Charging station recommendation method and device, equipment and medium
By acquiring vehicle status and navigation map information, determining charging motivation, and calculating the weight and score of charging stations, a low-cost and accurate charging station recommendation is achieved, solving the problems of high cost and low accuracy in existing technologies.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-22
- Publication Date
- 2026-03-31
AI Technical Summary
Existing methods for recommending charging stations have shortcomings in balancing cost and accuracy, requiring a large amount of cloud data and computing power, resulting in high development and maintenance costs.
By acquiring the vehicle's route navigation activation/deactivation status, road type, and battery state of charge, and combining this with the charging indicators searched by the user through the navigation map, the charging motivation is determined, the charging indicator weights and scores of charging stations are calculated, and then priority is recommended to achieve accurate recommendations.
It provides accurate charging station recommendations at low cost, reduces reliance on large-scale data storage and large model analysis, and improves intelligence and user experience.
Smart Images
Figure CN121766680A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of charging station technology, and in particular to a charging station recommendation method, apparatus, equipment and medium. Background Technology
[0002] Electric vehicle users are participants in the charging process. Their charging habits or choices of charging stations may be related to their personal environmental conditions (such as available stations and traffic congestion), vehicle condition, personal activity arrangements, personal subjective preferences, navigation routes, electricity prices, and navigation destinations. Therefore, the choice of charging stations from the user's perspective is a complex issue.
[0003] Currently, a relatively advanced, well-regarded, and effective solution is to build an AI system based on big data and conduct multi-dimensional AI learning. This involves complex data learning and training based on environmental factors, vehicle characteristics, individual activity patterns, decision-making traits, and charging activity feedback to establish a charging station recommendation system tailored to individual user characteristics. However, the overly complex learning and extrapolation of each user's personal habits, decisions, and activity patterns under different conditions requires massive amounts of cloud data and multi-node computing power across the data link, resulting in significant software and hardware development, maintenance, and data traffic costs.
[0004] Therefore, there is an urgent need to provide a new, low-cost, intelligent, and accurate charging station recommendation solution. Summary of the Invention
[0005] This application provides a charging station recommendation method, apparatus, equipment, and medium to address the shortcomings of existing charging station recommendation methods that struggle to simultaneously balance cost and accuracy, and to intelligently generate relatively accurate charging station recommendation schemes at a lower cost.
[0006] Firstly, this application provides a method for recommending charging stations, including: The system acquires the vehicle's route navigation activation / deactivation status, the road type the vehicle is on, the vehicle's battery state of charge, and the charging indicators of various charging stations obtained by the user through navigation map searches; these charging indicators are those that influence the user's charging behavior. Based on the route navigation activation / deactivation status, the road type, and the battery state of charge, the user's charging motivation is determined; the charging motivation is used to indicate the user's priority of demand for different charging indicators. Based on the charging motivation, the weights of the charging indicators for each charging station are determined. Based on the numerical values of the charging indicators of each charging station, a score for the charging indicator of each charging station is determined. Based on the scores and weights of the charging indicators of each charging station, the recommendation priority of each charging station is determined, and charging stations are recommended based on the recommendation priority.
[0007] Optionally, determining the user's charging motivation based on the route navigation activation / deactivation status, the road type, and the battery state of charge includes: The path navigation activation / deactivation status, the road type, and the battery charge status are matched in a preset rule base to obtain the charging motive; the preset rule base includes charging motives corresponding to different path navigation activation / deactivation statuses, different road types, and different battery charge statuses.
[0008] Optionally, the demand priority includes a first priority, a second priority, and a third priority; the first priority is higher than the second priority, and the second priority is higher than the third priority; The step of determining the weights of the charging indicators for each charging station based on the charging motivation includes: If the user's demand priority for the first charging indicator is the first priority, the weight of the first charging indicator is the first target value. If the user's demand priority for the second charging indicator is the second priority, the weight of the second charging indicator is the second target value; the second target value is less than the first target value; If the user's demand priority for the third charging indicator is the third priority, the weight of the third charging indicator is the third target value; the third target value is less than the second target value; the charging indicator of each charging station includes the first charging indicator, the second charging indicator and the third charging indicator.
[0009] Optionally, determining the score of the charging index for each charging station based on the numerical value of the charging index for each charging station includes: Determine the preset value range into which the values of the charging indicators of each charging station fall; Based on the preset score range corresponding to the preset numerical range, the score of the charging index of each charging station is determined.
