A vehicle energy replenishment route planning method and device

Abstract

Embodiments of the present invention relate to the field of electric vehicle technology and disclose a method and device for planning a vehicle recharging route. The method comprises: when a trigger condition for recharging route planning is met, calculating a first mileage required for the vehicle to reach a destination and a second mileage that the vehicle can travel; if the first mileage is greater than the second mileage, determining a first recharging method for the vehicle based on the vehicle's first energy data; and generating a first recharging route based on the first recharging method, vehicle data, road information, and user preference data. By applying the technical solution of the present invention, it is possible to recommend an energy recharging method that better meets the user's needs and generate a corresponding recharging route for users of dual-energy vehicles, thereby improving the flexibility of recharging route planning and making the planned recharging route more in line with the user's needs.

Description

Technical Field

[0001] Embodiments of the present invention relate to the technical field of electric vehicles, and more particularly to a method, apparatus, device, and computer-readable storage medium for planning a vehicle energy replenishment route. Background Art

[0002] Currently, REEV (Range Extended Electric Vehicle) electric vehicles offer two energy options: charging and refueling. They generally offer a longer range. However, REEV vehicles also face complex refueling scenarios and strategies along their routes. Especially on long-distance routes, charging and refueling stations at varying distances must be chosen, while also considering the driver's free time along the route for tasks such as meals and rest breaks.

[0003] Existing refueling route planning methods don't offer users the ability to choose energy refueling options. Long-distance users must make their own decisions about whether to recharge or refuel. Furthermore, different users have different long-distance refueling preferences: some prefer the most cost-effective refueling method, others the fastest refueling method, and still others prefer to refuel while dining and recharging simultaneously. Consequently, existing refueling route planning methods can't incorporate user preferences and schedules, resulting in limited flexibility and a poorly tailored route that doesn't meet users' travel needs. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a vehicle recharging route planning method, apparatus, device and computer-readable storage medium, which are used to solve the problems existing in the prior art that the vehicle recharging route cannot provide users with travel energy recharging selection functions, the flexibility of planning recharging routes is poor, and the planned recharging routes cannot meet the travel needs of users.

[0005] According to one aspect of an embodiment of the present invention, a method for planning a vehicle energy replenishment route is provided, the method comprising:

[0006] When a trigger condition for the energy replenishment route planning is met, calculating a first mileage required for the vehicle to reach the destination and a second mileage that the vehicle can travel;

[0007] If the first mileage is greater than the second mileage, determining a first energy replenishment method for the vehicle according to the first energy data of the vehicle;

[0008] A first energy replenishment route is generated according to the first energy replenishment method, vehicle data, road information and user preference data.

[0009] Specifically, unlike existing technologies that don't offer users the ability to select energy recharge options, the intelligent recharge planning and decision-making mechanism for dual-energy vehicles in this invention combines the current driving route and vehicle energy data to determine the optimal recharge method for dual-energy vehicles. This allows users of dual-energy vehicles to recommend a recharge method that best meets their needs, thereby improving vehicle recharge route planning capabilities. Furthermore, this invention flexibly adjusts vehicle recharge routes based on user preference data, further increasing the flexibility of recharge route planning and ensuring that the planned recharge route better meets user needs.

[0010] In an optional manner, determining the first energy replenishment mode of the vehicle according to the first energy data of the vehicle includes:

[0011] determining information of a plurality of energy recharging stations that the vehicle can reach based on the first energy data of the vehicle;

[0012] A first energy replenishment mode for the vehicle is determined based on information of the plurality of energy replenishment sites.

[0013] Specifically, the present invention considers the vehicle's energy data and the information of the recharging stations that the vehicle can reach, and makes a decision on whether the vehicle needs to refuel or charge based on the information of the recharging stations. It determines the optimal recharging method for dual-energy vehicles and can recommend energy recharging methods that better meet the user's needs to users of dual-energy vehicles, thereby improving the vehicle's recharging route planning capabilities.

[0014] In an optional manner, before determining the first energy replenishment mode for the vehicle based on information of the plurality of energy replenishment sites, the method further includes:

[0015] Determining whether there is a preset preference in the user preference data;

[0016] If there is a preset preference in the user preference data, determining a first energy replenishment method for the vehicle according to the preset preference;

[0017] If there is no preset preference in the user preference data, a first energy replenishment method for the vehicle is determined based on information of the plurality of energy replenishment sites.

[0018] Specifically, in the process of determining the first energy replenishment method, the present invention prioritizes determining the vehicle's energy replenishment method based on the preset preferences set by the user when the user has set a preset preference. This can recommend an energy replenishment method that better meets the user's needs to users of dual-energy vehicles, thereby improving the vehicle's energy replenishment route planning capabilities.

[0019] In an optional manner, determining the first energy replenishment mode of the vehicle according to information of the plurality of energy replenishment sites includes:

[0020] selecting, based on the first energy data and location information of the vehicle, at least one refueling station and at least one charging station from the plurality of refueling stations;

[0021] An optimal energy replenishment mode for the vehicle is determined based on the distance information and energy replenishment information of the gas station and the distance information and energy replenishment information of the charging station, and the optimal energy replenishment mode is used as the first energy replenishment mode for the vehicle.

[0022] Furthermore, the present invention determines an optimal recharging method between refueling and charging based on the distance information and recharging information of each gas station and the distance information and recharging information of each charging station in the information of recharging stations that the vehicle can reach. This can recommend an energy recharging method that is more in line with the user's preferences or actual needs to users of dual-energy vehicles, thereby improving the vehicle's recharging route planning capabilities.

[0023] In an optional manner, calculating a first mileage required for the vehicle to reach a destination and a second mileage that the vehicle can travel includes:

[0024] Taking the current position of the vehicle as a starting point and according to the current driving route, the first mileage is calculated; and the second mileage is calculated according to the current electric energy and fuel energy of the vehicle;

[0025] Alternatively, taking the position of the charging station corresponding to the current charging route of the vehicle as the starting point, the first mileage is calculated according to the current driving route; based on the current charging route of the vehicle, the predicted energy data of the vehicle after charging at the charging station corresponding to the current charging route is predicted; and the second mileage is calculated based on the predicted energy data.

[0026] Specifically, the present invention compares the mileage required to reach the destination along the current driving route at the current location with the mileage provided by the vehicle's current electric energy and fuel energy, and promptly determines whether the vehicle's current electric energy and fuel energy can support the vehicle to reach the destination, and then determines whether the vehicle needs to be recharged during the current driving route, thereby improving the vehicle's recharge route planning capabilities.

