A method and system for optimizing the efficiency of laser energy transmission network

Abstract

The present invention discloses a method and system for optimizing the efficiency of a laser energy transmission network, and belongs to the field of laser wireless energy transmission. The method includes: taking a laser transmitting end as a starting node, a receiving end as an ending node, and each relay end as an intermediate node, establishing edges for all two nodes that may have a laser transmission relationship, and taking the product of the energy conversion efficiency of the destination node device itself and the transmission efficiency of the laser with the edge as the path as the weight on the edge; starting from the starting node, searching for the most efficient energy transmission path to the ending node as the optimal energy transmission path; taking the minimum total loss of the laser energy transmission network as the goal, under the constraints of the output power of the laser transmitting end, the charge / discharge power and battery power of each relay end, the charge / discharge power, battery power and power balance of the receiving end, solving the charge / discharge power of each relay end in the optimal energy transmission path and the input power of the laser transmitting end, so as to improve the transmission efficiency of the laser energy transmission network.

Description

Technical Field

[0001] The present invention belongs to the technical field of laser wireless energy transmission, and more specifically, relates to a method and system for optimizing the efficiency of a laser energy transmission network. Background Art

[0002] At present, the research on laser wireless energy transmission networks at home and abroad is still in its infancy. No mature system has been formed either in terms of equipment for laser wireless energy transmission networks or in terms of control strategies and optimization methods for laser wireless energy transmission networks.

[0003] In the process of laser energy transmission, the energy transmission efficiency is not high because multiple electro-optical and photoelectric energy conversions are required. At the same time, according to the Beer-Lambert law, laser attenuation is inevitable when it is transmitted in the atmospheric medium, which further reduces the efficiency of the entire laser energy transmission process. The low efficiency of laser energy transmission is a key factor restricting the development of laser energy transmission technology. Summary of the invention

[0004] In view of the defects of the prior art, the purpose of the present invention is to provide a method and system for optimizing the efficiency of a laser energy transmission network, aiming to solve the problem of low efficiency of the existing laser energy transmission.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a method for optimizing the efficiency of a laser energy transmission network, wherein the laser energy transmission network to be optimized comprises: a laser transmitting end, a plurality of relay ends and a laser receiving end, and the method comprises:

[0006] S1. Construct a weighted directed graph of the laser transmission network to be optimized: take the laser transmitting end as the starting node, the laser receiving end as the ending node, and each relay end as the intermediate node, establish an edge <source node device, destination node device> for all two nodes that may have a laser transmission relationship, and take the product of the energy conversion efficiency of the destination node device itself and the transmission efficiency of the laser using this edge as the path as the weight on the edge;

[0007] S2. Determination of the optimal energy transmission path: Starting from the starting node of the weighted directed graph of the laser transmission network to be optimized, the most efficient energy transmission path to the end node is searched as the optimal energy transmission path;

[0008] S3. Efficiency optimization: With the goal of minimizing the total loss of the entire laser energy transmission network, under the output power constraints of the laser transmitting end, the charging / discharging power constraints of each relay end and the battery power constraints, the charging / discharging power constraints of the laser receiving end, the battery power constraints and the power balance constraints, the charging / discharging power of each relay end and the input power of the laser transmitting end in the optimal energy transmission path are solved.

[0009] Preferably, the calculation formula for the transmission efficiency of the laser with the edge as the path is as follows:

[0010]

[0011] Among them, S r is the area of ​​the laser photovoltaic cell, β is the divergence angle of the laser, q k is the occlusion factor, which takes the value 0 when the path is blocked and takes the value 1 when the path is not blocked. R is the distance from the source node to the destination node, μ is the attenuation coefficient calculation function, r is the distance variable from the source node to each point on the path, and λ is the laser wavelength.

[0012] Preferably, step S2 uses an improved Dijkstra algorithm to search for the most efficient energy transfer path. In the improved Dijkstra algorithm, the optimization goal each time is to maximize the product of the weights on each edge on the energy transfer path.

[0013] Preferably, step S3 comprises:

[0014] S31. Task segment splitting: splitting the entire working process of the laser receiving end into several sub-task segments;

[0015] S32. Determine decision variables: the charge / discharge power of each relay terminal in each subtask segment and the input power of the laser transmitting terminal in the optimal energy transfer path are used as decision variables;

[0016] S33. Construct the objective function expression and constraints: Q 1 =Q in -Q out As the objective function, Q in Q is the sum of the input energies of the laser transmitter, relay and laser receiver in all sub-task segments. out It is the sum of the energy consumed by the laser receiving end load in all subtask segments;

[0017] S34. Under the premise of satisfying various constraints, the objective function is minimized and solved to minimize the energy transfer loss of the system.

[0018] Preferably, the calculation formula for the total input energy of the laser transmitting end, the relay end and the laser receiving end in all subtask segments is as follows:

[0019]

[0020] Among them, K is the number of subtasks, I is the number of relay terminals, is the input power of the laser emission end in the kth subtask segment, is the charge / discharge power of relay terminal i in the kth subtask segment. It is positive when the relay terminal battery is charging and negative when the relay terminal battery is discharging. is the existence factor of relay terminal i in the kth subtask segment. When the optimal path in the kth subtask segment includes relay terminal i, the existence factor takes the value 1. When the optimal path in the kth subtask segment does not include relay terminal i, the existence factor takes the value 0. is the charge / discharge power of the laser receiving end in the kth subtask segment. It is positive when the battery at the laser receiving end is charging and negative when the battery at the laser receiving end is discharging. k is the duration of the kth subtask segment.

