Vehicle control method and device and storage medium

Abstract

The invention relates to the technical field of new energy vehicles, and discloses a vehicle control method and device and a storage medium. The method comprises the steps of predicting a charging probability of a target vehicle according to travel information and historical charging information of the target vehicle in a driving process of the target vehicle; according to the size relation between the charging probability and at least one charging probability threshold value, the operation mode of a range extender of the target vehicle is controlled, and a driving path covering a charging station is planned for the target vehicle. By adopting the method, personalized and efficient vehicle energy and navigation planning strategies can be provided for users, the vehicle energy efficiency is improved, and the user experience is optimized.

Description

Technical Field

[0001] This application relates to the technical field of new energy vehicles, and particularly to a vehicle control method, device, and storage medium. Background Art

[0002] With the rapid development of new energy vehicles, range-extended electric vehicles have received more and more users' favor due to their flexible energy replenishment methods. These electric vehicles are mainly driven by batteries, reducing fuel consumption to achieve environmental protection and energy conservation. Since the charging cost is relatively low, they can also save the vehicle use cost compared with fuel vehicles. The range extender installed on the electric vehicle generates electricity by burning fuel to supply power for vehicle driving and battery charging. For electric vehicles, it is a problem to be solved currently to reasonably plan the vehicle's energy usage strategy and navigation strategy during driving to improve vehicle energy efficiency and optimize the user experience. Summary of the Invention

[0003] In view of this, this application aims to propose a vehicle control method, device, and storage medium, aiming to provide personalized and efficient vehicle energy and navigation planning strategies for users, improve vehicle energy efficiency, and optimize the user experience.

[0004] To achieve the above object, the technical solution of this application is as follows:

[0005] The first aspect of the embodiment of this application provides a vehicle control method, and the method includes:

[0006] During the driving of the target vehicle, predict the charging probability of the target vehicle according to the travel information and historical charging information of the target vehicle;

[0007] According to the magnitude relationship between the charging probability and at least one charging probability threshold, control the operating mode of the range extender of the target vehicle, and plan a driving path covering the charging station for the target vehicle.

[0008] Optionally, according to the magnitude relationship between the charging probability and at least one charging probability threshold, control the operating mode of the range extender of the target vehicle, and plan a driving path covering the charging station for the target vehicle, including:

[0009] When the distance between the departure place and the destination of the target vehicle is less than the distance threshold, based on the magnitude relationship between the charging probability and the first charging probability threshold, control the operating mode of the range extender of the target vehicle, and plan the charging station at the destination as the charging station of the target vehicle;

[0010] When the distance between the departure location and the destination of the target vehicle is greater than or equal to the distance threshold, based on the magnitude relationship between the charging probability and multiple charging probability thresholds, control the operating mode of the range extender of the target vehicle, and plan a route for the target vehicle to pass through charging stations. The multiple charging probability thresholds at least include: a charging probability threshold less than the first charging probability threshold.

[0011] Optionally, when the distance between the departure location and the destination of the target vehicle is less than the distance threshold, based on the magnitude relationship between the charging probability and the first charging probability threshold, control the operating mode of the range extender of the target vehicle, including:

[0012] When the charging probability is greater than the first charging probability threshold, control the range extender to turn off when the remaining power is greater than the first remaining power threshold, and control the range extender to start when the remaining power is less than the first remaining power threshold until the remaining power is greater than the first remaining power threshold;

[0013] When the charging probability is less than or equal to the first charging probability threshold, control the range extender to turn off when the remaining power is greater than the second remaining power threshold, and control the operating mode of the range extender when the remaining power is less than or equal to the second remaining power threshold according to the magnitude relationship between the vehicle speed of the target vehicle and the vehicle speed threshold and the magnitude relationship between the remaining power and multiple remaining power thresholds. The multiple remaining power thresholds at least include: the first remaining power threshold and the second remaining power threshold.

[0014] Optionally, when the distance between the departure location and the destination of the target vehicle is greater than or equal to the distance threshold, based on the magnitude relationship between the charging probability and multiple charging probability thresholds, control the operating mode of the range extender of the target vehicle, and plan a route for the target vehicle to pass through charging stations, including:

[0015] When the charging probability is greater than the first charging probability threshold, based on the magnitude relationship between the remaining power and the third remaining power threshold, control the operating mode of the range extender of the target vehicle, and plan a route for the target vehicle to pass through charging stations with a first density of distribution;

[0016] When the charging probability is between the first charging probability threshold and the second charging probability threshold, based on the magnitude relationship between the remaining power and multiple remaining power thresholds, control the operating mode of the range extender of the target vehicle, and plan a route for the target vehicle to pass through charging stations with a second density of distribution. The multiple remaining power thresholds at least include: a fourth remaining power threshold greater than the third remaining power threshold;

[0017] When the charging probability is less than the second charging probability threshold, based on the magnitude relationship between the remaining power and the fifth remaining power threshold, control the operating mode of the range extender of the target vehicle, and plan a path with a third density of distribution of charging stations along the route for the target vehicle, where the fifth remaining power threshold is greater than the fourth remaining power threshold and the third remaining power threshold;

[0018] The third density is less than the first density, and the first density is less than the second density.

[0019] Optionally, when the charging probability is less than the second charging probability threshold, based on the magnitude relationship between the remaining power and the fifth remaining power threshold, controlling the operating mode of the range extender of the target vehicle includes:

[0020] When the charging probability is less than the second charging probability threshold, control the range extender to start until the remaining power is greater than the fifth remaining power threshold, and control the consumption of battery power according to the acceleration demand of the target vehicle.

