergySiteInListA (y)/TotalSupplySiteInListA (y), selecting the power supply station with the maximum margin coefficient as the power supply station to be selected, assigning the maximum margin coefficient to G3, setting G1 and G2 to be null, setting Type to be A, and assigning the power supply station to be selected to SelSite, wherein the T_range is completed through configuration;
Optimum principle of efficacy D: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to a line with the largest residual electric energy of the electric energy supply station after electric energy supply is selected from ListB to serve as an electric energy supply station to be selected, the residual electric energy after the electric energy supply station to be selected is assigned to G2, G1 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, selecting an electric energy supply station corresponding to the shortest line from the ListA as an electric energy supply station to be selected, wherein the length of the shortest line is assigned to G1, G2 and G3 are set to be empty, the Type is set to be A, and the electric energy supply station to be selected is assigned to SelSite;
optimum principle of efficacy E: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to a line with the largest residual electric energy of the electric energy supply station after electric energy supply is selected from ListB to serve as an electric energy supply station to be selected, the residual electric energy after the electric energy supply station to be selected is assigned to G2, G1 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, selecting an electric energy supply station corresponding to the line with the highest residual electric energy of the electric energy supply station after electric energy supply from the ListA as an electric energy supply station to be selected, assigning the residual electric energy after the electric energy supply station to be selected is completed to G2, setting G1 and G3 as null, setting Type as A, and assigning the electric energy supply station to be selected to SelSite;
Optimum principle F of efficacy: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to a line with the largest residual electric energy of the electric energy supply station after electric energy supply is selected from ListB to serve as an electric energy supply station to be selected, the residual electric energy after the electric energy supply station to be selected is assigned to G2, G1 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, calculating the total power supply amount TotalSupplySiteInListA (y) of power supply of each power supply station SiteInListA (y) in the ListA in a preset history period, calculating the residual power SurplusEnergySiteInListA (y) of each station after the current power supply is completed, obtaining the margin coefficient Coefficient (y) of each station through calculation SurplusEnergySiteInListA (y)/TotalSupplySiteInListA (y), selecting the power supply station with the largest margin coefficient as the power supply station to be selected, assigning the maximum margin coefficient to G3, setting G1 and G2 as null, setting Type as A, and assigning the power supply station to be selected to SelSite, wherein T_random is completed through configuration;
the values of G1, G2, G3, type, selSite, G1_last, G2_last, G3_last, type_last, selSite_last are the efficacy reference parameters, and the initial values are all set to be null.
Specifically, in step 2.6, the power management module performs iterative update according to the period P according to the optimal principle, then determines the current charging station CurrestSite, and updates the states of g1_last, g2_last, g3_last, type_last, and selsite_last, and the specific method is as follows:
2.6.1, if SelSite_last is empty, sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last, and determining SelSite as a current charging station CurestSite;
2.6.2 if SelSite _ last is not empty,
2.6.2.1 if the type_last value is A, the Type value is A
2.6.2.1.1, optimum efficacy principle a or D: if G1 is smaller than G1_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
2.6.2.1.2, optimum efficacy principle B or E: if G2 is greater than G2_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
2.6.2.1.3, optimum efficacy principle C or F: if G3 is greater than G3_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
2.6.2.2 if the type_last is A and the Type is B, determining the SelSite_last as the current charging station CurrestSite;
2.6.2.3 if the type_last is B and the Type is A, determining the SelSite as the current charging station CurrestSite, and sequentially assigning the SelSite, G1, G2, G3 and Type to the SelSite_last, the G1_last, the G2_last, the G3_last and the type_last;
2.6.2.4 if the type_last value is B, the Type value is B;
2.6.2.4.1, optimum efficacy principle a or B or C: if G1 is smaller than G1_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
2.6.2.4.2, optimum efficiency principle D or E or F: if G2 is greater than G2_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, selsite_last is determined as the current charging site CurrestSite.
