Range extended electric vehicle energy supplement control method and device and computer equipment

Abstract

The application relates to a range-extender electric vehicle energy supplement control method and device, computer equipment and a storage medium. The method comprises the following steps: in response to a user preference energy storage mode being a charging mode, acquiring current vehicle driving data of the range-extender electric vehicle, calculating estimated energy consumption of a current driving route of the range-extender electric vehicle according to the current vehicle driving data, and determining a first energy difference value according to a difference between current residual energy of the range-extender electric vehicle and the estimated energy consumption; in response to the first energy difference value being smaller than a charging mode energy difference threshold value, inputting the current residual energy, a user preferred charging station, a user preferred charging time, a user preferred charging use cost into a pre-trained energy storage site recommendation network model to obtain each to-be-recommended energy storage site and a corresponding to-be-recommended energy storage site recommendation coefficient, and controlling an energy storage operation of the range-extender electric vehicle according to the each to-be-recommended energy storage site and the corresponding recommendation coefficient. The method can improve the individualization degree.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle energy storage, in particular to a range extended electric vehicle energy supplement control method and device, computer equipment and storage medium. BACKGROUND

[0002] At present, range extended electric vehicles are more and more favored in the market. Compared with traditional vehicles, the range extended power system is matched with the high efficiency operating point of the engine, which greatly reduces the fuel consumption and emissions of the vehicle; compared with HEV (Hybrid Electric Vehicle, oil-electric hybrid vehicle) and PHEV (plug in hybrid electric vehicle, plug-in hybrid electric vehicle) hybrid vehicles, the range extended electric vehicle can reduce the range anxiety problem to the greatest extent, and realize the mileage of traditional vehicles and the driving experience of pure electric vehicles.

[0003] However, the current energy supplement method of the range extended electric vehicle has the problems of low individuality and poor convenience. SUMMARY

[0004] Therefore, it is necessary to provide a range extended electric vehicle energy supplement control method and device, computer equipment and storage medium which can improve the individuality and convenience.

[0005] In a first aspect, a range extended electric vehicle energy supplement control method is provided, the method comprising:

[0006] obtaining a user preference result of the range extended electric vehicle; the user preference result comprising a user preferred energy storage mode, a user preferred energy storage site corresponding to the user preferred energy storage mode, a user preferred energy storage time corresponding to the user preferred energy storage mode, a user preferred energy storage use fee corresponding to the user preferred energy storage mode, and a user preferred energy difference threshold corresponding to the user preferred energy storage mode; the user preferred energy storage mode comprising a charging mode; the user preferred energy storage site comprising a user preferred charging station; the user preferred energy storage time comprising a user preferred charging time; the user preferred energy storage use fee comprising a user preferred charging use fee; and the user preferred energy difference threshold comprising a charging mode energy difference threshold;

[0007] in response to the user preferred energy storage mode being the charging mode, obtaining current vehicle travel data of the range extended electric vehicle, calculating an estimated energy consumption of a current travel route of the range extended electric vehicle according to the current vehicle travel data, and determining a first energy difference value according to the difference between the current remaining energy of the range extended electric vehicle and the estimated energy consumption;

[0008] In response to the first energy difference value being less than the charging mode energy difference threshold, inputting the current residual energy, the user preferred charging station, the user preferred charging time, and the user preferred charging use fee into the pre-trained energy storage site recommendation network model to obtain each to-be-recommended energy storage site and a corresponding recommendation coefficient of the to-be-recommended energy storage site, and controlling the energy storage operation of the extended-range electric vehicle according to the recommendation coefficient of each to-be-recommended energy storage site and the corresponding recommendation coefficient of the to-be-recommended energy storage site; wherein, when the user preferred energy storage mode is the charging mode, the to-be-recommended energy storage site is a to-be-recommended charging station, and the energy storage operation is a charging operation.

[0009] In one of the embodiments, the user preference result of the extended-range electric vehicle is obtained by: obtaining user historical preference data of the extended-range electric vehicle; and analyzing the user historical preference data to obtain the user preference result.

[0010] In one of the embodiments, the user preferred energy storage mode includes a battery swap mode or a refueling mode; the user preferred energy storage station includes a user preferred refueling station or a user preferred battery swap station; the user preferred energy storage time includes a user preferred refueling time or a user preferred battery swap time; the user preferred energy storage use fee includes a user preferred refueling use fee or a user preferred battery swap use fee; and the user preferred energy difference threshold includes a refueling mode energy difference threshold or a battery swap mode energy difference threshold.

[0011] In one of the embodiments, the method further includes:

[0012] In response to the user preferred energy storage mode being the battery swap mode or the refueling mode, obtaining current vehicle travel data, calculating an estimated energy consumption according to the current vehicle travel data, and determining a second energy difference value according to a difference between a current residual energy total sum of the extended-range electric vehicle and the estimated energy consumption; wherein, the current residual energy total sum is a sum of a current residual electric energy and a current fuel energy of the extended-range electric vehicle.

[0013] In response to the second energy difference value being less than the refueling mode energy difference threshold and the user preferred energy storage mode being the refueling mode, inputting the current residual energy total sum, the user preferred refueling station, the user preferred refueling time, and the user preferred refueling use fee into the energy storage site recommendation network model to obtain each to-be-recommended energy storage site and a corresponding recommendation coefficient of the to-be-recommended energy storage site, and controlling the energy storage operation of the extended-range electric vehicle according to the recommendation coefficient of each to-be-recommended energy storage site and the corresponding recommendation coefficient of the to-be-recommended energy storage site; wherein, when the user preferred energy storage mode is the refueling mode, the to-be-recommended energy storage site is a to-be-recommended refueling station, and the energy storage operation is a refueling operation.

[0014] In response to the second energy difference value being less than the energy difference threshold of the battery swap mode and the user preference energy storage mode being the battery swap mode, the current total residual energy, the user preference battery swap station, the user preference battery swap time, and the user preference battery swap use fee are input into the energy storage site recommendation network model to obtain each to-be-recommended energy storage site and a corresponding to-be-recommended energy storage site recommendation coefficient, and the energy storage operation of the range extended electric vehicle is controlled according to the to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient; wherein, when the user preference energy storage mode is the battery swap mode, the to-be-recommended energy storage site is a to-be-recommended battery swap site, and the energy storage operation is a battery swap operation.

[0015] In one of the embodiments, the estimated energy consumption of the current driving route of the range extended electric vehicle is calculated according to the current vehicle driving data, including: inputting the current geographic position, the current driving energy consumption, and the current driving route of the range extended electric vehicle into the pre-trained energy consumption calculation network model to obtain the estimated energy consumption; wherein, the current vehicle driving data includes the current geographic position and the current driving energy consumption.

[0016] In one of the embodiments, the energy storage operation of the range extended electric vehicle is controlled according to the to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient, including: in response to the driving mode of the range extended electric vehicle being the automatic mode, a first target user preference energy storage site is determined as a first route transfer point; the first target user preference energy storage site is the to-be-recommended energy storage site corresponding to the maximum value of the to-be-recommended energy storage site recommendation coefficient; based on the path planning algorithm, a first adjusted driving route is obtained after path planning processing according to the current driving route and the first route transfer point, and the first adjusted driving route is displayed on the display screen of the range extended electric vehicle; in response to the confirmation operation of the first adjusted driving route, the automatic driving control is performed according to the first adjusted driving route.

[0017] In one of the embodiments, the energy storage operation of the range extended electric vehicle is controlled according to the to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient, including: in response to the driving mode of the range extended electric vehicle being the automatic mode, a first target user preference energy storage site is determined as a first route transfer point; the first target user preference energy storage site is the to-be-recommended energy storage site corresponding to the maximum value of the to-be-recommended energy storage site recommendation coefficient; based on the path planning algorithm, a first adjusted driving route is obtained after path planning processing according to the current driving route and the first route transfer point, and the first adjusted driving route is displayed on the display screen of the range extended electric vehicle; in response to the confirmation operation of the first adjusted driving route, the automatic driving control is performed according to the first adjusted driving route.

[0018] In one of the embodiments, the method further comprises: obtaining a preset number of historical user preference results of the target extended-range electric vehicle and corresponding historical to-be-recommended energy storage sites; the historical user preference result comprises a historical user preferred energy storage mode, a historical user preferred energy storage site corresponding to the historical user preferred energy storage mode, a historical user preferred energy storage time corresponding to the historical user preferred energy storage mode, a historical user preferred energy storage use fee corresponding to the historical user preferred energy storage mode, and a historical user preferred energy difference threshold corresponding to the historical user preferred energy storage mode; performing random division processing on each historical user preference result and the corresponding historical to-be-recommended energy storage site to generate a training sample set and a test sample set; training a preset energy storage site recommendation initial network model according to the training sample set, testing the energy storage site recommendation initial network model according to the test sample set, adjusting model parameters of the energy storage site recommendation initial network model based on indexes obtained through the training and the testing until the indexes meet preset requirements, generating an energy storage site recommendation network model, and outputting a corresponding to-be-recommended energy storage site and a recommendation coefficient of the corresponding to-be-recommended energy storage site based on the energy storage site recommendation network model.

[0019] In a second aspect, an energy storage control device for an extended-range electric vehicle is provided. The device comprises a data acquisition module, an energy consumption estimation module, and an energy storage site recommendation module.

[0020] The data acquisition module is configured to acquire a user preference result of the extended-range electric vehicle. The user preference result includes a user preferred energy storage mode, a user preferred energy storage site corresponding to the user preferred energy storage mode, a user preferred energy storage time corresponding to the user preferred energy storage mode, a user preferred energy storage use fee corresponding to the user preferred energy storage mode, and a user preferred energy difference threshold corresponding to the user preferred energy storage mode. The user preferred energy storage mode includes a charging mode. The user preferred energy storage site includes a user preferred charging station. The user preferred energy storage time includes a user preferred charging time. The user preferred energy storage use fee includes a user preferred charging use fee. The user preferred energy difference threshold includes a charging mode energy difference threshold. The energy consumption estimation module is configured to, in response to the user preferred energy storage mode being the charging mode, acquire current vehicle driving data of the extended-range electric vehicle, calculate an estimated energy consumption of a current driving route of the extended-range electric vehicle according to the current vehicle driving data, and determine a first energy difference value according to a difference between a current residual electric energy of the extended-range electric vehicle and the estimated energy consumption. The energy storage site recommendation module is configured to, in response to the first energy difference value being less than the charging mode energy difference threshold, input the current residual electric energy, the user preferred charging station, the user preferred charging time, and the user preferred charging use fee into a pre-trained energy storage site recommendation network model to obtain each to-be-recommended energy storage site and a corresponding to-be-recommended energy storage site recommendation coefficient, and control an energy storage operation of the extended-range electric vehicle according to the each to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient. When the user preferred energy storage mode is the charging mode, the to-be-recommended energy storage site is a to-be-recommended charging station, and the energy storage operation is a charging operation.

[0021] In a fourth aspect, a computer readable storage medium is provided. The computer readable storage medium has stored thereon a computer program. The computer program, when executed by a processor, implements the steps of any of the above method embodiments.

[0022] The range-extending electric vehicle energy supplement control method, device, computer equipment and storage medium described above, obtain a user preference result of the range-extending electric vehicle; the user preference result includes a user preferred energy storage mode, a user preferred energy storage site corresponding to the user preferred energy storage mode, a user preferred energy storage time corresponding to the user preferred energy storage mode, a user preferred energy storage use fee corresponding to the user preferred energy storage mode, and a user preferred energy difference threshold corresponding to the user preferred energy storage mode; the user preferred energy storage mode includes a charging mode; the user preferred energy storage site includes a user preferred charging station; the user preferred energy storage time includes a user preferred charging time; the user preferred energy storage use fee includes a user preferred charging use fee; and the user preferred energy difference threshold includes a charging mode energy difference threshold; then, in response to the user preferred energy storage mode being the charging mode, current vehicle driving data of the range-extending electric vehicle is obtained, an estimated energy consumption of a current driving route of the range-extending electric vehicle is calculated according to the current vehicle driving data, and a first energy difference value is determined according to a difference between current residual energy of the range-extending electric vehicle and the estimated energy consumption; then, in response to the first energy difference value being less than the charging mode energy difference threshold, the current residual energy, the user preferred charging station, the user preferred charging time, and the user preferred charging use fee are input into a pre-trained energy storage site recommendation network model to obtain each to-be-recommended energy storage site and a corresponding to-be-recommended energy storage site recommendation coefficient, and the energy storage operation of the range-extending electric vehicle is controlled according to the to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient; when the user preferred energy storage mode is the charging mode, the to-be-recommended energy storage site is a to-be-recommended charging station, and the energy storage operation is a charging operation, thereby improving the individuality and convenience of the energy storage scheme. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 An application environment diagram of the range-extending electric vehicle energy supplement control method in one embodiment;

[0024] Figure 2 A first flowchart of the range-extending electric vehicle energy supplement control method in one embodiment;

[0025] Figure 3 A flowchart of obtaining a user preference result of the range-extending electric vehicle in one embodiment;

[0026] Figure 4 A second flowchart of the range-extending electric vehicle energy supplement control method in one embodiment;

[0027] Figure 5 A first flowchart of controlling the energy storage operation of the range-extending electric vehicle according to each to-be-recommended energy storage site and the corresponding recommendation coefficient in one embodiment;

[0028] Figure 6A second flowchart illustrating a method for controlling the energy storage operation of the extended-range electric vehicle according to the recommended energy storage sites and the corresponding recommended coefficients in one embodiment;

[0029] Figure 7 A third flowchart illustrating a method for controlling the energy replenishment of the extended-range electric vehicle in one embodiment;

[0030] Figure 8 A block diagram illustrating the structure of a device for controlling the energy replenishment of the extended-range electric vehicle in one embodiment;

[0031] Figure 9 An internal structure diagram of a computer device in one embodiment. DETAILED DESCRIPTION

[0032] For the purpose of making the purpose, technical scheme and advantages of the present application more clear, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0033] For the purpose of making the purpose, technical scheme and advantages of the present application more clear, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0034] In order to facilitate the understanding of the present application, the present application will be described more fully below in combination with the relevant drawings. The drawings show embodiments of the present application. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive.

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used herein in the specification generally have only the meanings described herein and are not intended to limit the present application.

[0036] The energy replenishment control method for the extended-range electric vehicle provided by the present disclosure can be applied to Figure 1 In the extended-range electric vehicle 100 shown, the extended-range electric vehicle 100 can include a vehicle terminal 110. The vehicle terminal 110 includes at least one memory 20 and at least one processor 10, and the at least one memory 20 stores a computer program that, when executed by the at least one processor 10, performs a real-time tracking method for vehicle location information according to an exemplary embodiment of the present disclosure. It can be understood that the vehicle terminal 110 is not necessarily a single electronic device, but can also be any collection of devices or circuits that can individually or jointly execute the above computer program.

[0037] In the vehicle terminal 110, the processor 10 can include a central processing unit (CPU), a graphics processing unit (GPU), a programmable logic device, a special-purpose processor system, a microcontroller, or a microprocessor. By way of example, and not limitation, the processor 10 can also include an analog processor, a digital processor, a microprocessor, a multi-core processor, a processor array, or a network processor, etc.

[0038] In the vehicle terminal 110, the processor 10 can run a computer program stored in the memory 20, which can be divided into one or more modules / units (such as computer program 1, computer program 2, …), which are stored in the memory 20 and executed by the processor 10 to complete the present application. The one or more modules / units can be a series of computer program instruction segments that can complete a specific function, which are used to describe the execution process of the computer program in the terminal device. For example, the detail compensation model in the embodiments of the present disclosure can be one of the modules / units.

[0039] The memory 20 can be integrated with the processor 10, for example, arranging RAM or flash memory inside an integrated circuit microprocessor, etc. In addition, the memory can include a separate device, such as an external disk drive, a storage array, or any other storage device that can be used by a database system. The memory and the processor can be operatively coupled or can communicate with each other, for example, through I / O ports, network connections, etc., so that the processor can read the files stored in the memory.

[0040] In addition, the vehicle terminal 110 can also include a display device (such as a liquid crystal display) and a user interaction interface (such as a keyboard, a mouse, a touch input device, etc.). All components of the vehicle terminal 110 can be connected to each other via a bus and / or a network.

[0041] In one specific example, the vehicle terminal 110 can be, but is not limited to, a vehicle control unit (VCU), which is only a specific example, and in actual applications, it can be flexibly set according to user needs, which is not limited here.

[0042] In one embodiment, as shown in Figure 2 , a range-extended electric vehicle energy supplement control method is provided, which is applied to the vehicle terminal 110 of the range-extended electric vehicle 100 in Figure 1 for example, including the following steps 201 to 203.

[0043] Step 201, obtaining the user preference result of the range-extended electric vehicle.

[0044] The user preference result includes a user preferred energy storage mode, a user preferred energy storage site corresponding to the user preferred energy storage mode, a user preferred energy storage time corresponding to the user preferred energy storage mode, a user preferred energy storage use cost corresponding to the user preferred energy storage mode, and a user preferred energy difference threshold corresponding to the user preferred energy storage mode. The user preferred energy storage mode includes a charging mode. The user preferred energy storage site includes a user preferred charging station. The user preferred energy storage time includes a user preferred charging time. The user preferred energy storage use cost includes a user preferred charging use cost. The user preferred energy difference threshold includes a charging mode energy difference threshold. Specifically, the vehicle-mounted terminal 110 can obtain the user preference result of the extended-range electric vehicle.

[0045] In one embodiment, as shown in Figure 3 obtaining the user preference result of the extended-range electric vehicle includes steps 301-302.

[0046] Step 301: Obtain the user historical preference data of the extended-range electric vehicle.

[0047] Step 302: Analyze the user historical preference data to obtain the user preference result.

[0048] Specifically, the vehicle-mounted terminal 110 obtains the user historical preference data of the extended-range electric vehicle. Then, the user historical preference data is analyzed to obtain the user preference result, improving the efficiency and convenience of obtaining the user preference result.

[0049] In one specific example, analyzing the user historical preference data to obtain the user preference result includes: inputting the user historical preference data into a pre-trained user preference analysis model to obtain the user preference result. The above is only a specific example, and in actual application, the user demand is flexibly set, which is not limited here.

[0050] In this embodiment, the user historical preference data of the extended-range electric vehicle is obtained. Then, the user historical preference data is analyzed to obtain the user preference result, improving the efficiency and convenience of obtaining the user preference result.

[0051] Step 202: In response to the user preferred energy storage mode being a charging mode, obtaining the current vehicle driving data of the extended-range electric vehicle, calculating the estimated energy consumption of the current driving route of the extended-range electric vehicle according to the current vehicle driving data, and determining a first energy difference value according to the difference between the current remaining energy of the extended-range electric vehicle and the estimated energy consumption.

[0052] The user preferred energy storage mode being a charging mode indicates that the user of the extended-range electric vehicle tends to perform energy storage operation through charging operation when the vehicle needs to perform energy storage operation.

[0053] In one specific example, the current vehicle driving data of the extended-range electric vehicle can include, but is not limited to, the current driving energy consumption, the current vehicle operating state data obtained through the CAN bus module, the current vehicle diagnostic information obtained through the OBD-II interface module, the current vehicle tire pressure and the current vehicle fuel pressure collected through the pressure sensor, the engine temperature and the ambient temperature obtained through the temperature sensor, the current vehicle battery voltage, the current vehicle battery current, the current vehicle battery temperature and the current vehicle battery state obtained through the battery management system (BMS), and the current geographic location, the current driving route and the current vehicle speed information obtained through the GPS module. The above is only a specific example, and the user demand is flexibly set in actual application, which is not limited here.

[0054] Specifically, when the user preference for the energy storage mode is identified as the charging mode, the vehicle terminal 110 obtains the current vehicle driving data of the extended-range electric vehicle, calculates the estimated energy consumption of the current driving route of the extended-range electric vehicle according to the current vehicle driving data, and determines the first energy difference value according to the difference between the current remaining electric energy of the extended-range electric vehicle and the estimated energy consumption.

[0055] In one embodiment, the estimated energy consumption of the current driving route of the extended-range electric vehicle according to the current vehicle driving data includes:

[0056] The current geographic location, the current driving energy consumption and the current driving route of the extended-range electric vehicle are input into the pre-trained energy consumption calculation network model to obtain the estimated energy consumption.

[0057] The current vehicle driving data includes the current geographic location and the current driving energy consumption. Specifically, the vehicle terminal 110 inputs the current geographic location, the current driving energy consumption and the current driving route of the extended-range electric vehicle into the pre-trained energy consumption calculation network model to obtain the estimated energy consumption, thereby improving the accuracy of the estimated energy consumption.

[0058] In one specific example, the energy consumption calculation network model can use, but is not limited to, a long short-term memory network (Long Short-Term Memory, LSTM). The LSTM is a time recurrent neural network specially designed to solve the long-term dependence problem of general RNN (recurrent neural network). All RNNs have a chain form of repeated neural network modules. The above is only a specific example, and the user demand is flexibly set in actual application, which is not limited here.

[0059] In one specific example, the electric energy consumption is calculated based on the following expression:

[0060] E 电 =I×V×t

[0061] wherein E 电 is the electric energy consumption; I is the current vehicle battery current; V is the current vehicle battery voltage; and t is the time.

[0062] The fuel energy consumption is calculated based on the following expression:

[0063] E 油 = F x 1000 x t

[0064] wherein E 油 is the fuel energy consumption; F is the current vehicle fuel flow; and t is the time.

[0065] In this embodiment, the current geographic position, the current driving energy consumption and the current driving route of the extended-range electric vehicle are input into the pre-trained energy consumption calculation network model to obtain the estimated energy consumption, thereby improving the accuracy of the estimated energy consumption.

[0066] In step 203, in response to the first energy difference value being less than the charging mode energy difference threshold, the current residual electric energy, the user preferred charging station, the user preferred charging time, the user preferred charging use fee are input into the pre-trained energy storage site recommendation network model to obtain each to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient, and the energy storage operation of the extended-range electric vehicle is controlled according to the to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient.

[0067] It can be understood that when the user preferred energy storage mode is the charging mode, the to-be-recommended energy storage site is the to-be-recommended charging station, and the energy storage operation is the charging operation. Specifically, when the vehicle terminal 110 identifies that the first energy difference value is less than the charging mode energy difference threshold, it means that the electric energy needs to be supplemented at this time, so the current residual electric energy, the user preferred charging station, the user preferred charging time, the user preferred charging use fee are input into the pre-trained energy storage site recommendation network model to obtain each to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient, and the energy storage operation of the extended-range electric vehicle is controlled according to the to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient, thereby improving the individualization degree and convenience of the energy storage scheme.

[0068] In one specific example, in response to the first energy difference value being greater than or equal to the charging mode energy difference threshold, the loop processing performed in the step of obtaining the current vehicle driving data of the extended-range electric vehicle is returned to, and the above is only a specific example, and the actual application is flexibly set according to the user's needs, which is not limited here.

[0069] The above range-extending electric vehicle energy supplement control method, the user preference result of the range-extending electric vehicle is obtained; the user preference result includes a user preferred energy storage mode, a user preferred energy storage site corresponding to the user preferred energy storage mode, a user preferred energy storage time corresponding to the user preferred energy storage mode, a user preferred energy storage use fee corresponding to the user preferred energy storage mode, and a user preferred energy difference threshold value corresponding to the user preferred energy storage mode; the user preferred energy storage mode includes a charging mode; the user preferred energy storage site includes a user preferred charging station; the user preferred energy storage time includes a user preferred charging time; the user preferred energy storage use fee includes a user preferred charging use fee; and the user preferred energy difference threshold value includes a charging mode energy difference threshold value; then, in response to the user preferred energy storage mode being the charging mode, current vehicle driving data of the range-extending electric vehicle is obtained, an estimated energy consumption of a current driving route of the range-extending electric vehicle is calculated according to the current vehicle driving data, and a first energy difference value is determined according to a difference between a current residual energy of the range-extending electric vehicle and the estimated energy consumption; then, in response to the first energy difference value being less than the charging mode energy difference threshold value, the current residual energy, the user preferred charging station, the user preferred charging time, and the user preferred charging use fee are input into a pre-trained energy storage site recommendation network model to obtain each to-be-recommended energy storage site and a corresponding to-be-recommended energy storage site recommendation coefficient, and the energy storage operation of the range-extending electric vehicle is controlled according to the to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient; wherein, when the user preferred energy storage mode is the charging mode, the to-be-recommended energy storage site is a to-be-recommended charging station, and the energy storage operation is a charging operation, thereby improving the personalization and convenience of the energy storage scheme, achieving personalized design of the energy supplement strategy of the range-extending electric vehicle, and improving the service effect of vehicle energy supplement.

[0070] In one embodiment, as shown in Figure 4 the user preferred energy storage mode includes a battery replacement mode or a refueling mode; the user preferred energy storage site includes a user preferred refueling station or a user preferred battery replacement station; the user preferred energy storage time includes a user preferred refueling time or a user preferred battery replacement time; the user preferred energy storage use fee includes a user preferred refueling use fee or a user preferred battery replacement use fee; the user preferred energy difference threshold value includes a refueling mode energy difference threshold value or a battery replacement mode energy difference threshold value; and the above method further includes steps 401 to 403.

[0071] Step 401, in response to the user preferred energy storage mode being the battery replacement mode or the refueling mode, current vehicle driving data is obtained, an estimated energy consumption is calculated according to the current vehicle driving data, and a second energy difference value is determined according to a difference between a current total residual energy of the range-extending electric vehicle and the estimated energy consumption.

[0072] The current remaining energy sum is the sum of the current remaining electrical energy and the current fuel energy of the extended-range electric vehicle. Specifically, when the vehicle-mounted terminal 110 recognizes that the user's preferred energy storage mode is the battery swap mode or the refueling mode, it obtains the current vehicle driving data, calculates the estimated energy consumption based on the current vehicle driving data, and determines the second energy difference value based on the difference between the current remaining energy sum and the estimated energy consumption of the extended-range electric vehicle.

[0073] In step 402, in response to the second energy difference being less than the refueling mode energy difference threshold and the user's preferred energy storage mode being the refueling mode, the current total remaining energy, the user's preferred refueling station, the user's preferred refueling time, and the user's preferred refueling fee are input into the energy storage site recommendation network model to obtain recommendation coefficients for each to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site, and the energy storage operation of the extended-range electric vehicle is controlled according to the recommendation coefficients for each to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site.

[0074] It is understandable that when the user prefers the energy storage mode to be the refueling mode, the energy storage site to be recommended is the refueling site to be recommended, and the energy storage operation is the refueling operation.

[0075] Specifically, when the on-board terminal 110 recognizes that the second energy difference is less than the energy difference threshold of the refueling mode and the user's preferred energy storage mode is the refueling mode, it indicates that fuel needs to be replenished at this time. After inputting the current total remaining energy, the user's preferred refueling station, the user's preferred refueling time, and the user's preferred refueling usage fee into the energy storage site recommendation network model, the recommendation coefficients of each energy storage site to be recommended and the corresponding energy storage site to be recommended are obtained. The energy storage operation of the extended-range electric vehicle is controlled according to the recommendation coefficients of each energy storage site to be recommended and the corresponding energy storage site to be recommended, thereby improving the personalization and convenience of the energy storage solution.

[0076] Step 403, in response to the second energy difference being less than the energy difference threshold of the battery swap mode and the user's preferred energy storage mode being the battery swap mode, the current total remaining energy, the user's preferred battery swap station, the user's preferred battery swap time, and the user's preferred battery swap usage fee are input into the energy storage site recommendation network model to obtain the recommendation coefficients of each energy storage site to be recommended and the corresponding energy storage site to be recommended, and the energy storage operation of the extended-range electric vehicle is controlled according to the recommendation coefficients of each energy storage site to be recommended and the corresponding energy storage site to be recommended.

[0077] It can be understood that when the user prefers the energy storage mode to the battery swap mode, the energy storage site to be recommended is the battery swap site to be recommended, and the energy storage operation is the battery swap operation.

[0078] Specifically, when the on-board terminal 110 recognizes that the second energy difference is less than the energy difference threshold of the battery swap mode and the user's preferred energy storage mode is the battery swap mode, it indicates that battery swapping is required at this time. The current total remaining energy, the user's preferred battery swap station, the user's preferred battery swap time, and the user's preferred battery swap usage fee are input into the energy storage site recommendation network model to obtain the recommendation coefficients of each energy storage site to be recommended and the corresponding energy storage site to be recommended. The energy storage operation of the extended-range electric vehicle is controlled according to the recommendation coefficients of each energy storage site to be recommended and the corresponding energy storage site to be recommended.

[0079] In this embodiment, in response to the user's preferred energy storage mode being the battery replacement mode or the refueling mode, the current vehicle driving data is obtained, the estimated energy consumption is calculated based on the current vehicle driving data, and the second energy difference is determined based on the difference between the current remaining energy sum of the extended-range electric vehicle and the estimated energy consumption; the current remaining energy sum is the sum of the current remaining electric energy and the current fuel energy of the extended-range electric vehicle; then, in response to the second energy difference being less than the refueling mode energy difference threshold and the user's preferred energy storage mode being the refueling mode, the current remaining energy sum, the user's preferred refueling station, the user's preferred refueling time, and the user's preferred refueling usage fee are input into the energy storage site recommendation network model to obtain each energy storage site to be recommended and the corresponding recommendation coefficient of the energy storage site to be recommended, and the recommendation coefficient of each energy storage site to be recommended is obtained according to the energy storage site to be recommended. and the recommendation coefficient of the corresponding energy storage site to be recommended, controlling the energy storage operation of the extended-range electric vehicle; then, in response to the second energy difference being less than the energy difference threshold of the battery swap mode and the user's preferred energy storage mode being the battery swap mode, the current total remaining energy, the user's preferred battery swap station, the user's preferred battery swap time, and the user's preferred battery swap usage fee are input into the energy storage site recommendation network model to obtain the recommendation coefficients of each energy storage site to be recommended and the corresponding energy storage site to be recommended, and controlling the energy storage operation of the extended-range electric vehicle according to the recommendation coefficients of each energy storage site to be recommended and the corresponding energy storage site to be recommended; wherein, when the user's preferred energy storage mode is the battery swap mode, the energy storage site to be recommended is the battery swap site to be recommended, and the energy storage operation is the battery swap operation, which improves the personalization and convenience of the energy storage solution.

[0080] In one embodiment, Figure 5 As shown, the energy storage operation of the extended-range electric vehicle is controlled according to each energy storage site to be recommended and the recommendation coefficient of the corresponding energy storage site to be recommended, including steps 501 to 503.

[0081] Step 501 : In response to the driving mode of the extended-range electric vehicle being the automatic mode, a first target user preferred energy storage site is determined as a first route transfer point.

[0082] The first target user preferred energy storage site is the energy storage site to be recommended corresponding to the maximum value of the recommendation coefficient of the energy storage site to be recommended. Specifically, when the vehicle terminal 110 recognizes that the driving mode of the extended-range electric vehicle is the automatic mode, it determines the first target user preferred energy storage site as the first route transfer point.

[0083] Step 502 : Based on a path planning algorithm, a path planning process is performed according to the current driving route and the first route transfer point to obtain a first adjusted driving route, and the first adjusted driving route is displayed on a display screen of the extended-range electric vehicle.

[0084] Specifically, the vehicle terminal 110 performs a route planning process based on the current route and the first route transfer point based on a route planning algorithm to obtain a first adjusted route, and displays the first adjusted route on the display screen of the extended-range electric vehicle. Furthermore, the route planning algorithm may be, but is not limited to, an A-star algorithm or a Dijkstra algorithm.

[0085] Step 503: In response to the confirmation operation of the first adjusted driving route, automatic driving control is performed according to the first adjusted driving route.

[0086] Specifically, the vehicle-mounted terminal 110 identifies the confirmation operation of the first adjusted driving route and performs automatic driving control according to the first adjusted driving route, so that it can automatically drive to the first target user preferred energy storage site for energy storage operation and then drive to the end point of the current driving route, thereby improving the degree of automation and the convenience of vehicle energy replenishment.

[0087] In this embodiment, in response to the driving mode of the extended-range electric vehicle being the automatic mode, the first target user-preferred energy storage site is determined as the first route transfer point; the first target user-preferred energy storage site is the to-be-recommended energy storage site corresponding to the maximum value of the recommendation coefficient of the to-be-recommended energy storage site; then, based on the path planning algorithm, path planning processing is performed according to the current driving route and the first route transfer point to obtain a first adjusted driving route, and the first adjusted driving route is displayed on the display screen of the extended-range electric vehicle; then, in response to a confirmation operation on the first adjusted driving route, automatic driving control is performed according to the first adjusted driving route, so that the vehicle can automatically drive to the first target user-preferred energy storage site for energy storage operation and then drive to the end point of the current driving route, thereby improving the degree of automation and the convenience of vehicle energy replenishment.

[0088] In one embodiment, Figure 6 As shown, the energy storage operation of the extended-range electric vehicle is controlled according to each energy storage site to be recommended and the recommendation coefficient of the corresponding energy storage site to be recommended, and further includes steps 601 to 603.

[0089] At step 601, in response to the driving mode of the extended-range electric vehicle being the manual mode, each to-be-recommended energy storage station and a corresponding to-be-recommended energy storage station recommendation coefficient are displayed on the display screen.

[0090] The recommendation coefficient is used to represent the recommendation degree of the corresponding to-be-recommended energy storage station. Specifically, when the vehicle terminal 110 identifies that the driving mode of the extended-range electric vehicle is the manual mode, each to-be-recommended energy storage station and the corresponding to-be-recommended energy storage station recommendation coefficient are displayed on the display screen.

[0091] At step 602, in response to the screening operation of each to-be-recommended energy storage station, a second target user preferred energy storage station is determined according to the result of the screening operation, the second target user preferred energy storage station is determined as a second route transfer point, and the user preference result is updated according to the second target user preferred energy storage station.

[0092] Specifically, when the vehicle terminal 110 identifies the screening operation of each to-be-recommended energy storage station, a second target user preferred energy storage station is determined according to the result of the screening operation, the second target user preferred energy storage station is determined as a second route transfer point, and the user preference result is updated according to the second target user preferred energy storage station, so as to continuously update the user preference data, better meet the user's needs, and improve the user's vehicle use experience.

[0093] At step 603, based on a path planning algorithm, a second adjusted driving route is obtained after path planning processing according to the current driving route and the second route transfer point, and the vehicle navigation of the extended-range electric vehicle is updated according to the second adjusted driving route.

[0094] Specifically, the vehicle terminal 110 obtains a second adjusted driving route after path planning processing according to the current driving route and the second route transfer point based on a path planning algorithm, and updates the vehicle navigation of the extended-range electric vehicle according to the second adjusted driving route, so that the vehicle can be manually driven to the second target user preferred energy storage station for energy storage operation and then driven to the end point of the current driving route, improving the convenience of vehicle energy supplement.

[0095] In the embodiment, in response to the driving mode of the extended-range electric vehicle being the manual mode, each to-be-recommended energy storage station and the corresponding recommendation coefficient of the to-be-recommended energy storage station are displayed on the display screen; then, in response to a screening operation on each to-be-recommended energy storage station, the second target user preferred energy storage station is determined according to the result of the screening operation, the second target user preferred energy storage station is determined as a transfer point in the second route, and the user preference result is updated according to the second target user preferred energy storage station; then, based on the path planning algorithm, the second adjusted driving route is obtained after the path planning processing is performed according to the current driving route and the second route transfer point, and the vehicle navigation of the extended-range electric vehicle is updated according to the second adjusted driving route, so that the vehicle can be driven to the second target user preferred energy storage station for energy storage operation and then driven to the terminal point of the current driving route, thereby improving the convenience of vehicle energy supplement.

[0096] In one of the embodiments, as shown in FIG. 7, the method further includes steps 701 to 703. Figure 7 The method further includes steps 701 to 703.

[0097] In step 701, the historical user preference results of a preset number of target extended-range electric vehicles and corresponding historical to-be-recommended energy storage stations are obtained.

[0098] The historical user preference results include a historical user preferred energy storage mode, a historical user preferred energy storage station corresponding to the historical user preferred energy storage mode, a historical user preferred energy storage time corresponding to the historical user preferred energy storage mode, a historical user preferred energy storage use fee corresponding to the historical user preferred energy storage mode, and a historical user preferred energy difference threshold corresponding to the historical user preferred energy storage mode.

[0099] Specifically, the vehicle-mounted terminal 110 obtains the historical user preference results of a preset number of target extended-range electric vehicles and corresponding historical to-be-recommended energy storage stations.

[0100] In step 702, each historical user preference result and the corresponding historical to-be-recommended energy storage station are randomly divided to generate a training sample set and a test sample set.

[0101] Specifically, the vehicle-mounted terminal 110 randomly divides each historical user preference result and the corresponding historical to-be-recommended energy storage station to generate a training sample set and a test sample set.

[0102] In step 703, the preset energy storage station recommendation initial network model is trained according to the training sample set, and the energy storage station recommendation initial network model is tested according to the test sample set. The model parameters of the energy storage station recommendation initial network model are adjusted based on the indicators obtained by the training and the testing until the indicators meet the preset requirements, the energy storage station recommendation network model is generated, and the corresponding to-be-recommended energy storage station and the corresponding recommendation coefficient of the to-be-recommended energy storage station are output based on the energy storage station recommendation network model.

[0103] Specifically, the vehicle terminal 110 trains the preset energy storage site recommendation initial network model according to the training sample set, tests the energy storage site recommendation initial network model according to the test sample set, adjusts the model parameters of the energy storage site recommendation initial network model based on the indicators obtained by the training and the testing, until the indicators meet the preset requirements, generates the energy storage site recommendation network model, and outputs the corresponding to-be-recommended energy storage site and the recommendation coefficient of the corresponding to-be-recommended energy storage site based on the energy storage site recommendation network model, thereby improving the efficiency and convenience of generating the energy storage site recommendation network model. In addition, the energy storage site recommendation initial network model can be, but is not limited to, a recurrent neural network (RNN) or a long short-term memory network (LSTM).

[0104] In this embodiment, a preset number of historical user preference results of target extended-range electric vehicles and corresponding historical to-be-recommended energy storage sites are obtained. Then, each historical user preference result and the corresponding historical to-be-recommended energy storage site are randomly divided to generate a training sample set and a test sample set. Next, the preset energy storage site recommendation initial network model is trained according to the training sample set, and the energy storage site recommendation initial network model is tested according to the test sample set. The model parameters of the energy storage site recommendation initial network model are adjusted based on the indicators obtained by the training and the testing, until the indicators meet the preset requirements, the energy storage site recommendation network model is generated, and the corresponding to-be-recommended energy storage site and the recommendation coefficient of the corresponding to-be-recommended energy storage site are output based on the energy storage site recommendation network model, thereby improving the efficiency and convenience of generating the energy storage site recommendation network model.

[0105] It should be understood that, although Figures 2-7 the steps in the flowchart of Figures 2-7 may be shown in sequence according to the arrows, these steps are not necessarily executed in sequence according to the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other sequences. Moreover, at least part of the steps in

[0106] may include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of these sub-steps or stages is not necessarily sequential, but can be executed in rotation or alternation with at least part of other steps or sub-steps or stages of other steps. Figure 8 The second aspect, as shown in

[0107] The data acquisition module 810 is configured to acquire a user preference result of the extended-range electric vehicle; the user preference result comprises a user preferred energy storage mode, a user preferred energy storage site corresponding to the user preferred energy storage mode, a user preferred energy storage time corresponding to the user preferred energy storage mode, a user preferred energy storage use cost corresponding to the user preferred energy storage mode, and a user preferred energy difference threshold corresponding to the user preferred energy storage mode; the user preferred energy storage mode comprises a charging mode; the user preferred energy storage site comprises a user preferred charging station; the user preferred energy storage time comprises a user preferred charging time; the user preferred energy storage use cost comprises a user preferred charging use cost; and the user preferred energy difference threshold comprises a charging mode energy difference threshold. The energy consumption estimation module 820 is configured to, in response to the user preferred energy storage mode being the charging mode, acquire current vehicle travel data of the extended-range electric vehicle, calculate an estimated energy consumption of a current travel route of the extended-range electric vehicle according to the current vehicle travel data, and determine a first energy difference value according to a difference between a current residual electric energy of the extended-range electric vehicle and the estimated energy consumption. The energy storage site recommendation module 830 is configured to, in response to the first energy difference value being less than the charging mode energy difference threshold, input the current residual electric energy, the user preferred charging station, the user preferred charging time, and the user preferred charging use cost into a pre-trained energy storage site recommendation network model to obtain each to-be-recommended energy storage site and a corresponding to-be-recommended energy storage site recommendation coefficient, and control an energy storage operation of the extended-range electric vehicle according to the each to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient; when the user preferred energy storage mode is the charging mode, the to-be-recommended energy storage site is a to-be-recommended charging station, and the energy storage operation is a charging operation.

[0108] In one of the embodiments, the data acquisition module 810 comprises a data acquisition unit.

[0109] The data acquisition unit is configured to acquire user historical preference data of the extended-range electric vehicle; and the data acquisition unit is configured to analyze the user historical preference data to obtain the user preference result.

[0110] In one of the embodiments, the user preferred energy storage mode includes a battery swap mode or a refueling mode; the user preferred energy storage site includes a user preferred refueling station or a user preferred battery swap station; the user preferred energy storage time includes a user preferred refueling time or a user preferred battery swap time; the user preferred energy storage use fee includes a user preferred refueling use fee or a user preferred battery swap use fee; the user preferred energy difference threshold includes a refueling mode energy difference threshold or a battery swap mode energy difference threshold; the energy consumption estimation module 820 is configured to, in response to the user preferred energy storage mode being the battery swap mode or the refueling mode, acquire current vehicle driving data, calculate an estimated energy consumption according to the current vehicle driving data, and determine a second energy difference value according to a difference between a current total residual energy of the extended-range electric vehicle and the estimated energy consumption; the current total residual energy is a sum of a current residual electric energy and a current residual fuel energy of the extended-range electric vehicle; the energy storage site recommendation module 830 is configured to, in response to the second energy difference value being less than the refueling mode energy difference threshold and the user preferred energy storage mode being the refueling mode, input the current total residual energy, the user preferred refueling station, the user preferred refueling time, and the user preferred refueling use fee into an energy storage site recommendation neural network model to obtain each to-be-recommended energy storage site and a corresponding to-be-recommended energy storage site recommendation coefficient, and control an energy storage operation of the extended-range electric vehicle according to the each to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient; wherein, when the user preferred energy storage mode is the refueling mode, the to-be-recommended energy storage site is a to-be-recommended refueling station, and the energy storage operation is a refueling operation; the energy storage site recommendation module 830 is configured to, in response to the second energy difference value being less than the battery swap mode energy difference threshold and the user preferred energy storage mode being the battery swap mode, input the current total residual energy, the user preferred battery swap station, the user preferred battery swap time, and the user preferred battery swap use fee into the energy storage site recommendation neural network model to obtain each to-be-recommended energy storage site and a corresponding to-be-recommended energy storage site recommendation coefficient, and control an energy storage operation of the extended-range electric vehicle according to the each to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site recommendation coefficient; wherein, when the user preferred energy storage mode is the battery swap mode, the to-be-recommended energy storage site is a to-be-recommended battery swap station, and the energy storage operation is a battery swap operation.

[0111] In one of the embodiments, the calculating the estimated energy consumption of the current driving route of the extended-range electric vehicle according to the current vehicle driving data includes:

[0112] inputting the current geographic position, the current driving energy consumption, and the current driving route of the extended-range electric vehicle into a pre-trained energy consumption calculation neural network model to obtain the estimated energy consumption; wherein, the current vehicle driving data includes the current geographic position and the current driving energy consumption.

[0113] In one of the embodiments, the energy storage site recommendation module 830 includes an energy storage site recommendation unit.

[0114] The energy storage site recommendation unit is configured to determine a first target user preferred energy storage site as a transfer point in the first route in response to the driving mode of the extended-range electric vehicle being an automatic mode, the first target user preferred energy storage site being a to-be-recommended energy storage site corresponding to a maximum value of a recommendation coefficient of the to-be-recommended energy storage site; the energy storage site recommendation unit is configured to perform path planning processing based on a path planning algorithm according to the current driving route and the first transfer point in the first route to obtain a first adjusted driving route, and display the first adjusted driving route on a display screen of the extended-range electric vehicle; and the energy storage site recommendation unit is configured to perform automatic driving control according to the first adjusted driving route in response to a confirmation operation on the first adjusted driving route.

[0115] In one of the embodiments, the energy storage site recommendation unit is configured to display each to-be-recommended energy storage site and a corresponding recommendation coefficient of the to-be-recommended energy storage site on the display screen in response to the driving mode of the extended-range electric vehicle being a manual mode; the energy storage site recommendation unit is configured to determine a second target user preferred energy storage site according to a result of a screening operation on each to-be-recommended energy storage site, determine the second target user preferred energy storage site as a transfer point in a second route, and update the user preference result according to the second target user preferred energy storage site; and the energy storage site recommendation unit is configured to perform path planning processing based on a path planning algorithm according to the current driving route and the transfer point in the second route to obtain a second adjusted driving route, and update the vehicle navigation of the extended-range electric vehicle according to the second adjusted driving route. In one of the embodiments, the device further includes a model training module.

[0116] The model training module is configured to obtain a preset number of historical user preference results of target extended-range electric vehicles and corresponding historical to-be-recommended energy storage sites; the historical user preference result includes a historical user preferred energy storage mode, a historical user preferred energy storage site corresponding to the historical user preferred energy storage mode, a historical user preferred energy storage time corresponding to the historical user preferred energy storage mode, a historical user preferred energy storage use fee corresponding to the historical user preferred energy storage mode, and a historical user preferred energy difference threshold corresponding to the historical user preferred energy storage mode; the model training module is configured to perform random division processing on each historical user preference result and the corresponding historical to-be-recommended energy storage site to generate a training sample set and a test sample set; the model training module is configured to train a preset energy storage site recommendation initial network model according to the training sample set, test the energy storage site recommendation initial network model according to the test sample set, adjust model parameters of the energy storage site recommendation initial network model based on indexes obtained through the training and the testing until the indexes meet preset requirements, generate an energy storage site recommendation network model, and output a corresponding to-be-recommended energy storage site and a corresponding recommendation coefficient of the to-be-recommended energy storage site based on the energy storage site recommendation network model.

[0117] The specific definitions of the range-extending electric vehicle energy supplement control device can refer to the definitions of the range-extending electric vehicle energy supplement control method, which will not be repeated here. Each module in the range-extending electric vehicle energy supplement control device can be realized by software, hardware, or a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so that the processor calls and executes the operations corresponding to each of the above modules.

[0118] In one embodiment, a computer device, which can be a terminal, has an internal structure diagram as shown in Figure 9 The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The network interface of the computer device is used to communicate with external terminals through network connections. The computer program is executed by the processor to implement a range-extending electric vehicle energy supplement control method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball, or touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse, etc.

[0119] Those skilled in the art can understand that Figure 9 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0120] In a third aspect, a computer device is provided, which includes a memory and a processor. The memory stores a computer program, and the processor implements the steps of any of the above method embodiments when executing the computer program.

[0121] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program. The computer program is executed by a processor to implement the steps of any of the above method embodiments.

[0122] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, databases, or other media in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0123] The technical features of the above embodiments can be combined in any way. In order to make the description simple, not all possible combinations of the technical features in the above embodiments are described, but as long as the combinations of the technical features do not exist, they should be considered as the scope of the present application.

[0124] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, some modifications and improvements can be made, which are all within the scope of the present application. Therefore, the scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for controlling energy replenishment of an extended-range electric vehicle, the method comprising: Obtain user preference results for extended-range electric vehicles; The user preference result includes a user preferred energy storage mode, a user preferred energy storage site corresponding to the user preferred energy storage mode, a user preferred energy storage time corresponding to the user preferred energy storage mode, a user preferred energy storage usage fee corresponding to the user preferred energy storage mode, and a user preferred energy difference threshold corresponding to the user preferred energy storage mode; the user preferred energy storage mode includes a charging mode; the user preferred energy storage site includes a user preferred charging station; and the user preferred energy storage time includes a user preferred charging time. The user preferred energy storage usage fee includes the user preferred charging usage fee; the user preferred energy difference threshold includes the charging mode energy difference threshold; In response to the user preferring the energy storage mode to be the charging mode, obtaining current vehicle driving data of the extended-range electric vehicle, calculating an estimated energy consumption of a current driving route of the extended-range electric vehicle based on the current vehicle driving data, and determining a first energy difference value based on a difference between a current remaining electric energy of the extended-range electric vehicle and the estimated energy consumption; In response to the first energy difference being less than the charging mode energy difference threshold, the current remaining electric energy, the user preferred charging station, the user preferred charging time, and the user preferred charging usage fee are input into a pre-trained energy storage site recommendation network model to obtain recommendation coefficients for each energy storage site to be recommended and the corresponding energy storage site to be recommended, and the energy storage operation of the extended-range electric vehicle is controlled according to the recommendation coefficients for each energy storage site to be recommended and the corresponding energy storage site to be recommended; wherein, when the user preferred energy storage mode is the charging mode, the energy storage site to be recommended is the charging site to be recommended, and the energy storage operation is a charging operation.

2. The method according to claim 1, characterized in that The obtaining of user preference results for the extended-range electric vehicle includes: Obtaining historical user preference data of the extended-range electric vehicle; The user historical preference data is analyzed to obtain the user preference result.

3. The method according to claim 1, characterized in that The user preferred energy storage mode also includes a battery swap mode or a refueling mode; the user preferred energy storage site includes a user preferred refueling station or a user preferred battery swap station; the user preferred energy storage time includes a user preferred refueling time or a user preferred battery swap time; The user preferred energy storage usage fee includes the user preferred refueling usage fee or the user preferred battery replacement usage fee; The user preferred energy difference threshold includes a refueling mode energy difference threshold or a battery replacement mode energy difference threshold; The method further comprises: In response to the user's preferred energy storage mode being the battery swap mode or the refueling mode, obtaining current vehicle driving data of the extended-range electric vehicle, calculating an estimated energy consumption based on the current vehicle driving data, and determining a second energy difference value based on a difference between a current total remaining energy of the extended-range electric vehicle and the estimated energy consumption; the current total remaining energy being the sum of the current remaining electrical energy of the extended-range electric vehicle and the current fuel energy; In response to the second energy difference being less than the refueling mode energy difference threshold and the user-preferred energy storage mode being the refueling mode, the current remaining energy sum, the user-preferred refueling station, the user-preferred refueling time, and the user-preferred refueling usage fee are input into the energy storage site recommendation network model to obtain recommendation coefficients for each to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site, and the energy storage operation of the extended-range electric vehicle is controlled according to the recommendation coefficients for each to-be-recommended energy storage site and the corresponding to-be-recommended energy storage site; wherein, when the user-preferred energy storage mode is the refueling mode, the to-be-recommended energy storage site is a to-be-recommended refueling site, and the energy storage operation is a refueling operation; In response to the second energy difference being less than the battery exchange mode energy difference threshold and the user preferred energy storage mode being the battery exchange mode, the current total remaining energy, the user preferred battery exchange station, the user preferred battery exchange time, and the user preferred battery exchange usage fee are input into the energy storage site recommendation network model to obtain the recommendation coefficients of each energy storage site to be recommended and the corresponding energy storage site to be recommended, and the energy storage operation of the extended-range electric vehicle is controlled according to the recommendation coefficients of each energy storage site to be recommended and the corresponding energy storage site to be recommended; wherein, when the user preferred energy storage mode is the battery exchange mode, the energy storage site to be recommended is the battery exchange site to be recommended, and the energy storage operation is a battery exchange operation.

4. The method according to claim 1 or 3, characterized in that The calculating the estimated energy consumption of the current driving route of the extended-range electric vehicle based on the current vehicle driving data includes: The current geographic location, current driving energy consumption and current driving route of the extended-range electric vehicle are input into a pre-trained energy consumption calculation network model to obtain the estimated energy consumption; wherein the current vehicle driving data includes the current geographic location and the current driving energy consumption.

5. The method according to claim 1 or 3, characterized in that Controlling the energy storage operation of the extended-range electric vehicle according to each of the energy storage sites to be recommended and the recommendation coefficient of the corresponding energy storage site to be recommended includes: In response to the driving mode of the extended-range electric vehicle being the automatic mode, determining a first target user preferred energy storage site as a first route transfer point; the first target user preferred energy storage site being the energy storage site to be recommended corresponding to the maximum value of the recommendation coefficient of the energy storage site to be recommended; Based on a path planning algorithm, performing path planning processing according to the current driving route and the first route transfer point to obtain a first adjusted driving route, and displaying the first adjusted driving route on a display screen of the extended-range electric vehicle; In response to a confirmation operation of the first adjusted driving route, automatic driving control is performed according to the first adjusted driving route.

6. The method according to claim 5, characterized in that The method further includes controlling the energy storage operation of the extended-range electric vehicle according to each of the energy storage sites to be recommended and the recommendation coefficient of the corresponding energy storage site to be recommended: In response to the driving mode of the extended-range electric vehicle being a manual mode, displaying each of the energy storage sites to be recommended and a corresponding recommendation coefficient of the energy storage site to be recommended on the display screen; In response to a screening operation on each of the energy storage sites to be recommended, determining a second target user preferred energy storage site according to a result of the screening operation, determining the second target user preferred energy storage site as a second route transfer point, and updating the user preference result according to the second target user preferred energy storage site; Based on a path planning algorithm, a second adjusted driving route is obtained after path planning processing is performed according to the current driving route and the second route transfer point, and the vehicle navigation of the extended-range electric vehicle is updated according to the second adjusted driving route.

7. The method according to claim 1, characterized in that The method further comprises: Obtaining historical user preference results and corresponding historical energy storage sites to be recommended for a preset number of target extended-range electric vehicles; the historical user preference results include a historical user preferred energy storage mode, a historical user preferred energy storage site corresponding to the historical user preferred energy storage mode, a historical user preferred energy storage time corresponding to the historical user preferred energy storage mode, a historical user preferred energy storage usage fee corresponding to the historical user preferred energy storage mode, and a historical user preferred energy difference threshold corresponding to the historical user preferred energy storage mode; Randomly dividing each of the historical user preference results and the corresponding historical energy storage sites to be recommended to generate a training sample set and a test sample set; The preset energy storage site recommendation initial network model is trained according to the training sample set, and the energy storage site recommendation initial network model is tested according to the test sample set. The model parameters of the energy storage site recommendation initial network model are adjusted based on the indicators obtained from the training and testing until the indicators meet the preset requirements, and the energy storage site recommendation network model is generated to output the corresponding energy storage site to be recommended and the corresponding recommendation coefficient of the energy storage site to be recommended based on the energy storage site recommendation network model.

8. An energy replenishment control device for an extended-range electric vehicle, characterized in that: The device comprises: A data acquisition module is used to obtain user preference results for an extended-range electric vehicle; the user preference results include a user preferred energy storage mode, a user preferred energy storage site corresponding to the user preferred energy storage mode, a user preferred energy storage time corresponding to the user preferred energy storage mode, a user preferred energy storage usage fee corresponding to the user preferred energy storage mode, and a user preferred energy difference threshold corresponding to the user preferred energy storage mode; the user preferred energy storage mode includes a charging mode; the user preferred energy storage site includes a user preferred charging station; the user preferred energy storage time includes a user preferred charging time; the user preferred energy storage usage fee includes a user preferred charging usage fee; and the user preferred energy difference threshold includes a charging mode energy difference threshold; an energy consumption estimating module, configured to, in response to the user preferring the energy storage mode to be the charging mode, obtain current vehicle driving data of the extended-range electric vehicle, calculate an estimated energy consumption of a current driving route of the extended-range electric vehicle based on the current vehicle driving data, and determine a first energy difference value based on a difference between a current remaining electric energy of the extended-range electric vehicle and the estimated energy consumption; An energy storage site recommendation module is used to, in response to the first energy difference value being less than the charging mode energy difference threshold, input the current remaining energy, the user preferred charging station, the user preferred charging time, and the user preferred charging usage fee into a pre-trained energy storage site recommendation network model to obtain the recommendation coefficients of each energy storage site to be recommended and the corresponding energy storage site to be recommended, and control the energy storage operation of the extended-range electric vehicle according to the recommendation coefficients of each energy storage site to be recommended and the corresponding energy storage site to be recommended; wherein, when the user preferred energy storage mode is the charging mode, the energy storage site to be recommended is the charging site to be recommended, and the energy storage operation is the charging operation.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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

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