[0021] Optionally, when the charging probability is between the first charging probability threshold and the second charging probability threshold, based on the magnitude relationship between the remaining power and multiple remaining power thresholds, controlling the operating mode of the range extender of the target vehicle includes:

[0022] When the charging probability is between the first charging probability threshold and the second charging probability threshold, control the range extender to turn off when the remaining power is greater than the fourth remaining power threshold, and control the operating mode of the range extender when the remaining power is less than or equal to the fourth remaining power threshold according to the magnitude relationship between the vehicle speed of the target vehicle and the vehicle speed threshold and the magnitude relationship between the remaining power and multiple remaining power thresholds. The multiple remaining power thresholds at least include: the third remaining power threshold and the fourth remaining power threshold.

[0023] Optionally, when the charging probability is greater than the first charging probability threshold, based on the magnitude relationship between the remaining power and the third remaining power threshold, controlling the operating mode of the range extender of the target vehicle includes:

[0024] When the charging probability is greater than the first charging probability threshold, control the range extender to turn off when the remaining power is greater than the third remaining power threshold, and control the range extender to start when the remaining power is less than the third remaining power threshold until the remaining power is greater than the third remaining power threshold.

[0025] Optionally, predicting the charging probability of the target vehicle according to the trip information and historical charging information of the target vehicle includes:

[0026] Obtaining the current trip information of the target vehicle, including: destination, estimated destination SOC, estimated arrival time, current date, and number of times charged this week; and obtaining the historical charging information of the target vehicle, including: historical charging SOC, historical charging time, historical charging location, usage duration, total number of charges, and number of charges per week;

[0027] According to the historical charging information, statistically analyzing the probability distribution information and corresponding weights of the target vehicle in multiple dimensions; the probability distribution information in the multiple dimensions includes: SOC probability distribution, time period probability distribution, location probability distribution, and calculating the current remaining charging probability;

[0028] Based on the current trip information of the target vehicle and the probability distribution information in the multiple dimensions, determining the target probability of each dimension;

[0029] Predicting the charging probability of the target vehicle based on the target probability of each dimension and the corresponding weight.

[0030] According to the second aspect of the embodiments of the present application, there is provided a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps in the method provided in the first aspect of the embodiments of the present application are implemented.

[0031] According to the third aspect of the embodiments of the present application, there is provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the steps in the method provided in the first aspect of the embodiments of the present application are implemented.

[0032] By using the vehicle control method provided in the present application, during the driving process of the target vehicle, according to the trip information of the vehicle and the historical charging information of the user, the current charging probability is predicted in real time. Comparing the current charging probability with at least one charging probability threshold, thereby determining the operating mode and navigation strategy of the range extender of the target vehicle during the driving process. Since the charging probability is predicted based on the user's driving habits, when planning the operating mode and navigation strategy of the range extender, the user's personalized driving habits are fully considered. Therefore, by adopting this solution, it is possible to save fuel energy consumption, improve the overall vehicle energy efficiency, and reasonably plan the driving route covering charging stations along the way for the user to match the user's personalized needs and improve the user's driving experience. Description of the Drawings

[0033] To more clearly illustrate the technical solutions of the embodiments of the present application, the accompanying drawings required for the description of the embodiments of the present application will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other accompanying drawings can be obtained based on these drawings without creative efforts.

[0034] Figure 1 is a flowchart of a vehicle control method proposed in an embodiment of the present application;

[0035] Figure 2 is a schematic diagram of controlling the operation mode of a range extender in a weekday commuting scenario in an embodiment of the present application;

[0036] Figure 3 is a schematic diagram of controlling the operation mode of a range extender in a long-distance vehicle use scenario on holidays in an embodiment of the present application;

[0037] Figure 4 is a schematic diagram of a vehicle control device proposed in an embodiment of the present application;

[0038] Figure 5 is a schematic diagram of an electronic device proposed in an embodiment of the present application. Detailed implementation manners

[0039] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts fall within the scope of protection of the present application.

[0040] It should be understood that the "one embodiment" or "an embodiment" mentioned throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of the present application. Therefore, the "in one embodiment" or "in an embodiment" that appears throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0041] In various embodiments of the present application, it should be understood that the sequence numbers of the following processes do not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0042] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects detailed in the present application.

[0043] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other.

[0044] The current energy planning strategy for electric vehicles mainly plans the operation mode of the range extender and the navigation strategy based on vehicle-related factors such as the vehicle driving mileage and the remaining battery power. For example, simply determining whether to turn on the range extender based on the current remaining battery power of the vehicle and a fixed threshold, or temporarily searching for nearby charging stations based on the current remaining battery power and the remaining driving mileage, results in low energy efficiency, detouring during navigation, etc., causing a poor user experience.

[0045] The present application obtains the status information of the target vehicle and the historical charging behavior data of the user in real time during driving, and predicts the charging probability of the user in real time. Based on the prediction result of the charging probability, a personalized energy usage strategy and navigation strategy are provided for the user, and the operation mode of the range extender of the target vehicle during the journey is controlled and the route is reasonably planned to cover the location of the charging stations on the way.

[0046] The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0047] Figure 1 is a flowchart of a vehicle control method proposed in an embodiment of the present application. As Figure 1 shown, the method includes:

[0048] S1: During the driving of the target vehicle, predict the charging probability of the target vehicle according to the travel information and historical charging information of the target vehicle;

[0049] S2: Control the operation mode of the range extender of the target vehicle according to the magnitude relationship between the charging probability and at least one charging probability threshold, and plan a driving path covering the charging station for the target vehicle.