[0027] Unlike the existing technology that can only plan the next recharging route after recharging, the present invention determines the optimal recharging method and planned route for the next recharging route based on the driving route and energy data after recharging. It can calculate all recharging routes and recharging methods in a long-distance driving route at one time, so that the planned recharging route better meets user needs.

[0028] The present invention compares the distance required to reach the destination along the remaining route at the location after recharging with the preset recharging data, i.e., the distance provided by the energy provided by the vehicle after recharging, to promptly determine whether the electric energy and fuel energy provided by the vehicle after recharging can support the vehicle to reach the destination along the remaining route, and then determines whether the vehicle needs to be recharged in the remaining route, until the vehicle can support the vehicle to reach the destination after the last recharging. In this way, the present invention determines the nodes that require recharging along the long-distance route, and then sequentially plans all recharging routes and recharging methods along the long-distance route, thereby improving the flexibility of recharging route planning.

[0029] In an optional manner, before determining the first energy replenishment method of the vehicle according to the first energy data of the vehicle, the method further includes:

[0030] Determine whether there is a preset schedule task in the schedule information data;

[0031] When there is a preset schedule task in the schedule information data, determining a second energy replenishment method for the vehicle based on the charging station information at the location of the preset schedule task;

[0032] A second charging route is generated according to the second charging method, vehicle data, road information and user preference data.

[0033] Specifically, before determining the first energy replenishment method, the present invention prioritizes determining the vehicle's energy replenishment method based on the schedule information data set by the user, if the user has set the schedule information data. This can recommend an energy replenishment method that better meets the user's needs to users of dual-energy vehicles, thereby improving the vehicle's energy replenishment route planning capabilities.

[0034] In an optional manner, generating a first energy replenishment route according to the first energy replenishment method, vehicle data, road information, and user preference data includes:

[0035] generating a first recharging route based on the first recharging method, vehicle data, road information, and user preference data, in combination with a preset recommendation model;

[0036] The recommendation model is obtained by training an initial recommendation model based on user feedback data and execution feedback data; the initial recommendation model is integrated from several learning models.

[0037] Specifically, the present invention uses a recommendation model to calculate the recharging route. At the same time, the recommendation module uses user feedback data and execution feedback data to perform reinforcement learning iterations, where the execution feedback data is the user's actual travel data, continuously optimizing the recommendation mechanism of the recommendation model and improving the planning accuracy of the vehicle recharging route.

[0038] In an optional manner, the triggering condition for satisfying the energy replenishment route planning includes:

[0039] When receiving a recharging route planning instruction issued by a user, determining whether a triggering condition for recharging route planning is met;

[0040] Alternatively, when any one of the charging station information, schedule information data, the vehicle data, the road information and the user preference data corresponding to the current charging route of the vehicle undergoes a preset change, it is determined that the triggering condition for charging route planning is met.

[0041] Specifically, the present invention performs charging route planning when a user issues a charging route planning instruction; when any of the charging station information, the schedule information data, the vehicle data, the road information, and the user preference data undergoes a preset change, the charging route is automatically recalculated and the user is reminded, thereby achieving dynamic adjustment of the charging route and improving the vehicle charging route planning capability.

[0042] In an optional manner, the manner of triggering the preset change of the energy charging station information includes: the user modifies the energy charging station corresponding to the current energy charging route in the preset module;

[0043] The manner of triggering the preset change of the schedule information data includes: the user modifies the schedule information data in the preset module;

[0044] The preset module is used to determine and display the task content of each schedule task in the schedule information and the charging station information on the charging route according to the schedule information and the charging route, so that the user can manage the schedule information data or the charging station information.

[0045] Specifically, the present invention supports users' manual modification of schedule data or charging station information through a preset module. If the schedule data or charging station information is modified, it triggers a preset change in the corresponding data. The present invention then recalculates the charging route based on the changed data and notifies the user, enabling dynamic adjustment of the charging route to better meet user needs, thereby improving vehicle charging route planning capabilities.

[0046] According to another aspect of an embodiment of the present invention, a vehicle recharging route planning device is provided, comprising: a mileage calculation module, a recharging mode selection module, and a route planning module;

[0047] The mileage calculation module is configured to calculate a first mileage required for the vehicle to reach the destination and a second mileage that the vehicle can travel when it is determined that a trigger condition for the energy replenishment route planning is met;

[0048] The energy replenishment mode selection module is configured to determine a first energy replenishment mode for the vehicle based on first energy data of the vehicle if the first mileage is greater than the second mileage;

[0049] The route planning module is used to generate a first energy replenishment route according to the first energy replenishment method, vehicle data, road information and the user preference data.

[0050] According to another aspect of an embodiment of the present invention, a device for planning a vehicle recharging route is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus; the memory is configured to store at least one executable instruction, wherein the executable instruction causes the processor to perform the operations described in any one of the methods described above.

[0051] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, wherein the storage medium stores at least one executable instruction, wherein the executable instruction enables a vehicle energy replenishment route planning device / apparatus to perform the operation of any one of the vehicle energy replenishment route planning methods described above.

[0052] The embodiment of the present invention combines the current driving route and the vehicle's energy data to determine the optimal recharging method for dual-energy vehicles, and can recommend an energy recharging method that better meets the user's needs for dual-energy vehicle users. The embodiment of the present invention flexibly adjusts the vehicle's recharging route based on user preference data, and sequentially plans all recharging routes and recharging methods along the entire driving route, thereby enabling the planning of multiple recharging methods and routes for long-distance routes. Furthermore, when any of the recharging station information, the schedule information data, the vehicle data, the road information, and the user preference data undergoes a preset change, the embodiment of the present invention dynamically adjusts the recharging method and recharging route planning, thereby increasing the flexibility of recharging route planning and ensuring that the planned recharging route better meets the user's needs.