Specifically, in step 4, the inspection control module realizes inspection and electric energy supply control based on the inspection route planning information, and when the unmanned aerial vehicle adopts CurrestSite to charge, all selsite_last, g1_last, g2_last, g3_last and type_last are set to be empty.
Specifically, in the step 2 and the step 3, the electric energy supply station performs iterative updating based on the method of the step 2 according to the period P, and adjusts the electric energy supply inspection route in the inspection process according to the iterative updating result.
Specifically, in the step 3, the path planning adjustment module iteratively updates the inspection route according to the minimum path planning principle based on the information of the replenishment station and the information of the station to be inspected.
Specific embodiments of an inspection robot power supply apparatus are described below with specific examples:
as shown in fig. 3, the electric towers to be inspected in this embodiment include 6 electric towers, namely, electric tower 0, electric tower 1, electric tower 2, electric tower 3, electric tower 4 and electric tower 5. In the example, two stations for supplying electric energy are present, namely station 0 and station 1.
According to the method, after an unmanned aerial vehicle receives a routing inspection task, a route planning module completes routing inspection route planning according to a routing inspection site list and a starting and stopping stop position of the unmanned aerial vehicle, and the planning result is that the unmanned aerial vehicle performs routing inspection according to an unmanned aerial vehicle starting and inspection point- > electric tower 0- > electric tower 1- > electric tower 2- > electric tower 3- > electric tower 4- > electric tower 5- > unmanned aerial vehicle routing inspection stop point;
Then, according to the supplement 2, the electric energy management module determines the electric energy replenishment sites according to the instantaneous energy consumption, energy storage and electric energy replenishment site distribution in the unmanned aerial vehicle inspection process based on the efficiency optimization principle, in this embodiment, the electric energy management module updates the capacity parameters according to the preset period P, including CurrentInstantPerCost, surplusDistance, candidateSiteList, candidatePathList, surplusNumSite, according to steps 2.1 to 2.5, finally, according to step 2.6, updates ListA and ListB, then carries out assignment of G1, G2, G3, type and SelSite according to the efficiency optimization principle A, B, C, D, E, F, finally, according to the values of G1, G2, G3, type, selSite and g1_last, g2_last, g3_last, type_last and selsite_last, update g1_last, g2_last, g3_last, type_last and selte_last according to the efficiency optimization principle A, B, C, D, E, F, and determines the charging efficiency principle selected after the update, and finally, selects the whole efficiency principles of the charging CurrestSite a as the optimal implementation description example below:
optimum principle of efficacy a: in the embodiment, N is given a value of 1, if it appears that, according to period P, it is detected for the first time that there is an electric energy replenishment station within the radius range of the sulplus distance in the t1 st period, at this time, the electric energy management module calculates that the candidatelist includes only the electric energy replenishment station 0, the candidateplatlist is shown in detail by the dashed arrow in fig. 3, the sulplus numsite is 2 (i.e. there are two places to the electric tower 5 and the unmanned airplane tour stop point that cannot be completed, if the distance is 5 km), and therefore updates the period to 5km, sets G2 and G3 to null, sets Type to B, selSite as the electric energy replenishment station 0, and then sequentially assigns the SelSite, G1, G2, G3 and Type to the selsite_last, g1_last, g2_last, g3_last, and thus, and determines that the current charging site is the current site according to the efficiency optimization principle a, according to the step 2.6.1. Then, if it is detected that the electric energy replenishment station includes the electric energy replenishment station 0 and the electric energy replenishment station 1 within the radius range of the Surplus distance in the t2 th period, the electric energy management module calculates that the electric energy management module includes the electric energy replenishment station 0 and the electric energy replenishment station 1 to the Candida takieseiteList, and then provides the corresponding inspection route Candida takihlist (1) corresponds to the electric energy replenishment station 0 and Candida