[0021] Preferably, the charge / discharge power constraint expression of relay terminal i is:

[0022]

[0023] in, is the charge / discharge power of relay terminal i in the kth subtask segment, is the maximum discharge power of relay terminal i, is the maximum charging power of relay terminal i, is the input power of relay terminal i in the kth subtask segment, SOE i (0) is the initial power percentage of relay terminal i, is the lower limit of the power percentage of relay terminal i, is the upper limit of the power percentage of relay terminal i, is the charge / discharge power of relay terminal i in the fth subtask segment, t f is the duration of the fth subtask segment, EN i is the rated capacity of the battery at relay terminal i, k=1,2,…,K, K is the number of subtasks.

[0024] Preferably, the power balance constraint expression at the laser receiving end is:

[0025]

[0026] in, is the charge / discharge power of the laser receiving end in the kth subtask segment. It is positive when the battery of the laser receiving end is charging and negative when the battery of the laser receiving end is discharging. is the input power of the laser emission end in the kth subtask segment, e T is the efficiency of electro-optical conversion at the laser emission end, e TR is the transmission efficiency of the laser in the path from the laser transmitting end to the laser receiving end, S TRKis the path selection signal from the laser transmitting end to the laser receiving end in the kth subtask segment. When the optimal path of the kth subtask segment includes this path, the value is 1. When the optimal path of the kth subtask segment does not include this path, the value is 0. I is the number of relay ends. is the output laser power of relay terminal i in the kth subtask segment, e iR is the transmission efficiency of the laser in the path from the relay end i to the laser receiving end, S iRk is the path selection signal from the relay terminal i to the laser receiving terminal in the kth subtask segment. It takes a value of 1 when the optimal path of the kth subtask segment includes this path, and takes a value of 0 when the optimal path of the kth subtask segment does not include this path. is the efficiency of photoelectric conversion at the laser receiving end, is the load power in the kth subtask segment, k = 1, 2, …, K, K is the number of subtasks.

[0027] Preferably, the relationship between the input power of the relay end, the output laser power of the relay end, and the charge / discharge power of the relay end is as follows:

[0028]

[0029] in, is the input power of relay terminal i in the kth subtask segment, is the input power of the laser emission end in the kth subtask segment, e T is the efficiency of electro-optical conversion at the laser emission end, e Ti is the transmission efficiency of the laser in the path from the laser transmitting end to the relay end i, S Tik is the path selection signal from the laser transmitting end to the relay end i in the kth subtask segment. It takes the value of 1 when the optimal path of the kth subtask segment includes this path, and takes the value of 0 when the optimal path of the kth subtask segment does not include this path. is the output laser power of relay terminal i in the kth subtask segment, is the charge / discharge power of relay terminal i in the kth subtask segment, is the efficiency of electro-optical conversion at relay end i, is the existence factor of relay terminal i in the kth subtask segment. When relay terminal i exists in the optimal path of the kth subtask segment, the existence factor is 1. When relay terminal i does not exist in the optimal path of the kth subtask segment, the existence factor is 0.

[0030] To achieve the above-mentioned object, in a second aspect, the present invention provides a laser energy transmission network efficiency optimization system, comprising: a processor and a memory;

[0031] The memory is used to store computer programs or instructions;

[0032] The processor is used to execute the computer program or instructions in the memory so that the method described in the first aspect is executed.

[0033] In general, the above technical solution conceived by the present invention has the following beneficial effects compared with the prior art:

[0034] The present invention proposes a method and system for optimizing the efficiency of a laser energy transmission network, constructs a weighted directed graph of the laser transmission network to be optimized, determines the optimal energy transmission path, and then uses the loss of the entire task process as the objective function, and the input power of the energy station and the charging / discharging power of the relay end as decision variables. The optimization algorithm is used to find the optimal solution so that the objective function reaches the minimum value, that is, the total loss of the system is minimized, thereby optimizing the system and improving the transmission efficiency of the laser wireless energy transmission network. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A flow chart of a method for optimizing the efficiency of a laser energy transmission network provided by the present invention.

[0036] Figure 2 Schematic diagram of the laser wireless energy transmission system for a cruise robot provided in an embodiment of the present invention.

[0037] Figure 3 A schematic diagram of area factor calculation provided in an embodiment of the present invention.

[0038] Figure 4 Schematic diagram of the laser energy transmission network of the cruise robot provided in an embodiment of the present invention.

[0039] Figure 5 A flow chart of an improved Dijkstra algorithm provided in an embodiment of the present invention.

[0040] Figure 6 A flow chart of charge and discharge power optimization provided by an embodiment of the present invention.

[0041] Figure 7 This is a diagram of the optimization results of the optimal energy transfer path provided by an embodiment of the present invention.

[0042] Figure 8 This is a diagram of the charge and discharge power optimization results provided by an embodiment of the present invention.

