Charging pile determination method, device and equipment and readable storage medium

Abstract

The invention provides a charging pile determination method, device and equipment and a readable storage medium, and the method comprises the steps: setting a particle swarm, determining a charging pile corresponding to the position of each particle under the condition that the particle swarm completes movement each time, determining the fitness of the particles according to the feature parameters of the charging piles, and determining the fitness of the particles under the condition that the particle swarm completes multiple times of movement. Determining a fitness combination of each particle and a fitness set of a particle swarm; determining the maximum first fitness in the fitness combination of each particle and the maximum second fitness in the fitness set, and resetting the positions and speeds of the particles in the particle swarm under the condition that the characteristic parameters change; and according to the current position, the current speed, the first fitness and the second fitness of the particle, controlling the next movement of the particle until the particle swarm completes preset times of movement, and determining the maximum fitness in the fitness set and the corresponding target charging pile. The accuracy of determining the charging pile can be improved.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the technical field of electric vehicles, and in particular to a charging pile determination method, device, electronic device, and computer-readable storage medium. Background Art

[0002] With the development of electric vehicles, the demand for charging piles is growing. When the power of most electric vehicles is low, they need to drive to the charging pile and connect the electric vehicle to the charging pile to replenish the power. How to choose the right charging pile among many charging piles will affect the efficiency of power replenishment.

[0003] In the related art, a driving route is planned based on the current position and destination of the vehicle, and then a charging pile near the driving route is searched, for example, if there is a charging pile on the driving route, or the driving path is changed to find the nearest charging pile.

[0004] However, in the related art, the driving route between the current location and the destination is still used as the core to determine the charging pile, and the charging pile is not used as the core to determine the charging pile, resulting in low accuracy in determining the charging pile. Summary of the invention

[0005] In view of the above problems, the embodiments of the present disclosure are proposed to provide a charging pile determination method, device, electronic device and computer-readable storage medium that overcome the above problems or at least partially solve the above problems.

[0006] In a first aspect, an embodiment of the present disclosure discloses a method for determining a charging pile, including:

[0007] Setting a particle group; the particle group has a preset number of particles; each particle moves between different positions in the space based on its own position and speed; different positions correspond to different charging piles;

[0008] Each time the particle group completes its movement, determining the charging pile corresponding to the location of each particle, and determining the fitness of the particle according to the characteristic parameters of the charging pile;

[0009] When the particle group has completed multiple moves, determining a fitness combination of each particle and a fitness set of the particle group; each fitness combination has multiple fitnesses; and the fitness set has a preset number of fitness combinations;

[0010] Determine the largest first fitness in the fitness combination of each particle and the largest second fitness in the fitness set, and reset the position and speed of the particles in the particle group when the characteristic parameter changes;

[0011] According to the current position, current speed, first fitness and second fitness of each particle, the next movement of each particle is controlled until the particle group completes a preset number of movements, and the maximum fitness in the fitness set and the target charging pile corresponding to the maximum fitness are determined.

[0012] In a second aspect, an embodiment of the present disclosure discloses a charging pile determination device, including:

[0013] A particle setting module is used to set a particle group; the particle group has a preset number of particles; each particle moves between different positions in the space based on its own position and speed; different positions correspond to different charging piles;

[0014] An adaptation determination module, used to determine the charging pile corresponding to the position of each particle each time the particle group completes the movement, and determine the fitness of the particle according to the characteristic parameters of the charging pile;

[0015] A combination set module, used for determining the fitness combination of each particle and the fitness set of the particle swarm when the particle swarm completes multiple moves; each fitness combination has multiple fitnesses; and the fitness set has a preset number of fitness combinations;

[0016] a change response module, used to determine the largest first fitness in the fitness combination of each particle and the largest second fitness in the fitness set, and reset the position and speed of the particles in the particle group when the characteristic parameter changes;

[0017] A target determination module is used to control the next movement of each particle according to the current position, current speed, first fitness and second fitness of each particle until the particle group completes a preset number of movements, and determine the maximum fitness in the fitness set and the target charging pile corresponding to the maximum fitness.

[0018] In a third aspect, an embodiment of the present disclosure further discloses an electronic device, including a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the program or instructions are executed by the processor, the steps of the charging pile determination method described in the first aspect are implemented.

[0019] In a fourth aspect, an embodiment of the present disclosure further discloses a computer-readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the charging pile determination method as described in the first aspect are implemented.

[0020] In the embodiment of the present disclosure, a particle group is set, and a preset number of particles in the particle group move between different positions in the space based on their respective positions and speeds. Each time the particle group completes the movement, the charging pile corresponding to the position of each particle is determined, and the fitness of the particle is determined according to the characteristic parameters of the charging pile. When the particle group completes multiple movements, the fitness combination of each particle and the fitness set of the particle group are determined, and the largest first fitness in the fitness combination of each particle and the largest second fitness in the fitness set are determined. In the case of changes in the characteristic parameters, the position and speed of the particles in the particle group are reset, and the next movement of each particle is controlled according to the current position, current speed, first fitness and second fitness of each particle until the particle group completes the preset number of movements, and the maximum fitness in the fitness set and the target charging pile corresponding to the maximum fitness are determined. Based on the particle movement search method, the characteristic parameters of the charging pile can be used as the core parameters to determine the fitness of the particle after each movement, and considering the variability of the characteristic parameters, the particles are initialized to adapt to the changes in the characteristic parameters, so that after multiple iterative movements of the particle group, the target charging pile that meets the actual situation can be accurately found, thereby improving the accuracy of determining the charging pile. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a step diagram of a charging pile determination method provided by an embodiment of the present disclosure;