takioshlist (2) corresponds to the electric energy replenishment station 1) for the two electric energy replenishment stations, wherein the inspection route and the remaining station information of the electric energy replenishment station 0 are unchanged (namely, the inspection route is detailed with a dotted arrow, the Surplus NumSite (1) takes a value of 2), and the inspection route of the electric energy replenishment station 1 is detailed with a solid arrow in FIG. 3 and the Surplus NumSite (2) takes a value of 0, next, according to step 2.6, the power management module stores the patrol route having a value of 0 in SurplusNumSite (k) to queue ListA, stores the patrol route having a value other than 0 to queue ListB while Type is set to a, selSite is set to power replenishment site 1, since sullugntsite (2) is equal to 0, candidatehlist (2) is stored in ListA, since sullugntsite (1) is equal to 2, candidatehlist (1) is stored in ListB, since type_last has a value of B and Type has a value of a, and consequently, next, according to step 2.6.2.3, selSite is determined to be the current charging site CurrestSite, and setsite, G1, G2, G3, type are sequentially assigned to setsite_last, g1_last, g2_last, g3_last, type_last. As can be seen from this embodiment, the whole process involves the selection of multiple charging lines, the first selection result is that the unmanned aerial vehicle is charged at the electric energy supply station 0, and then the continuous voyage of the remaining voyage cannot be completed, so that the subsequent requirement and secondary charging are further caused, so that the efficiency is low. The t1 th cycle is determined to be 1, the t2 nd cycle is determined to be 2), the unmanned aerial vehicle and the charging station in the current cycle pairing candidate set are paired and optimally selected based on the efficiency optimization principle (in the embodiment, the t2 nd cycle is selected through the efficiency optimization principle because of two candidate sets), finally, the optimal matching charging selection (in the embodiment, the scheme that the inspection can be completed after the inspection by finally selecting one time of charging is completed) of the unmanned aerial vehicle and the charging station in the current pairing optimization selection result and the historical non-execution optimization pairing selection result is compared (in the embodiment, the optimal selection result of the t2 nd cycle is compared with the optimal selection result of the t1 st cycle, and finally, the scheme of the electric energy supplementing station 1 selected by the t2 nd cycle is selected), the continuous iterative updating of the optimal pairing result is realized, and the maximum limit time of the unmanned aerial vehicle electric energy failure (in the embodiment, the electric energy failure maximum limit time corresponds to the first determination of the electric energy supplementing station 0, but the final moment before the electric tower 2 arrives) is realized, thereby promote inspection unmanned aerial vehicle electric energy supply efficiency.
The implementation principles of the efficiency optimal principle B, the efficiency optimal principle C, the efficiency optimal principle D, the efficiency optimal principle E and the efficiency optimal principle F are consistent, and are not described repeatedly.
According to the method, the capacity parameters are updated periodically, the pairing candidate set of the unmanned aerial vehicle and the charging station in the current period is dynamically built, the unmanned aerial vehicle and the charging station in the current period pairing candidate set are paired and optimally selected based on the efficiency optimal principle, finally, the continuous iterative updating of the optimal pairing result is realized by comparing the efficiency difference of the current pairing optimal selection result and the historical non-execution optimal pairing selection result, and the optimal matching charging selection of the unmanned aerial vehicle and the charging station in the maximum limit time of the unmanned aerial vehicle electric energy failure is realized, so that the energy supply efficiency of the inspection unmanned aerial vehicle is improved.
The foregoing is merely a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and variations may be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.
While the foregoing description of the embodiments of the present application has been presented in conjunction with the drawings, it should be understood that it is not intended to limit the scope of the application, but rather, it is intended to cover all modifications or variations which may be resorted to without undue burden to those skilled in the art, having the benefit of the present application.