[0043] Fig. 9 An iterative diagram for optimizing system energy transfer loss provided by an embodiment of the present invention.

[0044] Fig.10 This is a diagram of the change in power level of each battery provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0046] Figure 1 The present invention provides a flow chart of a method for optimizing the efficiency of a laser energy transmission network. The laser energy transmission network to be optimized includes: a laser transmitting end, a plurality of relay ends and a laser receiving end. Figure 1 As shown, the method includes:

[0047] Step S1. Construct a weighted directed graph of the laser transmission network to be optimized.

[0048] The laser transmitting end is taken as the starting node, the laser receiving end is taken as the ending node, and each relay end is taken as the intermediate node. The edge <source node device, destination node device> is established for all two nodes that may have a laser transmission relationship. The product of the energy conversion efficiency of the destination node device itself and the transmission efficiency of the laser using this edge as the path is taken as the weight on the edge.

[0049] Preferably, the calculation formula for the transmission efficiency of the laser with the edge as the path is as follows:

[0050]

[0051] Among them, S r is the area of ​​the laser photovoltaic cell, β is the divergence angle of the laser, q k is the occlusion factor, which takes the value 0 when the path is blocked and takes the value 1 when the path is not blocked. R is the distance from the source node to the destination node, μ is the attenuation coefficient calculation function, r is the distance variable from the source node to each point on the path, and λ is the laser wavelength.

[0052] Step S2: Determine the optimal energy transfer path.

[0053] Starting from the starting node of the weighted directed graph of the laser transmission network to be optimized, the most efficient energy transmission path to the end node is searched as the optimal energy transmission path.

[0054] Preferably, step S2 uses an improved Dijkstra algorithm to search for the most efficient energy transfer path. In the improved Dijkstra algorithm, the optimization goal each time is to maximize the product of the weights on each edge on the energy transfer path.

[0055] Step S3: Efficiency optimization.

[0056] With the goal of minimizing the total loss of the entire laser energy transmission network, under the output power constraints of the laser transmitting end, the charging / discharging power constraints and battery power constraints of each relay end, the charging / discharging power constraints, battery power constraints and power balance constraints of the laser receiving end, the charging / discharging power of each relay end and the input power of the laser transmitting end in the optimal energy transmission path are solved.

[0057] Preferably, step S3 comprises:

[0058] S31. Task segment splitting: splitting the entire working process of the laser receiving end into several sub-task segments;

[0059] S32. Determine the decision variables: the charge / discharge power of each relay terminal in each subtask segment and the input power of the laser transmitting terminal in the optimal energy transfer path are used as decision variables;

[0060] S33. Construct the objective function expression and constraints: Q 1 =Q in -Q out As the objective function, Q in Q is the sum of the input energies of the laser transmitter, relay and laser receiver in all sub-task segments. out It is the sum of the energy consumed by the laser receiving end load in all subtask segments;

[0061] S34. Under the premise of satisfying various constraints, the objective function is minimized and solved to minimize the energy transfer loss of the system.

[0062] Preferably, the calculation formula for the total input energy of the laser transmitting end, the relay end and the laser receiving end in all subtask segments is as follows:

[0063]

[0064] Among them, K is the number of subtasks, I is the number of relay terminals, is the input power of the laser emission end in the kth subtask segment, is the charge / discharge power of relay terminal i in the kth subtask segment. It is positive when the relay terminal battery is charging and negative when the relay terminal battery is discharging. is the existence factor of relay terminal i in the kth subtask segment. When the optimal path in the kth subtask segment includes relay terminal i, the existence factor takes the value 1. When the optimal path in the kth subtask segment does not include relay terminal i, the existence factor takes the value 0. is the charge / discharge power of the laser receiving end in the kth subtask segment. It is positive when the battery at the laser receiving end is charging and negative when the battery at the laser receiving end is discharging. k is the duration of the kth subtask segment.

[0065] Preferably, the charging power constraint expression of relay terminal i is:

[0066]

[0067] in, is the charge / discharge power of relay terminal i in the kth subtask segment, is the maximum discharge power of relay terminal i, is the maximum charging power of relay terminal i, is the input power of relay terminal i in the kth subtask segment, SOE i (0) is the initial power percentage of relay terminal i, is the lower limit of the power percentage of relay terminal i, is the upper limit of the power percentage of relay terminal i, is the charge / discharge power of relay terminal i in the fth subtask segment, t f is the duration of the fth subtask segment, EN i is the rated capacity of the battery at relay terminal i, k=1,2,…,K, K is the number of subtasks.

[0068] Preferably, the power balance constraint expression at the laser receiving end is:

[0069]

[0070] in, is the charge / discharge power of the laser receiving end in the kth subtask segment. It is positive when the battery of the laser receiving end is charging and negative when the battery of the laser receiving end is discharging. is the input power of the laser emission end in the kth subtask segment, e T is the efficiency of electro-optical conversion at the laser emission end, e TR is the transmission efficiency of the laser in the path from the laser transmitting end to the laser receiving end, S TRK is the path selection signal from the laser transmitting end to the laser receiving end in the kth subtask segment. When the optimal path of the kth subtask segment includes this path, the value is 1. When the optimal path of the kth subtask segment does not include this path, the value is 0. I is the number of relay ends. is the output laser power of relay terminal i in the kth subtask segment, e iR is the transmission efficiency of the laser in the path from the relay end i to the laser receiving end, S iRk is the path selection signal from the relay terminal i to the laser receiving terminal in the kth subtask segment. It takes a value of 1 when the optimal path of the kth subtask segment includes this path, and takes a value of 0 when the optimal path of the kth subtask segment does not include this path. is the efficiency of photoelectric conversion at the laser receiving end, is the load power in the kth subtask segment, k = 1, 2, …, K, K is the number of subtasks.