[0022] Figure 2 is a schematic diagram of a particle swarm algorithm provided by an embodiment of the present disclosure;

[0023] Figure 3 is a schematic diagram of a dynamic response particle swarm algorithm provided by an embodiment of the present disclosure;

[0024] Figure 4 is a step diagram of another charging pile determination method provided by an embodiment of the present disclosure;

[0025] Figure 5 is a block diagram of a charging pile determination device provided by an embodiment of the present disclosure;

[0026] Figure 6 It is a block diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0027] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0028] Figure 1 A step diagram of a charging pile determination method provided by an embodiment of the present disclosure is shown, and the method includes:

[0029] Step 101, setting a particle group; the particle group has a preset number of particles; each particle moves between different positions in the space based on its own position and speed; different positions correspond to different charging piles.

[0030] In the embodiment of the present disclosure, when the battery level of the electric vehicle is low, it is necessary to find a charging station for charging. The steps of the charging station determination method may be executed by an on-board terminal on the vehicle, or by other devices on the vehicle with data processing capabilities, or by a server, without specific limitation.

[0031] When determining a suitable charging pile, a virtual particle group may be provided, which includes a preset number of particles, such as 50, 100, or other numbers. Each particle may move between different positions in the multidimensional space based on its own position and speed.

[0032] The position is the current position of each particle, and the speed includes the speed direction and speed magnitude. In a multidimensional space, for example, a D-dimensional space, the position of the i-th particle is: X i =(x1,x2,...x D ), the velocity of the ith particle is: V i =(v1,v2,...v D ).

[0033] Each particle can start from the current position and move to the next position based on the direction and magnitude of the velocity, thus continuously moving in the multidimensional space. When setting up a particle swarm, the position and velocity of each particle can be initialized, for example, an initial position and initial velocity are randomly set for each particle, and each particle starts to move based on the initial position and initial velocity.

[0034] Different positions in the multi-dimensional space can correspond to charging piles. This does not mean that the position in the multi-dimensional space and the physical position of the charging pile are the same, but that different positions in the multi-dimensional space are associated with different charging piles.

[0035] Step 102, each time the particle group completes the movement, the charging pile corresponding to the position of each particle is determined, and the fitness of the particle is determined according to the characteristic parameters of the charging pile.

[0036] After each particle completes a move, the entire particle group completes a move. In the case where each particle group completes a move, the charging pile corresponding to the position can be determined based on the position of each particle.

[0037] The characteristic parameters of the charging pile may include parameters used to describe the operating status of the charging pile, such as charging efficiency, vehicles to be charged, charging price, etc., and may also include some other characteristic parameters, such as the speed of the vehicle currently needing to be charged, the remaining power of the vehicle, the distance from the vehicle to the charging pile, etc.

[0038] Based on the characteristic parameters of the charging pile, the fitness can be calculated and used as the fitness of the particle that has currently arrived at the corresponding position. The fitness can indicate whether the current charging pile is suitable for charging the current vehicle and the degree of suitability. For example, the characteristic parameters include the distance from the vehicle to the charging pile. If the distance from the vehicle to the charging pile is too far, the vehicle is not suitable for charging at the charging pile. If the distance from the vehicle to the charging pile is short, the vehicle is relatively suitable for charging at the charging pile.

[0039] Step 103, when the particle swarm has completed multiple moves, determine the fitness combination of each particle and the fitness set of the particle swarm; each fitness combination has multiple fitnesses; and the fitness set has a preset number of fitness combinations.

[0040] When the particle group completes multiple moves (at least twice), since a fitness of a particle can be determined after each move, a fitness combination of each particle can be obtained after multiple moves, and each particle's fitness combination has multiple fitnesses (at least two).

[0041] The entire particle swarm also has a corresponding fitness set. After information is shared between particles, the fitness set can include a preset number of fitness combinations, that is, the fitness set of the entire particle swarm is composed of the fitness combination corresponding to each particle in the particle swarm.

[0042] After the particle group continues to move, the corresponding fitness combination and fitness set content can also add new fitness accordingly to update the data content of the fitness combination and fitness set.

[0043] Step 104, determining the largest first fitness in the fitness combination of each particle and the largest second fitness in the fitness set, and resetting the position and speed of the particles in the particle group when the characteristic parameter changes.

[0044] After multiple moves, each particle has multiple fitnesses in its fitness combination. The largest first fitness in the fitness combination is determined, and each particle has its own first fitness. Since each fitness is determined based on the location of the particle, the fitness of the corresponding charging pile is determined. Therefore, the location corresponding to the largest first fitness in the fitness combination indicates the most suitable charging pile found by the current particle during multiple moves. It is the individual optimal solution of each particle, that is, the individual extreme value.

[0045] The fitness set includes the fitness combination of all particles, so the largest second fitness in the fitness set indicates the most suitable charging pile found by all particles in the process of multiple moves. The second fitness is the global optimal solution of the entire particle swarm, that is, the global extreme value.

[0046] In addition, since the characteristic parameters of the charging pile may change, such as the charging efficiency, the vehicles to be charged, the charging price, etc., the fitness corresponding to different positions will change, which means that the fitness determined by the previous particle movement does not match the situation after the change.

[0047] For example, if it is detected that the number of remaining charging piles of a certain charging pile changes rapidly (i.e., the charging efficiency increases or decreases), the particles in the particle swarm can be initialized so that the particles can move and search again based on the new position and new speed to adapt to the changed characteristic parameters and fitness.