Claims (3)
1. The method for supplying the electrical energy to the inspection unmanned aerial vehicle is characterized by comprising the following specific steps of:
step 1, a line planning module completes the routing inspection line planning according to an inspection station list and the starting and stopping stop positions of the unmanned aerial vehicle;
step 2, the electric energy management module determines an electric energy supply station based on the efficiency optimization principle according to instantaneous energy consumption, energy storage and electric energy supply station distribution in the unmanned aerial vehicle inspection process;
step 3, the path planning and adjusting module updates the routing inspection route planning based on the electric energy supply station information and the station information to be inspected;
step 4, the inspection control module realizes inspection and electric energy supply control based on the inspection route planning information;
in the step 1, the routing inspection route planning method adopts shortest path planning;
in the step 2, the specific steps of determining the electric energy supply station by the electric energy management module are as follows:
step 2.1, the electric energy management module updates a current instantaneous energy consumption value CurrentInstantPerCost according to a preset period P, wherein the calculation method of the current instantaneous energy consumption value CurrentInstantPerCost comprises the following steps: calculating the energy consumption PeriodEnergyCost (m) generated in the mth period divided by the sailing distance PeriodDistance (m) in the mth period to obtain an instantaneous energy consumption value InstantPerCost (m) in the mth period, and selecting one with the maximum energy consumption value from the instantaneous energy consumption values in the last N periods as a currentInstantPerCost, wherein P, N is completed through configuration;
Step 2.2, the electric energy management module divides the current energy storage value CurrentEnergyStorage of the unmanned aerial vehicle by the current instantaneous energy consumption value CurrentInstantPerCost to obtain a residual sailing distance SurplunsDistance, then judging whether the SurplunsDistance is larger than the residual inspection line length, if so, determining that the number of electric energy supply stations is zero, and if not, jumping to step 2.3;
step 2.3, the electric energy management module takes the current position of the unmanned aerial vehicle as a center, takes Surplus distance as a radius, and determines charging stations existing in the radius as candidate charging stations to form a candidate charging station list Candida atesiiteList;
step 2.4, the electric energy management module performs candidate path planning by combining with a candidate charging site list Candida parapsilosist, and outputs a candidate path list Candida parapsilosist;
2.5, the electric energy management module calculates SurplusNumSite (K) of the remaining inspection towers when the electric energy supply inspection is performed according to each candidate path K in the candidateplist, wherein the value of K is 1 and the number of the elements in the candidateplist list is K;
step 2.6, the electric energy management module stores the patrol route with the value of 0 in SurplusNumSite (k) into a queue ListA, stores the patrol route with the value of not 0 into a queue ListB, and then determines an electric energy supply station from the ListA or ListB based on the optimal efficiency principle;
In the step 2.4, the specific method for outputting the candidatepphlist by the electric energy management module is as follows:
step 2.4.1, the electric energy management module judges whether the Candida parapsiloside is empty or not, if yes, the step 2.4.4 is skipped, if no, a site Q is selected from the Candida parapsiloside, and the Q is deleted from the Candida parapsiloside;
step 2.4.2, the electric energy management module forms a patrol target set by the station Q and the electric tower to be patrol;
step 2.4.3, the electric energy management module performs shortest inspection path planning on the inspection target set, and places the inspection target set into a queue candidateplathlist and then jumps to step 2.4.1;
step 2.4.4, outputting a Candida natepisList;
in the step 2.5, the specific method for the power management module to calculate SurplusNumSite (k) is as follows:
step 2.5.1, setting k equal to 1 by the electric energy management module, and clearing SurplunmSite (k);
step 2.5.2, the electric energy management module judges whether K is greater than K, if yes, jump to step 2.5.6, if no, take CandidatePathList (K) out of Candida nathList, and jump to step 2.5.3;