[0071] Preferably, the relationship between the input power of the relay end, the output laser power of the relay end, and the charge / discharge power of the relay end is as follows:

[0072]

[0073] in, is the input power of relay terminal i in the kth subtask segment, is the input power of the laser emission end in the kth subtask segment, e T is the efficiency of electro-optical conversion at the laser emission end, e Ti is the transmission efficiency of the laser in the path from the laser transmitting end to the relay end i, S Tik is the path selection signal from the laser transmitting end to the relay end i in the kth subtask segment. It takes the value of 1 when the optimal path of the kth subtask segment includes this path, and takes the value of 0 when the optimal path of the kth subtask segment does not include this path. is the output laser power of relay terminal i in the kth subtask segment, is the charge / discharge power of relay terminal i in the kth subtask segment, is the efficiency of electro-optical conversion at relay end i, is the existence factor of relay terminal i in the kth subtask segment. When relay terminal i exists in the optimal path of the kth subtask segment, the existence factor is 1. When relay terminal i does not exist in the optimal path of the kth subtask segment, the existence factor is 0.

[0074] The following takes a simple laser energy transmission network as an example to explain in detail the method for optimizing the efficiency of the laser energy transmission network of the present invention.

[0075] Taking a cruise robot laser wireless energy transmission system as an example, a laser energy transmission network efficiency optimization method proposed in the present invention is described. Figure 2 Schematic diagram of the laser wireless energy transmission system for a cruise robot provided by an embodiment of the present invention. Figure 2 As shown, the system includes: an energy station, four relay stations, a cruise robot and a factory building.

[0076] The cruise robot laser wireless energy transmission system has the following characteristics: the cruise robot patrols around the factory building, and the cruise robot carries a battery and a laser photovoltaic cell. The laser photovoltaic cell can receive lasers transmitted by other equipment and convert laser energy into electrical energy, which is used to maintain the load requirements of the cruise robot. When the electric power converted by the laser photovoltaic cell is greater than the load power, the excess electric energy is charged into the battery to charge the battery. When the electric power converted by the laser photovoltaic cell is less than the load power, the battery actively discharges to make up for the power shortage of the load.

[0077] The energy station in the cruise robot's laser wireless energy transmission system includes: a laser, a collimation unit, and a tracking unit, which can emit a fixed-power directional laser beam to provide energy for the relay station or the cruise robot.

[0078] The relay station in the cruise robot laser wireless energy transmission system includes: laser photovoltaic cells, batteries, lasers, and tracking units. The relay station is used to provide energy relay nodes, which can receive laser energy emitted by energy stations or other relay stations, and can also emit laser beams to cruise robots or other relay stations. The battery of the relay station can store the excess laser energy received or transmit energy to other devices.

[0079] The network construction module calculates the transmission efficiency of the laser in each energy transmission path according to the characteristic parameters, meteorological parameters and position coordinates of the equipment in the network, and then constructs a network diagram composed of nodes and edges. The energy conversion efficiency of the energy station, relay station and cruise robot in the cruise robot laser wireless energy transmission system is determined by the actual equipment. Take the energy station as the starting node, the cruise robot as the end node, and each relay station as the intermediate node. Establish an edge <source node device, destination node device> for all two nodes that may have a laser transmission relationship. The product of the energy conversion efficiency of the destination node device itself and the transmission efficiency of the laser with this edge as the path is used as the weight on the edge. The transmission efficiency of the laser in the path can be calculated by the Beer-Lambert law. The Beer-Lambert law involves the influence of molecular scattering and absorption, aerosols and meteorological conditions on the laser transmission efficiency. Many literatures show that for lasers with a wavelength of 808 nanometers, the laser power attenuation caused by molecular scattering and absorption can be ignored. Therefore, when solving the transmission efficiency of the laser in the path, only the influence of aerosols and meteorological conditions can be considered, and the Beer-Lambert law can be expressed as:

[0080]

[0081] Where, I(R) is the laser power at the receiving point, I 0 is the laser power at the transmitting point, R is the distance between the transmitting point and the receiving point, μ is the attenuation coefficient calculation formula, and the attenuation coefficient at position r is mainly related to the laser wavelength λ, rainfall and visibility.