[0050] The charging behavior of users is personalized. Different users' driving habits (e.g., common commuting routes), charging habits (e.g., the SOC (State of Charge) of the vehicle during charging, charging time periods, common charging locations), etc. will all affect the charging probability of users. For example, some users like to charge the vehicle when there is still a relatively large amount of battery remaining, while some users are used to charging when the remaining battery power is relatively low.

[0051] In the embodiments of the present application, based on the personalized charging behavior of users, combined with factors such as the navigation route and battery information of the target vehicle, a comprehensive analysis is carried out, so as to fully consider the charging habits of users and the current vehicle state when predicting the charging probability, and improve the accuracy of charging probability prediction. Furthermore, the predicted charging probability is compared with one or more preset charging probability thresholds, and based on the comparison result, the operation mode of the range extender during the vehicle driving process and the navigation route are reasonably planned to ensure energy consumption savings while conforming to the users' charging habits, and improve the overall vehicle energy efficiency and user experience.

[0052] As an implementation manner of the present application, according to the magnitude relationship between the charging probability and at least one charging probability threshold, the operation mode of the range extender of the target vehicle is controlled, and a driving path covering the charging station is planned for the target vehicle, including:

[0053] When the distance between the departure place and the destination of the target vehicle is less than the distance threshold, based on the magnitude relationship between the charging probability and the first charging probability threshold, the operation mode of the range extender of the target vehicle is controlled, and the charging station located at the destination is planned as the charging station of the target vehicle;

[0054] When the distance between the departure place and the destination of the target vehicle is greater than or equal to the distance threshold, based on the magnitude relationship between the charging probability and multiple charging probability thresholds, the operation mode of the range extender of the target vehicle is controlled, and a path passing through the charging station is planned for the target vehicle, and the multiple charging probability thresholds at least include: a charging probability threshold less than the first charging probability threshold.

[0055] In the case of a relatively high charging probability, it indicates that the user is very likely to charge. Therefore, the battery power is preferentially used to save energy consumption, and the charging station near the destination is planned. For example, in the short-distance commuting scenario of users going to and from work, the battery electric energy is preferentially consumed, and the charging location at the destination (residence) is planned for charging. In the case of a relatively low charging probability, it indicates that the user is almost unlikely to charge this time. Therefore, it is necessary to preferentially use the range extender to generate electricity and force the battery to maintain power, ensuring that the battery power remains at a relatively high state. For example, when users go on a long-distance self-driving tour to remote areas, it is necessary to forcibly retain a relatively high battery power and cover charging stations intensively during the journey for guarantee.

[0056] In this embodiment, different control strategies are adopted for the charging behavior differences of users in short-distance driving scenarios and long-distance driving scenarios, so that the operation of the range extender and navigation planning are more in line with the driving scenarios. In the embodiment of the present application, the short-distance driving scenario is determined based on a distance threshold. If the trip length is greater than or equal to the distance threshold, it is determined as a long-distance driving scenario. For example, when a user drives to another place for a self-driving tour during a festival, it belongs to a long-distance driving scenario. If the trip length is less than the distance threshold, it is determined as a short-distance driving scenario. For example, a user's daily commute to and from work belongs to a short-distance driving scenario. Specifically, for the short-distance driving scenario, according to the magnitude relationship between the predicted charging probability and the first charging probability threshold, the operation mode of the range extender is controlled, and a charging station is planned for the user near the destination. For the long-distance driving scenario, a dynamic power retention strategy is adopted. Based on the magnitude relationship between the predicted charging probability and multiple charging probability thresholds, the operation mode of the range extender is determined, and a navigation route covering charging stations along the way is also planned for the user according to the magnitude of the charging probability to ensure the normal driving of the vehicle. Among them, the multiple charging probability thresholds include the first charging probability threshold and at least one other charging probability threshold smaller than the first charging probability threshold.

[0057] As an implementation manner of the present application, when the distance between the departure place and the destination of the target vehicle is less than the distance threshold, based on the magnitude relationship between the charging probability and the first charging probability threshold, controlling the operation mode of the range extender of the target vehicle includes:

[0058] When the charging probability is greater than the first charging probability threshold, controlling the range extender to turn off when the remaining power is greater than the first remaining power threshold, and controlling the range extender to start when the remaining power is less than the first remaining power threshold until the remaining power is greater than the first remaining power threshold;

[0059] When the charging probability is less than or equal to the first charging probability threshold, controlling the range extender to turn off when the remaining power is greater than the second remaining power threshold, and setting the operation mode of the range extender when the remaining power is less than or equal to the second remaining power threshold according to the magnitude relationship between the vehicle speed of the target vehicle and the vehicle speed threshold and the magnitude relationship between the remaining power and multiple remaining power thresholds. The multiple remaining power thresholds at least include: the first remaining power threshold and the second remaining power threshold.

[0060] In one embodiment, based on the relationship between the charging probability and the first charging probability threshold, the operation mode of the range extender in the short-distance vehicle use scenario is controlled. Optionally, the first charging probability threshold is set to 70%. For example, in the short-distance vehicle use scenario, the charging probability is compared with the first charging probability threshold. When the charging threshold is greater than the first charging threshold, the battery power is preferentially used to save energy consumption. When the battery SOC drops to less than the first remaining power threshold, the range extender is turned on to generate electricity for low-power protection to ensure that the battery power during driving is not lower than the first remaining power threshold. Optionally, in the short-distance vehicle use scenario, the first remaining power threshold is set to 15% of the battery capacity.