step 2.5.3, the electric energy management module calculates a distance DisttanceTmp from the current position of the unmanned aerial vehicle to the electric energy supply station according to a planning path corresponding to CandidatePathList (k), calculates a current energy storage-DisttanceTmp, obtains electric energy storage site remained by the unmanned aerial vehicle reaching the electric energy supply station according to a planning line CandidatePathList (k) by using a current energy InstantPercost, jumps to step 2.5.4 if the electric energy storage site is greater than or equal to 0, assigns SurplusNumSite (k) as the total station number of the inspection operation if the electric energy storage site is less than 0, assigns k+1 to k, and jumps to step 2.5.2;
Step 2.5.4, the electric energy management module inquires the amount of charge energy supply provided by the current electric energy supply station, and then takes min (energy storage ArriveSite+ EnergySupply, maxEnergyStorage) as the electric quantity energy supply after the unmanned aerial vehicle finishes electric energy supply, wherein min (A, B) is a smaller value in the value A, B, and the MaxEnergyStorage is the maximum energy storage value of the unmanned aerial vehicle;
step 2.5.5, power management Module calculation
The energy aftersupply/currentlnstantpercost obtains a patrol distance after electric energy supply, then determines the last electric tower SiteLast capable of completing patrol after electric energy supply according to a patrol route, determines the number of electric towers positioned behind SiteLast on the patrol route CandidatePathList (k) as SurplusNumSite (k), assigns (k+1) to k, and jumps to step 2.5.2;
step 2.5.6, output SurplusNumSite (k);
in the step 2.6, the efficiency optimization principle specifically includes:
optimum principle of efficacy a: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to the shortest route of the remaining routing inspection line is selected from ListB to serve as an electric energy supply station to be selected, the length of the shortest route of the routing inspection line is assigned to G1, G2 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, selecting an electric energy supply station corresponding to the shortest line from the ListA as an electric energy supply station to be selected, wherein the length of the shortest line is assigned to G1, G2 and G3 are set to be empty, the Type is set to be A, and the electric energy supply station to be selected is assigned to SelSite;
Optimum efficiency principle B: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to the shortest route of the remaining routing inspection line is selected from ListB to serve as an electric energy supply station to be selected, the length of the shortest route of the routing inspection line is assigned with G1, G2 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, selecting an electric energy supply station corresponding to the line with the highest residual electric energy of the electric energy supply station after electric energy supply from the ListA as an electric energy supply station to be selected, assigning the residual electric energy after the selected electric energy supply station finishes supplying to G2, setting G1 and G3 as null, setting Type as A, and assigning the electric energy supply station to be selected to SelSite;
optimum principle of efficacy C: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to the shortest route of the remaining routing inspection line is selected from ListB to serve as an electric energy supply station to be selected, the length of the shortest route of the routing inspection line is assigned with G1, G2 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, calculating the total power supply amount TotalSupplySiteInListA (y) of power supply of each power supply station SiteInListA (y) in the ListA in a preset history period T_range, calculating the residual power SurplusEnergySiteInListA (y) of each station after the current power supply is completed, obtaining the margin coefficient Coefficient (y) of each station through calculation SurplusEnergySiteInListA (y)/TotalSupplySiteInListA (y), selecting the power supply station with the maximum margin coefficient as the power supply station to be selected, assigning the maximum margin coefficient to G3, setting G1 and G2 to be null, setting Type to be A, and assigning the power supply station to be selected to SelSite, wherein the T_range is completed through configuration;
Optimum principle of efficacy D: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to a line with the largest residual electric energy of the electric energy supply station after electric energy supply is selected from ListB to serve as an electric energy supply station to be selected, the residual electric energy after the electric energy supply station to be selected is assigned to G2, G1 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, selecting an electric energy supply station corresponding to the shortest line from the ListA as an electric energy supply station to be selected, wherein the length of the shortest line is assigned to G1, G2 and G3 are set to be empty, the Type is set to be A, and the electric energy supply station to be selected is assigned to SelSite;