[0082] The Beer-Lambert law is a formula for calculating the transmission efficiency of the laser in the path under relatively ideal conditions. In actual applications, the energy transmission path may be blocked by obstacles (factory buildings). At this time, the transmission efficiency of the laser in the path should be 0. Therefore, the occlusion factor is introduced to reflect the occlusion of the laser energy transmission path. When the energy transmission path is blocked by an obstacle, the occlusion factor is 0, and when the energy transmission path is not blocked by an obstacle, the occlusion factor is 1. At the same time, the laser will inevitably diverge gradually during the transmission process. The longer the laser transmission distance, the greater the divergence angle of the laser source, and the larger the laser spot area at the receiving point. Since the area of ​​the laser photovoltaic panel is fixed, when the spot area is larger than the area of ​​the laser photovoltaic panel, the laser energy cannot be fully received by the laser photovoltaic cell, so the area coefficient is introduced to correct the transmission efficiency of the laser in the path. Figure 3 A schematic diagram of area factor calculation provided by an embodiment of the present invention.

[0083] Combining the Beer-Lambert law, the shielding factor and the area factor, the transmission efficiency of the laser in the path is calculated as follows:

[0084]

[0085] Among them, S r is the area of ​​the laser photovoltaic cell, β is the divergence angle of the laser source, q k is the shielding factor, R is the distance from the laser source to the laser receiver, λ is the laser wavelength, and r is the distance variable from the laser source to a certain point.

[0086] According to the above formula, the transmission efficiency of the laser in each path can be calculated. The energy conversion efficiency of the destination device on each path is attributed to the transmission efficiency of the path, and the diagram of the cruise robot laser wireless energy transmission network can be constructed, as shown in Figure 4 shown. Figure 4 Node 1 represents the energy station, node 2 represents relay station A, node 3 represents relay station D, node 4 represents relay station B, node 5 represents relay station C, and node 6 represents the cruise robot. Figure 4 There are a total of 21 laser energy transfer paths.

[0087] There are multiple optional paths when the energy station transmits laser energy to the cruise robot. The optimal path selection module is based on the graph of the cruise robot's laser energy transmission network and uses a search algorithm (for example, Dijkstra's algorithm) to search for the most efficient energy transmission path.

[0088] Dijkstra's algorithm is an algorithm for finding the shortest path from the starting node to the remaining vertices in the graph. It starts from the starting node and adopts the strategy of greedy algorithm. Each time, it selects a vertex with the shortest distance from the starting node from the unvisited vertices and marks it, and sets it as the intermediate point of this calculation. Then, it optimizes the distance between the starting node and all the neighboring nodes of the intermediate point, and repeats the above operation until all vertices are marked. Figure 5 The flowchart of the improved Dijkstra algorithm provided in the embodiment of the present invention. In this embodiment, some improvements are made to the Dijkstra algorithm to solve the optimal energy transfer path of the laser wireless energy transfer network. Specifically, a weight matrix is ​​established according to the graph of the wireless energy transfer network of the cruise robot, and the optimization objective function of each time is replaced from summing the total path to producting the total efficiency, and the minimum value of the objective function is replaced by the maximum value of the objective function, so that the Dijkstra algorithm can be used to solve the optimal path.

[0089] The Dijkstra algorithm in this embodiment can solve the most efficient energy transmission path under given conditions. After the optimal energy transmission path is determined, the charging and discharging power optimization module is used to optimize the charging / discharging power of each relay station in the energy transmission path and the input power of the energy station, thereby minimizing the energy loss of the system during operation while meeting the system performance requirements, thereby improving the efficiency of the cruise robot's laser wireless energy transmission system.

[0090] Figure 6 The following is a flow chart of charge and discharge power optimization provided by an embodiment of the present invention. Figure 6 As shown, the charging and discharging power optimization module includes: task segment splitting, determining the number of decision variables, listing the objective function expression, listing the constraints of each device, and solving the optimization algorithm.

[0091] The task segment splitting is used to split the entire cruising process of the cruise robot into several small task segments according to a certain time unit. Since the time length of each task segment is short, it can be approximately considered that each parameter in the system is a constant in each task segment, so that the problem can be solved. The time for the cruise robot in this embodiment to cruise around the factory building is 640 seconds, and a cruising process is divided into 16 sub-task segments with 40 seconds as a time unit.

[0092] The decision variable number determination module is used to determine the number of decision variables. In each subtask segment, the input power of the energy station is the decision variable, the charge / discharge power of the relay station is the decision variable, the power is positive when the battery of the relay station is charged, and the power is negative when the battery of the relay station is discharged. There is no decision variable for the cruise robot. The cruise process of this embodiment includes 16 subtask segments in total, so there are 80 decision variables in total. The total number of decision variables is calculated as follows:

[0093] (1+4*1)*16=80

[0094] The objective function expression module writes the objective function with the system loss as the target, and the total loss of the cruise robot during the cruising process is the difference between the total input energy of the system and the total output energy of the system.

[0095] The total output energy in this embodiment is the sum of the load energy consumed by the cruise robot in the 16 subtask segments. The calculation formula for the total output energy in this embodiment is:

[0096]

[0097] Among them, Q out is the total output energy of the system, is the load power in the kth subtask segment, t k is the duration of the kth subtask segment.

[0098] The total input energy in this embodiment is the sum of the input energies of the energy station, relay station and cruise robot in the 16 sub-task segments. The calculation formula for the total input energy in this embodiment is:

[0099]

[0100] Among them, Q in is the total input energy of the system, is the input power of the laser emission end in the kth subtask segment, is the charge / discharge power of relay terminal i in the kth subtask segment. It is positive when the relay terminal battery is charging and negative when the relay terminal battery is discharging. is the existence factor of relay terminal i in the kth subtask segment. When the optimal path in the kth subtask segment includes relay terminal i, the existence factor takes the value 1. When the optimal path in the kth subtask segment does not include relay terminal i, the existence factor takes the value 0. is the charge / discharge power of the laser receiving end in the kth subtask segment. It is positive when the battery at the laser receiving end is charging and negative when the battery at the laser receiving end is discharging. k is the duration of the kth subtask segment.