[0053] The above description is only an overview of the technical solutions of the embodiments of the present invention. In order to more clearly understand the technical means of the embodiments of the present invention, they can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiments of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present invention. In addition, the same reference symbols are used to represent the same components throughout the drawings. In the drawings:

[0055] Figure 1 A schematic flow chart showing a first embodiment of a vehicle energy replenishment route planning method provided by the present invention;

[0056] Figure 2 A schematic diagram showing a first route of the vehicle energy replenishment route planning method provided by the present invention;

[0057] Figure 3 A schematic diagram showing a second route of the vehicle energy replenishment route planning method provided by the present invention;

[0058] Figure 4 A schematic diagram showing a process of generating an energy replenishment route in the vehicle energy replenishment route planning method provided by the present invention is shown;

[0059] Figure 5 A schematic diagram showing a task icon of the vehicle energy replenishment route planning method provided by the present invention;

[0060] Figure 6 A schematic diagram showing a flow chart of determining a first energy replenishment mode for a vehicle in the vehicle energy replenishment route planning method provided by the present invention;

[0061] Figure 7 A schematic diagram showing the flow of recommendation model training for the vehicle recharging route planning method provided by the present invention is shown;

[0062] Figure 8 The following is a business logic diagram of the vehicle recharging route planning method provided by the present invention;

[0063] Figure 9 A schematic structural diagram of a first embodiment of a vehicle energy replenishment route planning device provided by the present invention is shown;

[0064] Figure 10 A schematic structural diagram of an embodiment of a vehicle recharging route planning device provided by the present invention is shown. DETAILED DESCRIPTION

[0065] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0066] Figure 1 The flowchart of the first embodiment of the vehicle charging route planning method of the present invention is shown, and the method is executed by the vehicle charging route planning device. Figure 1 As shown, the method includes the following steps:

[0067] Step 110: When a trigger condition for energy replenishment route planning is met, a first mileage required for the vehicle to reach a destination and a second mileage that the vehicle can travel are calculated.

[0068] In some embodiments of the present invention, calculating a first mileage required for the vehicle to reach a destination and a second mileage that the vehicle can travel includes:

[0069] Taking the current position of the vehicle as a starting point and according to the current driving route, the first mileage is calculated; and the second mileage is calculated according to the current electric energy and fuel energy of the vehicle;

[0070] Alternatively, taking the position of the charging station corresponding to the current charging route of the vehicle as the starting point, the first mileage is calculated according to the current driving route; based on the current charging route of the vehicle, the predicted energy data of the vehicle after charging at the charging station corresponding to the current charging route is predicted; and the second mileage is calculated based on the predicted energy data.

[0071] Specifically, predicting the predicted energy data of the vehicle after recharging at the recharging station corresponding to the current recharging route includes:

[0072] The energy data of the vehicle when it arrives at the energy replenishment station corresponding to the current energy replenishment route and the preset energy replenishment data are calculated to obtain the predicted energy data of the vehicle after it is recharged at the energy replenishment station corresponding to the current energy replenishment route.

[0073] Preferably, the preset energy replenishment data is determined based on the charging time and charging power of the vehicle at the last charging station, or based on the number of liters of fuel consumed by the vehicle at the last gas station.

[0074] For details, please refer to Figure 2 When the triggering condition for the recharging route planning is met, if the number of recharging routes currently planned by the planning device is zero, the planning device takes the current position X of the vehicle as the starting point and calculates the first mileage required for the vehicle to reach the destination Y according to the current driving route; the planning device calculates the second mileage that the vehicle can travel using the current electric energy and fuel energy based on the current electric energy and fuel energy of the vehicle.

[0075] If the first mileage is greater than the second mileage, the planning device uses the vehicle's current electric energy and fuel energy as the first energy data to determine the vehicle's energy replenishment method; and determines the location of the energy replenishment station A based on the energy replenishment method, vehicle data, road information and user preference data, and generates an energy replenishment route from the current position X to the energy replenishment station A.

[0076] Please refer to Figure 3When the triggering conditions for recharging route planning are met, if the number of recharging routes currently planned by the planning device is not zero, that is, the planning device has planned at least one recharging route, the planning device uses the location of recharging station B corresponding to the current recharging route as the starting point and calculates the first mileage required for the vehicle to reach destination Y based on the current driving route. Recharging station B corresponding to the current recharging route is the last recharging station in the current recharging route. Based on the vehicle's current recharging route, the planning device predicts predicted energy data for the vehicle after recharging at recharging station B corresponding to the current recharging route; and calculates the second mileage based on the predicted energy data.

[0077] If the first mileage is greater than the second mileage, the planning device uses the predicted energy data of the vehicle after recharging at recharging station B as the first energy data to determine the vehicle's recharging method; and based on the recharging method, vehicle data, road information and user preference data, determines the location of the next recharging station C, and generates a recharging route from recharging station B to recharging station C.

[0078] If the first mileage is not greater than the second mileage, the next refueling route will not be planned.

[0079] For example, please refer to Figure 4 ,The planning device calculates the first mileage required to reach the destination from the current location / position after recharging based on the current / remaining driving route, schedule information data, energy consumption, expected vehicle speed and other information.

[0080] The planning device calculates the second mileage that the vehicle can provide based on the current electric energy and fuel energy of the vehicle, or the second energy data after recharging; and subtracts the second mileage from the first mileage to obtain the mileage required for recharging.

[0081] If the mileage required for recharging is greater than zero, the planning device determines the first recharging method of the vehicle based on the vehicle's first energy data, schedule information data and user preference data; generates a first recharging route based on the first recharging method, vehicle data, road information and user preference data; after generating the first recharging route, the planning device calculates the second energy data after recharging based on the generated first recharging route, and returns to the calculation process of the first mileage.

[0082] If the mileage required for refueling is not greater than zero, the planning device ends the process.

[0083] Specifically, unlike the prior art method of only planning the next refueling route after refueling, the present invention, after generating any refueling route, uses the location of the refueling station corresponding to the vehicle's current refueling route as a starting point and recalculates the first mileage based on the current route. Based on the vehicle's current refueling route, the planning device predicts the energy data when the vehicle arrives at the refueling station corresponding to the current refueling route, as well as the preset refueling data, and recalculates the second mileage to obtain the required refueling mileage. The present invention then uses the required refueling mileage to determine whether the vehicle needs refueling for the remainder of the route, until the last refueling allows the vehicle to reach its destination. This method allows the present invention to identify nodes requiring refueling along long-distance routes and subsequently plan all refueling routes and refueling methods along the long-distance route, thereby increasing the flexibility of refueling route planning. The present invention eliminates the need for multiple user instructions and can simultaneously plan all refueling routes and refueling methods for the entire long-distance route, thus improving vehicle refueling route planning capabilities.

[0084] In some embodiments of the present invention, the triggering condition for satisfying energy replenishment route planning includes:

[0085] When receiving a recharging route planning instruction issued by a user, determining whether a triggering condition for recharging route planning is met;

[0086] Alternatively, when any one of the charging station information, schedule information data, the vehicle data, the road information and the user preference data corresponding to the current charging route of the vehicle undergoes a preset change, it is determined that the triggering condition for charging route planning is met.