optimum principle of efficacy E: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to a line with the largest residual electric energy of the electric energy supply station after electric energy supply is selected from ListB to serve as an electric energy supply station to be selected, the residual electric energy after the electric energy supply station to be selected is assigned to G2, G1 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, selecting an electric energy supply station corresponding to the line with the highest residual electric energy of the electric energy supply station after electric energy supply from the ListA as an electric energy supply station to be selected, assigning the residual electric energy after the electric energy supply station to be selected is completed to G2, setting G1 and G3 as null, setting Type as A, and assigning the electric energy supply station to be selected to SelSite;
Optimum principle F of efficacy: the electric energy management module judges whether ListA is empty or not, if so, an electric energy supply station corresponding to a line with the largest residual electric energy of the electric energy supply station after electric energy supply is selected from ListB to serve as an electric energy supply station to be selected, the residual electric energy after the electric energy supply station to be selected is assigned to G2, G1 and G3 are set to be empty, type is set to be B, and the electric energy supply station to be selected is assigned to SelSite; if not, calculating the total power supply amount TotalSupplySiteInListA (y) of power supply of each power supply station SiteInListA (y) in the ListA in a preset history period, calculating the residual power SurplusEnergySiteInListA (y) of each station after the current power supply is completed, obtaining the margin coefficient Coefficient (y) of each station through calculation SurplusEnergySiteInListA (y)/TotalSupplySiteInListA (y), selecting the power supply station with the largest margin coefficient as the power supply station to be selected, assigning the maximum margin coefficient to G3, setting G1 and G2 as null, setting Type as A, and assigning the power supply station to be selected to SelSite, wherein T_random is completed through configuration;
the G1, G2, G3, type, selSite, G1_last, G2_last, G3_last, type_last, selSite_last are efficacy reference parameters, and the initial values are all set to be null;
In the step 2.6, the electric energy management module performs iterative updating according to the optimal principle and then determines according to the period P, determines the current charging station CurrestSite, and updates the states of g1_last, g2_last, g3_last, type_last and selsite_last, and the specific method is as follows:
2.6.1, if SelSite_last is empty, sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last, and determining SelSite as a current charging station CurestSite;
2.6.2 if SelSite _ last is not empty,
2.6.2.1 if the type_last value is A, the Type value is A
2.6.2.1.1, optimum efficacy principle a or D: if G1 is smaller than G1_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
2.6.2.1.2, optimum efficacy principle B or E: if G2 is greater than G2_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
2.6.2.1.3, optimum efficacy principle C or F: if G3 is greater than G3_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
2.6.2.2 if the type_last is A and the Type is B, determining the SelSite_last as the current charging station CurrestSite;
2.6.2.3 if the type_last is B and the Type is A, determining the SelSite as the current charging station CurrestSite, and sequentially assigning the SelSite, G1, G2, G3 and Type to the SelSite_last, the G1_last, the G2_last, the G3_last and the type_last;
2.6.2.4 if the type_last value is B, the Type value is B;
2.6.2.4.1, optimum efficacy principle a or B or C: if G1 is smaller than G1_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
2.6.2.4.2, optimum efficiency principle D or E or F: if G2 is greater than G2_last, determining SelSite as the current charging station CurrestSite, and sequentially assigning SelSite, G1, G2, G3 and Type to SelSite_last, G1_last, G2_last, G3_last and type_last; otherwise, the SelSite_last is determined to be the current charging station CurrestSite;
In the step 4, the inspection control module realizes inspection and electric energy supply control based on inspection route planning information, and when the unmanned aerial vehicle adopts CurrentSite to charge, all the SelSite_last, G1_last, G2_last, G3_last and type_last are set to be empty.
2. The inspection robot electrical energy supply method of claim 1, wherein:
in the step 2 and the step 3, the electric energy supply station performs iterative updating based on the method of the step 2 according to the period P, and adjusts an electric energy supply inspection route in the inspection process according to the iterative updating result.