[0101] The objective function expression of this embodiment is:

[0102] Q 1 =Q in -Q out

[0103] Among them, Q 1 is the total loss of the system, Q in is the total input energy of the system, Q out is the total output energy of the system.

[0104] The constraint conditions in this embodiment are determined by the characteristics of each device. The energy station has an output power constraint, and the output power of the energy station cannot exceed the upper limit of the output power. The constraint of the energy station is expressed as follows:

[0105]

[0106] in, is the input power of the energy station in the kth subtask segment, e T is the electro-optical conversion efficiency of the energy station, is the maximum output power of the energy station.

[0107] The relay station in this embodiment has charging / discharging power constraints and battery power constraints. The charging / discharging power constraints of the relay station are: on the one hand, the charging / discharging power constraints of the relay station cannot exceed the upper limit of the charging / discharging power allowed by the equipment, and on the other hand, the charging power of the relay station cannot exceed the input power transmitted to the relay station by other equipment; the battery power constraint of the relay station is: within each subtask segment, the power of the relay station battery cannot be lower than the lower limit of the battery power, nor higher than the upper limit of the battery power, to prevent overcharging and over-discharging of the battery. Specifically, the constraint expression of the relay station is:

[0108]

[0109] in, is the charge / discharge power of relay terminal i in the kth subtask segment, is the maximum discharge power of relay terminal i, is the maximum charging power of relay terminal i, is the input power of relay terminal i in the kth subtask segment, SOE i (0) is the initial power percentage of relay terminal i, is the lower limit of the power percentage of relay terminal i, is the upper limit of the power percentage of relay terminal i, is the charge / discharge power of relay terminal i in the fth subtask segment, t f is the duration of the fth subtask segment, EN i is the rated capacity of the battery at relay end i.

[0110] The constraints of the cruise robot in this embodiment include: charge / discharge power constraint, battery power constraint and power balance constraint. The charge / discharge power constraint of the cruise robot is: the charge / discharge power of the cruise robot cannot exceed its charge / discharge power limit; the battery power constraint of the cruise robot is: in each subtask segment, the battery power of the cruise robot cannot be lower than the lower limit of the battery power, nor can it be higher than the upper limit of the battery power, to prevent overcharging and over-discharging of the battery. The power balance constraint of the cruise robot is: the charge / discharge power of the cruise robot is equal to the difference between the total power transmitted to the cruise robot by the energy station and the relay station and the load power. When the power transmitted to the cruise robot by the energy station and the relay station is greater than the load power, part of the power received by the cruise robot is required to maintain the load, and the other part is charged to the battery of the cruise robot. At this time, the charge / discharge power of the cruise robot is a positive value. When the power transmitted to the cruise robot by the energy station and the relay station is less than the load power, the cruise robot receives all the power and supplies it to the load. At the same time, the cruise robot's battery also discharges to the load to make up for the shortfall in load power. At this time, the charge / discharge power of the cruise robot is negative. Specifically, the constraint expression of the cruise robot is:

[0111]

[0112] in, is the charge / discharge power of the cruise robot in the kth subtask segment. It is positive when the cruise robot battery is charging and negative when the cruise robot battery is discharging. is the upper limit of the cruise robot's charging power. is the upper limit of the cruise robot’s discharge power, is the input power of the energy station in the kth subtask segment, e T The efficiency of electrical-to-optical conversion for energy stations, e TR is the transmission efficiency of the laser from the energy station to the cruise robot, S TRK is the path selection signal from the energy station to the cruise robot in the kth subtask segment. It takes a value of 1 when the optimal path of the kth subtask segment includes this path, and takes a value of 0 when the optimal path of the kth subtask segment does not include this path. is the output laser power of relay station i in the kth subtask segment, e iR is the transmission efficiency of the laser in the path from relay station i to the cruise robot, S iRk is the path selection signal from relay station i to the cruise robot in the kth subtask segment. It takes a value of 1 when the optimal path of the kth subtask segment includes this path, and takes a value of 0 when the optimal path of the kth subtask segment does not include this path. The efficiency of photoelectric conversion for the cruise robot, is the load power in the kth subtask segment. SOE R (0) is the initial power percentage of the cruise robot battery, is the lower limit of the battery power percentage of the cruise robot, The upper limit of the battery power percentage of the cruise robot. is the charge / discharge power of the cruise robot in the fth subtask segment, t f is the duration of the fth subtask segment, EN R is the rated capacity of the battery of the cruise robot.