[0061] When the charging threshold is less than or equal to the first charging threshold, the battery SOC of the target vehicle is compared with the first remaining power threshold and the second remaining power threshold. When the battery SOC is greater than the second remaining power threshold, the range extender is turned off, and the battery power is preferentially used to save energy consumption; when the battery SOC is less than the second remaining power threshold, the real-time vehicle speed of the vehicle is monitored, and according to the speed of the vehicle and the relationship between the battery SOC and the first remaining power threshold, the operation mode of the range extender is dynamically controlled to ensure the power performance of the vehicle. Optionally, in the short-distance vehicle use scenario, the second remaining power threshold is set to 25% of the battery capacity.

[0062] Specifically, when the battery SOC is less than the second remaining power threshold, the real-time vehicle speed of the vehicle is obtained. If the real-time vehicle speed is greater than or equal to the speed threshold (for example, 60 km / h on the highway), it is determined that the current target vehicle is driving at a high speed. When the vehicle is driving at a high speed and the battery SOC is between the first remaining power threshold and the second remaining power threshold, the range extender is controlled to start to ensure the power performance of the vehicle; if the real-time vehicle speed is less than the speed threshold, the range extender is turned off. In addition, when the battery SOC is less than the first remaining power threshold, low-power protection is executed, the range extender is turned on, and the battery SOC during driving is maintained not to be lower than the first remaining power threshold.

[0063] Optionally, according to the operation mode of the range extender and the driving route planned by the navigation, a first prompt message is generated and the user is prompted through the cockpit to improve the user experience. For example, in the short-distance vehicle use scenario, a fixed route is planned for the user, and the cockpit prompts: "This trip gives priority to using electricity, and the estimated remaining power upon arrival is: 15%", and after arriving at the destination, the cockpit prompts: "Have arrived at the destination, the current remaining power is 16%, it is recommended to use the common charging station A for charging".

[0064] As an implementation manner of the present application, when the distance between the departure place and the destination of the target vehicle is greater than or equal to the distance threshold, based on the magnitude relationship between the charging probability and multiple charging probability thresholds, control the operation mode of the range extender of the target vehicle, and plan a path for the target vehicle to pass through charging stations, including:

[0065] When the charging probability is greater than the first charging probability threshold, based on the magnitude relationship between the remaining power and the third remaining power threshold, control the operation mode of the range extender of the target vehicle, and plan a path for the target vehicle to pass through charging stations with a first density of distribution;

[0066] When the charging probability is between the first charging probability threshold and the second charging probability threshold, based on the magnitude relationship between the remaining power and multiple remaining power thresholds, control the operation mode of the range extender of the target vehicle, and plan a path for the target vehicle to pass through charging stations with a second density of distribution, the multiple remaining power thresholds at least include: a fourth remaining power threshold greater than the third remaining power threshold;

[0067] When the charging probability is less than the second charging probability threshold, based on the magnitude relationship between the remaining power and the fifth remaining power threshold, control the operation mode of the range extender of the target vehicle, and plan a path for the target vehicle to pass through charging stations with a third density of distribution, the fifth remaining power threshold being greater than the fourth remaining power threshold and the third remaining power threshold;

[0068] The third density is less than the first density, and the first density is less than the second density.

[0069] In one embodiment, based on the magnitude relationship between the charging probability and the first charging probability threshold, control the operation mode of the range extender in the long-distance vehicle use scenario. Specifically, in the long-distance vehicle use scenario, compare the charging probability with the first charging probability threshold. When the charging threshold is greater than the first charging threshold, compare the battery SOC with the third remaining power threshold, control the operation mode of the range extender according to the comparison result, and cover charging stations along the way with the first density to improve the reliability of the journey and enhance the ability to cope with various road conditions (such as: uphill, congestion, headwind, etc.) during the journey. Optionally, set the first density to 100 km. That is, when navigating and planning the driving route, at least 1 charging station is covered every 100 km.

[0070] Optionally, according to the operating mode of the range extender and the driving route planned by the navigation, a second prompt message is generated and the user is prompted through the cockpit to enhance the user experience. For example, in the scenario of long-distance vehicle use, the route with the lowest energy consumption is planned for the user and charging stations along the route are covered at a density of 100 km, and the cockpit prompts: "You can use electricity with confidence for this trip, and the charging stations along the route have been covered."

[0071] In the case where the charging probability is less than the first charging probability threshold, the charging probability is compared with the second charging probability threshold. Optionally, the second charging probability threshold is set to 30%. In the case where the charging probability is between the first charging probability threshold and the second charging probability threshold, based on the comparison results of the battery SOC with the third remaining power threshold and the fourth remaining power threshold, the operating mode of the range extender is dynamically controlled, and charging stations are covered in the navigation path at the second density. In one embodiment, the second density is set to 200 km. That is, when planning the driving route of the navigation, at least 1 charging station is covered every 200 km.

[0072] Optionally, according to the operating mode of the range extender and the driving route planned by the navigation, a third prompt message is generated and the user is prompted through the cockpit to enhance the user experience. For example, in the scenario of long-distance vehicle use, during the driving process, charging stations along the route are covered at a basic density of 200 km, and according to the dynamic change of the battery SOC during the driving process, charging stations are dynamically inserted into the remaining route, and the cockpit prompts: "The nearest charging station B is 2 km away, it is recommended to recharge to save fuel."