3. The inspection robot electrical energy supply method of claim 1, wherein:
in the step 3, the path planning adjustment module iteratively updates the inspection route according to the minimum path planning principle based on the replenishing station information and the station information to be inspected.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311296882.6A CN117022715B (en) | 2023-10-09 | 2023-10-09 | Method for supplying electric energy to inspection unmanned aerial vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311296882.6A CN117022715B (en) | 2023-10-09 | 2023-10-09 | Method for supplying electric energy to inspection unmanned aerial vehicle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117022715A CN117022715A (en) | 2023-11-10 |
| CN117022715B true CN117022715B (en) | 2024-02-06 |
Family
ID=88645348
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311296882.6A Active CN117022715B (en) | 2023-10-09 | 2023-10-09 | Method for supplying electric energy to inspection unmanned aerial vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117022715B (en) |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015131462A1 (en) * | 2014-03-07 | 2015-09-11 | 国家电网公司 | Centralized monitoring system and monitoring method for unmanned aerial vehicle to patrol power transmission line |
| CN106092083A (en) * | 2016-05-31 | 2016-11-09 | 夏烬楚 | A kind of unmanned plane path planning management system and method |
| CN111752303A (en) * | 2020-06-15 | 2020-10-09 | 中国人民解放军国防科技大学 | Method and system for planning relay charging path of small unmanned aerial vehicle |
| CN113050696A (en) * | 2021-03-31 | 2021-06-29 | 国网江苏省电力有限公司徐州供电分公司 | Method, device and equipment for determining routing inspection route of power transmission line and storage medium |
| CN113381331A (en) * | 2021-06-23 | 2021-09-10 | 国网山东省电力公司济宁市任城区供电公司 | Intelligent inspection system for transformer substation |
| CN113989952A (en) * | 2021-10-22 | 2022-01-28 | 国网山东省电力公司利津县供电公司 | Power equipment inspection system based on distributed power supply network points |
| JP2022036467A (en) * | 2020-08-24 | 2022-03-08 | 住友電気工業株式会社 | Facility inspection system, flying body, repeating device, and facility inspection method |
| CN115924102A (en) * | 2022-11-03 | 2023-04-07 | 清华大学 | Optimum design method for series hybrid power system of vertical take-off and landing aircraft during flight |
| CN116125995A (en) * | 2023-04-04 | 2023-05-16 | 华东交通大学 | Path planning method and system for high-speed rail inspection robot |
| CN116203984A (en) * | 2023-03-02 | 2023-06-02 | 深圳市多翼南电科技有限公司 | UAM site selection evaluation method and unmanned aerial vehicle routing planning method |
| CN116661494A (en) * | 2023-05-25 | 2023-08-29 | 国网山东省电力公司聊城市茌平区供电公司 | Automatic inspection method for power equipment |
| WO2023160012A1 (en) * | 2022-02-25 | 2023-08-31 | 南京信息工程大学 | Unmanned aerial vehicle assisted edge computing method for random inspection of power grid line |
-
2023
- 2023-10-09 CN CN202311296882.6A patent/CN117022715B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015131462A1 (en) * | 2014-03-07 | 2015-09-11 | 国家电网公司 | Centralized monitoring system and monitoring method for unmanned aerial vehicle to patrol power transmission line |
| CN106092083A (en) * | 2016-05-31 | 2016-11-09 | 夏烬楚 | A kind of unmanned plane path planning management system and method |
| CN111752303A (en) * | 2020-06-15 | 2020-10-09 | 中国人民解放军国防科技大学 | Method and system for planning relay charging path of small unmanned aerial vehicle |
| JP2022036467A (en) * | 2020-08-24 | 2022-03-08 | 住友電気工業株式会社 | Facility inspection system, flying body, repeating device, and facility inspection method |
| CN113050696A (en) * | 2021-03-31 | 2021-06-29 | 国网江苏省电力有限公司徐州供电分公司 | Method, device and equipment for determining routing inspection route of power transmission line and storage medium |