[0010] Optionally, determining the recommendation priority of each charging station based on the scores of the charging indicators of each charging station and the weights of the charging indicators of each charging station includes: The recommended score for each charging station is obtained by multiplying the score of the charging index of each charging station by the weight of the charging index of each charging station. Based on the recommendation scores of each charging station, the recommendation priority of each charging station is determined.
[0011] Optionally, if the route navigation is enabled, the charging indicator includes one or more of the following indicators: The first distance between the vehicle and the charging station, the first waiting time for charging during off-peak hours at the charging station, the charging price at the charging station, the second waiting time for charging at the charging station, the first time required to reach the charging station, the second distance between the charging station and the target location, the number of times the vehicle has been charged at the charging station in the past, the third distance between the charging station and the driving destination, and the second time required for the vehicle to reach the driving destination after the charging station is included in the navigation route. If the route navigation is in the off state, the charging indicator includes one or more of the following indicators: The first distance, the first waiting time, the charging price, the second waiting time, the first required time, the second distance, and the historical number of charging attempts.
[0012] Optionally, the recommended methods for charging stations also include: If, during multiple charging station recommendations, a target charging station has a higher recommendation priority than a preset priority, the historical charging count of the target charging station is not zero, and the number of times the user has not selected the target charging station consecutively is greater than or equal to a preset number, then the historical charging count of the target charging station will be cleared to zero.
[0013] Secondly, this application also provides a charging station recommendation device, comprising: The data acquisition module is used to acquire the vehicle's route navigation activation / deactivation status, the road type where the vehicle is located, the vehicle's battery state of charge, and the charging indicators of various charging stations obtained by the user through navigation map search; the charging indicators are indicators that affect the user's charging behavior. The first determining module is used to determine the user's charging motivation based on the path navigation activation / deactivation status, the road type, and the battery state of charge; the charging motivation is used to represent the user's priority of demand for different charging indicators; The second determining module is used to determine the weight of the charging index of each charging station based on the charging motivation. The third determining module is used to determine the score of the charging index of each charging station based on the numerical value of the charging index of each charging station. The fourth determining module is used to determine the recommendation priority of each charging station based on the score of the charging index of each charging station and the weight of the charging index of each charging station, and to recommend charging stations based on the recommendation priority.
[0014] Thirdly, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in the first aspect.
[0015] Fourthly, this application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect.
[0016] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.
[0017] The charging station recommendation method, apparatus, equipment, and medium provided in this application analyze the user's charging motivation by acquiring the vehicle's route navigation activation / deactivation status, the road type the vehicle is on, the vehicle's battery state of charge, and the charging indicators of various charging stations obtained by the user through navigation map searches. Then, it determines the score and weight of the charging indicators of each charging station, and finally determines the recommendation priority of each charging station. It fully considers the user's charging motivation and the specific charging indicators of the charging stations, thus enabling accurate recommendations. Moreover, it is entirely based on existing information systems, which can be implemented through the vehicle's in-vehicle system or local hardware. It can accurately analyze user needs without large-scale data storage and large-scale model analysis, simplifying the process, highly intelligent, and at a low cost. Attached Figure Description
[0018] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 This is a flowchart illustrating the charging station recommendation method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the charging station recommendation device provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation
[0020] With the rapid growth of electric vehicle sales and the surge in green electricity, time-of-use pricing mechanisms are being gradually implemented. These mechanisms use price as a regulatory tool to balance charging supply and demand. This approach is highly compatible with the current state of the social power system, information system, charging piles, and vehicle-side technology, enabling rapid adoption. As charging map technology matures, functions such as displaying the map location of charging stations, navigation distance and time, and route planning are now widely available on map applications. Charging station information is integrated into a unified local regulatory platform or a designated large operating platform. This platform will then release the data in a standardized and open manner to certified data requesters, making access to charging station information on maps no longer an obstacle. Charging station performance indicators, such as price, number of people waiting, charging pile occupancy, number of idle charging piles, and station evaluation information, will also have a unified information portal and standardized interface for program access.
[0021] Therefore, a smart and concise charging station recommendation solution that acquires environmental characteristics, charging index information, customer behavior characteristics, and decision-making characteristics can avoid excessive reliance on cloud resources and intelligent models, which is key to feasible commercialization. Based on the current information chain, this application constructs a fast and user-characteristic-matched smart charging station recommendation solution, providing users with a highly intelligent and convenient experience tailored to their individual usage characteristics.