[0073] In the case where the charging probability threshold is less than the second charging threshold, the battery SOC is compared with the fifth remaining power threshold, and the operating mode of the range extender is controlled according to the comparison result. In the scenario of long-distance vehicle use, if the charging probability is less than the second charging threshold, it is determined that the charging probability is extremely low. In this case, the battery power needs to be maintained in a relatively high range to cope with different road conditions that may occur on the way. Optionally, the fifth remaining power threshold is set to 40%. In addition, it is also necessary to cover charging stations more densely in the navigation path to meet the possible emergency charging needs and reduce the user's driving anxiety. Optionally, the third density is set to 50 km, that is, when planning the driving route of the navigation, at least 1 charging station is covered every 50 km.

[0074] Optionally, according to the operating mode of the range extender and the driving route planned by the navigation, a fourth prompt message is generated and the user is prompted through the cockpit to enhance the user experience. For example, in the scenario of long-distance vehicle use, during the driving process, charging stations along the route are compulsorily covered at a density of 50 km, and when approaching each charging station along the route, the cockpit prompts: "The nearest charging station C is 2 km away, it is recommended to recharge to save fuel."

[0075] As an implementation manner of the present application, when the charging probability is between the first charging probability threshold and the second charging probability threshold, based on the magnitude relationship between the remaining power and multiple remaining power thresholds, controlling the operation mode of the range extender of the target vehicle includes:

[0076] When the charging probability is between the first charging probability threshold and the second charging probability threshold, controlling the range extender to turn off when the remaining power is greater than the fourth remaining power threshold, and, according to the magnitude relationship between the vehicle speed of the target vehicle and the vehicle speed threshold and the magnitude relationship between the remaining power and multiple remaining power thresholds, controlling the operation mode of the range extender when the remaining power is less than or equal to the fourth remaining power threshold, the multiple remaining power thresholds at least including: the third remaining power threshold and the fourth remaining power threshold.

[0077] In the above embodiment, in the long-distance vehicle use scenario, if the charging probability is between the second charging probability threshold and the first charging probability threshold, compare the battery SOC with the third remaining power threshold (for example, 20%) and the fourth remaining power threshold (for example, 30%). Specifically, when the battery SOC is greater than the fourth remaining power threshold, turn off the range extender and preferentially use the battery power to save energy consumption; when the battery SOC is less than the fourth remaining power threshold, monitor the real-time vehicle speed of the vehicle, and dynamically control the operation mode of the range extender according to the speed of the vehicle and the magnitude relationship between the battery SOC and the third remaining power threshold to ensure the power performance of the vehicle.

[0078] As an implementation manner of the present application, when the charging probability is greater than the first charging probability threshold, based on the magnitude relationship between the remaining power and the third remaining power threshold, controlling the operation mode of the range extender of the target vehicle includes:

[0079] When the charging probability is greater than the first charging probability threshold, controlling the range extender to turn off when the remaining power is greater than the third remaining power threshold, and, controlling the range extender to start when the remaining power is less than the third remaining power threshold until the remaining power is greater than the third remaining power threshold.

[0080] In the above embodiments, when the battery SOC is less than the fourth remaining power threshold, the battery SOC is compared with the third remaining power threshold. When the battery SOC is greater than or equal to the third remaining power threshold, the real-time vehicle speed is monitored, and the operation of the range extender is dynamically controlled according to the speed. Specifically, if the real-time vehicle speed reaches the speed threshold (for example, 60 km / h on the highway), it is determined that the current vehicle is driving at a high speed. When the vehicle is driving at a high speed and the battery SOC is between the third remaining power threshold and the fourth remaining power threshold, the range extender is controlled to start to ensure the power performance of the vehicle. If the real-time vehicle speed is less than the speed threshold, the range extender is turned off and the battery power is used.

[0081] In addition, when the battery SOC is less than the third remaining power threshold, low-power protection is performed, the range extender is turned on and the battery power is maintained not to be lower than the third remaining power threshold.

[0082] As an implementation manner of the present application, when the charging probability is less than the second charging probability threshold, based on the magnitude relationship between the remaining power and the fifth remaining power threshold, the operation mode of the range extender of the target vehicle is controlled, including:

[0083] When the charging probability is less than the second charging probability threshold, the range extender is controlled to start until the remaining power is greater than the fifth remaining power threshold, and the battery power is consumed according to the acceleration demand of the target vehicle.

[0084] In one embodiment, when in a scenario of long-distance vehicle use with a very low charging probability, the range extender is turned on throughout the journey, and the motor is completely driven by the power generated by the range extender. At the same time, the instantaneous power of the target vehicle is also monitored. When instantaneous high-power situations such as sudden acceleration and climbing occur, the range extender and the battery are controlled to supply power together. In addition, the magnitude relationship between the battery SOC and the fifth remaining power threshold (for example, 40%) is also monitored in real time. When the battery SOC is less than the fifth remaining power threshold, the power generation power of the range extender is increased until the battery power is not lower than the fifth remaining power threshold.