[0048] Step 105, according to the current position, current speed, first fitness and second fitness of each particle, control the next movement of each particle until the particle group completes a preset number of movements, and determine the maximum fitness in the fitness set and the target charging pile corresponding to the maximum fitness.

[0049] After moving for many times, each particle has its own first fitness, but each particle corresponds to the same second fitness. Since the first fitness is the individual extreme value of the current particle and the second fitness is the global extreme value, the movement of the particle can be controlled according to the positions corresponding to the first fitness and the second fitness, so that the particle will try to approach or reach the individual extreme value and the global extreme value after the next movement.

[0050] Therefore, the next movement of the particle can be controlled according to the current position and current speed of the particle combined with the positions corresponding to the first fitness and the second fitness.

[0051] Since the fitness combination of each particle will increase by one fitness after the next move is completed, the subsequent first fitness may change, and similarly, the second fitness may also change. However, based on a similar control process, the next move is still controlled based on the current position, current speed, first fitness and second fitness until the particle group completes the preset number of moves.

[0052] The preset number of moves can be understood as a termination condition for an iterative move. Since iterative moves can always be performed based on the current position, current speed, first fitness, and second fitness, a termination condition needs to be set to end the iterative process. After the preset number of moves is completed, the iteration can be stopped, the maximum fitness in the current fitness set and the position corresponding to the maximum fitness are determined, and then the target charging pile is determined based on the position.

[0053] After determining the target charging station, a path planning can be generated to navigate the vehicle to the target charging station.

[0054] It can be understood that although the steps in the above embodiments are based on the particle swarm algorithm, there are still obvious differences. Figure 2 is a schematic diagram of a particle swarm algorithm provided by an embodiment of the present disclosure;

[0055] Step 201, start;

[0056] Step 202, initializing the speed and position of each particle;

[0057] Step 203, calculating the fitness of the particle;

[0058] Step 204, solving the individual extreme value of each particle;

[0059] Step 205, solving the global extreme value in the population;

[0060] Step 206, updating the velocity and position of the particle;

[0061] Step 207, determining whether the termination condition is met;

[0062] Step 208, if the termination condition is met, then the process ends; if the termination condition is not met, then the process continues to move to calculate the fitness of the particle.

[0063] Figure 3 is a schematic diagram of a dynamic response particle swarm algorithm provided by an embodiment of the present disclosure;

[0064] Step 301, start;

[0065] Step 302, initializing the speed and position of each particle;

[0066] Step 303, calculating the fitness of the particle;

[0067] Step 304, solving the individual extreme value of each particle;

[0068] Step 305, solving the global extreme value in the population;

[0069] Step 306, updating the velocity and position of the particle;

[0070] Step 307, determining whether a characteristic parameter change occurs;

[0071] Step 308, if a characteristic parameter changes, the speed and position of the particle are reset;

[0072] Step 309: If no characteristic parameter changes occur, determine whether the termination condition is met;

[0073] Step 310, if the termination condition is met, then the process ends; if the termination condition is not met, then the process continues to move to calculate the fitness of the particle.

[0074] In summary, in the embodiment of the present disclosure, a particle swarm is set, and a preset number of particles in the particle swarm move between different positions in the space based on their respective positions and speeds. Each time the particle swarm completes the movement, the charging pile corresponding to the position of each particle is determined, and the fitness of the particle is determined according to the characteristic parameters of the charging pile. When the particle swarm completes multiple movements, the fitness combination of each particle and the fitness set of the particle swarm are determined, and the largest first fitness in the fitness combination of each particle and the largest second fitness in the fitness set are determined. In the case of changes in the characteristic parameters, the position and speed of the particles in the particle swarm are reset, and the next movement of each particle is controlled according to the current position, current speed, first fitness and second fitness of each particle until the particle swarm completes the preset number of movements, and the maximum fitness in the fitness set and the target charging pile corresponding to the maximum fitness are determined. Based on the particle movement search method, the characteristic parameters of the charging pile can be used as the core parameters to determine the fitness of the particle after each movement, and considering the variability of the characteristic parameters, the particles are initialized to adapt to the changes in the characteristic parameters, so that after multiple iterative movements of the particle swarm, the target charging pile that meets the actual situation can be accurately found, thereby improving the accuracy of determining the charging pile.

[0075] refer to Figure 4 , which shows a flowchart of the steps of a charging pile determination method provided by an embodiment of the present disclosure, the method comprising:

[0076] Step 401, setting a particle group; the particle group has a preset number of particles; each particle moves between different positions in the space based on its own position and speed; different positions correspond to different charging piles;

[0077] Step 402, each time the particle group completes the movement, determining the charging pile corresponding to the location of each particle, and determining the fitness of the particle according to the characteristic parameters of the charging pile;

[0078] Step 403, when the particle swarm has completed multiple moves, determine the fitness combination of each particle and the fitness set of the particle swarm; each fitness combination has multiple fitnesses; and the fitness set has a preset number of fitness combinations;

[0079] Step 404, determining the largest first fitness in the fitness combination of each particle and the largest second fitness in the fitness set, and resetting the position and speed of the particle in the particle group when the characteristic parameter changes;

[0080] Step 405, according to the current position, current speed, first fitness and second fitness of each particle, control the next movement of each particle until the particle group completes a preset number of movements, and determine the maximum fitness in the fitness set and the target charging pile corresponding to the maximum fitness.

[0081] The above steps 401-405 can refer to the above Figure 1 The contents of the embodiments will not be described in detail here.

