New energy automobile service station active recommendation method and system, and storage medium

Abstract

The invention belongs to the technical field of intelligent recommendation, and discloses a new energy automobile service station active recommendation method and system, and a storage medium. The method comprises the following steps: acquiring a proportion A: B of attention of a user to service site distance and service quality, and forming a user portrait; service sites in the search range are inquired; all services contained in each service site are obtained; obtaining services possibly needed by the user; obtaining associated services thereof; the urgency degree of the service is obtained; according to the user portrait and the urgency degree of the service, the weights of the recommendation indexes are distributed; scoring the service sites, and recommending the service sites to the user according to scores; correcting the user portrait according to the rating of the service site after the user accepts the service and the acceptability of the recommended service site; according to the invention, the demand of a user for a single service is met, a potential consumption environment is created, the service range is extended, the demand of the user is met to a greater extent, and the advantages of a comprehensive service site are embodied.

Description

[0001] Divisional application This application is a divisional application of the Chinese invention patent application [Application Number: 202410977863.8] [Name: A method and system for actively recommending new energy vehicle service stations, and storage medium] filed on July 19, 2024. Technical Field

[0002] The present invention relates to the field of intelligent recommendation technology, and in particular to a method and system for actively recommending new energy vehicle service sites, and a storage medium. Background Art

[0003] With the development of new energy technology and information technology, new energy vehicles have the new three characteristics of "electrification, intelligence and sharing". Among them, "electrification" is the carrier of the future development of the automobile industry, mainly referring to the power system of new energy vehicles, as a change in the way of automobile energy drive; "intelligence" is the technical condition for the development of the future automobile industry, mainly developing automatic driving and vehicle networking technology; "sharing" is a social form and value carrier, mainly referring to car sharing and mobile travel. Based on these three characteristics, consumers have higher and higher requirements for the intelligence and convenience of new energy vehicle after-sales service.

[0004] Compared with traditional fuel vehicles, new energy vehicles require energy replenishment time ranging from tens of minutes to several hours due to the characteristics of the battery. In order to effectively use the time waiting for charging, new energy vehicle owners will carry out other activities such as leisure and shopping during charging, thus creating a new business format. For new energy vehicle owners, service stations with charging and battery replacement services alone can no longer meet their needs, but a comprehensive service center with multiple service projects is needed. Of course, due to various reasons, it is impossible for every service station to be fully functional, so how to choose a service station that suits your needs is an urgent problem to be solved.

[0005] Prior art Chinese patent application CN202311753205.2 discloses a charging station recommendation method, a charging station recommendation device, and a charging station recommendation system. The recommendation method includes obtaining charging station information within a preset distance range, the preset distance range is the range of the vehicle's remaining power that can be driven; generating an operation score of the charging station based on the charging data of the charging station; generating an equipment score of the charging station based on the charging pile information of the charging station; generating a service score of the charging station based on the service information; generating a user evaluation score of the charging station based on the user evaluation information; sorting the charging stations according to the operation score, equipment score, service score, and user evaluation score, generating a sorting result of the charging station, and recommending the sorting result to the user.

[0006] For another example, the prior art Chinese patent application CN202111673428.9, "Optimization method and device for battery swap station recommendation method", includes the following steps: executing the battery swap station recommendation method and sending recommended battery swap station information to the user group; obtaining the feedback behavior of the user group for the recommended battery swap station information; dividing the user group into valid recommended users and invalid recommended users according to whether the feedback behavior meets the preset conditions; optimizing the battery swap station recommendation method according to the proportion of valid recommended users in the user group. The present invention optimizes the battery swap station recommendation method according to the proportion of valid recommended users in the user group, so that a closed loop can be formed between the recommended battery swap station and the user's feedback based on the recommended battery swap station, thereby making the recommended battery swap station more in line with the user's battery swap needs, and improving the effectiveness of the recommendation, that is, realizing the optimization of the battery swap station recommendation method and improving the user experience of the battery swap process.

[0007] In the above-mentioned existing technologies, the recommendation process is mainly centered around charging or battery replacement, and the main evaluation indicators are also charging-related equipment, prices, services, evaluations, etc., which do not take into account the comprehensive needs of users and do not conform to the current positioning of comprehensive service stations.

[0008] In addition, currently when users find that the remaining power is low, they search for service stations on the map or in applications. However, in actual applications, when users forget to pay attention to the remaining power, the remaining power may be too low to support the service station, or not enough to support the service station with better service quality, which makes the user either unable to charge or have a bad charging service experience. Summary of the invention

[0009] The purpose of the present invention is to provide a method and system for actively recommending new energy vehicle service sites, and a storage medium, which partially solves or alleviates the above-mentioned deficiencies in the prior art and can actively recommend the most suitable service site to the user.

[0010] In order to solve the above-mentioned technical problems, the present invention specifically adopts the following technical solutions: a method for actively recommending new energy vehicle service stations, comprising: Obtain the ratio A:B between the user's attention to the distance to the service site and the service quality, and form a user profile; Obtain the user's geographical location and the remaining battery power of the vehicle; define a search range based on the user's geographical location and the remaining battery power of the vehicle, query the service sites within the search range; and obtain all services included in each service site; According to the remaining power of the vehicle, the abnormal state of the vehicle, the historical service acceptance record of the user and the historical search record, the service that the user may need is obtained; specifically, if the remaining power of the vehicle train is greater than a preset threshold, according to the abnormal state of the vehicle, and / or the historical service acceptance record and the historical search record of the user, the service that the user may need is obtained; if the remaining power of the vehicle train is less than or equal to the preset threshold, it is determined that the service required by the user is a charging or battery replacement service; Obtain related services based on the services that users may need; The urgency of obtaining services based on the types of services that users may need; The weights of the recommendation indicators are allocated according to the user profile and the urgency of the service; the recommendation indicators include distance weight, service quality weight and associated service weight; Scoring service sites within the search range that have services that the user may need based on the recommendation index, and recommending service sites to the user based on the scores; Modify the user profile based on the user's rating of the service site after receiving the service and the user's acceptance of the recommended service site; Among them, the method of obtaining the urgency of the service according to the service that the user may need includes: Classify services and rank the urgency of services into levels one to three according to the service type; When the urgency is at the first level, the distance weight adjustment coefficient is D1, the service quality weight adjustment coefficient is S1, and D1+S1=1; When the urgency is at the second level, the distance weight adjustment coefficient is D2, the service quality weight adjustment coefficient is S2, D2+S2=1, D1>D2; When the urgency is at the third level, the distance weight adjustment coefficient is D3, the service quality weight adjustment coefficient is S3, D3+S3=1, D2>D3; The steps for allocating weights of recommendation indicators based on user profiles and service urgency include: Initialize the weights of the recommended indicators and assign an initial weight to each recommended indicator. The initial distance weight is D0, the initial service quality weight is S0, and the initial associated service weight is C0. D0+S0+C0=1. When the urgency is at the first level, the adjusted distance weight D = D0*(A*D1) / [(A*D1)+(B*S1)]; the adjusted service quality weight S = S0*(B*S1) / [(A*D1)+(B*S1)]; the adjusted associated service weight C = C0; When the urgency is at the second level, the adjusted distance weight D = D0*(A*D2) / [(A*D2)+(B*S2)]; the adjusted service quality weight S = S0*(B*S2) / [(A*D2)+(B*S2)]; the adjusted associated service weight C = C0; When the urgency is at the third level, the adjusted distance weight D = D0*(A*D3) / [(A*D3)+(B*S3)]; the adjusted service quality weight S = S0*(B*S3) / [(A*D3)+(B*S3)]; the adjusted associated service weight C = C0.

[0011] As an improvement, the method for obtaining the ratio between the user's attention to the distance to the service site and the service quality includes: When a user registers, a progress bar is displayed on the user registration page; one end of the progress bar is the distance, and the other end is the service quality; a slider that can slide along the progress bar is provided on the progress bar; the user changes the ratio between the distance end and the service quality end by dragging the slider, and the sum of the distance end ratio and the service quality end ratio is a constant value.

[0012] As an improvement, the steps of obtaining the associated services of the service according to the service name specifically include: If the service that the user may need is a service that the user has received in the past, the service that was performed at the same time when the user received the service in the past is regarded as an associated service; In the case that the service that the user may need is a service that the user has never received, a related service is selected according to the service association map.

[0013] As a further improvement, the service association graph uses services as nodes and relationships between services as edges; In the service association graph, services that the user may need are selected, and services that are directly connected to the services that the user may need or / and services that are indirectly connected through edges less than a threshold number are used as associated services.

[0014] As an improvement, the steps of scoring the service sites having services that the user may need according to the recommendation index specifically include: Obtain the distance between the service site and the user, and score the distance value based on the adjusted distance weight; Obtain a single evaluation of the services that the user may need at the service site and a comprehensive evaluation of the service site, and score them according to the adjusted service quality weights to obtain a service quality score; The number of associated services included in the service site is obtained, and the associated service scores are obtained by scoring the associated services according to the adjusted associated service weights; The sum of the distance score, the service quality score, and the associated service score is taken as the score of the service site.

[0015] As an improvement, the score ratio of the single evaluation of the service that the user may need in the service site and the comprehensive evaluation of the service site is K1:K2, where K1>K2.

[0016] As an improvement, the steps of recommending service sites to users based on the ratings specifically include: Sort the service sites in descending order according to their scores, and recommend service sites with a ranking higher than the ranking threshold to users; or, The service sites whose scores are higher than the score threshold are recommended to the user.

[0017] As an improvement, the steps of modifying the user profile according to the user's rating of the service site after receiving the service and the acceptance of the recommended service site specifically include: When the number of times that the user does not accept the recommended merchants exceeds the threshold, the user profile is adjusted; the adjustment steps specifically include: The average score A1 of the user on the service quality is compared with the average score A2 of the service quality of all other users. When A1<A2, the service quality weight is increased by a first percentage; when A1≥A2 and A1 is not a full score, the service quality weight is increased by a second percentage; when A1 is a full score, the service quality weight is reduced by a third percentage; wherein the first percentage>the second percentage.

[0018] The present invention also provides a new energy vehicle service site active recommendation system, comprising: The user portrait building module is used to obtain the ratio A:B between the user's attention to the distance to the service site and the service quality, and form a user portrait; The service site search module is used to obtain the user's geographical location and the remaining power of the vehicle; define the search range according to the user's geographical location and the remaining power of the vehicle, query the service sites within the search range; and obtain all services included in each service site; The service demand acquisition module acquires the services that the user may need according to the remaining power of the vehicle, the abnormal state of the vehicle, the historical service acceptance record of the user, and the historical search record; acquires the associated services according to the services that the user may need; specifically, if the remaining power of the vehicle train is greater than a preset threshold, acquires the services that the user may need according to the abnormal state of the vehicle, and / or the historical service acceptance record and the historical search record of the user; if the remaining power of the vehicle train is less than or equal to the preset threshold, determines that the service required by the user is a charging or battery replacement service; An urgency acquisition module is used to acquire the urgency of a service based on the type of service that a user may require; A weight allocation module is used to allocate weights of recommendation indicators according to user portraits and service urgency; the recommendation indicators include distance weights, service quality weights, and associated service weights; A recommendation module, used to score service sites within the search range that have services that the user may need according to the recommendation index, and recommend service sites to the user according to the scores; A user portrait correction module is used to correct the user portrait according to the user's rating of the service site after receiving the service and the acceptance of the recommended service site; The method in which the urgency acquisition module acquires the urgency of a service according to the service that the user may need includes: Classify services and rank the urgency of services into levels one to three according to the service type; When the urgency is at the first level, the distance weight adjustment coefficient is D1, the service quality weight adjustment coefficient is S1, and D1+S1=1; When the urgency is at the first level, the distance weight adjustment coefficient is D2, the service quality weight adjustment coefficient is S2, D2+S2=1, D1>D2; When the urgency is at the first level, the distance weight adjustment coefficient is D3, the service quality weight adjustment coefficient is S3, D3+S3=1, D2>D3; The weight allocation module allocates the weights of the recommendation indicators according to the user portrait and the urgency of the service, specifically including: Initialize the weights of the recommended indicators and assign an initial weight to each recommended indicator. The initial distance weight is D0, the initial service quality weight is S0, and the initial associated service weight is C0. D0+S0+C0=1. When the urgency is at the first level, the adjusted distance weight D = D0*(A*D1) / [(A*D1)+(B*S1)]; the adjusted service quality weight S = S0*(B*S1) / [(A*D1)+(B*S1)]; the adjusted associated service weight C = C0; When the urgency is at the second level, the adjusted distance weight D = D0*(A*D2) / [(A*D2)+(B*S2)]; the adjusted service quality weight S = S0*(B*S2) / [(A*D2)+(B*S2)]; the adjusted associated service weight C = C0; When the urgency is at the third level, the adjusted distance weight D = D0*(A*D3) / [(A*D3)+(B*S3)]; the adjusted service quality weight S = S0*(B*S3) / [(A*D3)+(B*S3)]; the adjusted associated service weight C = C0.

[0019] The present invention also provides a storage medium, in which a computer program is stored; when the computer program is executed, the above-mentioned new energy vehicle service site active recommendation method can be implemented.

[0020] The present invention is beneficial in that: The present invention actively recommends service sites to users based on the remaining power. Specifically, when the remaining power is less than or equal to a preset threshold (the preset threshold is actually a default safety threshold, which allows the vehicle to reach at least two service sites after driving a certain distance), it is determined that the service required is a charging or battery replacement service, and then the user's personalization (for example, user portrait) is integrated, and the distance, service quality and related services are considered to actively recommend suitable service sites to users. On the one hand, it can remind users to pay attention to the power, and reduce the situation where users forget to pay attention to the power and search for service sites when the power is extremely low. On the other hand, by pushing suitable service sites to users, the user experience is improved. Further, when the remaining power is greater than the preset threshold, it means that the power is sufficient. Therefore, the focus should be on vehicle abnormalities, or services that users are interested in (for example, service types in historical search records), and then actively recommend to users, which greatly improves the user experience. For example, during driving, for some small abnormalities, on the one hand, users usually find it troublesome, and on the other hand, users do not know which service sites can provide corresponding services. Therefore, they will not search for service sites immediately, but will choose to ignore them. However, such small anomalies will actually affect the driving experience. Therefore, if appropriate service sites that can provide corresponding services can be proactively recommended to users when an anomaly is detected, it will help users resolve the anomaly, thereby improving both the driving experience and the user experience.

[0021] The present invention first constructs a user portrait to express the user's concern about the distance and service quality; then queries the service sites within the search range; obtains the services and related services that the user may need based on the remaining power of the vehicle, the abnormal state of the vehicle, the user's historical service acceptance records and historical search records. Then, the urgency of the service is obtained based on the type of service that the user may need; then, the user portrait is used as the basis and the urgency is used as the adjustment coefficient to allocate the weight of the recommendation indicators in the scoring system. Among them, the related services of the services required by the user are also used as one of the recommendation indicators.

[0022] The present invention combines distance, service quality, and related services to comprehensively score all service sites within the search range, which not only meets the user's needs for a single service, but also creates a potential consumption environment, extends the scope of services, meets the user's needs to a greater extent, and reflects the advantages of comprehensive service sites.

[0023] The present invention does not rely on artificial intelligence models, and is free from reliance on chips and large computing power. It is more in line with the needs of the times in the context of an increasingly tense international situation. Despite the lack of artificial intelligence support, the present invention can still accurately predict the needs of users, thereby recommending the most suitable merchants to users. The present invention can also make self-corrections based on user feedback, thereby gradually improving itself and making it more in line with the true face of users. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, each element or part is not necessarily drawn according to the actual scale. Obviously, the drawings described below are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without paying creative labor.

[0025] Figure 1 The present invention is a flowchart of a method for actively recommending new energy vehicle service stations according to an embodiment of the present invention.

[0026] Figure 2 The present invention is a schematic structural diagram of a new energy vehicle service station active recommendation system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0028] Herein, suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present invention, and have no specific meanings by themselves. Therefore, "module", "component" or "unit" can be used mixedly.

[0029] In this document, the terms "upper", "lower", "inner", "outer", "front", "back", "one end", "the other end" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0030] In this document, unless otherwise clearly specified and limited, the terms "installed", "provided with", "connected", etc. should be understood in a broad sense. For example, "connected" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0031] Herein "and / or" includes any and all combinations of one or more of the associated listed items.

[0032] Herein, "plurality" means two or more than two, ie, it includes two, three, four, five, etc.

[0033] Embodiment 1: Figure 1 As shown, the present invention provides a method for actively recommending new energy vehicle service sites. The present invention actively triggers based on the user's geographical location and the remaining power of the vehicle to recommend comprehensive service sites that include the services they need to the user, thereby improving the user experience while inducing user consumption to form a new business model. The specific steps include: S201 obtains the ratio A:B between the user's concerns about the distance to the service site and the service quality, and forms a user portrait.

[0034] A comprehensive service station should include core services related to new energy vehicles and peripheral services related to car owners. The core services include charging, battery replacement, repair, maintenance, etc., and peripheral services include catering, entertainment, shopping, leisure, etc. Therefore, when recommending service stations to car owners, it is also necessary to explore other needs of car owners.

[0035] For new energy vehicle owners, of course, they still focus more on the core services they need. Only when the core services are met will they consider some surrounding services. As for the core services, the distance of the service station and the service quality are the first issues that new energy vehicle owners, i.e. users, consider.

[0036] Based on this, in order to more accurately recommend service sites to users, the present embodiment first needs to obtain the user's attention to the distance and service quality of the service site. In order to better express the difference between the attention to distance and service quality, the present embodiment uses a ratio to quantify the attention to the two.

[0037] In actual applications, there are many ways to obtain the proportion of users' attention to the distance to the service site and the service quality, but the existing methods either require filling in data or multiple clicks, which are both cumbersome. In today's fast-paced life, a large number of users cannot patiently input as required.

[0038] In order to solve this problem, in this implementation, when a user registers, a progress bar is displayed on the user registration page; one end of the progress bar is the distance, and the other end is the service quality; a slider that can slide along the progress bar is provided on the progress bar; the user changes the ratio between the distance end and the service quality end by dragging the slider, and the sum of the distance end ratio and the service quality end ratio is a constant value, that is, the sum of the distance end ratio and the service quality end ratio is fixed.

[0039] When the user pulls the slider, the changes in the ratio are displayed at both ends. For example, when the slider is initially in the middle, the ratio of the distance end and the ratio of the service quality end are both 50%. When the user pulls the slider toward the distance end, the distance end becomes shorter and the ratio decreases; while the service quality end becomes longer and the ratio increases synchronously.

[0040] The above method is very convenient and intuitive when inputting different ratios, which is easy for users to use and also makes it easier to obtain data in the background.

[0041] Of course, it is possible that some users are still unwilling to provide the ratio between their concerns about distance and service quality. In this case, it is only necessary to directly match a default template for such users.

[0042] S202 obtains the user's geographical location and the remaining battery power of the vehicle; defines a search range according to the user's geographical location and the remaining battery power of the vehicle, queries service sites within the search range; and obtains all services included in each service site; In this embodiment, the system can be deployed on the vehicle computer of the new energy vehicle to implement the method, or the system can be deployed on the smart device to implement the method claimed by the present invention by interconnecting with the vehicle computer. Of course, other methods that can be interconnected with the vehicle computer to obtain information such as the remaining power of the vehicle can also be used, which will not be repeated or limited in this embodiment.

[0043] The remaining power of the vehicle and the historical average power consumption can be used to calculate the distance the vehicle can travel. With the user's location as the center and the distance the vehicle can travel as the radius, a search range can be obtained.

[0044] Of course, taking various factors into consideration, the search radius is generally determined by halving the distance that the vehicle can travel.

[0045] After defining the search scope, you can query all service sites within the scope and obtain all services included in each site.

[0046] S203 obtains services that the user may need based on the remaining battery power of the vehicle, the abnormal state of the vehicle, the user's historical service acceptance records, and the historical search records.

[0047] If the remaining power of the user's vehicle is below a certain threshold, such as below 30%, then the user is likely to require charging or battery replacement services. At the same time, from the perspective of protecting the vehicle battery, it is best to charge when the remaining power reaches this threshold. Therefore, the corresponding charging or battery replacement services can be actively recommended to the user to avoid the user panicking and finding a nearby service station to charge when the remaining power is too low, which reduces the user experience. Of course, the threshold can be customized by the user, or specified by the manufacturer by default from the perspective of protecting the battery.

[0048] Of course, if the remaining power is greater than the threshold, the services that the user may need can be obtained based on the abnormal status of the vehicle, the user's historical service acceptance records, and historical search records.

[0049] The abnormal state of the vehicle is an alarm issued by the vehicle computer based on the vehicle's operating conditions. Since this system is connected to the vehicle computer, it can also obtain abnormal conditions of the vehicle, such as low tire pressure, battery overheating, abnormal air conditioning, etc.; when the vehicle has an abnormal condition, the user is likely to need corresponding maintenance services. Of course, in other embodiments, when the remaining power is less than or equal to the above threshold, there may also be an abnormal state of the vehicle, that is, there are two service requirements at the same time, among which the charging service requirement has the highest priority, that is, the highest urgency.

[0050] In addition, the services that the user has received or searched for are also likely to be the services that the user needs. For example, according to the recent search records, it can be found that the user has searched for services that the user may need.

[0051] When a service site within the range has services that the user may need, the system will be triggered to proactively recommend them to the user.

[0052] S204 obtains the associated services according to the services that the user may need.

[0053] The steps for obtaining associated services in this step specifically include: S2041: If the service that the user may need is a service that the user has received in the past, the service that was performed simultaneously when the user received the service in the past is considered as a related service.

[0054] For example, when the user charged last time, he also went to the cafe of the service station to drink coffee and bought a pack of cigarettes in the small supermarket of the service station. Then when selecting the charging service this time, the coffee sale and cigarette sale services will be included as related services.

[0055] S2042: When the service that the user may need is a service that the user has never received, select a related service according to the service association map.

[0056] There is also a situation where the service a user may need is a service he has never received before. For example, if the tire pressure is too low, the user may need a tire repair, but the user has no consumption record of tire repair at a service station. In this case, the user can only select related services based on the service association map.

[0057] In this embodiment, the service association graph is pre-built, and the service association graph uses services as nodes and the relationships between services as edges. A service is directly connected to another service by an edge, which is called a strong association. A service needs to be indirectly associated with another service through other services, which is called a weak association.

[0058] The service relationship map is constructed based on the relationship between services and consumption habits. For example, tire replacement and wheel repair are the relationship between services, while charging and cigarette sales are the relationship between consumption habits.

[0059] In this implementation, services that the user may need are selected in the service association graph, and services that are directly connected (strongly associated) to the services that the user may need or / and services that are indirectly connected (weakly associated) through less than a threshold number of edges are used as associated services.

[0060] S205 obtains the urgency of the service according to the type of service that the user may need.

[0061] The degree of urgency of the user can be roughly determined based on the type of service that the user may need. For example, charging and changing tires are largely emergency situations (i.e., the first gear), and they need to be charged as soon as possible or the tires need to be repaired immediately. It is highly likely that a distant service station will not be chosen, which means that the user is more concerned about the distance. For example, services such as car washing (the second gear) do not affect driving safety and therefore do not need to be completed immediately, and the stay time will not be too long. Therefore, users are more willing to go to service stations that are farther away and have better service quality (i.e., better user experience), which means that users are more concerned about service quality, and the distance weight can be appropriately reduced. For another example, maintenance, film pasting, etc. (the third gear) do not affect driving safety and therefore do not need to be completed immediately, and the waiting time is long. Users are more willing to go to service stations that are farther away but have better service quality and more supporting services, such as leisure and entertainment, that is, service stations with comprehensive services are not willing to go nearby, which means that users are more concerned about service quality, and accordingly, the distance weight can be appropriately lowered.

[0062] In this embodiment, services (mainly core services) are classified, and the urgency of services is divided into levels one to three according to the service type; When the urgency is at the first level, the distance weight adjustment coefficient is D1, the service quality weight adjustment coefficient is S1, D1+S1=1; preferably, D1>S1; When the urgency is at the first level, the distance weight adjustment coefficient is D2, the service quality weight adjustment coefficient is S2, D2+S2=1, D1>D2; When the urgency is at the first level, the distance weight adjustment coefficient is D3, the service quality weight adjustment coefficient is S3, D3+S3=1, D2>D3.

[0063] For example, in some embodiments, the urgency of the “charging” service may be ranked first. In this case, the distance weight adjustment coefficient may be set to 0.8, and the service quality weight adjustment coefficient may be adjusted to 0.2.

[0064] S206 allocates weights of recommendation indicators according to the user portrait and the urgency of the service; the recommendation indicators include distance weights, service quality weights, and associated service weights.

[0065] In this embodiment, the method for allocating weights of recommendation indicators includes: S2601 initializes the weights of the recommended indicators and assigns an initial weight to each recommended indicator. The initial distance weight is D0, the initial service quality weight is S0, and the initial associated service weight is C0. D0+S0+C0=1.

[0066] In order to avoid the case where the user does not provide the ratio between the degree of concern for the distance and the service quality, this embodiment directly matches a default template for such users. This step can also use the template when initializing the user.

[0067] For example, initially, the distance weight is 40%, the service quality weight is 40%, and the associated service weight is 20%.

[0068] S2602 When the urgency is at the first level, the adjusted distance weight D = D0*(A*D1) / [(A*D1)+(B*S1)]; the adjusted service quality weight S = S0*(B*S1) / [(A*D1)+(B*S1)]; the adjusted associated service weight C = C0.

[0069] S1403 When the urgency is at the second level, the adjusted distance weight D = D0*(A*D2) / [(A*D2)+(B*S2)]; the adjusted service quality weight S = S0*(B*S2) / [(A*D2)+(B*S2)]; the adjusted associated service weight C = C0; S1404 When the urgency is at the third level, the adjusted distance weight D = D0*(A*D3) / [(A*D3)+(B*S3)]; the adjusted service quality weight S = S0*(B*S3) / [(A*D3)+(B*S3)]; the adjusted associated service weight C = C0.

[0070] If the ratio of users' concerns about distance and service quality obtained based on user portraits is 60%:40%, and the distance weight adjustment coefficient of the first tier is D1=0.8, and the service quality weight adjustment coefficient is S1=0.2, then according to the above formula, the adjusted weights are 68.6% for distance, 11.4% for service quality, and 20% for related services.

[0071] S207 scores the service sites that have services that the user may need within the search range according to the recommendation index, and recommends the service sites to the user according to the scores.

[0072] Specifically, the method for scoring service sites that may need services according to recommendation indicators in this embodiment includes: S2071 obtains the distance between the service site and the user, and scores the distance based on the adjusted distance weight to obtain a distance score.

[0073] For example, the distance between the service station and the user is defined as 0 as 100 points, and the farthest distance of 50 km is defined as 0 points. After scoring, the distance weight is used to weight the score to obtain the distance score. If the distance between a service station and the user is 5 km and the score is 90, the distance score after weighting by 60% is 54.

[0074] S2072 obtains individual evaluations of services that may be required by users in the service site and a comprehensive evaluation of the service site, and scores them according to the adjusted service quality weights to obtain a service quality score.

[0075] In this embodiment, the score ratio of the single evaluation of the service that the user may need in the service site and the comprehensive evaluation of the service site is K1:K2, where K1>K2.

[0076] For example, if the service required by the user has a single score of 90 at a certain site, and the total score of the site is 80, after adjusting the ratio of K1 to K2 by 2:1, its score is 87. Then, the service quality score after weighting by 20% is 17.4.

[0077] S2073 obtains the number of associated services included in the service site, and scores the associated services according to the adjusted associated service weights to obtain associated service scores.

[0078] If a service site contains all the related services that users may need, the score is 100, and none of them is 0. Then when a service site contains all the related services, its score of 100 is 20 after being weighted by the related service weight of 20%.

[0079] S2074 uses the sum of the distance score, the service quality score and the associated service score as the score of the service site.

[0080] The sum of the above three scores, i.e. 54+17.4+20=91.4, is the final score of the service site.

[0081] This implementation provides two methods for recommending service sites to users based on ratings.

[0082] First, the service sites are sorted in descending order according to the service site scores, and the service sites ranked higher than the ranking threshold are recommended to the user. For example, the top three service sites are recommended to the user.

[0083] Second, service sites with scores higher than the score threshold are recommended to users, for example, service sites with scores higher than 90 are recommended to users.

[0084] S208 modifies the user portrait according to the user's rating of the service site after receiving the service and the user's acceptance of the recommended service site.

[0085] In this implementation, after recommending service sites to users, the user profile can also be modified based on user feedback, thereby achieving closed-loop management, specifically including: The method for adjusting the user profile when the number of times that the user does not accept the recommended service site exceeds the number threshold includes: The average score A1 of the user on the service quality is compared with the average score A2 of the service quality of all other users. When A1<A2, the service quality weight is increased by a first percentage; when A1≥A2 and A1 is not a full score, the service quality weight is increased by a second percentage; when A1 is a full score, the service quality weight is reduced by a third percentage; wherein the first percentage>the second percentage.

[0086] For example, when a user does not select a service site recommended by the system for three consecutive times, it indicates that there is a problem in the weight setting of the recommendation parameters, so adjustments are made.

[0087] In this embodiment, the basis for adjustment is the user's evaluation, which is not just the evaluation of a single service, but a comprehensive evaluation of all users.

[0088] For example, when the average user's evaluation of service quality is 80, while the average evaluation of service quality by other users is 90, it means that the user has very strict requirements on service quality and the weight of service quality needs to be significantly increased, such as increasing it by 30% on the original basis. Correspondingly, the distance weight should be reduced accordingly.

[0089] For example, another user's average score for service quality is 95, which is higher than the average score of other users of 90. This means that the user still cares about the service quality, but is more easily satisfied. Therefore, the weight of is slightly increased, for example, by 5% on the original basis. Similarly, the distance weight should be reduced accordingly.

[0090] For example, another user's service evaluation is full marks, which means that the user does not care much about the service quality and just habitually gives good reviews. Therefore, the weight of service quality can be appropriately reduced, for example, by 10% on the original basis, and the distance weight can be increased accordingly.

[0091] It can be foreseen that after the user portrait is corrected, the next recommendation activity will be based on the corrected user portrait.

[0092] Embodiment 2: as Figure 2 As shown, the present invention also provides a new energy vehicle service site active recommendation system, comprising: The user portrait building module is used to obtain the ratio A:B between the user's attention to the distance to the service site and the service quality, and form a user portrait; The service site search module is used to obtain the user's geographical location and the remaining power of the vehicle; define the search range according to the user's geographical location and the remaining power of the vehicle, query the service sites within the search range; and obtain all services included in each service site; The service demand acquisition module acquires the services that the user may need based on the remaining battery power of the vehicle, the abnormal status of the vehicle, the user's historical service acceptance records and historical search records; and acquires the related services based on the services that the user may need; An urgency acquisition module is used to acquire the urgency of a service based on the type of service that a user may require; A weight allocation module is used to allocate weights of recommendation indicators according to user portraits and service urgency; the recommendation indicators include distance weights, service quality weights, and associated service weights; A recommendation module, used to score service sites within the search range that have services that the user may need according to the recommendation index, and recommend service sites to the user according to the scores; A user portrait correction module is used to correct the user portrait according to the user's rating of the service site after receiving the service and the acceptance of the recommended service site; The method in which the urgency acquisition module acquires the urgency of a service according to the service that the user may need includes: Classify services and rank the urgency of services into levels one to three according to the service type; When the urgency is at the first level, the distance weight adjustment coefficient is D1, the service quality weight adjustment coefficient is S1, D1+S1=1; preferably, D1>S1; When the urgency is at the first level, the distance weight adjustment coefficient is D2, the service quality weight adjustment coefficient is S2, D2+S2=1, D1>D2; When the urgency is at the first level, the distance weight adjustment coefficient is D3, the service quality weight adjustment coefficient is S3, D3+S3=1, D2>D3; The method in which the weight allocation module allocates the weights of the recommendation indicators according to the user portrait and the urgency of the service includes: Initialize the weights of the recommended indicators and assign an initial weight to each recommended indicator. The initial distance weight is D0, the initial service quality weight is S0, and the initial associated service weight is C0. D0+S0+C0=1. When the urgency is at the first level, the adjusted distance weight D = D0*(A*D1) / [(A*D1)+(B*S1)]; the adjusted service quality weight S = S0*(B*S1) / [(A*D1)+(B*S1)]; the adjusted associated service weight C = C0; When the urgency is at the second level, the adjusted distance weight D = D0*(A*D2) / [(A*D2)+(B*S2)]; the adjusted service quality weight S = S0*(B*S2) / [(A*D2)+(B*S2)]; the adjusted associated service weight C = C0; When the urgency is at the third level, the adjusted distance weight D = D0*(A*D3) / [(A*D3)+(B*S3)]; the adjusted service quality weight S = S0*(B*S3) / [(A*D3)+(B*S3)]; the adjusted associated service weight C = C0.

[0093] Embodiment 3: The present invention also provides a storage medium, in which a computer program is stored; when the computer program is executed, the above-mentioned method for actively recommending new energy vehicle service sites can be implemented.

[0094] It should be noted that, in this article, the terms "include", "comprises" or any other variations 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, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0095] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a computer terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0096] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are within the protection of the present invention.

Claims

1. A method for actively recommending new energy vehicle service stations, characterized in that include: Obtain the ratio A:B between the user's attention to the distance to the service site and the service quality, and form a user profile; Obtain the user's geographic location and the remaining battery power of the vehicle; Define the search range based on the user's geographical location and the remaining battery power of the vehicle, query all service sites within the search range; and obtain all services included in each service site; According to the remaining power of the vehicle, the abnormal state of the vehicle, the user's historical service acceptance record and the historical search record, the service that the user may need is obtained; specifically, if the remaining power of the vehicle train is greater than a preset threshold, according to the abnormal state of the vehicle, and / or the user's historical service acceptance record and the historical search record, the service that the user may need is obtained; if the remaining power of the vehicle train is less than or equal to the preset threshold, according to the abnormal state of the vehicle and the remaining power, the service required by the user is determined to be a charging or battery replacement service and a maintenance service, among which the charging or battery replacement service has the highest priority; Obtain related services based on the services that users may need; The urgency of obtaining services based on the types of services that users may need; The weights of the recommendation indicators are allocated according to the user profile and the urgency of the service; the recommendation indicators include distance weight, service quality weight and associated service weight; Scoring service sites within the search range that have services that the user may need based on the recommendation index, and recommending service sites to the user based on the scores; Modify the user profile based on the user's rating of the service site after receiving the service and the user's acceptance of the recommended service site; The step of obtaining the urgency of the service according to the type of service that the user may need includes: Classify the core services and classify the urgency of the core services into levels one to three according to the service type; the core services include charging, battery replacement, and maintenance; When the urgency is at the first level, the distance weight adjustment coefficient is D1, the service quality weight adjustment coefficient is S1, D1+S1=1, D1>S1; When the urgency is at the second level, the distance weight adjustment coefficient is D2, the service quality weight adjustment coefficient is S2, D2+S2=1, D1>D2; When the urgency is at the third level, the distance weight adjustment coefficient is D3, the service quality weight adjustment coefficient is S3, D3+S3=1, D2>D3; The steps for allocating weights of recommendation indicators based on user profiles and service urgency include: Initialize the weights of the recommended indicators and assign an initial weight to each recommended indicator. The initial distance weight is D0, the initial service quality weight is S0, and the initial associated service weight is C0. D0+S0+C0=1. When the urgency is at the first level, the adjusted distance weight D = D0*(A*D1) / [(A*D1)+(B*S1)]; the adjusted service quality weight S = S0*(B*S1) / [(A*D1)+(B*S1)]; When the urgency is at the second level, the adjusted distance weight D = D0*(A*D2) / [(A*D2)+(B*S2)]; the adjusted service quality weight S = S0*(B*S2) / [(A*D2)+(B*S2)]; When the urgency is at the third level, the adjusted distance weight D = D0*(A*D3) / [(A*D3)+(B*S3)]; the adjusted service quality weight S = S0*(B*S3) / [(A*D3)+(B*S3)].

2. A method for actively recommending new energy vehicle service stations according to claim 1, characterized in that The step of obtaining the ratio between the user's attention to the distance to the service site and the service quality specifically includes: When a user registers, a progress bar is displayed on the user registration page; one end of the progress bar is the distance, and the other end is the service quality; a slider that can slide along the progress bar is provided on the progress bar; the user changes the ratio between the distance end and the service quality end by dragging the slider, and the sum of the distance end ratio and the service quality end ratio is a constant value.

3. The method for actively recommending new energy vehicle service stations according to claim 1, characterized in that The steps for obtaining the associated services according to the services that the user may need include: In the case where the service that the user may need is a service that the user has historically received, other services that were performed simultaneously when the user historically received the service are considered as associated services; In the case that the service that the user may need is a service that the user has never received, a related service is selected according to the service association map.

4. The method for actively recommending new energy vehicle service sites according to claim 3, characterized in that: The service association graph has services as nodes and relationships between services as edges; In the service association graph, services that the user may need are selected, and services that are directly connected to the services that the user may need or / and services that are indirectly connected through edges less than a threshold number are used as associated services.

5. The method for actively recommending new energy vehicle service stations according to claim 1, characterized in that The steps of scoring the service sites having services that the user may need according to the recommendation index specifically include: Obtain the distance between the service site and the user, and score the distance value based on the adjusted distance weight; Obtain a single evaluation of the services that users may need at the service site and a comprehensive evaluation of the service site, and score them according to the adjusted service quality weights to obtain a service quality score; The number of associated services included in the service site is obtained, and the associated service scores are obtained by scoring the associated services according to the adjusted associated service weights; The sum of the distance score, the service quality score, and the associated service score is taken as the score of the service site.

6. A method for actively recommending new energy vehicle service sites according to claim 5, characterized in that: The score ratio of the single evaluation of the service that the user may need in the service site and the comprehensive evaluation of the service site is K1:K2, where K1>K2.

7. The method for actively recommending new energy vehicle service stations according to claim 1, characterized in that The steps of recommending service sites to users based on the ratings specifically include: Sort all service sites in descending order according to their scores, and recommend service sites with a ranking higher than the ranking threshold to users; or, The service sites with scores higher than the score threshold are recommended to the user.

8. The method for actively recommending new energy vehicle service stations according to claim 1, characterized in that The steps of modifying the user profile according to the user's rating of the service site after receiving the service and the acceptance of the recommended service site specifically include: When the number of times that the user does not accept the recommended service site exceeds the number threshold, the user profile is adjusted; the adjustment steps specifically include: The average score A1 of the user on the service quality is compared with the average score A2 of the service quality of all other users. When A1<A2, the service quality weight is increased by a first percentage; when A1≥A2 and A1 is not a full score, the service quality weight is increased by a second percentage; when A1 is a full score, the service quality weight is reduced by a third percentage; wherein the first percentage>the second percentage.

9. A new energy vehicle service station active recommendation system, characterized in that include: The user portrait building module is used to obtain the ratio A:B between the user's attention to the distance to the service site and the service quality, and form a user portrait; The service site search module is used to obtain the user's geographical location and the remaining power of the vehicle; define the search range according to the user's geographical location and the remaining power of the vehicle, query the service sites within the search range; and obtain all services included in each service site; The service demand acquisition module acquires the services that the user may need according to the remaining power of the vehicle, the abnormal state of the vehicle, the user's historical service acceptance records and the historical search records; acquires the associated services according to the services that the user may need; specifically, determines whether the remaining power of the vehicle train is greater than a preset threshold, and if so, acquires the services that the user may need according to the abnormal state of the vehicle and / or the user's historical service acceptance records and the historical search records; if the remaining power of the vehicle train is less than or equal to the preset threshold, determines that the services required by the user are charging or battery replacement services and maintenance services according to the abnormal state of the vehicle and the remaining power, among which the charging or battery replacement services have the highest priority; An urgency acquisition module is used to acquire the urgency of a service based on the type of service that a user may require; A weight allocation module is used to allocate weights of recommendation indicators according to user portraits and service urgency; the recommendation indicators include distance weights, service quality weights, and associated service weights; A recommendation module, used to score service sites within the search range that have services that the user may need according to the recommendation index, and recommend service sites to the user according to the scores; A user portrait correction module is used to correct the user portrait according to the user's rating of the service site after receiving the service and the acceptance of the recommended service site; The urgency acquisition module specifically acquires the urgency of services according to the services that the user may need: Classify services and rank the urgency of services into levels one to three according to the service type; When the urgency is at the first level, the distance weight adjustment coefficient is D1, the service quality weight adjustment coefficient is S1, D1+S1=1, D1>S1; When the urgency is at the second level, the distance weight adjustment coefficient is D2, the service quality weight adjustment coefficient is S2, D2+S2=1, D1>D2; When the urgency is at the third level, the distance weight adjustment coefficient is D3, the service quality weight adjustment coefficient is S3, D3+S3=1, D2>D3; The weight allocation module allocates the weights of the recommendation indicators according to the user portrait and the urgency of the service, specifically including: Initialize the weights of the recommended indicators and assign an initial weight to each recommended indicator. The initial distance weight is D0, the initial service quality weight is S0, and the initial associated service weight is C0. D0+S0+C0=1. When the urgency is at the first level, the adjusted distance weight D = D0*(A*D1) / [(A*D1)+(B*S1)]; the adjusted service quality weight S = S0*(B*S1) / [(A*D1)+(B*S1)]; the adjusted associated service weight C = C0; When the urgency is at the second level, the adjusted distance weight D = D0*(A*D2) / [(A*D2)+(B*S2)]; the adjusted service quality weight S = S0*(B*S2) / [(A*D2)+(B*S2)]; the adjusted associated service weight C = C0; When the urgency is at the third level, the adjusted distance weight D = D0*(A*D3) / [(A*D3)+(B*S3)]; the adjusted service quality weight S = S0*(B*S3) / [(A*D3)+(B*S3)]; the adjusted associated service weight C = C0.

10. A storage medium, characterized in that: The storage medium stores a computer program; when the computer program is executed, it can implement the method for actively recommending new energy vehicle service sites as described in any one of claims 1 to 8.

Images