[0085] As an implementation manner of the present application, the charging probability of the target vehicle is predicted according to the travel information and historical charging information of the target vehicle, including:

[0086] Obtain the current travel information of the target vehicle, including: destination, estimated destination SOC, estimated arrival time, current date, and the number of times charged this week; and obtain the historical charging information of the target vehicle, including: historical charging SOC, historical charging time, historical charging location, usage duration, total number of charges, and number of charges per week;

[0087] According to the historical charging information, statistically analyze the probability distribution information and corresponding weights of the target vehicle in multiple dimensions; the probability distribution information in multiple dimensions includes: SOC probability distribution, time period probability distribution, location probability distribution, and calculate the current remaining charging probability;

[0088] Based on the current trip information of the target vehicle and the probability distribution information in multiple dimensions, determine the target probability of each dimension;

[0089] Based on the target probability of each dimension and the corresponding weight, predict the charging probability of the target vehicle.

[0090] In the embodiments of the present application, the trip information of the vehicle is combined with the personalized charging habits of the user for comprehensive analysis, so as to accurately predict the charging probability. Specifically, first obtain the trip information of the vehicle, including: historical charging SOC, historical charging time, historical charging location, usage duration, total number of charging times, and number of charging times per week; obtain the historical charging information of the user, including: historical charging SOC, historical charging time, historical charging location, usage duration, total number of charging times, and number of charging times per week.

[0091] In one embodiment, statistically analyze the original charging data of the vehicle, including charging start time, charging end time, charging start SOC, charging end SOC, charging location, charging type, charging location type, etc., and clean these data to obtain the historical charging information required for calculating the charging probability in this solution. The original charging data is shown in Table 1 below.

[0092] Table 1

[0093]

[0094] Clean the above original charging information, including:

[0095] (1) According to the charging start time and charging end time, remove the data with a charging duration less than 5 minutes;

[0096] (2) According to the charging end SOC and charging start SOC, remove the data with a charging amount less than 5% of the maximum battery capacity;

[0097] (3) Remove the data with a charging start SOC greater than or equal to 95% of the battery capacity;

[0098] (4) Integrate the charging data of multiple short time periods and merge them into 1 time. If the interval time between two adjacent chargings is less than 30 minutes, merge them into 1 charging;

[0099] (5) Remove the error charging location. To avoid the error caused by GPS (Global Positioning System) positioning deviation, when determining the charging location, obtain 10 reported data after the start of charging, and select the GPS positioning point with the most occurrences of the same location from them as the charging location point.

[0100] After the cleaning of the original charging information is completed, count the cleaned original charging information according to the dimensions in Table 2 below to obtain the probability distribution of each dimension.

[0101] Table 2

[0102]

[0103] According to the probability distribution information of each dimension obtained from the statistical analysis and the influence degree of each dimension information on the charging probability, set the corresponding weights in advance. In actual application, the weights corresponding to each dimension can be set according to experience. In the embodiment of the present application, the specific weights are set as follows: the SOC probability corresponds to the first weight of 40%; the time period probability corresponds to the second weight of 30%; the location probability corresponds to the third weight of 20%; the remaining charging probability corresponds to the fourth weight of 10%.

[0104] When calculating the current charging probability, determine the target probability of the trip information corresponding to each dimension according to the current trip information of the target vehicle and the probability distribution information of each dimension. For example, in the statistical SOC probability distribution, the proportion of the historical charging start SOC in the second SOC interval (21% - 40%) is 17%, and the estimated destination SOC in the current trip information is 35%, which falls within the second SOC interval. Therefore, the corresponding SOC probability is determined to be 17%.

[0105] After determining the probability of the trip information corresponding to each dimension and the weights of each dimension, calculate the current charging probability by using the weighted summation method:

[0106] Charging probability = SOC probability × first weight + time period probability × second weight + location probability × third weight + remaining charging probability × fourth weight.

[0107] The following uses a specific example to illustrate the specific method of predicting the charging probability. Suppose the current destination of the target vehicle is "residence", the estimated arrival time is "20:30", the estimated destination SOC is "15%", the current date is "Wednesday", and the number of charges this week is 1 time. Determine the corresponding probability and weight according to each trip information respectively, as follows:

[0108] The currently estimated destination SOC of the target vehicle is 15%, within the range (10 - 20%), with a corresponding SOC probability of 50% and a first weight of 40%.

[0109] The estimated arrival time is 20:30, within the range of 18 - 22 o'clock, with a corresponding time period probability of 50% and a second weight of 30%.

[0110] The navigation destination is a residence, that is, the type of the user's charging location is determined to be a residence, with a corresponding location probability of 75% and a third weight of 20%.

[0111] The current date is Wednesday (a working day), the number of times charged this week is 1, and the average weekly charging times is 4. The remaining charging probability is calculated to be 75%, and the fourth weight is 10%. Furthermore, the charging probability is calculated as: 50% × 40% + 50% × 30% + 75% × 20% + 75% × 10% = 57.5%.

[0112] In one embodiment, according to the current trip information, the weights of each dimension are dynamically adjusted, and dynamic weights are used to strengthen the influence of the user's charging habits on the charging probability, further improving the accuracy of charging probability prediction. Specifically, the adjustment coefficients of each dimension are determined according to the trip information, and then the weights are adjusted according to the adjustment coefficient K:

[0113] The adjusted weight = adjustment coefficient K × the weight before adjustment.

[0114] In this embodiment, the adjustment coefficients are determined and the weights of each dimension are adjusted. The specific method is as follows:

[0115] (1) For the first weight of the SOC probability, the first coefficient K1 is determined according to the urgency of the battery SOC (the lower the battery SOC, the more urgent the charging demand). Optionally, the determination of the first coefficient also considers the influence of holidays on the urgency. Based on the vehicle usage habits on weekdays and holidays, different first coefficients with different focuses are set as follows: k1 = 1 + α × (1 - destination SOC); where the parameter α is set to 0.6 on weekdays and 0.3 on holidays.