[0113] The input power and output laser power of the relay station can be obtained by iteratively solving the equation group. After the input power of the energy station and the charge / discharge power of the relay station are determined, any initial value is given as the input power and output laser power of the relay station, and the following equation group is iterated until the input power and output laser power of the relay station no longer change, that is, the input power and output laser power of the relay station are obtained. The equation group expression for iterative solution is as follows:

[0114]

[0115] in, is the input power of relay terminal i in the kth subtask segment, is the input power of the laser emission end in the kth subtask segment, e T is the efficiency of electro-optical conversion at the laser emission end, e Ti is the transmission efficiency of the laser in the path from the laser transmitting end to the relay end i, S Tik is the path selection signal from the laser transmitting end to the relay end i in the kth subtask segment. It takes the value of 1 when the optimal path of the kth subtask segment includes this path, and takes the value of 0 when the optimal path of the kth subtask segment does not include this path. is the output laser power of relay terminal i in the kth subtask segment, is the charge / discharge power of relay terminal i in the kth subtask segment, is the efficiency of electro-optical conversion at relay end i, is the existence factor of relay terminal i in the kth subtask segment. When relay terminal i exists in the optimal path of the kth subtask segment, the existence factor is 1. When relay terminal i does not exist in the optimal path of the kth subtask segment, the existence factor is 0.

[0116] The above analysis and modeling of the cruise robot laser energy transmission network have been carried out, and the objective function and constraint conditions for charging and discharging power optimization have been listed. The optimization algorithm is used to solve the planning problem. In this embodiment, the particle swarm algorithm is used for solving. In this embodiment, the upper limit of the charging power of each device is 800W, the upper limit of the discharging power is also 800W, the load power is 100W, the lower limit of the battery power of each device is 50%, the upper limit of the battery power is 95%, and the electro-optical conversion efficiency and photoelectric conversion efficiency of each device are set to 60%.

[0117] Figure 7 This is a diagram of the optimal energy transfer path optimization result provided by the embodiment of the present invention. Figure 7 As shown, S2 to S18 represent the path selection signals of each path respectively. When the selection signal value is 1, it indicates that the corresponding path is turned on, and when the selection signal value is 0, it indicates that the corresponding path is turned off. Figure 7 It can be seen that in the two time periods of 0 to 160s and 480s to 640s, only the path selection signal value of S3 is 1. Figure 2 and Figure 4 From the path correspondence relationship, it can be seen that this means that in the 1st to 4th sub-task segments and the 13th to 16th sub-task segments, the optimal energy transmission path is the path from the energy station to the cruise robot directly. In the time period from 160s to 320s, only the path selection signal value of S5 and S18 is 1, which means that in the 5th to 8th sub-task segments, the optimal energy transmission path is the path from the energy station to the cruise robot via the relay station B. In the time period from 320s to 480s, only the path selection signal value of S2 and S17 is 1, which means that in the 9th to 12th sub-task segments, the optimal energy transmission path is the path from the energy station to the cruise robot via the relay station D. Further analysis shows that when the cruise robot moves from position E to position F, it corresponds to the 1st to 4th subtask segments and the 13th to 16th subtask segments. At this time, the energy station can directly shoot the cruise robot, so the direct path is the optimal energy transfer path; when the cruise robot moves from position F to position G, it corresponds to the 5th to 8th subtask segments. At this time, the energy station needs to pass through relay station B or relay station C to transmit energy to the cruise robot. There are differences in the positions and energy conversion efficiency of relay stations B and C, so the algorithm selects the more efficient relay station B as the relay point; when the cruise robot moves from position G to position E, it corresponds to the 9th to 12th subtask segments. At this time, the energy station needs to pass through relay station A or relay station D to transmit energy to the cruise robot. There are differences in the positions and energy conversion efficiency of relay stations A and D, so the algorithm selects the more efficient relay station D as the relay point.

[0118] Figure 8 This is a diagram of the charge and discharge power optimization results provided by the embodiment of the present invention. Figure 8As shown, relay station B and relay station D are both in a discharging state during their respective working time periods, and relay station A and relay station C do not need to be charged or discharged because they are not in the optimal energy transfer path.

[0119] Fig. 9 This is an iterative diagram for optimizing the system energy transfer loss provided by the embodiment of the present invention. Fig. 9 As shown in the figure, the total energy loss of the system during the entire working process gradually decreases with the iteration of the algorithm, and finally reaches a minimum value and remains constant, which shows that it is feasible to use the particle swarm algorithm to optimize the system loss.

[0120] Fig.10 The figure is a graph showing the change in the amount of electricity of each battery provided in the embodiment of the present invention. Fig.10 As shown, during the entire working process, the power of the batteries of each device is within the constraints of the lower limit and the upper limit of power, which meets the set requirements for the system working performance.