[0082] Since the appropriate charging pile is to be selected, it is necessary to accurately calculate the fitness of the particles when they reach different positions during the movement. If the fitness calculation is inaccurate, the correct charging pile cannot be selected.

[0083] Optionally, each time the particle group completes the movement, determining the charging pile corresponding to the position of each particle, and determining the fitness of the particle according to the characteristic parameters of the charging pile, step 402 includes:

[0084] Sub-step 4021, determining the current position of each particle each time the particle group completes the movement; the current position is determined by the previous position and speed of the particle;

[0085] Sub-step 4022, determining a target charging pile corresponding to the current position according to a mapping relationship between a preset position and a charging pile;

[0086] Sub-step 4023, determining the fitness of the particle according to the time cost parameter and the charging cost parameter of the target charging pile.

[0087] In the disclosed embodiment, the current position of each particle is determined by the last position and speed of the particle, and the current position of each particle is determined each time the particle group completes the movement. According to the mapping relationship between the preset position and the charging pile, the target charging pile corresponding to the current position is determined.

[0088] The characteristic parameters of the charging pile may include a time cost parameter and a charging cost parameter. The fitness corresponding to the time cost can be calculated based on the time cost parameter, and the fitness corresponding to the charging cost can be calculated based on the charging cost parameter. Then, the fitness of the two can be added together to obtain the fitness of the particle. The fitness corresponding to the time cost can be calculated by the following formula:

[0089]

[0090] Simplifying, we get:

[0091]

[0092] Where: T n is the time cost fitness, and the time cost parameters include: d n is the distance from the starting point to the nth charging station, and v is the vehicle’s speed; is the waiting time from when the vehicle arrives at the charging station to when charging begins; d is the total distance from the starting point to the end point (the location the user ultimately hopes to reach).

[0093] The fitness corresponding to the charging cost can be calculated by the following formula:

[0094]

[0095]

[0096] in, It is the charging cost adaptability. The charging cost parameters include: is the charging unit price of the nth charging pile at time t, The remaining power of the vehicle when it arrives at the charging station; B cap is the vehicle battery capacity; η n (t) is the charging efficiency of the nth charging pile at time t; The remaining battery power during vehicle path planning, pd n Indicates the average power consumption per unit distance.

[0097] Based on the time cost fitness and charging cost fitness, the fitness of the particle is comprehensively obtained.

[0098] In the implementation of the embodiment of the present disclosure, each time the particle group completes the movement, the current position of each particle is determined, and the target charging pile corresponding to the current position is determined according to the mapping relationship between the preset position and the charging pile, and the fitness of the particle is determined according to the time cost parameter and the charging cost parameter of the target charging pile. The fitness of the particle can be determined by measuring the suitability of charging at a specific charging pile from the two perspectives of time cost and charging cost, thereby improving the accuracy of determining the fitness, and further improving the accuracy of determining the charging pile.

[0099] Measuring fitness from the perspectives of time cost and charging cost can determine fitness more comprehensively. However, different users have different demands for time cost and charging cost, which may easily lead to the final target charging pile still unable to accurately meet the user's personalized needs.

[0100] Optionally, the sub-step 4023 of determining the fitness of the particle according to the time cost parameter and the charging cost parameter of the target charging pile includes:

[0101] Step A1, determining a preset first weight and a second weight; the first weight corresponds to a time cost parameter; the second weight corresponds to a charging cost parameter;

[0102] Step A2: determining the fitness of the particle based on the first weight and the second weight, and the time cost parameter and the charging cost parameter of the target charging pile.

[0103] In the embodiment of the present disclosure, the time cost parameter and the charging cost parameter correspond to different weights, namely, a first weight and a second weight. The first weight and the second weight may be preset, for example, determined based on user settings, and the user may set a ratio of the time cost to the charging cost, and then the first weight and the second weight may be determined based on the ratio.

[0104] For example, if the ratio of time cost to charging cost is 2, the first weight of the time cost parameter may be 2, and the second weight of the charging cost parameter may be 1.

[0105] When the time cost fitness is calculated based on the time cost parameter, the time cost fitness can be multiplied by the first weight to obtain the adjusted time cost fitness. Similarly, when the charging cost fitness is calculated based on the charging cost parameter, the charging cost fitness can be multiplied by the second weight to obtain the adjusted charging cost fitness.

[0106] In the implementation of the embodiment of the present disclosure, the first weight and the second weight are determined, the first weight corresponds to the time cost parameter, and the second weight corresponds to the charging cost parameter. Based on the first weight and the second weight, and the time cost parameter and the charging cost parameter of the target charging pile, the fitness of the particle is determined. Based on different weights, the role of different characteristic parameters in calculating the fitness can be strengthened or weakened, and the charging pile finally determined can be more time-saving or more charging cost-saving for the user, thereby meeting the personalized needs of the user, and ultimately improving the flexibility and accuracy of determining the charging pile.

[0107] When the characteristic parameters change, the fitness of each particle has been calculated based on the characteristic parameters between the changes, and each particle has moved according to its current position, current speed, first fitness and second fitness, that is, the entire particle group has actually moved to the global extreme value corresponding to the second fitness. After the characteristic parameters change, the new global extreme value may be in other positions, but because the entire particle group has been concentrated near the old global extreme value, it is easy to lead to local optimality.

[0108] Optionally, there are multiple characteristic parameters; when the characteristic parameters change, the step of resetting the position and speed of particles in the particle group includes:

[0109] When any characteristic parameter among the plurality of characteristic parameters changes, determining a preset proportion of target particles in the particle group;

[0110] For each target particle, the position and velocity of the target particle are set to random values.