[0116] (2) For the second weight of the time period probability, according to the high-frequency charging time periods (such as the evening rush hour) in the user's historical charging data, the corresponding second coefficient K2 is determined as follows:

[0117] For the 22 - 2 time period, k2 is 1.4; for the 2 - 6 time period, k2 is 1.3; for the 6 - 10 time period, k2 is 1; for the 10 - 14 time period, k2 is 1.1; for the 14 - 18 time period, k2 is 1.2; for the 18 - 22 time period, k2 is 1.3.

[0118] (3) For the third weight of the location probability, according to the user's high-frequency charging locations and dates, determine the corresponding third coefficient K3. Optionally, the determination of the third coefficient also considers the impact of holidays on the urgency level, and sets different emphases for the third coefficient based on the vehicle usage habits on weekdays and holidays, as follows: When charging at home on weekdays, K3 is 1.3; when charging at public locations on weekdays, K3 is 0.7; when charging at home on holidays, K3 is 0.7; when charging at public locations on holidays, K3 is 1.3;

[0119] (4) For the fourth weight of the remaining charging probability, reflect the user's charging urgency through the number of remaining charging times this week. The more remaining times, the more urgent the charging demand. Specifically, use the gap rate to represent the corresponding fourth coefficient K4:

[0120] Remaining charging opportunities = (Number of days remaining before the weekend / 7) × Average weekly charging times;

[0121] Gap rate K4 = (Average weekly charging times - Number of times charged) ÷ Remaining charging opportunities.

[0122] In the trip information of the above example, the current destination of the target vehicle is "home", the estimated arrival time is "20:30", the estimated SOC at the destination is "15%", the current date is "Wednesday", and the number of times charged this week is 1. In this example, the SOC probability is 50%, and the first weight is 40%; the time period probability is 50%, and the second weight is 30%; the location probability is 75%, and the third weight is 20%; the remaining charging probability is 75%, and the fourth weight is 10%. According to the above method of adjusting weights, the weights are adjusted as follows:

[0123] Determine the first coefficient: K1 = 1 + 0.6×(1 - 0.15) = 1.51; Based on K1, adjust the first weight to: 40% * 1.51 = 60.4%;

[0124] Determine the second coefficient: k2 = 1.3; Based on K2, adjust the second weight to: 30% * 1.3 = 39%;

[0125] Determine the third coefficient: k = 1.3; Based on K3, adjust the third weight to 20% * 1.3 = 26%

[0126] Determine the fourth coefficient: Calculate the remaining charging opportunities = 5 / 7 * 4 = 20 / 7; Further calculate the gap rate K4 = (4 - 1) / (20 / 7) = 1.05, that is, K4 is 1.05; Based on K4, adjust the fourth weight to 10% * 1.05 = 10.5%.

[0127] It should be noted that after dynamically adjusting the weights of each dimension, it is also necessary to perform normalization processing on the weights of all dimensions to ensure that the sum of the weights of all dimensions is 100%.

[0128] In this embodiment, each of the dynamically adjusted weights is normalized to obtain a normalized first weight of 44.44%, a normalized second weight of 28.7%, a normalized third weight of 19.13%, and a normalized fourth weight of 7.73%.

[0129] Finally, based on the weights of each dimension after normalization and the corresponding probabilities, the charging probability is calculated by weighted summation as follows:

[0130] 50% * 44.44% + 50% * 28.7% + 75% * 19.13% + 75% * 7.73% = 56.715%.

[0131] Taking the travel information of the vehicle in the above example as an example, it is determined that the current vehicle usage scenario is: a short-distance vehicle usage scenario on weekdays, and the charging probability is less than the first charging probability threshold (70%). Based on this, the corresponding range extender working mode is determined as follows: it is turned off when the battery SOC is greater than or equal to the second remaining power threshold (25%), and pure electric driving is used; when the battery SOC is between 15% and 25%, it is only turned on when driving at a high speed with a vehicle speed greater than the vehicle speed threshold (60 km / h); and when the battery SOC is less than 15%, low-power power preservation is performed, and the range extender runs continuously until the battery power is greater than or equal to 15%.

[0132] As shown in Table 3 below, it is the range extender mode switching strategy and navigation planning strategy set in an embodiment of the present application. Among them, the first charging probability threshold is set to 70%; the second charging threshold is set to 30%; the first remaining power threshold is set to 15%; the second remaining power threshold is set to 25%; the third remaining power threshold is set to 20%; the fourth remaining power threshold is set to 30%; the fifth remaining power threshold is set to 40%.

[0133] Table 3

[0134]

[0135] Based on the range extender mode switching strategy and navigation planning strategy provided in Table 3 above, combined with the user's real-time vehicle usage scenario and charging probability, dynamic planning of the energy and navigation during the current driving process of the vehicle is realized. Figure 2 It is a schematic diagram of controlling the running mode of the range extender in the weekday commuting scenario in an embodiment of the present application. As Figure 2As shown in the figure, in the commuting scenario, first obtain the commuting route, calculate the current charging probability P based on the commuting route, and then compare the charging probability with the first charging probability threshold (70%). If the charging probability is greater than or equal to the first charging probability threshold, run the pure electric mode: turn off the range extender and use the battery power, and turn on the range extender when the battery SOC is less than 15% to maintain the power greater than 15%. Also, the navigation adopts a fixed route plan and prompts available charging stations through the cockpit at the end point. After the trip ends, display the current remaining battery power of the vehicle.