[0022] Specifically, this application can refine and categorize users through in-depth user behavior characteristic surveys, thereby greatly simplifying the intelligent recommendation scheme. Based on their search behavior at different battery levels, it comprehensively considers factors such as anxiety about low battery levels, concern about charging costs, tolerance for waiting during off-peak hours, tolerance for traffic congestion during arrival, tolerance for waiting for charging station occupancy, reliance on personal experience in choosing a charging station, personal route planning, and destination charging habits to make optimal recommendations. This application can also learn from user selection results and adjust the recommendation scheme for the next time. The above process can be completed using existing information chain systems and local programs, reducing the reliance on databases for independent data learning and behavioral analysis of users, thus lowering the cost of use.
[0023] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0024] This application provides a method for recommending charging stations, the execution subject of which can be an electronic device, such as a controller. The following description uses a controller as the execution subject of the method. Figure 1 This is a flowchart illustrating the charging station recommendation method provided in an embodiment of this application. (Refer to...) Figure 1 The method may include: Step 110: Obtain the vehicle's route navigation activation / deactivation status, the road type the vehicle is on, the vehicle's battery charge status, and the charging indicators of each charging station obtained by the user through navigation map search; charging indicators are indicators that affect the user's charging behavior. Step 120: Based on the route navigation on / off status, road type, and battery state of charge, determine the user's charging motivation; the charging motivation is used to indicate the user's priority of demand for different charging indicators. Step 130: Based on the charging motivation, determine the weight of the charging indicators for each charging station; Step 140: Determine the score of each charging station's charging index based on the numerical value of each charging station's charging index. Step 150: Based on the scores and weights of the charging indicators of each charging station, determine the recommendation priority of each charging station, and recommend charging stations based on the recommendation priority.
[0025] In step 110, the controller can obtain the vehicle's route navigation activation / deactivation status, the road type the vehicle is on, the vehicle's battery state of charge, and the charging indicators of various charging stations obtained by the user through navigation map searches. These charging indicators are metrics that influence the user's charging behavior, such as the distance to the vehicle's current location and the number of available charging stations.
[0026] In step 120, the controller can predict the user's charging motivation by analyzing the route navigation's on / off status, road type, and battery state of charge. The user's charging motivation may differ depending on whether route navigation is on or off, whether the road type is a highway or urban road, and whether the battery state of charge is high or low. Charging motivations may include: concerns about charging costs, tolerance for waiting during off-peak hours, tolerance for traffic congestion during arrival, tolerance for waiting at charging stations, reliance on personal experience in choosing charging stations, personal route planning, and destination charging habits.
[0027] In step 130, the controller can determine the weight of the charging indicators for each charging station based on the user's charging motivation.
[0028] In step 140, the controller can determine the score of each charging station's charging index based on the numerical value of each charging station's charging index. For example, if the charging index is the distance to the vehicle's current location, then the closer the distance, the higher the score of the charging station's "distance to the vehicle's current location" index.
[0029] In step 150, the controller determines the recommended score of each charging station based on the scores of the charging indicators of each charging station and the weights of the charging indicators of each charging station, thereby determining the recommendation priority of each charging station, and recommending charging stations based on the recommendation priority.
[0030] The charging station recommendation method provided in this application analyzes the user's charging motivation by acquiring the vehicle's route navigation activation / deactivation status, the road type the vehicle is on, the vehicle's battery state of charge, and the charging indicators of various charging stations obtained by the user through navigation map searches. Then, it determines the score and weight of the charging indicators of each charging station, and finally determines the recommendation priority of each charging station. It fully considers the user's charging motivation and the specific charging indicators of the charging stations, thus making accurate recommendations. Moreover, it is entirely based on existing information systems, which can be implemented by the vehicle's in-vehicle system or local hardware. It can accurately analyze user needs without large-scale data storage and large model analysis, simplifying the process, being highly intelligent, and having a low cost.
[0031] In some embodiments, determining a user's charging motivation based on the route navigation activation / deactivation status, road type, and battery charge status includes: matching the route navigation activation / deactivation status, road type, and battery charge status in a preset rule base to obtain the charging motivation; the preset rule base includes charging motivations corresponding to different route navigation activation / deactivation statuses, different road types, and different battery charge statuses.
[0032] Specifically, the preset rule base is derived by analyzing the impact of route navigation activation / deactivation, road type, and battery state of charge (SOC) on the user's charging motivation. When route navigation is active and the user is on a highway or major arterial road (important transportation routes between cities), they have a clear driving task. At low SOC, users are prone to high charging anxiety and forced choices, leading to anticipated scarcity of charging facilities. The ability to charge as quickly as possible is the first two most important primary factors. When the battery has a certain amount of charge, there are more options, and the predicted optimal route to the destination is the one the user expects to complete the trip. However, due to the faster energy consumption on highways or arterial roads, users still experience charging anxiety. Therefore, the next consideration is to prioritize charging stations as close as possible to the user within reach. At high battery levels, users experience the lowest charging anxiety, and the vehicle's own charging capacity is also limited. Users are likely to prioritize the availability of charging stations near their destination, and the optimization of the trip's completion is the next consideration.