[0111] In the disclosed embodiment, there may be multiple characteristic parameters, and when any characteristic parameter among the multiple characteristic parameters changes, the actual fitness will change. Then, a preset proportion of target particles is selected from the particle group, and a preset proportion of particles can be randomly selected, and the preset proportion can be 10% or 30%, etc.

[0112] For each target particle, the position and velocity of each target particle are initialized, that is, the position and velocity are set to random values. Thus, the particle group is prevented from being concentrated near the old global extreme value, and some particles can be redistributed to other positions in the multidimensional space. Based on this, there is a greater possibility of searching for the changed global extreme value.

[0113] In implementing the embodiments of the present disclosure, when any characteristic parameter among multiple characteristic parameters changes, a preset proportion of target particles is determined in the particle swarm, and for each target particle, the position and speed of the target particle are set to random values, thereby avoiding the particle swarm from being concentrated near the old global extreme value, avoiding the problem of local optimality, being able to adapt to changes in characteristic parameters, and improving the accuracy of determining the charging pile.

[0114] When controlling movement based on the current position, current speed, first fitness, and second fitness, the current position is fixed and cannot be changed directly. The position needs to be moved before it can be changed. Therefore, the speed needs to be adjusted to control the movement of the particles. The movement control of the particles affects whether the accurate charging pile can be determined in the end.

[0115] Optionally, the step of controlling the next movement of each particle according to the current position, current speed, first fitness and second fitness of each particle includes:

[0116] According to a first fitness of each particle, determining a first position corresponding to the first fitness, and according to the second fitness, determining a second position corresponding to the second fitness;

[0117] Determining a first speed update parameter according to the first position of each particle and the current position of the particle, and determining a second speed update parameter according to the second position and the current position of the particle;

[0118] Based on the first speed update parameter and the preset third weight of each particle, the second speed update parameter and the preset fourth weight, the current speed is adjusted to obtain the update speed of each particle;

[0119] Based on the current position and update speed of each particle, the next movement of each particle is controlled to control the next movement of the particle group.

[0120] In the disclosed embodiment, firstly, the movement of the particle needs to be based on the current position, starting from the current position and moving at a certain speed. Since there are already individual extreme values ​​of the current particle and global extreme values ​​of the particle group, any particle needs to be close to the individual extreme value and the global extreme value, so that the particle has a greater possibility of finding the optimal solution.

[0121] For each particle, there is a corresponding first fitness and a second fitness. Since each fitness is actually determined based on a position reached by the particle, the corresponding first position can be determined according to the first fitness of each particle, and the corresponding second position can be determined according to the second fitness. The first position (individual optimal position) can be expressed as P i =(P i,1 ,P i,2 ,...P i,D ), the second position (global optimal position) can be expressed as G = (G1, G2, ... G D ).

[0122] Further, a first speed update parameter is determined according to the first position of each particle and the current position of the particle, and a second speed update parameter is determined according to the second position and the current position of the particle. The first speed update parameter may be obtained by subtracting the current position from the first position, and similarly, the second speed update parameter may be obtained by subtracting the current position from the second position.

[0123] The first speed update parameter and the second speed update parameter may also be speeds of different directions and magnitudes. When adjusting the speed of the particle, the current speed direction and speed magnitude are adjusted based on the speed corresponding to the direction and magnitude of the speed update parameter, thereby affecting the next movement of the particle.

[0124] When adjusting the speed according to the speed update parameter, different speed update parameters may correspond to different weights. The first speed update parameter corresponds to a preset third weight, the second speed update parameter corresponds to a fourth weight, and the third weight and the fourth weight are used to further adjust the influence of each speed update parameter on the speed. For example, if the particle is expected to be closer to the global extreme value relative to the individual extreme value, the fourth weight may be larger than the third weight.

[0125] The speed of the particle can be adjusted by the following formula:

[0126]

[0127] In the above formula, is the velocity of the ith particle during the k+1th movement, is the speed of the ith particle during the kth movement (i.e., the current speed), w k is the inertia weight of the kth move, w k The setting can be large in the early stage of particle movement, and gradually reduced later. It can be set to w k =[0.4,0.9]; ∝ is the individual learning factor, i.e., the third weight, and β is the group learning factor, i.e., the fourth weight, which respectively determine the degree to which the particle approaches its own optimal position and the global optimal position; rand() is a random number uniformly distributed in the interval [0,1], which is used to increase the randomness of the search; P i k is the first position (individual extreme value) corresponding to the i-th particle during the k-th movement, is the second position (global extreme value) corresponding to the i-th particle during the k-th movement, is the position of the i-th particle at the k-th move (i.e., the current position).

[0128] In order to prevent the particle speed from being too high and causing the particle to miss some positions in space, the particle speed can be limited. The formula is as follows:

[0129]

[0130] In the above formula, v i,d is the velocity of the ith particle in a certain dimension d, v max is the preset speed limit. If the particle's speed in a certain dimension exceeds v max , then set it to v max ; If the speed is less than -vmax , set it to -v max .