[0121] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for optimizing the efficiency of a laser energy transmission network, characterized in that: The laser energy transmission network to be optimized includes: a laser transmitting end, a plurality of relay ends and a laser receiving end. The method includes: S1. Construct a weighted directed graph of the laser transmission network to be optimized: take the laser transmitting end as the starting node, the laser receiving end as the ending node, and each relay end as the intermediate node, establish an edge <source node device, destination node device> for all two nodes that may have a laser transmission relationship, and take the product of the energy conversion efficiency of the destination node device itself and the transmission efficiency of the laser using this edge as the path as the weight on the edge; S2. Determination of the optimal energy transmission path: Starting from the starting node of the weighted directed graph of the laser transmission network to be optimized, the most efficient energy transmission path to the end node is searched as the optimal energy transmission path; S3. Efficiency optimization: With the goal of minimizing the total loss of the entire laser energy transmission network, under the constraints of the output power of the laser transmitting end, the charging / discharging power constraints of each relay end and the battery power constraint, the charging / discharging power constraints of the laser receiving end, the battery power constraint and the power balance constraint, the charging / discharging power of each relay end and the input power of the laser transmitting end in the optimal energy transmission path are solved; The calculation formula of the transmission efficiency of the laser with this edge as the path is as follows: in, is the area of ​​the laser photovoltaic cell, is the divergence angle of the laser, is the occlusion factor, which takes the value 0 when the path is occluded and takes the value 1 when the path is not occluded. is the distance from the source node to the destination node, is the attenuation coefficient calculation function, is the distance variable from the source node to each point on the path, is the laser wavelength; Step S3 includes: S31. Task segment splitting: splitting the entire working process of the laser receiving end into several sub-task segments; S32. Determine decision variables: the charge / discharge power of each relay terminal in each subtask segment and the input power of the laser transmitting terminal in the optimal energy transfer path are used as decision variables; S33. Construct the objective function expression and various constraints: As the objective function, is the sum of the input energies of the laser transmitting end, the relay end, and the laser receiving end in all subtask segments, It is the sum of the energy consumed by the laser receiving end load in all subtask segments; S34. Under the premise of satisfying all constraints, the objective function is minimized and solved, so as to minimize the energy transfer loss of the system; The calculation formula for the total input energy of the laser transmitter, relay and laser receiver in all sub-task segments is as follows: in, is the number of subtasks, is the number of relays, For the The input power of the laser transmitter in each sub-task segment is: For the Subtask segment relay The charge / discharge power is positive when the relay end battery is charging and negative when the relay end battery is discharging. For the Subtask segment relay The existence factor of The optimal path in the subtask segment contains the relay end When there is a factor with the value 1, The optimal path in the subtask segment does not contain the relay end When , there is a factor with the value 0, For the The charge / discharge power of the laser receiving end in each sub-task segment is positive when the battery at the laser receiving end is charged and negative when the battery at the laser receiving end is discharged; For the The duration of each subtask segment.

2. The method according to claim 1, characterized in that Step S2 uses an improved Dijkstra algorithm to search for the most efficient energy transfer path. In the improved Dijkstra algorithm, the optimization goal each time is to maximize the product of the weights of each edge on the energy transfer path.

3. The method according to claim 1, characterized in that Relay The charge / discharge power constraint expression is: in, For relay In the The charge / discharge power within each sub-task segment, For relay The maximum discharge power, For relay The maximum charging power, For the Subtask segment relay The input electrical power, For relay The initial charge percentage, For relay The lower limit of the power percentage, For relay The upper limit of the battery percentage, For relay In the The charge / discharge power within each sub-task segment, For the The duration of each subtask segment, For relay The rated capacity of the battery, , is the number of subtasks.

4. The method according to claim 1, characterized in that The power balance constraint expression at the laser receiving end is: in, For the laser receiving end The charge / discharge power in each sub-task segment is positive when the laser receiving end battery is charged and negative when the laser receiving end battery is discharged; The laser emission end is The input power in each sub-task segment is is the efficiency of electro-optical conversion at the laser emission end, is the transmission efficiency of the laser in the path from the laser transmitting end to the laser receiving end, For the The path selection signal from the laser transmitting end to the laser receiving end in the sub-task segment is The value is 1 when the optimal path of the subtask segment contains the path. If the optimal path of each subtask segment does not contain this path, the value is 0; is the number of relays, For relay In the The output laser power in each sub-task segment is For laser at the relay end The transmission efficiency in the path to the laser receiving end, For the Subtask segment relay The path selection signal to the laser receiving end, when the The value is 1 when the optimal path of the subtask segment contains the path. If the optimal path of each subtask segment does not contain this path, the value is 0; is the efficiency of photoelectric conversion at the laser receiving end, For the The load power in each sub-task segment is , is the number of subtasks.

5. The method according to claim 3 or 4, characterized in that The relationship between the input power of the relay end, the output laser power of the relay end, and the charge / discharge power of the relay end is as follows: in, For the Subtask segment relay The input electrical power, The laser emission end is The input power in each sub-task segment is is the efficiency of electro-optical conversion at the laser emission end, For the laser from the laser transmitting end to the relay end The transmission efficiency in the path, For the From the laser transmitter to the relay end within the sub-task segment The path selection signal, when the The value is 1 when the optimal path of the subtask segment contains this path. If the optimal path of the subtask segment does not contain this path, the value is 0; For relay In the The output laser power in each sub-task segment is For relay In the The charge / discharge power within each sub-task segment, For relay The efficiency of electro-optical conversion, For the Subtask segment relay The existence factor of Exists in When there are multiple subtask segments in the optimal path, the existence factor takes the value of 1. Not present in When there is an optimal path for subtask segments, the existence factor takes the value of 0.

6. A laser energy transmission network efficiency optimization system, characterized in that: include: Processor and memory; The memory is used to store computer programs or instructions; The processor is configured to execute the computer program or instruction in the memory so that the method according to any one of claims 1 to 5 is performed.

Images