[0033] If navigation is enabled and the user is on urban roads with a clear driving route, and their State of Charge (SOC) is low, it's predicted that the user will experience high charging anxiety and feel forced to make charging choices. Traffic congestion during the journey is also a characteristic of urban environments, making short distance and quick arrival the top two most important factors influencing the user's charging choices. When the user's SOC has a certain amount of charge, urban locations often offer more options than highways or main roads. Therefore, the user prioritizes achieving the optimal route to the destination for the current trip, followed by cost savings. When the battery is high, the user's goal is not immediate charging, and the developed urban environment offers better infrastructure and more options. It's predicted that the user will likely prioritize the availability of charging stations near their destination, followed by the search for cost savings.
[0034] If navigation is off and the user is on a highway or major arterial road (important transportation routes between cities), and has no specific route to take, at a low State of Charge (SOC), the user is predicted to experience high charging anxiety and feel forced to make a choice. Their destination is likely already near, so the nearest and fastest charging station recommendation is necessary. When the vehicle's SOC has a certain amount of charge, due to the faster energy consumption on highways or arterial roads, the user is still predicted to experience charging anxiety. Therefore, the next priority is to recommend charging stations with the shortest possible waiting time within reach. At a high battery level, the user's charging anxiety is lowest, and the vehicle's charging capacity is also limited. The user is likely to be near a familiar area, so priority should be given to charging stations they have previously visited or those closest to home, work, or frequently visited locations. Considering the applicability of the recommendations, the distance to charging stations is a secondary consideration.
[0035] If navigation is off and the user is on city roads with no driving route, they are predicted to experience high charging anxiety at low SOC (State of Charge). However, they also have many choices, and their choice of charging station environment will be influenced by personal habits, such as shopping environment, rest area, and nearby facilities. This information is often not explicitly expressed, and preferences for previously visited charging stations may be implicit. Therefore, distance to charging stations is the primary consideration, followed by previously visited stations. When the vehicle's SOC has a certain amount of charge, compared to highways and main roads where urban infrastructure is more developed, user anxiety is lower, and there are more choices. At this point, the vehicle has sufficient capacity to charge, saving money. The most economical charging station is the primary consideration, followed by previously visited stations. When the battery is high, the user's purpose is not immediate charging. Developed urban environments have better infrastructure and more options. Users are predicted to be familiar with the surrounding environment or looking for low-cost charging opportunities. Therefore, proximity to home, work, or frequently visited locations is the primary consideration, along with the most economical charging station.
[0036] Based on the above motivation analysis, the preset rule base can be obtained as shown in the table below:
[0037] In some embodiments, the demand priority includes a first priority, a second priority, and a third priority; the first priority is higher than the second priority, and the second priority is higher than the third priority; based on charging motivation, the weight of the charging indicator for each charging station is determined, including: if the user's demand priority for the first charging indicator is the first priority, the weight of the first charging indicator is the first target value; if the user's demand priority for the second charging indicator is the second priority, the weight of the second charging indicator is the second target value; the second target value is less than the first target value; if the user's demand priority for the third charging indicator is the third priority, the weight of the third charging indicator is the third target value; the third target value is less than the second target value; the charging indicator for each charging station includes the first charging indicator, the second charging indicator, and the third charging indicator.
[0038] The priority of charging motives in the preset rule base is first priority, then second priority, and generally third priority.
[0039] The first target value can be set to 1.2, the second target value can be set to 1.1, and the third target value can be set to 1.
[0040] The charging station recommendation method provided in this application matches users' charging motivations through a preset rule base, thereby determining the priority of users' needs for different charging indicators, then determining the weight of each charging indicator, and finally determining the recommendation priority of each charging station. It is highly intelligent, fully considering users' charging motivations and the specific charging indicators of charging stations, thus enabling accurate recommendations at a low cost.
[0041] In some embodiments, if the route navigation is enabled, the charging metrics include one or more of the following metrics: a first distance between the vehicle and the charging station, a first waiting time for charging at the charging station during off-peak hours, the charging price at the charging station, a second waiting time for charging at the charging station, a first required time to reach the charging station, a second distance between the charging station and the target location, the number of times the vehicle has been charged at the charging station in the past, a third distance between the charging station and the driving destination, and a second required time for the vehicle to reach the driving destination after the charging station is included in the navigation route; if the route navigation is disabled, the charging metrics include one or more of the following metrics: a first distance, a first waiting time, a charging price, a second waiting time, a first required time, a second distance, and the number of times the vehicle has been charged in the past.
[0042] The controller can obtain the location of charging stations from the navigation map, the distance and time to reach the charging station, and search for map favorites, home, workplace and other target locations along the way when planning the route; information about charging stations, such as price, number of people waiting, number of charging piles occupied, number of idle charging piles, and station evaluation information, are also obtained from a unified platform data entry point.
[0043] In some embodiments, determining the score of the charging index of each charging station based on the numerical value of the charging index of each charging station includes: determining the preset numerical range into which the value of the charging index of each charging station falls; and determining the score of the charging index of each charging station based on the preset numerical range and the preset score range corresponding to the preset score range.
[0044] The following diagram illustrates how the scores and weights of different charging indicators are determined:
[0045] In the table above, if the first distance between the vehicle and the charging station is 0 kilometers, falling within the preset value range of 0 to 3 kilometers, and the corresponding preset score range is 1 to 0.7 points, then the score for the first distance of the charging indicator is 1 point; if the first distance between the vehicle and the charging station is 3 kilometers, falling within the preset value range of 0 to 3 kilometers, and the corresponding preset score range is 1 to 0.7 points, then the score for the first distance of the charging indicator is 0.7 points; if the first distance between the vehicle and the charging station is 1 kilometer, falling within the preset value range of 0 to 3 kilometers, and the corresponding preset score range is 1 to 0.7 points, then the score for the first distance of the charging indicator is 0.9 points. In other words, except for the charging indicator "the second time required for the vehicle to reach its destination after including the charging station in the navigation route," the scores for other charging indicators decrease linearly within the preset score range.
[0046] In the preset rule base, the user's charging motivation, "distance to charging station" corresponds to "the first distance between the vehicle and the charging station" in the table above; "charging waiting time" corresponds to "the second waiting time for charging at the charging station"; "priority of navigation route after inserting station" corresponds to "the second time required for the vehicle to reach the destination after the charging station is included in the navigation route"; "destination" corresponds to "the third distance between the charging station and the destination"; "charging station arrival time" corresponds to "the first time required to reach the charging station"; "most economical charging price" corresponds to "the charging price at the charging station"; "shortest arrival time" corresponds to "the first time required to reach the charging station"; "previously visited stations" corresponds to "the number of times the charging station has been used in the past" which is not zero; and "closest to home, company, or frequently visited locations" corresponds to "the second distance between the charging station and the target location".
[0047] The charging station recommendation method provided in this application divides the numerical values of charging indicators into different preset numerical ranges. Different preset numerical ranges correspond to different preset score ranges, thereby allocating appropriate scores to the numerical values of charging indicators. This facilitates the final determination of the recommendation priority of each charging station, fully considers the specific charging indicators of the charging stations, and thus enables accurate recommendations.
[0048] In some embodiments, the recommendation priority of each charging station is determined based on the scores and weights of the charging indicators of each charging station, including: multiplying the scores of the charging indicators of each charging station by the weights of the charging indicators of each charging station to obtain the recommendation score of each charging station; and determining the recommendation priority of each charging station based on the recommendation scores of each charging station.
[0049] The recommended score is calculated as follows:
[0050] in, These are the recommended scores for each charging station. It is the total number of charging indicators. It is the first The scores of each indicator, It is the first The weight of each indicator.
[0051] The higher the recommendation score, the higher the priority of the charging station recommendation. The controller arranges the charging stations in order according to their recommendation scores, and prioritizes recommending the top three charging stations. If a user scrolling operation is detected, the fourth to sixth charging stations will be recommended, and the display method of recommended charging stations can be adjusted according to how the user views the charging stations.
[0052] The charging station recommendation method provided in this application analyzes the user's charging motivation by acquiring the vehicle's route navigation activation / deactivation status, the road type where the vehicle is located, the vehicle's battery state of charge, and the charging indicators of each charging station. Then, it determines the score and weight of the charging indicators of each charging station and finally determines the recommendation priority of each charging station. It has a high degree of intelligence, fully considers the user's charging motivation and the specific charging indicators of the charging station, so as to make accurate recommendations. Moreover, it does not use artificial intelligence agents, is simple to calculate, and has a low cost.
[0053] In some embodiments, the charging station recommendation method further includes: if, during multiple charging station recommendations, there is a target charging station with a recommendation priority higher than a preset priority, the historical charging count of the target charging station is not zero, and the number of times the user has not selected the target charging station consecutively is greater than or equal to a preset number, then the historical charging count of the target charging station is cleared to zero.
[0054] For example: if the target charging station is a previously visited station, appears in the top three recommended stations, and is not selected by the user twice in a row, then when the target charging station is recommended in the next round, if the target charging station is within the selectable range, the historical charging count will be reset to zero. If the target charging station is subsequently selected by the user, its historical charging count will be re-accumulated.
[0055] The charging station recommendation method provided in this application records the historical charging times of charging stations and learns from users' charging station selection behavior to make the charging station recommendations more accurate, more adaptable to user characteristics, and improve user experience.
[0056] The charging station recommendation device provided in this application is described below. The charging station recommendation device described below can be referred to in correspondence with the charging station recommendation method described above.
[0057] Figure 2 This is a schematic diagram of the charging station recommendation device provided in an embodiment of this application. (Refer to...) Figure 2 The charging station recommendation device provided in this application embodiment may include: The data acquisition module 210 is used to acquire the vehicle's route navigation activation / deactivation status, the road type where the vehicle is located, the vehicle's battery state of charge, and the charging indicators of various charging stations obtained by the user through navigation map search; the charging indicators are indicators that affect the user's charging behavior. The first determining module 220 is used to determine the user's charging motivation based on the path navigation on / off status, the road type, and the battery state of charge; the charging motivation is used to represent the user's priority of demand for different charging indicators; The second determining module 230 is used to determine the weight of the charging index of each charging station based on the charging motivation. The third determining module 240 is used to determine the score of the charging index of each charging station based on the numerical value of the charging index of each charging station. The fourth determining module 250 is used to determine the recommendation priority of each charging station based on the score of the charging index of each charging station and the weight of the charging index of each charging station, and to recommend charging stations based on the recommendation priority.
[0058] The charging station recommendation device provided in this application analyzes the user's charging motivation by acquiring the vehicle's route navigation activation / deactivation status, the road type the vehicle is on, the vehicle's battery state of charge, and the charging indicators of various charging stations obtained by the user through navigation map searches. It then determines the score and weight of each charging station's charging indicator and ultimately determines the recommendation priority of each charging station. This device fully considers the user's charging motivation and the specific charging indicators of the charging stations, enabling accurate recommendations. Moreover, it is entirely based on existing information systems, can be implemented using the vehicle's infotainment system or local hardware, and can accurately analyze user needs without large-scale data storage and large-scale model analysis. It simplifies complex processes, is highly intelligent, and has a low cost.
[0059] In some embodiments, the first determining module is configured to: The path navigation activation / deactivation status, the road type, and the battery charge status are matched in a preset rule base to obtain the charging motive; the preset rule base includes charging motives corresponding to different path navigation activation / deactivation statuses, different road types, and different battery charge statuses.
[0060] In some embodiments, the demand priority includes a first priority, a second priority, and a third priority; the first priority is higher than the second priority, and the second priority is higher than the third priority; The step of determining the weights of the charging indicators for each charging station based on the charging motivation includes: If the user's demand priority for the first charging indicator is the first priority, the weight of the first charging indicator is the first target value. If the user's demand priority for the second charging indicator is the second priority, the weight of the second charging indicator is the second target value; the second target value is less than the first target value; If the user's demand priority for the third charging indicator is the third priority, the weight of the third charging indicator is the third target value; the third target value is less than the second target value; the charging indicator of each charging station includes the first charging indicator, the second charging indicator and the third charging indicator.
[0061] In some embodiments, the third determining module is used to: Determine the preset value range into which the values of the charging indicators of each charging station fall; Based on the preset score range corresponding to the preset numerical range, the score of the charging index of each charging station is determined.
[0062] In some embodiments, the fourth determining module is used to: The recommended score for each charging station is obtained by multiplying the score of the charging index of each charging station by the weight of the charging index of each charging station. Based on the recommendation scores of each charging station, the recommendation priority of each charging station is determined.
[0063] In some embodiments, if the route navigation is enabled, the charging indicator includes one or more of the following indicators: The first distance between the vehicle and the charging station, the first waiting time for charging during off-peak hours at the charging station, the charging price at the charging station, the second waiting time for charging at the charging station, the first time required to reach the charging station, the second distance between the charging station and the target location, the number of times the vehicle has been charged at the charging station in the past, the third distance between the charging station and the driving destination, and the second time required for the vehicle to reach the driving destination after the charging station is included in the navigation route. If the route navigation is in the off state, the charging indicator includes one or more of the following indicators: The first distance, the first waiting time, the charging price, the second waiting time, the first required time, the second distance, and the historical number of charging attempts.
[0064] In some embodiments, the acquisition module is further configured to: If, during multiple charging station recommendations, a target charging station has a higher recommendation priority than a preset priority, the historical charging count of the target charging station is not zero, and the number of times the user has not selected the target charging station consecutively is greater than or equal to a preset number, then the historical charging count of the target charging station will be cleared to zero.
[0065] Specifically, the charging station recommendation device provided in this application embodiment can implement all the method steps implemented by the method embodiment with the controller as the execution subject, and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.
[0066] Figure 3 This is a schematic diagram of the structure of the electronic device provided in an embodiment of this application. For example... Figure 3 As shown, the electronic device may include: a processor 310, a communications interface 320, a memory 330, and a communication bus 340, wherein the processor 310, the communications interface 320, and the memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions in the memory 330 to execute the recommended methods for charging stations, such as: The system acquires the vehicle's route navigation activation / deactivation status, the road type the vehicle is on, the vehicle's battery state of charge, and the charging indicators of various charging stations obtained by the user through navigation map searches; these charging indicators are those that influence the user's charging behavior. Based on the route navigation activation / deactivation status, the road type, and the battery state of charge, the user's charging motivation is determined; the charging motivation is used to indicate the user's priority of demand for different charging indicators. Based on the charging motivation, the weights of the charging indicators for each charging station are determined. Based on the numerical values of the charging indicators of each charging station, a score for the charging indicator of each charging station is determined. Based on the scores and weights of the charging indicators of each charging station, the recommendation priority of each charging station is determined, and charging stations are recommended based on the recommendation priority.
[0067] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0068] On the other hand, this application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the charging station recommendation method provided by the above methods, including, for example: The system acquires the vehicle's route navigation activation / deactivation status, the road type the vehicle is on, the vehicle's battery state of charge, and the charging indicators of various charging stations obtained by the user through navigation map searches; these charging indicators are those that influence the user's charging behavior. Based on the route navigation activation / deactivation status, the road type, and the battery state of charge, the user's charging motivation is determined; the charging motivation is used to indicate the user's priority of demand for different charging indicators. Based on the charging motivation, the weights of the charging indicators for each charging station are determined. Based on the numerical values of the charging indicators of each charging station, a score for the charging indicator of each charging station is determined. Based on the scores and weights of the charging indicators of each charging station, the recommendation priority of each charging station is determined, and charging stations are recommended based on the recommendation priority.
[0069] Furthermore, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to perform the steps of the charging station recommendation method provided by the above methods, such as including: The system acquires the vehicle's route navigation activation / deactivation status, the road type the vehicle is on, the vehicle's battery state of charge, and the charging indicators of various charging stations obtained by the user through navigation map searches; these charging indicators are those that influence the user's charging behavior. Based on the route navigation activation / deactivation status, the road type, and the battery state of charge, the user's charging motivation is determined; the charging motivation is used to indicate the user's priority of demand for different charging indicators. Based on the charging motivation, the weights of the charging indicators for each charging station are determined. Based on the numerical values of the charging indicators of each charging station, a score for the charging indicator of each charging station is determined. Based on the scores and weights of the charging indicators of each charging station, the recommendation priority of each charging station is determined, and charging stations are recommended based on the recommendation priority.
[0070] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.
[0071] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.
[0072] It should also be noted that in the embodiments of this application, the terms "first," "second," etc., are used to distinguish similar objects, and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same class, and the number of objects is not limited. For example, the first object can be one or more.
[0073] In this application embodiment, the term "and / or" describes the association relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.
[0074] In this application's embodiments, "determine B based on A" means that factor A must be considered when determining B. It is not limited to "B can be determined based solely on A," but should also include: "determine B based on A and C," "determine B based on A, C, and E," "determine C based on A, and further determine B based on C," etc. Additionally, it can include using A as a condition for determining B, for example, "when A meets the first condition, determine B using the first method"; another example, "when A meets the second condition, determine B," etc.; another example, "when A meets the third condition, determine B based on the first parameter," etc. Of course, it can also be a condition where A is a factor in determining B, for example, "when A meets the first condition, determine C using the first method, and further determine B based on C," etc.
[0075] In the embodiments of this application, the term "multiple" refers to two or more, and other quantifiers are similar.
[0076] In this application, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this application, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.
[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.
Claims
1. A charging station recommendation method characterized by, The method comprises: obtaining a path navigation on-off state of a vehicle, a road type where the vehicle is located, a battery state of charge of the vehicle, and charging indicators of each charging station searched by a user through a navigation map; the charging indicators are indicators affecting charging behaviors of the user; determining a charging motive of the user based on the path navigation on-off state, the road type, and the battery state of charge; the charging motive is used to represent a demand priority of the user for different charging indicators; determining weights of the charging indicators of the each charging station based on the charging motive; determining scores of the charging indicators of the each charging station based on numerical values of the charging indicators of the each charging station; determining a recommended priority of the each charging station based on the scores of the charging indicators of the each charging station and the weights of the charging indicators of the each charging station, and recommending the charging station based on the recommended priority.
2. The charging station recommendation method according to claim 1, characterized by, The determination of the charging motive of the user based on the path navigation on-off state, the road type, and the battery state of charge comprises: matching the path navigation on-off state, the road type, and the battery state of charge in a preset rule base to obtain the charging motive; the preset rule base comprises charging motives corresponding to different path navigation on-off states, different road types, and different battery states of charge respectively.
3. The charging station recommendation method according to claim 1, characterized by, The demand priority comprises a first priority, a second priority, and a third priority; the first priority is higher than the second priority, and the second priority is higher than the third priority. The determination of the weights of the charging indicators of the each charging station based on the charging motive comprises: if the demand priority of the user for a first charging indicator is the first priority, a weight of the first charging indicator is a first target value; if the demand priority of the user for a second charging indicator is the second priority, a weight of the second charging indicator is a second target value; the second target value is less than the first target value; if the demand priority of the user for a third charging indicator is the third priority, a weight of the third charging indicator is a third target value; the third target value is less than the second target value; the charging indicators of each charging station comprise the first charging indicator, the second charging indicator, and the third charging indicator.
4. The charging station recommendation method according to claim 1, characterized by, The determination of the scores of the charging indicators of the each charging station based on the numerical values of the charging indicators of the each charging station comprises: determining preset numerical value intervals into which the numerical values of the charging indicators of the each charging station fall; determining scores of the charging indicators of the each charging station based on preset score intervals corresponding to the preset numerical value intervals.
5. The charging station recommendation method of claim 1, wherein, The determination of the recommended priority of the each charging station based on the scores of the charging indicators of the each charging station and the weights of the charging indicators of the each charging station comprises: multiplying the score of the charging index of each charging station by the weight of the charging index of each charging station to obtain a recommended score of each charging station; determining a recommended priority of each charging station based on the recommended score of each charging station.
6. The charging station recommendation method of claim 1, wherein, If the path navigation on-off state is on, the charging index includes one or more of the following indexes: a first distance between the vehicle and a charging station, a first waiting time length for charging at a valley price period of a charging station, a charging price of a charging station, a second waiting time length for charging at a charging station, a first required time length for reaching a charging station, a second distance between a charging station and a target location, a historical charging frequency at a charging station, a third distance between a charging station and a travel destination, a second required time length for the vehicle to reach the travel destination after the charging station is planned into a navigation path; If the path navigation on-off state is off, the charging index includes one or more of the following indexes: the first distance, the first waiting time length, the charging price, the second waiting time length, the first required time length, the second distance, and the historical charging frequency.
7. The charging station recommendation method according to claim 6, characterized by, Further comprising: If, when the charging station recommendation is performed multiple times, the recommended priority of a target charging station is higher than a preset priority, the historical charging frequency of the target charging station is not zero, and the number of times that the user continuously does not select the target charging station is greater than or equal to a preset number of times, the historical charging frequency of the target charging station is cleared.
8. A charging station recommendation device characterized by comprising: Comprise: a collection module configured to acquire a path navigation on-off state of a vehicle, a road type in which the vehicle is located, a battery state of charge of the vehicle, and charging indexes of each charging station obtained by a user through navigation map search; the charging index is an index affecting the charging behavior of the user; a first determination module configured to determine a charging motive of the user based on the path navigation on-off state, the road type, and the battery state of charge; the charging motive is used to represent the demand priority of the user for different charging indexes; a second determination module configured to determine a weight of the charging index of each charging station based on the charging motive; a third determination module configured to determine a score of the charging index of each charging station based on the numerical value of the charging index of each charging station; a fourth determination module configured to determine a recommended priority of each charging station based on the score of the charging index of each charging station and the weight of the charging index of each charging station, and to perform charging station recommendation based on the recommended priority.
9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the charging station recommendation method of any one of claims 1 to 7. 10.A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the charging station recommendation method of any one of claims 1 to 7.