| CN113381331A (en) * | 2021-06-23 | 2021-09-10 | 国网山东省电力公司济宁市任城区供电公司 | Intelligent inspection system for transformer substation |
| CN113989952A (en) * | 2021-10-22 | 2022-01-28 | 国网山东省电力公司利津县供电公司 | Power equipment inspection system based on distributed power supply network points |
| WO2023160012A1 (en) * | 2022-02-25 | 2023-08-31 | 南京信息工程大学 | Unmanned aerial vehicle assisted edge computing method for random inspection of power grid line |
| CN115924102A (en) * | 2022-11-03 | 2023-04-07 | 清华大学 | Optimum design method for series hybrid power system of vertical take-off and landing aircraft during flight |
| CN116203984A (en) * | 2023-03-02 | 2023-06-02 | 深圳市多翼南电科技有限公司 | UAM site selection evaluation method and unmanned aerial vehicle routing planning method |
| CN116125995A (en) * | 2023-04-04 | 2023-05-16 | 华东交通大学 | Path planning method and system for high-speed rail inspection robot |
| CN116661494A (en) * | 2023-05-25 | 2023-08-29 | 国网山东省电力公司聊城市茌平区供电公司 | Automatic inspection method for power equipment |
Non-Patent Citations (3)
| Title |
|---|
| 智能巡检机器人调度与路线规划能力;徐波 等;长春工业大学学报;第37卷(第3期);第269-272页 * |
| 栅格遗传算法的变电站巡检机器人路径规划;姜英杰;吕学勤;段利伟;;科技与创新(第06期);12-14 * |
| 配电线路采用无人机巡线的应用分析;张捷 等;电力与能源;第34卷(第4期);第365-368页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117022715A (en) | 2023-11-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11376979B2 (en) | System and method for charging a network of mobile battery-operated units on-the-go | |
| US20210284043A1 (en) | Multi-level battery systems for battery-operated entities, methods for rapid charge transfer therebetween, and methods for optimizing entity routing and network charge distribution | |
| CN109946998B (en) | Unmanned aerial vehicle pasture cruising method and system | |
| EP4354368A1 (en) | Electric-quantity-based path planning method for electric vehicle compatible with energy storage charging pile | |
| CN105529788B (en) | Unmanned plane method for charging batteries, system and unmanned plane | |
| US11409300B2 (en) | Autonomous car, traveling controller, traveling control method, and storage medium storing control program | |
| US8725331B2 (en) | Charge-discharge management apparatus and system for vehicle | |
| US20130285608A1 (en) | Charging control device, charging control method, and program | |
| CN107534293B (en) | Power supply system using power generation equipment using renewable energy | |
| US20150165915A1 (en) | Vehicle charging system | |
| CN108237942A (en) | Electric vehicle rescue system and electric vehicle rescue mode | |
| KR20180032075A (en) | Wireless charging device and control method for unmanned aerial vehicle | |
| Zhu et al. | Aerial refueling: Scheduling wireless energy charging for UAV enabled data collection | |
| US20190265716A1 (en) | Information processing apparatus | |
| US20190263288A1 (en) | Information processing apparatus | |
| KR101033880B1 (en) | Charge and discharge method for battery of electric vehicle | |
| CN110418434A (en) | A kind of the wireless sensor network charging method and device of unmanned plane auxiliary | |
| JP2020088940A (en) | Charge control device of vehicle | |
| CN117022715B (en) | Method for supplying electric energy to inspection unmanned aerial vehicle | |
| JP2019118219A (en) | Traveling energy distribution system, traveling energy distribution method, and traveling energy distribution program | |
| CN108233445B (en) | Charging control method and device for vehicle | |
| CN111845430B (en) | Method and system for replacing unmanned aerial vehicle battery | |
| JP7173439B2 (en) | power management system | |
| US20220105828A1 (en) | Information processing apparatus, information processing system, non-transitory computer readable medium, and autonomous vehicle | |
| KR102095877B1 (en) | All-In-One Fueling System |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |