WO2023125695A1

WO2023125695A1 - Method and apparatus for optimizing battery swapping station recommendation method, and electronic device and storage medium

Info

Publication number: WO2023125695A1
Application number: PCT/CN2022/142921
Authority: WO
Inventors: 白留伟
Original assignee: 奥动新能源汽车科技有限公司; 上海电巴新能源科技有限公司
Priority date: 2021-12-31
Filing date: 2022-12-28
Publication date: 2023-07-06
Also published as: CN116415076A

Abstract

Disclosed in the present invention are a method and apparatus for optimizing a battery swapping station recommendation method, and an electronic device and a storage medium. The method for optimizing a battery swapping station recommendation method comprises the following steps: executing a battery swapping station recommendation method, and sending information of a recommended battery swapping station to a user group; acquiring feedback behavior of the user group regarding the information of the recommended battery swapping station; dividing the user group into effectively recommended users and ineffectively recommended users according to whether the feedback behavior satisfies a preset condition; and optimizing the battery swapping station recommendation method according to the proportion of the effectively recommended users of the user group. In the present invention, a battery swapping station recommendation method is optimized according to the proportion of effectively recommended users of a user group, such that a closed loop can be formed between a recommended battery swapping station and feedback of users on the recommended battery swapping station, and the recommended battery swapping station can better meet battery swapping requirements of the users, thereby improving the effectiveness of recommendation, i.e. optimizing a battery swapping station recommendation method, and improving the user experience during a battery swapping process.

Description

Optimization method and device, electronic equipment, and storage medium for recommended method of power station replacement

This application claims the priority of Chinese patent application 2021116734289 with a filing date of 2021/12/31. This application cites the full text of the above-mentioned Chinese patent application.

technical field

The present invention relates to the technical field of battery swapping, and in particular to an optimization method and device, electronic equipment, and a storage medium for a recommended method of a battery swapping station.

Background technique

With the popularization of electric vehicles, it has become an indispensable way to supply electric energy to electric vehicles by means of battery swapping. Specifically, the method of battery swap means that the electric vehicle goes to the battery swap station to remove the battery that has lost power and install a fully charged battery. The power exchange station can provide fast battery exchange service for electric vehicles to solve the battery life problem of electric vehicles. In order to ensure the battery life of electric vehicles, there are more and more new battery exchange stations. Choose, currently, the recommendation method will be used to recommend power stations to users, but it is not known whether the recommended power stations meet the needs of users. If you keep recommending power stations that do not meet the needs of users, it will cause trouble for users and reduce the cost of battery replacement. Process user experience.

Contents of the invention

The technical problem to be solved by the present invention is to overcome the above-mentioned defects in the prior art, and provide an optimization method and device, electronic equipment and a storage medium for a power station recommendation method.

The present invention solves the above technical problems through the following technical solutions:

A first aspect of the present invention provides an optimization method for a power station recommendation method, comprising the following steps:

Execute the method of recommending the replacement station, and send the recommended replacement station information to the user group;

Obtaining the feedback behavior of the user group with respect to the information of the recommended battery swapping station;

According to whether the feedback behavior meets preset conditions, the user group is divided into valid recommended users and invalid recommended users;

According to the proportion of effective recommended users in the user group, the method for recommending power stations is optimized.

In this solution, the power exchange recommendation method is optimized according to the proportion of effective recommended users in the user group, so that a closed loop can be formed between the recommended power exchange and the user's feedback based on the recommended power exchange, and the recommended power exchange can be more in line with the user's power exchange In order to meet the needs, the effectiveness of the recommendation is improved, that is to say, the optimization of the recommended method for the power station is realized, and the user experience of the power replacement process is improved.

Optionally, the step of implementing the method for recommending a power station replacement specifically includes:

Select at least two alternative substations;

A recommended switching station is determined according to the at least two candidate switching stations.

In this scheme, at least two alternative substations are selected from all the substations, and then the recommended substation is determined from at least two alternative substations. The recommended efficiency of the plant.

Optionally, the step of selecting at least two alternative substations specifically includes:

According to the distance between the current position of the user's vehicle and the switching station, and/or the historical driving trajectory of the user's vehicle, at least two candidate switching stations are selected.

In this solution, based on the two dimensions of the current location of the user's vehicle and/or the historical driving trajectory of the user's vehicle, an alternative power station that meets the needs of the user is initially selected, which improves the efficiency of power station recommendation.

Optionally, the step of determining the recommended switching station according to the at least two candidate switching stations specifically includes:

According to the remaining mileage of the user's vehicle and the distance between the current location and the at least two alternative switching stations, determine an optional switching station from at least two alternative switching stations;

According to the distance between the optional power station and the current position of the user's vehicle and the busyness of the optional power station, the weighted summation is performed to obtain the calculation result;

The recommended switching station is determined from the optional switching stations according to the calculation result.

In this scheme, according to the remaining mileage of the user's vehicle, the optional swapping station is determined from the alternative swapping stations, and the recommended swapping station is determined from the optional swapping stations, which can prevent the user's vehicle from being unable to reach the recommended swapping station before the power consumption is exhausted. ;Furthermore, combined with the distance between the optional swap station and the current location of the user's vehicle and the busyness of the optional swap station to recommend the swap station, a better recommended swap station can be further determined. The timeliness is high, and the actual situation of the battery replacement process is comprehensively considered, which meets the user's battery replacement needs to a certain extent, and the recommendation accuracy is high.

Optionally, the optimization method also includes the following steps:

Obtain the number of people in line and the number of replaceable batteries of the replaceable power station, and calculate the busyness of the replaceable power station.

In this scheme, the number of people queuing up for the replaceable power station and the number of replaceable batteries together reflect the busyness of the replaceable power station, and the busyness calculated by combining the number of people in the queue and the number of replaceable batteries can be closer to the actual busyness of the replaceable power station degree, higher accuracy.

Optionally, the step of optimizing the power-swapping station recommendation method according to the ratio of effective recommended users to the user group specifically includes:

Calculate the ratio of effective recommended users to the user group;

The weight parameter of the distance between the switchable power station and the current location of the user's vehicle and the weight parameter of the busyness of the switchable power station are adjusted according to the ratio.

In this solution, the two weight parameters used in the power swapping recommendation method are adjusted by the ratio of the effective recommended users to the user group, so as to realize the optimization of the power swapping recommendation method.

Optionally, the step of adjusting the weight parameters of the distance between the optional swappable power station and the current location of the user's vehicle and the busyness of the optional swappable power station according to the ratio specifically includes:

Judging whether the ratio is lower than a preset value; if so, adjusting the weight parameter of the distance between the optional swappable power station and the current location of the user's vehicle and the weight parameter of the busyness of the optional swappable power station.

In this scheme, if the proportion of effective recommended users in the user group is lower than the preset value, it means that the power replacement station recommended by the power replacement station recommendation method does not fit the user's power replacement needs particularly well. By adjusting the weight parameters used in the power replacement station recommendation method The method for recommending a battery swapping station can recommend a swapping station that is more in line with a battery swapping requirement to a user.

Optionally, the optimization method also includes the following steps:

According to the adjusted weight parameters, execute the power station replacement recommendation method again, and obtain the ratio of effective recommended users to the user group;

It is judged whether the ratio is increased; if so, the weight parameter is updated to complete the optimization of the power station recommendation method.

In this scheme, after the weight parameter adjustment in the power station replacement recommendation method, it is determined whether to update the weight parameter in the power station replacement recommendation method according to whether the proportion of effective recommended users in the user group increases. Specifically, if the ratio increases, the power station replacement The weight parameter in the recommended method is updated to the adjusted weight parameter to realize the optimization of the recommended method for power station replacement; if the ratio does not increase, the weight parameter in the recommended method for power station replacement will not be updated, and on this basis, other methods can be tried. The way to adjust the parameters.

Optionally, the feedback behavior includes: at least one of display screen touch, voice feedback, and battery replacement.

Optionally, the step of dividing the user group into valid recommended users and invalid recommended users according to whether the feedback behavior satisfies a preset condition specifically includes:

Judging whether the feedback behavior of each user in the user group belongs to at least one of the screen touch confirmation to select the recommended replacement station, the voice feedback to confirm the selection of the recommended replacement station, and the completion of the power replacement order at the recommended replacement station;

If yes, classify the user as a valid recommendation user; if not, classify the user as an invalid recommendation user.

In this solution, the selection of the recommended replacement station through the touch screen confirmation, the voice feedback confirmation of the selection of the recommended replacement station, and the completion of the replacement order at the recommended replacement station can all reflect that the recommended replacement station meets the user's replacement needs, so there will be these feedback behaviors The users are divided into effective recommended users, and further according to the proportion of effective recommended users to the user group, it is determined whether it is necessary to optimize the method of recommending power stations to improve the accuracy of recommending power stations.

The second aspect of the present invention provides an optimization device for a power station recommendation method, including:

The recommendation module is used to implement the method for recommending the replacement station, and send the recommended replacement station information to the user group;

An acquisition module, configured to acquire the feedback behavior of the user group with respect to the information of the recommended battery swapping station;

A division module, configured to divide the user group into valid recommendation users and invalid recommendation users according to whether the feedback behavior satisfies a preset condition;

The optimization module is used to optimize the power-swapping station recommendation method according to the ratio of effective recommended users to the user group.

A third aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. When the processor executes the computer program, the computer program described in the first aspect is implemented. The optimization method of the recommended method for power-swapping stations.

A fourth aspect of the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for optimizing the method for recommending a battery-swapping station as described in the first aspect is implemented.

The positive and progressive effect of the present invention lies in that: according to the proportion of effective recommended users in the user group, the method for recommending power stations is optimized, so that a closed loop can be formed between the recommended power stations and the user's feedback based on the recommended power stations, and the recommended power stations can be more in line with The effectiveness of the recommendation is improved according to the user's battery replacement needs, that is, the optimization of the recommended method for the battery replacement station is realized, and the user experience in the battery replacement process is improved.

Description of drawings

FIG. 1 is a flow chart of an optimization method for a power station recommendation method provided in Embodiment 1 of the present invention.

FIG. 2 is a flow chart of step S12 provided by Embodiment 1 of the present invention.

Fig. 3 is a schematic diagram of a funnel model provided by Example 1 of the present invention.

FIG. 4 is a structural block diagram of an optimization device for a method for recommending a battery swapping station provided in Embodiment 1 of the present invention.

FIG. 5 is a schematic structural diagram of an electronic device provided by Embodiment 2 of the present invention.

Detailed ways

The present invention is further illustrated below by means of examples, but the present invention is not limited to the scope of the examples.

Example 1

Figure 1 is a schematic flow chart of an optimization method for a power station recommendation method provided in this embodiment. The optimization method for a power station recommendation method can be executed by an optimization device for a power station recommendation method, and the optimization device for a power station recommendation method can pass Realized in the form of software and/or hardware, the optimization device of the power station recommendation method may be part or all of the electronic equipment. Wherein, the electronic device in this embodiment can be a personal computer (Personal Computer, PC), such as a desktop computer, an all-in-one computer, a notebook computer, a tablet computer, etc., or a mobile phone, a wearable device, a personal digital assistant (Personal Digital Assistant, PDA) and other terminal equipment. In the following, the optimization method of the method for recommending a battery swap station provided in this embodiment will be introduced with the electronic device as the execution subject.

As shown in FIG. 1 , the optimization method of the recommended method for power station replacement provided in this embodiment may include the following steps S1-S4:

Step S1. Execute the method for recommending battery swapping stations, and send information about the recommended swapping stations to the user group. Among them, the user group can be all users who register for the battery swap application program, and can also be potential users, that is, non-churn users who register for the battery swap application program.

Execute the method of recommending the replacement station to get the recommended replacement station. Specifically, the recommended replacement station information can be sent to the user group through the battery replacement application program, and the recommended replacement station information can be sent to the user group through the navigation application program, so that the user can directly navigate to the recommended replacement station. ; It is also possible to send information on recommended replacement stations to user groups through instant messaging applications. Wherein, the information of the recommended battery exchange station may include the location of the recommended battery exchange station, the name of the recommended battery exchange station, the number of people queuing up at the recommended battery exchange station, the number of replaceable batteries at the recommended battery exchange station, and the like.

In an optional implementation manner, step S1 includes the following steps S11-S12:

Step S11, selecting at least two alternative substations.

In a specific implementation, at least two alternative switching stations may be selected according to the distance between the current location of the user's vehicle and the switching station, and/or the historical driving trajectory of the user's vehicle.

In a specific example, at least two candidate switching stations with the shortest distance between the current position of the user's vehicle and the switching station are selected. Specifically, the distance d between the current position of the user's vehicle and the power station can be calculated according to the following formula:

d=111.12cos{1/[sinΦXsinΦY ten cosΦXcosΦYcos(λY—λX)]};

Wherein, the longitude and latitude of the current location X of the user's vehicle are λX and ΦX respectively, and the longitude and latitude of the location Y of the power station are λY and ΦY respectively.

In another specific example, at least two candidate switching stations with the shortest distance between the historical position of the user's vehicle and the switching station are selected according to the historical driving trajectory of the user's vehicle.

Step S12, determining a recommended switching station according to the at least two candidate switching stations.

Wherein, the number of recommended replacement stations may be one or multiple, which may be set according to actual conditions.

In an optional implementation manner, as shown in FIG. 2, the above step S12 includes the following steps S121-S123:

Step S121, according to the remaining mileage of the user's vehicle and the distance between the current location and the at least two alternative switching stations, determine the optional switching stations from the at least two candidate switching stations.

Wherein, the remaining mileage of the user's vehicle refers to the mileage that the energy of the current battery can provide for the user's vehicle to travel. If the distance between the current position of the user's vehicle and the alternative power station does not exceed the remaining mileage of the user's vehicle, then the alternative power station is determined as an optional power station. If the distance between the current position of the user's vehicle and the alternative power station exceeds the remaining mileage of the user's vehicle, then the alternative power station is determined to be an unavailable power station.

Step S122 , performing a weighted summation according to the distance between the optional swappable power station and the current location of the user's vehicle and the busyness of the optional swappable power station to obtain a calculation result. Specifically, the weight parameter rate1 of the distance between the optional swappable power station and the current location of the user's vehicle and the weight parameter rate2 of the busyness of the optional swappable power station can be set according to the actual situation. Among them, rate1+rate2=1.

In a specific implementation, the busyness of the replaceable power station can be calculated by obtaining the number of queued people in the replaceable power station and the number of replaceable batteries. In a specific example, the busyness of the replaceable power station=the number of queued people in the replaceable power station/the number of replaceable batteries in the replaceable power station.

Step S123: Determine the recommended switching station from the optional switching stations according to the calculation result. Specifically, the calculation results may be sorted, and the optional switching stations corresponding to the largest N values or the smallest N values in the sorting results are determined as recommended switching stations. Wherein, N is an integer, and N≥1.

It should be noted that, if the number of optional switching stations is one, it is not necessary to perform steps S122 and S123 after step S121, and the optional switching station can be directly determined as the recommended switching station, or the number of alternative switching stations can be increased. Re-determine the optional replacement station from the alternative replacement stations, and then determine the recommended replacement station.

Step S2. Obtain the feedback behavior of the user group with respect to the information of the recommended switching station. Specifically, the feedback behavior of the user group within a period of time may be obtained, for example, within a day, within a week, and so on.

In a specific implementation, the feedback behavior may be at least one of display screen touch, voice feedback, and battery replacement.

Step S3, according to whether the feedback behavior satisfies a preset condition, the user group is divided into valid recommendation users and invalid recommendation users. Among them, the preset condition can be set according to the actual interaction between the user and the recommended battery exchange station, for example, it can be set to confirm the selection of the recommended battery exchange station, complete the battery exchange order at the recommended battery exchange station, and so on.

In the example where the feedback behavior is display screen touch, it is judged whether the feedback behavior of each user in the user group belongs to the display screen touch confirmation to select the recommended replacement station, if so, the user is divided into an effective recommended user, if not, then Classify users as invalid referral users. Effectively recommended users in this example may also be referred to as intended users.

In the example where the feedback behavior is voice feedback, it is judged whether the feedback behavior of each user in the user group belongs to the voice feedback to confirm the selection of the recommended switching station, if so, the user is divided into valid recommended users, if not, the user Classified as an invalid referral user. Effectively recommended users in this example may also be referred to as intended users.

In the example where the feedback behavior is the implementation of battery replacement, it is judged whether the feedback behavior of each user in the user group belongs to the completion of the power replacement order at the recommended power replacement station, if yes, the user is divided into valid recommended users, if not, Classify users as invalid referral users. The effectively recommended users in this example may also be referred to as battery exchange users.

Step S4: Optimizing the method for recommending power stations according to the ratio of effective recommended users to the user group.

In this embodiment, the power exchange recommendation method is optimized according to the proportion of effective recommended users in the user group, so that a closed loop can be formed between the recommended power exchange and the user's feedback based on the recommended power exchange, so that the recommended power exchange can be more in line with the user's power exchange The effectiveness of the recommendation is improved, that is, the optimization of the recommended method for the power station is realized, and the user experience of the power replacement process is improved.

In an optional implementation manner, step S4 includes the following steps S41-S42:

Step S41, calculating the ratio of effective recommended users to the user group. Specifically, the ratio between the number of effectively recommended users and the number of users in the user group is calculated.

Step S42 , adjusting the weight parameter rate1 of the distance between the optional swappable power station and the current location of the user's vehicle and the weight parameter rate2 of the busyness of the optional swappable power station according to the ratio.

In this embodiment, by adjusting the weight parameters rate1 and rate2, the goal of optimizing the method for recommending a power station including steps S11, S121, S122 and S123 is achieved.

In an optional implementation of step S42, it is judged whether the ratio is lower than a preset value; if so, the weight parameter rate1 of the distance between the optional swap station and the current location of the user's vehicle and the busyness of the optional swap station are adjusted The weight parameter rate2. Wherein, the preset value can be set according to the actual situation, for example, it can be set to any value from 0 to 100%.

Specifically, since rate1+rate2=1, the adjustment can be realized by increasing the weight parameter rate1 and decreasing the weight parameter rate2, and can also be realized by reducing the weight parameter rate1 and increasing the weight parameter rate2.

In an optional implementation manner, the above optimization method further includes: performing the station replacement recommendation method again according to the adjusted weight parameter, and obtaining the ratio of effective recommended users to the user group; judging whether the ratio is increased; if so, The weight parameter is then updated to complete the optimization of the power station recommendation method.

In this embodiment, the recommended power exchange station is determined based on the weight parameters rate1 and rate2, and the user group is divided into valid recommended users and invalid recommended users according to the feedback behavior of the user group for the recommended power station information, and the ratio of valid recommended users to the user group can be obtained for R0. According to the ratio R0, the weight parameter rate1 is adjusted to rate1', and the weight parameter rate2 is adjusted to rate2', and steps S1-S3 are executed again, and the ratio of effective recommended users to the user group can be obtained as R1.

If R1>R0, it means that the adjustment of the weight parameter has optimized the recommended method for power station replacement, that is, the recommended success rate of power station replacement can be improved. At this time, the weight parameter used in the power station recommendation method is updated to the adjusted weight The parameters rate1' and rate2', that is, the next time the recommended battery replacement station is determined based on the weight parameters rate1' and rate2'.

Conversely, if R1<R0, it means that the adjustment of the weight parameters this time does not optimize the power station recommendation method, but will reduce the success rate of power station recommendation. At this time, the weight parameters used in the power station recommendation method are not updated, but It is to re-adjust the weight parameters on the basis of the weight parameters rate1 and rate2, and determine the recommended replacement station based on the re-adjusted weight parameters next time.

Similarly, if R1=R0, the weight parameters used in the power swapping recommendation method may be updated to the adjusted weight parameters rate1' and rate2', or the weighting parameters used in the power swapping recommendation method may not be updated. Specifically, it can be set according to the actual situation.

In the above example of determining the recommended battery swap station based on the distance between the optional swap station and the current location of the user's vehicle and the busyness of the optional swap station, the method for recommending the swap station is optimized by adjusting the weight parameters rate1 and rate2 of the two. It should be noted that it is also possible to optimize the method for recommending battery swapping stations by increasing the factors for determining the recommended swapping stations. The distance, the busyness of the optional swapping stations, and the preferential swapping resources of the optional swapping stations jointly determine the recommended swapping stations.

FIG. 3 is used to illustrate a funnel model, which is used to represent the number of users at different levels. The funnel model shown in Figure 3, from top to bottom, is the user group, candidate switching stations, recommended switching stations, intended users, switching users, and successful recommendations. Among them, the intended user and the battery exchange user are valid recommended users. Among them, the user group includes valid recommendation users and invalid recommendation users, and has the largest number. Compared with the number of user groups, the number of users who have been matched with alternative power stations has decreased. The number of users who have been matched with recommended switching stations has decreased compared to the number of users who have been matched with alternative switching stations. Intended users refer to users whose feedback behavior for the recommended battery swap station meets the preset conditions, and their number is reduced compared with the number of users who match the recommended battery swap station. Power exchange users refer to users who implement power exchange at recommended power exchange stations, and their number has decreased compared with the number of intended users. Successfully recommended users refer to users who have successfully completed the power exchange order at the recommended exchange station, and their number has decreased compared with the number of power exchange users. The optimization method of the power station recommendation method provided in this embodiment aims to increase the ratio of effective recommended users to the user group.

This embodiment also provides an optimization device 40 for a method for recommending a power station, as shown in FIG. 4 , including a recommendation module 41 , an acquisition module 42 , a division module 43 and an optimization module 44 .

The recommendation module 41 is used to execute the method for recommending a battery swapping station, and send information about the recommended swapping station to the user group.

The obtaining module 42 is used to obtain the feedback behavior of the user group with respect to the recommended site information.

The division module 43 is used to divide the user group into valid recommendation users and invalid recommendation users according to whether the feedback behavior satisfies a preset condition.

The optimization module 44 is used to optimize the method for recommending the power station according to the ratio of effective recommended users to the user group.

In an optional implementation manner, the above recommendation module specifically includes a selection unit and a determination unit. The selection unit is used to select at least two alternative substations, and the determination unit is used to determine a recommended substation according to the at least two alternatives.

In an optional implementation manner, the selection unit is specifically configured to select at least two alternative switching stations according to the distance between the current location of the user's vehicle and the switching station, and/or the historical driving trajectory of the user's vehicle.

In an optional implementation manner, the determination unit is specifically configured to determine from at least two alternative substations based on the remaining mileage of the user's vehicle and the distance between the current location and the at least two alternative substations. Select and replace the power station; and perform weighted summation according to the distance between the optional replacement station and the current position of the user's vehicle and the busyness of the optional replacement station to obtain a calculation result; and determine the recommended replacement station from the optional replacement stations according to the calculation result .

In an optional implementation manner, the above-mentioned optimization device further includes a calculation module, configured to obtain the number of people in line and the number of replaceable batteries of the replaceable power station, and calculate the busyness of the replaceable power station.

In an optional embodiment, the above-mentioned optimization module is specifically used to calculate the ratio of effective recommended users to the user group; adjust the weight parameter of the distance between the optional power station and the current position of the user's vehicle and the weight parameter of the optional power station according to the ratio The weight parameter of busyness.

In an optional embodiment, the above-mentioned optimization module is specifically used to judge whether the ratio is lower than a preset value; if so, adjust the weight parameter and the optional power station The weight parameter of busyness.

In an optional embodiment, the above optimization device further includes an update module, configured to execute the power station recommendation method again according to the adjusted weight parameter, and obtain the ratio of effective recommended users to the user group; and determine the ratio Whether to increase; if so, update the weight parameter to complete the optimization of the recommended method for the power station.

In an optional implementation manner, the feedback behavior includes: at least one of display screen touch, voice feedback, and battery replacement.

In an optional implementation manner, the above division module is specifically used to judge whether the feedback behavior of each user in the user group belongs to the screen touch confirmation to select the recommended switching station, the voice feedback to confirm the selection of the recommended switching station, and the recommended switching station. The power exchange station completes at least one of the power exchange orders; if so, the user is classified as a valid recommended user; if not, the user is classified as an invalid recommended user.

Regarding the various modules/units included in the optimization device of the power station recommendation method described in this embodiment, they may be software modules/units, or hardware modules/units, or partly software modules/units, partly hardware module/unit. For the specific implementation and beneficial effects of the above embodiments, please refer to an embodiment of an optimization method for a power station recommendation method, which has been described in detail above and will not be repeated here.

Example 2

FIG. 5 is a schematic structural diagram of an electronic device provided in this embodiment. The electronic device includes at least one processor and a memory communicatively coupled to the at least one processor. Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor, so that the at least one processor can execute the power station recommendation in Embodiment 1. method of optimization. The electronic device provided in this embodiment may be a personal computer, such as a desktop computer, an all-in-one computer, a notebook computer, a tablet computer, etc., and may also be a terminal device such as a mobile phone, a wearable device, or a handheld computer. The electronic device 3 shown in FIG. 5 is only an example, and should not limit the functions and scope of use of this embodiment of the present invention.

Components of the electronic device 3 may include but not limited to: the at least one processor 4 mentioned above, the at least one memory 5 mentioned above, and the bus 6 connecting different system components (including the memory 5 and the processor 4 ).

The bus 6 includes a data bus, an address bus and a control bus.

The memory 5 may include a volatile memory, such as a random access memory (RAM) 51 and/or a cache memory 52 , and may further include a read only memory (ROM) 53 .

Memory 5 may also include a program/utility tool 55 having a set (at least one) of program modules 54 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, which Each or some combination of the examples may include the implementation of a network environment.

The processor 4 executes various functional applications and data processing by running the computer program stored in the memory 5 , such as the optimization method of the above-mentioned method for recommending a power station.

Electronic device 3 may also communicate with one or more external devices 7 (eg, keyboards, pointing devices, etc.). This communication can take place through an input/output (I/O) interface 8 . Moreover, the electronic device 3 can also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN) and/or a public network such as the Internet) through the network adapter 9 . As shown in FIG. 5 , the network adapter 9 communicates with other modules of the electronic device 3 through the bus 6 . It should be appreciated that although not shown in FIG. 5 , other hardware and/or software modules may be used in conjunction with electronic device 3, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array ) systems, tape drives, and data backup storage systems.

It should be noted that although several units/modules or subunits/modules of an electronic device are mentioned in the above detailed description, such division is only exemplary and not mandatory. Actually, according to the embodiment of the present invention, the features and functions of two or more units/modules described above may be embodied in one unit/module. Conversely, the features and functions of one unit/module described above can be further divided to be embodied by a plurality of units/modules. For the specific implementation and beneficial effects of the above embodiments, please refer to an embodiment of an optimization method for a power station recommendation method, which has been described in detail above and will not be repeated here.

Example 3

This embodiment provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the optimization method of the method for recommending a power station in Embodiment 1 is implemented.

Wherein, the readable storage medium may more specifically include but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device or any of the above-mentioned the right combination.

In a possible implementation manner, the present invention can also be implemented in the form of a program product, which includes program code, and when the program product runs on the electronic device, the program code is used to make the electronic device execute An optimization method for the method for recommending a power station in Example 1. For the specific implementation and beneficial effects of the above embodiments, please refer to an embodiment of an optimization method for a power station recommendation method, which has been described in detail above and will not be repeated here.

Wherein, the program code for executing the present invention can be written in any combination of one or more programming languages, and the program code can be completely executed on the electronic device, partially executed on the electronic device, or used as an independent The software package executes, partly on the electronic device and partly on the remote device, or entirely on the remote device.

Although the specific implementation of the present invention has been described above, those skilled in the art should understand that this is only an example, and the protection scope of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principle and essence of the present invention, but these changes and modifications all fall within the protection scope of the present invention.

Claims

An optimization method for a power station recommendation method, characterized in that it comprises the following steps:

Execute the method of recommending the replacement station, and send the recommended replacement station information to the user group;

Obtaining the feedback behavior of the user group with respect to the information of the recommended battery swapping station;

dividing the user group into valid recommendation users and invalid recommendation users according to whether the feedback behavior meets preset conditions;

According to the proportion of effective recommended users in the user group, the method for recommending power stations is optimized.
The optimization method according to claim 1, characterized in that, the step of implementing the method for recommending a station replacement specifically comprises:

Select at least two alternative substations;

A recommended switching station is determined according to the at least two candidate switching stations.
The optimization method according to claim 2, wherein the step of selecting at least two alternative substations specifically includes:

According to the distance between the current position of the user's vehicle and the switching station, and/or the historical driving trajectory of the user's vehicle, at least two candidate switching stations are selected.
The optimization method according to claim 2, wherein the step of determining the recommended switching station according to the at least two candidate switching stations specifically comprises:

According to the remaining mileage of the user's vehicle and the distance between the current location and the at least two alternative switching stations, determine an optional switching station from at least two alternative switching stations;

According to the distance between the optional power station and the current position of the user's vehicle and the busyness of the optional power station, the weighted summation is performed to obtain the calculation result;

The recommended switching station is determined from the optional switching stations according to the calculation result.
The optimization method according to claim 4, further comprising the steps of:

Obtain the number of people in line and the number of replaceable batteries of the replaceable power station, and calculate the busyness of the replaceable power station.
The optimization method according to claim 4, wherein the step of optimizing the power-swapping station recommendation method according to the proportion of effective recommended users in the user group specifically includes:

Calculate the ratio of effective recommended users to the user group;

The weight parameter of the distance between the switchable power station and the current location of the user's vehicle and the weight parameter of the busyness of the switchable power station are adjusted according to the ratio.
The optimization method according to claim 6, wherein the step of adjusting the weight parameters of the distance between the optional swappable power station and the current location of the user’s vehicle and the busyness of the optional swappable power station according to the ratio specifically includes:

Judging whether the ratio is lower than a preset value; if so, adjusting the weight parameter of the distance between the optional swappable power station and the current location of the user's vehicle and the weight parameter of the busyness of the optional swappable power station.
The optimization method according to claim 6, further comprising the steps of:

According to the adjusted weight parameters, execute the power station replacement recommendation method again, and obtain the ratio of effective recommended users to the user group;

It is judged whether the ratio is increased; if so, the weight parameter is updated to complete the optimization of the power station recommendation method.
The optimization method according to any one of claims 1-8, wherein the feedback behavior includes: at least one of display screen touch, voice feedback, and battery replacement.
The optimization method according to claim 9, wherein the step of dividing the user group into valid recommendation users and invalid recommendation users according to whether the feedback behavior satisfies a preset condition specifically includes:

Judging whether the feedback behavior of each user in the user group belongs to at least one of the screen touch confirmation to select the recommended replacement station, the voice feedback to confirm the selection of the recommended replacement station, and the completion of the power replacement order at the recommended replacement station;

If yes, classify the user as a valid recommendation user; if not, classify the user as an invalid recommendation user.
An optimization device for a power station recommendation method, characterized in that it includes:

The recommendation module is used to implement the method for recommending the replacement station, and send the recommended replacement station information to the user group;

An acquisition module, configured to acquire the feedback behavior of the user group with respect to the information of the recommended battery swapping station;

A division module, configured to divide the user group into valid recommendation users and invalid recommendation users according to whether the feedback behavior satisfies a preset condition;

The optimization module is used to optimize the power-swapping station recommendation method according to the ratio of effective recommended users to the user group.
An electronic device, comprising a memory, a processor, and a computer program stored on the memory and operable on the processor, characterized in that, when the processor executes the computer program, any one of claims 1-10 is implemented. The optimization method of the recommended method for the power station described in the item.
A computer-readable storage medium, on which a computer program is stored, is characterized in that, when the computer program is executed by a processor, the optimization method of the method for recommending a power station according to any one of claims 1-10 is implemented.