[0087] Exemplarily, preset changes in charging station information include but are not limited to: changes in charging stations, changes in the availability of charging stations, or changes in queues at gas stations; preset changes in vehicle data include but are not limited to: the vehicle's power consumption exceeds the expected power value for a continuous preset period of time; preset changes in road information include but are not limited to: changes in the driving route due to road conditions and other factors, changes in the driving route due to manual route adjustment by the user, changes in the parking situation in the service area corresponding to the schedule information data, the user's previous trip ended early, or the user's previous trip was delayed; methods for triggering preset changes in user preference data include: the user manually setting the preference options on the planning device.

[0088] Specifically, the planning device obtains the user's input schedule tasks and corresponding time periods to obtain schedule information data. Schedule tasks include, but are not limited to, meals and rest. For example, the schedule information data includes: a first meal time period (e.g., 12:00-14:00), a first meal duration (e.g., 60 minutes); a first rest time period (e.g., 20:00-24:00), a first rest duration (e.g., 120 minutes).

[0089] Preferably, the planning device provides user preference data options on the route selection panel for the user to select. User preference data options include, but are not limited to, "Smart Recommendation," "Shortest Time," "Lowest Cost," "Most Convenient," "Most Comfortable," "Refueling Only," and "Charging Only." The default initial option for user preference data is "Smart Recommendation," and the user can switch between different options on the route selection panel.

[0090] In some embodiments of the present invention, when any one of the charging station information corresponding to the current charging route of the vehicle, the schedule information data, the vehicle data, the road information, and the user preference data undergoes a preset change, including:

[0091] The method of triggering the preset change of the energy charging station information includes: the user modifies the energy charging station corresponding to the current energy charging route in the preset module;

[0092] The manner of triggering the preset change of the schedule information data includes: the user modifies the schedule information data in the preset module;

[0093] The preset module is used to determine and display the task content of each schedule task in the schedule information and the charging station information on the charging route according to the schedule information and the charging route, so that the user can manage the schedule information data or the charging station information.

[0094] Specifically, the planning device calculates the refueling route based on the schedule information data, and obtains the restaurant data, hotel data, gas station data and charging station data on the driving route that meet the schedule task and the refueling task. Preferably, the planning device provides several task icons on the user interface, please refer to Figure 5 From left to right, there are icons for charging stations, gas stations, restaurants, and rest areas. When a user clicks an icon, the planning device displays the corresponding restaurant, hotel, gas station, or charging station data.

[0095] Preferably, the planning device generates corresponding task detail cards based on the scheduled tasks and recharge tasks, allowing users to manage the scheduled tasks and recharge tasks on the task detail cards. Users can modify meal periods, meal durations, rest periods, rest durations, recharge methods, or recharge locations by deleting, adding, or modifying tasks.

[0096] Specifically, users can change the schedule information data or charging station information in the task details card, triggering preset changes in the corresponding data. The planning device will then recalculate the charging route based on the changed data and remind the user, thereby dynamically adjusting the charging route. The adjusted charging route is more in line with user needs, thereby improving the vehicle charging route planning capabilities.

[0097] Step 120: If the first mileage is greater than the second mileage, determining a first energy replenishment method for the vehicle according to the first energy data of the vehicle.

[0098] In some embodiments of the present invention, determining a first energy replenishment method for the vehicle according to the first energy data of the vehicle includes:

[0099] determining information of a plurality of energy recharging stations that the vehicle can reach based on the first energy data of the vehicle;

[0100] A first energy replenishment mode for the vehicle is determined based on information of the plurality of energy replenishment sites.

[0101] In some embodiments of the present invention, before determining the first energy replenishment method for the vehicle based on information of the plurality of energy replenishment sites, the method further includes:

[0102] Determining whether there is a preset preference in the user preference data;

[0103] If there is a preset preference in the user preference data, determining a first energy replenishment method for the vehicle according to the preset preference;

[0104] If there is no preset preference in the user preference data, a first energy replenishment method for the vehicle is determined based on information of the plurality of energy replenishment sites.

[0105] For example, when the planning device determines that there is a charging station among the several charging stations that the vehicle can reach, and the option of the user preference data selected by the user is "charging only" or "lowest cost", the planning device determines that the first charging method of the vehicle is charging.

[0106] In some embodiments of the present invention, determining the first energy replenishment mode of the vehicle based on information of the plurality of energy replenishment sites includes:

[0107] selecting, based on the first energy data and location information of the vehicle, at least one refueling station and at least one charging station from the plurality of refueling stations;

[0108] An optimal energy replenishment mode for the vehicle is determined based on the distance information and energy replenishment information of the gas station and the distance information and energy replenishment information of the charging station, and the optimal energy replenishment mode is used as the first energy replenishment mode for the vehicle.

[0109] Specifically, the planning device determines the optimal energy replenishment method for the vehicle based on the distance information, refueling time and refueling cost of the gas station, and the distance information, charging time and charging cost of the charging station, and uses the optimal energy replenishment method as the first energy replenishment method for the vehicle.

[0110] Furthermore, if among the several energy replenishment stations there are only gas stations but no charging stations, the planning device determines that the first energy replenishment method for the vehicle is refueling; if among the several energy replenishment stations there are only charging stations but no gas stations, the planning device determines that the first energy replenishment method for the vehicle is charging.

[0111] In some embodiments of the present invention, before determining the first energy replenishment method of the vehicle according to the first energy data of the vehicle, the method further includes:

[0112] Determine whether there is a preset schedule task in the schedule information data;

[0113] When there is a preset schedule task in the schedule information data, determining a second energy replenishment method for the vehicle based on the charging station information at the location of the preset schedule task;

[0114] A second charging route is generated according to the second charging method, vehicle data, road information and user preference data.

[0115] Exemplarily, the preset schedule task is a schedule task for dining or resting. When a schedule task for dining or resting exists in the schedule information data, assuming that the dining or resting location is in a service area, the planning device determines whether there is a charging station in the service area; if there is a charging station in the service area and the charging station has available charging piles, the planning device determines that the first energy replenishment method of the vehicle is charging.

[0116] In some embodiments of the present invention, when there is no preset schedule task in the schedule information data, the first energy replenishment method of the vehicle is determined according to the first energy data of the vehicle.

[0117] For example, please refer to Figure 6 , the planning device determines whether there is a schedule task of dining or rest in the schedule information data.

[0118] When there is a schedule task for dining or resting in the schedule information data, assuming that the dining or resting place is in a service area, the planning device determines whether there is a charging station in the service area; if there is a charging station in the service area and the charging station has available charging piles, the planning device determines that the first energy replenishment method of the vehicle is charging.

[0119] When there is no meal or rest schedule task in the schedule information data, the planning device estimates the SOC data of the vehicle when it arrives at each refueling station.

[0120] If the vehicle's SOC is greater than 20% when it arrives at the next refueling station, or if the vehicle's SOC is less than 20% when it arrives at the next refueling station and the vehicle's remaining energy is insufficient to reach the next refueling station, the planning device determines whether the user's preference data option is "Charge Only" or "Minimum Cost." The next refueling station must be closer to the current location than the next refueling station, and the next refueling station offers both charging and refueling options.

[0121] If the option selected by the user in the user preference data is "charging only" or "lowest cost", it means that the user prefers to give priority to the charging energy replenishment method, and the planning device determines that the first energy replenishment method of the vehicle is charging.

[0122] If the option selected by the user in the user preference data is not "charging only" or "lowest cost", indicating that the user does not prefer charging as the energy replenishment method, the planning device determines, based on the first energy data and location information of the vehicle, distance information and energy replenishment information of at least one gas station, and distance information and energy replenishment information of at least one charging station;

[0123] Based on the distance information, refueling time and refueling cost of the gas station, and the distance information, charging time and charging cost of the charging station, the planning device determines the optimal energy replenishment method for the vehicle and uses the optimal energy replenishment method as the first energy replenishment method for the vehicle.

[0124] If the SOC data of the vehicle when it arrives at the next recharging station is no more than 20% and the remaining energy of the vehicle supports reaching the location of the next recharging station, the planning device determines that the vehicle does not need to be recharged temporarily.

[0125] Specifically, the present invention uses user-configured schedule data to determine whether the user has idle time, such as for meals or rest, when the vehicle is not in use. Charging, compared to refueling, requires longer time. The present invention combines idle time with corresponding charging station information to determine the vehicle's charging method, maximizing the user's available time for charging.

[0126] If there is no idle time for meals or rest, the user is determined to have a preference for charging based on the recharging preference data. If the user is more inclined to prefer charging, the planning device determines charging as the vehicle's first recharging method. If the user is not inclined to prefer charging, the planning device determines the optimal recharging method between refueling and charging based on the distance information and recharging information between gas stations and charging stations.

[0127] The present invention combines schedule information data, charging preferences and the vehicle's remaining power to decide on the optimal charging method for the vehicle. It can recommend energy charging methods that are more in line with user preferences or actual needs for dual-energy vehicle users, thereby improving the vehicle's charging route planning capabilities.

[0128] Step 130: Generate a first charging route based on the first charging method, vehicle data, road information and user preference data.

[0129] In some embodiments of the present invention, generating a first energy replenishment route according to the first energy replenishment method, vehicle data, road information, and user preference data includes:

[0130] generating a first recharging route based on the first recharging method, vehicle data, road information, and user preference data, in combination with a preset recommendation model;

[0131] The recommendation model is obtained by training an initial recommendation model based on user feedback data and execution feedback data; the initial recommendation model is integrated from several learning models.

[0132] For example, please refer to Figure 7 The present invention loads the variable data required for the recommendation model's decision-making as input data, State, including navigation information, road information, driving information, energy information, and other information. Navigation information includes the route, slope, and historical congestion; road information includes the estimated speed for each road section, along-way charging and refueling station information; driving information includes driving mode, energy recovery mode, and the number of passengers on board; energy information includes the remaining battery life, energy consumption per 100 kilometers, and onboard device power; and other information includes the duration of meal and rest periods.

[0133] The present invention imports the input data State and user feedback data into the reinforcement learning database Replay Buffer. The user feedback data is obtained through multimodal sensing technology and vehicle control methods. The user feedback data includes feedback data from vehicle owners and passengers.

[0134] The present invention combines three learning models, Model1, Mldel2, and Model3, as the initial recommendation model. Preferably, a regression tree model, an XGBoost model, and a fully connected neural network model are combined as the initial recommendation model. The planning device imports the input data, State, into the initial recommendation model, performs ensemble learning on the prediction results of the three learning models, and obtains a recommendation decision. The system then automatically generates and executes a refueling route, obtaining execution feedback data.

[0135] The planning device imports the execution feedback data into the reinforcement learning system. At the same time, the planning device imports the model input data State and the reinforcement learning database Replay Buffer data into the reinforcement learning system.

[0136] The reinforcement learning system performs online deduction of the online Q-Learning algorithm based on the input model data State, and offline training of the offline reinforcement learning algorithm (Batch-Constained Q Leaming) based on data from the reinforcement learning database Replay Buffer. The algorithm is continuously optimized with the goal of maximizing environmental rewards. Based on the Replay Memory mechanism and execution feedback data, the reinforcement learning system fine-tunes the parameters of the initial recommendation model to obtain the recommended model.

[0137] Specifically, the present invention uses a recommendation model to calculate the recharging route. At the same time, the recommendation module uses user feedback data and execution feedback data to perform reinforcement learning iterations, where the execution feedback data is the user's actual travel data, continuously optimizing the recommendation mechanism of the recommendation model and improving the planning accuracy of the vehicle recharging route.

[0138] To better illustrate the embodiments of the present invention, please refer to Figure 8 The business logic of the vehicle recharging route planning method is as follows: high-precision route estimation, intelligent analysis of recharging planning, and real-time strategy adjustment.

[0139] During the high-precision route estimation phase, the planning device collects full-scene data, calculates vehicle energy consumption using a navigation energy consumption algorithm, and calculates the current charging time required for the vehicle using a charging duration algorithm. Based on the collected full-scene data, calculated vehicle energy consumption, and charging time, the planning device generates several high-precision recharging routes.

[0140] Full-scenario data includes both vehicle and non-vehicle data. Vehicle data includes remaining battery charge, energy consumption per 100 kilometers, vehicle load, number of passengers, driving mode (e.g., sport or energy-saving), energy recovery mode, and the power of onboard devices such as the air conditioner. Non-vehicle data includes navigation routes, slope, temperature, congestion history, charging station locations, charging station availability, charging station charges, gas station locations, gas station queues, and meal and rest schedules.

[0141] During the intelligent analysis phase of refueling planning, the system recommends a refueling route that meets the user's preferences from among several high-precision refueling routes generated based on the user's selected preference data. For example, if the user selects the "Intelligent Recommendation" option, the system uses an intelligent recommendation strategy to recommend the optimal refueling route, taking into account factors such as meal times, rest breaks, waiting time in queues, and refueling costs. If the user selects the "Shortest Time" option, the planning device selects the refueling route with the shortest total time while meeting the user's schedule. If the user selects the "Lowest Cost" option, the planning device selects the route with the lowest total cost while meeting the user's schedule. If the user selects the "Most Convenient" option, the planning device selects the route with the fewest stops and detours while meeting the user's schedule. If the user selects the "Most Comfortable" option, the planning device selects a service area with the best ratings and comprehensive amenities while meeting the user's schedule.

[0142] During the real-time strategy adjustment phase, the planning device updates the algorithm in real time based on changes in remaining battery power and congestion conditions, replanning and recommending recharging routes. Changes that trigger algorithm updates include: road condition updates, user schedule updates, changes in vehicle power consumption, charging station availability, gas station queues, parking conditions at service areas, premature end or delay of the previous journey, and user route adjustments.

[0143] An embodiment of the present invention provides a method for planning a vehicle recharging route. The embodiment of the present invention combines the current driving route, schedule information data, and user preference data to determine the optimal recharging method for a dual-energy vehicle, and can recommend an energy recharging method that better meets the user's needs to users of dual-energy vehicles. The embodiment of the present invention flexibly adjusts the vehicle recharging route based on the user's schedule information data and user preference data, and sequentially plans all recharging routes and recharging methods in the entire driving route to implement the planning of multiple recharging methods and routes for long-distance routes. At the same time, when any one of the recharging site information, the schedule information data, the vehicle data, the road information, and the user preference data undergoes a preset change, the embodiment of the present invention dynamically adjusts the recharging method and recharging route planning, thereby improving the flexibility of recharging route planning so that the planned recharging route better meets the user's needs.

[0144] Figure 9FIG1 shows a schematic diagram of the structure of the first embodiment of the vehicle charging route planning device of the present invention. Figure 7 As shown, the device 700 includes: a mileage calculation module 710, a charging mode selection module 720 and a route planning module 730;

[0145] The mileage calculation module 710 is configured to calculate a first mileage required for the vehicle to reach the destination and a second mileage that the vehicle can travel when it is determined that a trigger condition for the recharging route planning is met;

[0146] The energy replenishment mode selection module 720 is configured to determine a first energy replenishment mode for the vehicle based on the first energy data of the vehicle if the first mileage is greater than the second mileage;

[0147] The route planning module 730 is configured to generate a first charging route according to the first charging method, vehicle data, road information, and user preference data.

[0148] In an optional manner, the triggering condition for satisfying the energy replenishment route planning includes:

[0149] When receiving a recharging route planning instruction issued by a user, determining whether a triggering condition for recharging route planning is met;

[0150] Alternatively, when any one of the charging station information, schedule information data, the vehicle data, the road information and the user preference data corresponding to the current charging route of the vehicle undergoes a preset change, it is determined that the triggering condition for charging route planning is met.

[0151] In an optional manner, when any one of the charging station information corresponding to the current charging route of the vehicle, the schedule information data, the vehicle data, the road information, and the user preference data undergoes a preset change, including:

[0152] The method of triggering the preset change of the energy charging station information includes: the user modifies the energy charging station corresponding to the current energy charging route in the preset module;

[0153] The manner of triggering the preset change of the schedule information data includes: the user modifies the schedule information data in the preset module;

[0154] The preset module is used to determine and display the task content of each schedule task in the schedule information and the charging station information on the charging route according to the schedule information and the charging route, so that the user can manage the schedule information data or the charging station information.

[0155] In an optional manner, the mileage calculation module 710 includes: a first calculation unit and a second calculation unit;

[0156] The first calculation unit is used to calculate the first mileage based on the current driving route of the vehicle with the current position of the vehicle as the starting point; and calculate the second mileage based on the current electric energy and fuel energy of the vehicle;

[0157] The second calculation unit is configured to calculate the first mileage based on the current driving route, starting from the location of a recharging station corresponding to the vehicle's current recharging route. The second calculation unit is configured to predict, based on the vehicle's current recharging route, second energy data after the vehicle is recharged at the recharging station corresponding to the current recharging route; and calculate the second mileage based on the second energy data.

[0158] In an optional manner, the energy replenishment mode selection module 720 includes: a first selection unit, a second selection unit, and a third selection unit;

[0159] The first selection unit is configured to determine whether there is a preset schedule task in the schedule information data before determining the first energy replenishment method of the vehicle according to the first energy data of the vehicle;

[0160] When there is a preset schedule task in the schedule information data, determining a second energy replenishment method for the vehicle based on the charging station information at the location of the preset schedule task;

[0161] A second charging route is generated according to the second charging method, vehicle data, road information and user preference data.

[0162] The second selection unit is used to determine information of a plurality of energy replenishment stations that the vehicle can reach based on the first energy data of the vehicle;

[0163] A first energy replenishment mode for the vehicle is determined based on information of the plurality of energy replenishment sites.

[0164] The third selection unit is configured to determine whether a preset preference exists in the user preference data before determining the first energy replenishment method for the vehicle based on the information of the plurality of energy replenishment sites;

[0165] If there is a preset preference in the user preference data, determining a first energy replenishment method for the vehicle according to the preset preference;

[0166] If there is no preset preference in the user preference data, a first energy replenishment method for the vehicle is determined based on information of the plurality of energy replenishment sites.

[0167] The determining of the first energy replenishment mode of the vehicle based on information of the plurality of energy replenishment sites includes:

[0168] selecting, based on the first energy data and location information of the vehicle, at least one refueling station and at least one charging station from the plurality of refueling stations;

[0169] An optimal energy replenishment mode for the vehicle is determined based on the distance information and energy replenishment information of the gas station and the distance information and energy replenishment information of the charging station, and the optimal energy replenishment mode is used as the first energy replenishment mode for the vehicle.

[0170] In an optional manner, the route planning module 730 includes: a route planning unit;

[0171] The route planning unit is configured to generate a first recharging route based on the first recharging method, vehicle data, road information, and user preference data in combination with a preset recommendation model;

[0172] The recommendation model is obtained by training an initial recommendation model based on user feedback data and execution feedback data; the initial recommendation model is integrated from several learning models.

[0173] An embodiment of the present invention provides a vehicle recharging route planning device, wherein a mileage calculation module and a recharging method selection module determine the optimal recharging method for a dual-energy vehicle based on the current driving route and the vehicle's energy data, and are capable of recommending an energy recharging method that better meets the user's needs for the dual-energy vehicle. A route planning module flexibly adjusts the vehicle recharging route based on the user's user preference data, and sequentially plans all recharging routes and recharging methods along the entire driving route, thereby enabling the planning of multiple recharging methods and routes for long-distance routes. Furthermore, when any of the recharging station information, the schedule information data, the vehicle data, the road information, and the user preference data undergoes a preset change, the route planning module dynamically adjusts the recharging method and recharging route planning, thereby increasing the flexibility of recharging route planning and ensuring that the planned recharging route better meets the user's needs.

[0174] Figure 10 A schematic structural diagram of an embodiment of a vehicle charging route planning device according to the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the vehicle charging route planning device.

[0175] like Figure 10 As shown, the vehicle charging route planning device may include: a processor (processor) 802 , a communications interface (Communications Interface) 804 , a memory (memory) 806 , and a communication bus 808 .

[0176] Processor 802, communication interface 804, and memory 806 communicate with each other via communication bus 808. Communication interface 804 is used to communicate with other devices, such as clients or other server network elements. Processor 802 is used to execute program 810, which may specifically perform the steps described in the aforementioned embodiment of the method for planning a vehicle recharging route.

[0177] Specifically, the program 810 may include program code including computer-executable instructions.

[0178] Processor 802 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included in the vehicle recharging route planning device may be of the same type, such as one or more CPUs, or different types, such as one or more CPUs and one or more ASICs.

[0179] The memory 806 is used to store the program 810. The memory 806 may include a high-speed RAM memory, or may also include a non-volatile memory (non-volatile memory), such as at least one disk storage.

[0180] Program 810 may be specifically invoked by processor 802 to enable the vehicle recharging route planning device to perform the following operations:

[0181] When a trigger condition for the energy replenishment route planning is met, calculating a first mileage required for the vehicle to reach the destination and a second mileage that the vehicle can travel;

[0182] If the first mileage is greater than the second mileage, determining a first energy replenishment method for the vehicle according to the first energy data of the vehicle;

[0183] A first energy replenishment route is generated according to the first energy replenishment method, vehicle data, road information and user preference data.

[0184] In an optional manner, determining the first energy replenishment mode of the vehicle according to the first energy data of the vehicle includes:

[0185] determining information of a plurality of energy recharging stations that the vehicle can reach based on the first energy data of the vehicle;

[0186] A first energy replenishment mode for the vehicle is determined based on information of the plurality of energy replenishment sites.

[0187] In an optional manner, before determining the first energy replenishment mode for the vehicle based on information of the plurality of energy replenishment sites, the method further includes:

[0188] Determining whether there is a preset preference in the user preference data;

[0189] If there is a preset preference in the user preference data, determining a first energy replenishment method for the vehicle according to the preset preference;

[0190] If there is no preset preference in the user preference data, a first energy replenishment method for the vehicle is determined based on information of the plurality of energy replenishment sites.

[0191] In an optional manner, determining the first energy replenishment mode of the vehicle according to information of the plurality of energy replenishment sites includes:

[0192] selecting, based on the first energy data and location information of the vehicle, at least one refueling station and at least one charging station from the plurality of refueling stations;

[0193] An optimal energy replenishment mode for the vehicle is determined based on the distance information and energy replenishment information of the gas station and the distance information and energy replenishment information of the charging station, and the optimal energy replenishment mode is used as the first energy replenishment mode for the vehicle.

[0194] In an optional manner, calculating a first mileage required for the vehicle to reach a destination and a second mileage that the vehicle can travel includes:

[0195] Taking the current position of the vehicle as a starting point and according to the current driving route, the first mileage is calculated; and the second mileage is calculated according to the current electric energy and fuel energy of the vehicle;

[0196] Alternatively, taking the position of the charging station corresponding to the current charging route of the vehicle as the starting point, the first mileage is calculated according to the current driving route; based on the current charging route of the vehicle, the predicted energy data of the vehicle after charging at the charging station corresponding to the current charging route is predicted; and the second mileage is calculated based on the predicted energy data.

[0197] In an optional manner, before determining the first energy replenishment method of the vehicle according to the first energy data of the vehicle, the method further includes:

[0198] Determine whether there is a preset schedule task in the schedule information data;

[0199] When there is a preset schedule task in the schedule information data, determining a second energy replenishment method for the vehicle based on the charging station information at the location of the preset schedule task;

[0200] A second charging route is generated according to the second charging method, vehicle data, road information and user preference data.

[0201] In an optional manner, generating a first energy replenishment route according to the first energy replenishment method, vehicle data, road information, and user preference data includes:

[0202] Generate a first recharging route based on the first recharging method, vehicle data, road information, and user preference data, combined with a preset recommendation model;

[0203] The recommendation model is obtained by training an initial recommendation model based on user feedback data and execution feedback data; the initial recommendation model is integrated from several learning models.

[0204] In an optional manner, the triggering condition for satisfying the energy replenishment route planning includes:

[0205] When receiving a recharging route planning instruction issued by a user, determining whether a triggering condition for recharging route planning is met;

[0206] Alternatively, when any one of the charging station information, schedule information data, the vehicle data, the road information and the user preference data corresponding to the current charging route of the vehicle undergoes a preset change, it is determined that the triggering condition for charging route planning is met.

[0207] The method of triggering the preset change of the energy charging station information includes: the user modifies the energy charging station corresponding to the current energy charging route in the preset module;

[0208] The manner of triggering the preset change of the schedule information data includes: the user modifies the schedule information data in the preset module;

[0209] The preset module is used to determine and display the task content of each schedule task in the schedule information and the charging station information on the charging route according to the schedule information and the charging route, so that the user can manage the schedule information data or the charging station information.

[0210] An embodiment of the present invention provides a vehicle recharging route planning device. The device combines the current driving route and the vehicle's energy data to determine the optimal recharging method for a dual-energy vehicle, and can recommend an energy recharging method that better meets the user's needs for the dual-energy vehicle. The device flexibly adjusts the vehicle recharging route based on the user's user preference data, and sequentially plans all recharging routes and recharging methods along the entire driving route, thereby enabling the planning of multiple recharging methods and routes for long-distance routes. Furthermore, when any of the recharging station information, the schedule information data, the vehicle data, the road information, and the user preference data undergoes a preset change, the device dynamically adjusts the recharging method and recharging route planning, thereby increasing the flexibility of recharging route planning and ensuring that the planned recharging route better meets the user's needs.

[0211] An embodiment of the present invention provides a computer-readable storage medium storing at least one executable instruction. When the executable instruction is executed on a vehicle energy replenishment route planning device / apparatus, the vehicle energy replenishment route planning device / apparatus executes the vehicle energy replenishment route planning method in any of the above-mentioned method embodiments.

[0212] An embodiment of the present invention provides a computer-readable storage medium, wherein the storage medium stores at least one executable instruction. The executable instruction enables a vehicle recharging route planning device / apparatus to determine the optimal recharging method for a dual-energy vehicle based on the current driving route, schedule information data, and user preference data, and to recommend an energy recharging method that better meets the user's needs for a dual-energy vehicle. The planning device / apparatus flexibly adjusts the vehicle recharging route based on the user's schedule information data and user preference data, and sequentially plans all recharging routes and recharging methods along the entire driving route, thereby realizing the planning of multiple recharging methods and routes for long-distance routes. At the same time, when any one of the recharging station information, the schedule information data, the vehicle data, the road information, and the user preference data undergoes a preset change, the planning device / apparatus dynamically adjusts the recharging method and recharging route planning, thereby increasing the flexibility of recharging route planning so that the planned recharging route better meets the user's needs.

[0213] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system or other device. In addition, the embodiments of the present invention are not directed to any particular programming language.

[0214] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the present invention may be practiced without these specific details. Similarly, in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of embodiments of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. The claims that follow the detailed description are hereby expressly incorporated into that detailed description, with each claim itself serving as a separate embodiment of the present invention.

[0215] Those skilled in the art will appreciate that the modules in the devices of the embodiments can be adaptively changed and installed in one or more devices different from the embodiments. The modules, units, or components in the embodiments can be combined into one module, unit, or component, and furthermore, they can be divided into multiple submodules, subunits, or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive.

[0216] It should be noted that the above embodiments illustrate rather than limit the invention, and that alternative embodiments may be devised by a person skilled in the art without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments should not be understood as limiting the order of execution unless otherwise specified.

Claims

1. A method for planning a vehicle recharging route, characterized in that: The method comprises: When a trigger condition for the energy replenishment route planning is met, calculating a first mileage required for the vehicle to reach the destination and a second mileage that the vehicle can travel; If the first mileage is greater than the second mileage, determining a first energy replenishment method for the vehicle according to the first energy data of the vehicle; the first energy replenishment method includes refueling or charging; A first energy replenishment route is generated according to the first energy replenishment method, vehicle data, road information and user preference data.

2. The vehicle recharging route planning method according to claim 1, characterized in that: Determining a first energy replenishment method for the vehicle according to the first energy data of the vehicle includes: determining information of a plurality of energy recharging stations that the vehicle can reach based on the first energy data of the vehicle; A first energy replenishment mode for the vehicle is determined based on information of the plurality of energy replenishment sites.

3. The vehicle recharging route planning method according to claim 2, characterized in that: Before determining the first energy replenishment method for the vehicle based on the information of the plurality of energy replenishment sites, the method further includes: Determining whether there is a preset preference in the user preference data; If there is a preset preference in the user preference data, determining a first energy replenishment method for the vehicle according to the preset preference; If there is no preset preference in the user preference data, a first energy replenishment method for the vehicle is determined based on information of the plurality of energy replenishment sites.

4. The vehicle recharging route planning method according to claim 2, characterized in that: The determining, based on information of the plurality of energy replenishment sites, a first energy replenishment mode for the vehicle includes: selecting, based on the first energy data and location information of the vehicle, at least one refueling station and at least one charging station from the plurality of refueling stations; An optimal energy replenishment mode for the vehicle is determined based on the distance information and energy replenishment information of the gas station and the distance information and energy replenishment information of the charging station, and the optimal energy replenishment mode is used as the first energy replenishment mode for the vehicle.

5. The vehicle recharging route planning method according to any one of claims 1 to 4, characterized in that: Calculating a first mileage required for the vehicle to reach a destination and a second mileage that the vehicle can travel, including: Taking the current position of the vehicle as a starting point and according to the current driving route, the first mileage is calculated; and the second mileage is calculated according to the current electric energy and fuel energy of the vehicle; Alternatively, taking the position of the charging station corresponding to the current charging route of the vehicle as the starting point, the first mileage is calculated according to the current driving route; based on the current charging route of the vehicle, the predicted energy data of the vehicle after charging at the charging station corresponding to the current charging route is predicted; and the second mileage is calculated based on the predicted energy data.

6. The vehicle recharging route planning method according to any one of claims 1 to 4, characterized in that: Before determining the first energy replenishment method of the vehicle according to the first energy data of the vehicle, the method further includes: Determine whether there is a preset schedule task in the schedule information data; When there is a preset schedule task in the schedule information data, determining a second energy replenishment method for the vehicle based on the charging station information at the location of the preset schedule task; A second charging route is generated according to the second charging method, vehicle data, road information and user preference data.

7. The vehicle recharging route planning method according to claim 1, characterized in that: Generating a first energy replenishment route according to the first energy replenishment method, vehicle data, road information, and user preference data, including: Generate a first recharging route based on the first recharging method, vehicle data, road information, and user preference data, combined with a preset recommendation model; The recommendation model is obtained by training an initial recommendation model based on user feedback data and execution feedback data; the initial recommendation model is integrated from several learning models.

8. The vehicle recharging route planning method according to claim 1, characterized in that: The triggering conditions for satisfying the energy replenishment route planning include: When receiving a recharging route planning instruction issued by a user, determining whether a triggering condition for recharging route planning is met; Alternatively, when any one of the charging station information, schedule information data, the vehicle data, the road information and the user preference data corresponding to the current charging route of the vehicle undergoes a preset change, it is determined that the triggering condition for charging route planning is met.

9. The vehicle recharging route planning method according to claim 8, characterized in that: The method of triggering the preset change of the energy charging station information includes: the user modifies the energy charging station corresponding to the current energy charging route in the preset module; The manner of triggering the preset change of the schedule information data includes: the user modifies the schedule information data in the preset module; The preset module is used to determine and display the task content of each schedule task in the schedule information and the charging station information on the charging route according to the schedule information and the charging route, so that the user can manage the schedule information data or the charging station information.

10. A vehicle recharging route planning device, characterized in that: The device includes: a mileage calculation module, an energy replenishment mode selection module and a route planning module; The mileage calculation module is configured to calculate a first mileage required for the vehicle to reach the destination and a second mileage that the vehicle can travel when it is determined that a trigger condition for the energy replenishment route planning is met; The energy replenishment mode selection module is configured to determine a first energy replenishment mode for the vehicle based on the first energy data of the vehicle if the first mileage is greater than the second mileage; the first energy replenishment mode includes refueling or charging; The route planning module is used to generate a first energy replenishment route according to the first energy replenishment method, vehicle data, road information and user preference data.

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