[0131] After adjusting the speed, the next movement of each particle can be controlled based on the current position of the particle and the updated speed, thereby controlling the next movement of the particle group. The process of moving based on the updated speed and current position can be expressed as:

[0132]

[0133] The above formula indicates that according to the updated speed and current location After moving, arrive

[0134] In the embodiment of the present disclosure, the first position corresponding to each particle is determined according to the first fitness, and the second position corresponding to the second fitness is determined according to the first position and the current position of each particle, the first speed update parameter is determined according to the second position and the current position, the second speed update parameter is determined according to the first speed update parameter of each particle and the preset third weight, the second speed update parameter and the preset fourth weight, the current speed is adjusted to obtain the update speed of each particle, and the next movement of each particle is controlled based on the current position and the update speed of each particle to control the next movement of the particle group. The influence of the speed update parameter on the speed can be adjusted by different weights, so that the movement of the particles can be flexibly controlled, and the control accuracy of the particle movement is improved.

[0135] The third weight and the fourth weight can adjust the influence of the speed update parameter on the speed, so as to control the movement of the particles. If the third weight and the fourth weight are fixed values, the adjustment effect when adjusting the influence of the speed update parameter on the speed is consistent, but since the characteristic parameters are changing, the application of fixed weight values ​​is likely to lead to inaccurate results.

[0136] Optionally, the step of adjusting the current speed to obtain the update speed of each particle based on the first speed update parameter and the preset third weight of each particle, the second speed update parameter and the preset fourth weight, comprises:

[0137] According to the variation range of the characteristic parameter, respectively adjusting the preset third weight and the preset fourth weight to obtain an updated third weight and an updated fourth weight;

[0138] Based on the first speed update parameter of each particle and the updated third weight, the second speed update parameter and the updated fourth weight, the current speed is adjusted to obtain the updated speed of each particle.

[0139] In the embodiment of the present disclosure, when the characteristic parameter changes, the change range of the characteristic parameter can be determined, and based on the change range, the preset third weight and the preset fourth weight are adjusted.

[0140] For example, the characteristic parameter is vehicle speed, which can indicate the degree of congestion. If more vehicles are on the road and the speed decreases, the degree of congestion on the road increases, and the road at this time is considered not to be the road corresponding to the target charging pile. The characteristic parameter can also be degree efficiency and other parameters.

[0141] The third weight can be reduced and the fourth weight can be increased by the change in vehicle speed. The degree of congestion can also be calculated based on the change in vehicle speed, and the third and fourth weights can be adjusted based on the degree of congestion. If the third weight is α, α=2.5-ε; the fourth weight is β, β=0.5+ε; the degree of congestion is ε, ε∈[0,1], when the vehicle speed is reduced to half of the normal speed, the congestion degree ε can be 0.5, then α is 2, and β is 1. This allows the user to combine dynamic traffic data and accurately provide intelligent judgment and decision-making for travel and charging.

[0142] In the implementation of the embodiment of the present disclosure, the preset third weight and the preset fourth weight are adjusted respectively according to the variation range of the characteristic parameter to obtain the updated third weight and the updated fourth weight, and the current speed is adjusted based on the first speed update parameter of each particle and the updated third weight, the second speed update parameter and the updated fourth weight to obtain the updated speed of each particle. The third weight and the fourth weight can be adjusted based on the variation range of the characteristic parameter, and the influence of the speed update parameter on the speed can be flexibly adjusted, and the characteristic parameter can be adapted to the variation, and the accuracy of determining the charging pile is finally improved.

[0143] The particle swarm algorithm includes a termination condition for the number of iterations. When the number of movement of the particle swarm reaches the preset number, it will no longer iterate. However, during the iterative movement of the particle swarm, a suitable target charging pile may have been found, but due to the limitation of the number of iterations, it still needs to continue iterative movement until the termination condition for the number of iterations is met, which affects the efficiency of determining the charging pile.

[0144] Optionally, the method further includes:

[0145] When the particle swarm has completed multiple movements, determining fitness sets corresponding to the most recent several movements, and the maximum fitness in each fitness set;

[0146] Determine the position corresponding to each maximum fitness and the charging pile corresponding to each position respectively;

[0147] When the charging piles corresponding to the most recent movements are the same, the charging pile is determined to be the target charging pile.

[0148] In the disclosed embodiment, after the particle group moves multiple times, a fitness set is generated, in which the maximum fitness, namely the second fitness, is included. After each move, a new fitness is added to the fitness set, and the maximum fitness in the new fitness set is still determined.

[0149] The maximum fitness in the fitness set after each move can be recorded, and the position corresponding to the maximum fitness and the charging pile corresponding to the position are the target charging pile after the current move. If the fitness sets corresponding to the most recent moves and the positions corresponding to the maximum fitness in each fitness set are the same, it means that the same target charging pile is determined after the most recent moves, which means that the global extreme value has stabilized.

[0150] Therefore, if the charging piles corresponding to the most recent several movements are the same, the charging pile can be determined as the final target charging pile, and it is no longer necessary to iterate the movement until the preset number of times before determining the target charging pile.

[0151] In the implementation of the embodiment of the present disclosure, when the particle group has completed multiple movements, the fitness sets corresponding to the most recent several movements and the maximum fitness in each fitness set are determined, and the positions corresponding to each maximum fitness and the charging pile corresponding to each position are determined respectively. When the charging piles corresponding to the most recent several movements are the same, the charging pile is determined to be the target charging pile. The limitation of the preset number of iterations can be avoided. When a stable target charging pile has been searched, the target charging pile is determined, and the number of iterative movements and the time of iterative movements can be shortened, thereby improving the efficiency of determining the charging pile.

[0152] Figure 5 A charging pile determination device provided by an embodiment of the present disclosure includes:

[0153] A particle setting module is used to set a particle group; the particle group has a preset number of particles; each particle moves between different positions in the space based on its own position and speed; different positions correspond to different charging piles;

[0154] An adaptation determination module, used to determine the charging pile corresponding to the position of each particle each time the particle group completes the movement, and determine the fitness of the particle according to the characteristic parameters of the charging pile;

[0155] A combination set module, used for determining the fitness combination of each particle and the fitness set of the particle swarm when the particle swarm completes multiple moves; each fitness combination has multiple fitnesses; and the fitness set has a preset number of fitness combinations;

[0156] a change response module, used to determine the largest first fitness in the fitness combination of each particle and the largest second fitness in the fitness set, and reset the position and speed of the particles in the particle group when the characteristic parameter changes;

[0157] A target determination module is used to control the next movement of each particle according to the current position, current speed, first fitness and second fitness of each particle until the particle group completes a preset number of movements, and determine the maximum fitness in the fitness set and the target charging pile corresponding to the maximum fitness.

[0158] Optionally, adapt the module to include:

[0159] A position determination submodule, used to determine the current position of each particle each time the particle group completes movement; the current position is determined by the previous position and speed of the particle;

[0160] A charging pile determination submodule, used to determine a target charging pile corresponding to the current position according to a mapping relationship between a preset position and a charging pile;

[0161] The fitness determination submodule is used to determine the fitness of the particle according to the time cost parameter and the charging cost parameter of the target charging pile.

[0162] Optional, fitness determination submodule, including:

[0163] A cost weight determination unit, used to determine a preset first weight and a second weight; the first weight corresponds to a time cost parameter; the second weight corresponds to a charging cost parameter;

[0164] A cost weight calculation unit is used to determine the fitness of the particle based on the first weight and the second weight, and the time cost parameter and the charging cost parameter of the target charging pile.

[0165] Optionally, there are multiple characteristic parameters; the change response module includes:

[0166] A particle proportion submodule, used for determining a preset proportion of target particles in the particle group when any characteristic parameter among the plurality of characteristic parameters changes;

[0167] The particle initialization submodule is used to set the position and speed of each target particle to random values.

[0168] Optional, target determination module, including:

[0169] an influence position submodule, configured to determine, according to a first fitness of each particle, a first position corresponding to the first fitness, and, according to the second fitness, determine a second position corresponding to the second fitness;

[0170] a speed update parameter submodule, for determining a first speed update parameter according to a first position of each particle and a current position of the particle, and determining a second speed update parameter according to the second position and the current position of the particle;

[0171] A speed parameter weight submodule, for adjusting the current speed to obtain an update speed of each particle based on a first speed update parameter and a preset third weight of each particle, a second speed update parameter and a preset fourth weight;

[0172] The movement control submodule is used to control the next movement of each particle based on the current position and update speed of each particle, so as to control the next movement of the particle group.

[0173] Optional, speed parameter weight submodule, including:

[0174] A characteristic change amplitude unit, used to adjust the preset third weight and the preset fourth weight respectively according to the change amplitude of the characteristic parameter to obtain an updated third weight and an updated fourth weight;

[0175] The weighted speed update unit is used to adjust the current speed to obtain the updated speed of each particle based on the first speed update parameter of each particle and the updated third weight, the second speed update parameter and the updated fourth weight.

[0176] Optionally, the device further comprises:

[0177] A fitness detection module is used to determine the fitness sets corresponding to the most recent several movements and the maximum fitness in each fitness set when the particle swarm has completed multiple movements;

[0178] A multi-charging pile module, used to respectively determine the position corresponding to each maximum fitness and the charging pile corresponding to each position;

[0179] The consistency judgment module is used to determine that the charging pile is the target charging pile when the charging piles corresponding to the most recent several movements are the same.

[0180] In summary, in the embodiment of the present disclosure, a particle swarm is set, and a preset number of particles in the particle swarm move between different positions in the space based on their respective positions and speeds. Each time the particle swarm completes the movement, the charging pile corresponding to the position of each particle is determined, and the fitness of the particle is determined according to the characteristic parameters of the charging pile. When the particle swarm completes multiple movements, the fitness combination of each particle and the fitness set of the particle swarm are determined, and the largest first fitness in the fitness combination of each particle and the largest second fitness in the fitness set are determined. In the case of changes in the characteristic parameters, the position and speed of the particles in the particle swarm are reset, and the next movement of each particle is controlled according to the current position, current speed, first fitness and second fitness of each particle until the particle swarm completes the preset number of movements, and the maximum fitness in the fitness set and the target charging pile corresponding to the maximum fitness are determined. Based on the particle movement search method, the characteristic parameters of the charging pile can be used as the core parameters to determine the fitness of the particle after each movement, and considering the variability of the characteristic parameters, the particles are initialized to adapt to the changes in the characteristic parameters, so that after multiple iterative movements of the particle swarm, the target charging pile that meets the actual situation can be accurately found, thereby improving the accuracy of determining the charging pile.

[0181] The present application also provides an electronic device, such as Figure 6 As shown, it includes a processor 1001 , a communication interface 1002 , a memory 1003 and a communication bus 1004 , wherein the processor 1001 , the communication interface 1002 , and the memory 1003 communicate with each other via the communication bus 1004 .

[0182] The memory 1003 is used to store computer programs.

[0183] When the processor 1001 is used to execute the program stored in the memory 1003, the steps in the above-mentioned charging pile determination method are implemented, which will not be repeated here.

[0184] The communication bus mentioned in the above electronic device can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0185] The communication interface is used for communication between the above electronic device and other devices.

[0186] The memory may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0187] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0188] In another embodiment provided in the present application, a computer-readable storage medium is also provided, in which instructions are stored. When the computer-readable storage medium is executed on a computer, the computer executes the charging pile determination method described in the above embodiment.

[0189] In another embodiment provided in the present application, a computer program product including instructions is also provided. When the computer program product is executed on a computer, the computer executes the charging pile determination method described in the above embodiment.

[0190] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive Solid State Disk (SSD)), etc.

[0191] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0192] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. For the embodiments of the device, electronic device, computer-readable storage medium and computer program products containing instructions, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0193] The above description is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application are included in the protection scope of the present application.

Claims

1. A method for determining a charging pile, characterized in that: The method comprises: Setting a particle group; the particle group has a preset number of particles; each particle moves between different positions in the space based on its own position and speed; different positions correspond to different charging piles; Each time the particle group completes the movement, determining the charging pile corresponding to the position of each particle, and determining the fitness of the particle according to the characteristic parameters of the charging pile; When the particle group has completed multiple moves, determining a fitness combination of each particle and a fitness set of the particle group; each fitness combination has multiple fitnesses; and the fitness set has a preset number of fitness combinations; Determine the largest first fitness in the fitness combination of each particle and the largest second fitness in the fitness set, and reset the position and speed of the particles in the particle group when the characteristic parameter changes; According to the current position, current speed, first fitness and second fitness of each particle, the next movement of each particle is controlled until the particle group completes a preset number of movements, and the maximum fitness in the fitness set and the target charging pile corresponding to the maximum fitness are determined.

2. The method according to claim 1, characterized in that Each time the particle group completes its movement, the step of determining the charging pile corresponding to the position of each particle, and determining the fitness of the particle according to the characteristic parameters of the charging pile includes: Each time the particle group completes its movement, determining the current position of each particle; the current position is determined by the previous position and velocity of the particle; Determine a target charging pile corresponding to the current position according to a mapping relationship between a preset position and a charging pile; The fitness of the particle is determined according to the time cost parameter and the charging cost parameter of the target charging pile.

3. The method according to claim 2, characterized in that The step of determining the fitness of the particle according to the time cost parameter and the charging cost parameter of the target charging pile comprises: Determine a preset first weight and a second weight; the first weight corresponds to a time cost parameter; the second weight corresponds to a charging cost parameter; The fitness of the particle is determined based on the first weight and the second weight, and a time cost parameter and a charging cost parameter of the target charging pile.

4. The method according to claim 1, characterized in that: There are multiple characteristic parameters; when the characteristic parameters change, the step of resetting the position and speed of the particles in the particle group includes: When any characteristic parameter among the plurality of characteristic parameters changes, determining a preset proportion of target particles in the particle group; For each target particle, the position and velocity of the target particle are set to random values.

5. The method according to claim 1, characterized in that The step of controlling the next movement of each particle according to the current position, current speed, first fitness and second fitness of each particle comprises: According to a first fitness of each particle, determining a first position corresponding to the first fitness, and according to the second fitness, determining a second position corresponding to the second fitness; Determining a first speed update parameter according to the first position of each particle and the current position of the particle, and determining a second speed update parameter according to the second position and the current position of the particle; Based on the first speed update parameter and the preset third weight of each particle, the second speed update parameter and the preset fourth weight, the current speed is adjusted to obtain the update speed of each particle; Based on the current position and update speed of each particle, the next movement of each particle is controlled to control the next movement of the particle group.

6. The method according to claim 5, characterized in that The step of adjusting the current speed to obtain the update speed of each particle based on the first speed update parameter and the preset third weight of each particle, the second speed update parameter and the preset fourth weight, comprises: According to the variation range of the characteristic parameter, respectively adjusting the preset third weight and the preset fourth weight to obtain an updated third weight and an updated fourth weight; Based on the first speed update parameter of each particle and the updated third weight, the second speed update parameter and the updated fourth weight, the current speed is adjusted to obtain the updated speed of each particle.

7. The method according to claim 1, characterized in that The method further comprises: When the particle swarm has completed multiple movements, determining fitness sets corresponding to the most recent several movements, and the maximum fitness in each fitness set; Determine the position corresponding to each maximum fitness and the charging pile corresponding to each position respectively; When the charging piles corresponding to the most recent several movements are the same, the charging pile is determined to be the target charging pile.

8. A charging pile determination device, characterized in that: The device comprises: A particle setting module is used to set a particle group; the particle group has a preset number of particles; each particle moves between different positions in the space based on its own position and speed; different positions correspond to different charging piles; An adaptation determination module, used to determine the charging pile corresponding to the position of each particle each time the particle group completes the movement, and determine the fitness of the particle according to the characteristic parameters of the charging pile; A combination set module, used for determining the fitness combination of each particle and the fitness set of the particle swarm when the particle swarm completes multiple moves; each fitness combination has multiple fitnesses; and the fitness set has a preset number of fitness combinations; a change response module, used to determine the largest first fitness in the fitness combination of each particle and the largest second fitness in the fitness set, and reset the position and speed of the particles in the particle group when the characteristic parameter changes; A target determination module is used to control the next movement of each particle according to the current position, current speed, first fitness and second fitness of each particle until the particle group completes a preset number of movements, and determine the maximum fitness in the fitness set and the target charging pile corresponding to the maximum fitness.

9. An electronic device, characterized in that: include: Processor, communication interface, memory and communication bus; The processor, the communication interface and the memory communicate with each other via a communication bus; Memory, used to store computer programs; The processor is used to implement the steps in the charging pile determination method as described in any one of claims 1 to 7 when executing the program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps in the charging pile determination method as described in any one of claims 1 to 7 are implemented.

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