[0136] If the charging probability is less than the first charging probability threshold, adopt the intelligent power conservation strategy: flexibly switch the operation mode of the range extender according to the battery SOC. Specifically, when the battery SOC≥25%, drive in pure electric mode and turn off the range extender; when 15%≤battery SOC<25%, control the start of the range extender according to whether the vehicle speed reaches 60 km / h. If the vehicle speed≥60 km / h, start the range extender; if the vehicle speed<60 km / h, turn off the range extender; when the battery SOC<15%, continuously operate the range extender throughout the journey and maintain the battery power not less than 15%. Also, under the intelligent power conservation strategy, the navigation adopts a fixed route plan and prompts that charging can be carried out through the cockpit at the key point. After the trip ends, display the current remaining battery power of the vehicle.

[0137] Figure 3 It is a schematic diagram of controlling the operation mode of the range extender in the long-distance vehicle use scenario during holidays in an embodiment of the present application. As Figure 3 shown, in the long-distance vehicle use scenario, first estimate the distance to the destination based on the destination, and calculate the current charging probability P according to the distance. Then, compare the charging probability with the first charging probability threshold (70%). If the charging probability is greater than or equal to the first charging probability threshold, run the pure electric mode: turn off the range extender and use the battery power, and turn on the range extender when the battery SOC is less than 20% to maintain the power greater than 20%. Also, the navigation adopts a dynamic programming energy consumption optimal route and forcibly covers charging stations along the way at a density of no more than 100 km intervals. After the trip ends, display the current remaining battery power of the vehicle.

[0138] If the charging probability is less than the first charging probability threshold, further compare the charging probability with the second charging probability threshold (30%). If the charging probability is less than 70% and not less than 30%, control the range extender to run in the hybrid power conservation mode according to the size relationship between the battery SOC and the fourth remaining power threshold (30%). Also, the navigation adopts a dynamic programming energy consumption optimal route and covers charging stations along the way at a density of no more than 200 km intervals. After the trip ends, display the current remaining battery power of the vehicle.

[0139] If the charging probability is less than 30%, the control runs in the range extender priority mode, runs the range extender throughout the journey, and maintains the battery power at no less than 40%. Also, the navigation uses the optimal energy consumption route of dynamic programming, and forcibly covers charging stations along the way at a density with an interval not greater than 50 km. After the journey ends, the current remaining battery power of the vehicle is displayed.

[0140] Based on the same inventive concept, an embodiment of the present application provides a vehicle control device. Refer to Figure 4 , Figure 4 is a schematic diagram of a vehicle control device 100 proposed in an embodiment of the present application. As Figure 4 shown, the device includes:

[0141] A prediction module 101, configured to predict the charging probability of the target vehicle according to the travel information and historical charging information of the target vehicle during the driving process of the target vehicle;

[0142] A control module 102, configured to control the operation mode of the range extender of the target vehicle according to the magnitude relationship between the charging probability and at least one charging probability threshold, and plan a driving path covering charging stations for the target vehicle.

[0143] As an implementation manner of the present application, the control module 102, configured to control the operation mode of the range extender of the target vehicle according to the magnitude relationship between the charging probability and at least one charging probability threshold, and plan a driving path covering charging stations for the target vehicle, includes:

[0144] When the distance between the departure place and the destination of the target vehicle is less than the distance threshold, based on the magnitude relationship between the charging probability and the first charging probability threshold, control the operation mode of the range extender of the target vehicle, and plan the charging station at the destination as the charging station of the target vehicle;

[0145] When the distance between the departure place and the destination of the target vehicle is greater than or equal to the distance threshold, based on the magnitude relationship between the charging probability and multiple charging probability thresholds, control the operation mode of the range extender of the target vehicle, and plan a path passing through charging stations for the target vehicle, where the multiple charging probability thresholds at least include: a charging probability threshold less than the first charging probability threshold.

[0146] As an implementation manner of the present application, the control module 102, configured to, when the distance between the departure place and the destination of the target vehicle is less than the distance threshold, control the operation mode of the range extender of the target vehicle based on the magnitude relationship between the charging probability and the first charging probability threshold, includes:

[0147] When the charging probability is greater than the first charging probability threshold, control the range extender to turn off when the remaining power is greater than the first remaining power threshold, and control the range extender to start when the remaining power is less than the first remaining power threshold until the remaining power is greater than the first remaining power threshold;

[0148] When the charging probability is less than or equal to the first charging probability threshold, control the range extender to turn off when the remaining power is greater than the second remaining power threshold, and control the operating mode of the range extender when the remaining power is less than or equal to the second remaining power threshold according to the magnitude relationship between the vehicle speed of the target vehicle and the vehicle speed threshold and the magnitude relationship between the remaining power and multiple remaining power thresholds. The multiple remaining power thresholds at least include: the first remaining power threshold and the second remaining power threshold.

[0149] As an implementation manner of the present application, the control module 102 is configured to, when the distance between the departure place and the destination of the target vehicle is greater than or equal to the distance threshold, control the operating mode of the range extender of the target vehicle based on the magnitude relationship between the charging probability and multiple charging probability thresholds, and plan a path passing through a charging station for the target vehicle, including:

[0150] When the charging probability is greater than the first charging probability threshold, control the operating mode of the range extender of the target vehicle based on the magnitude relationship between the remaining power and the third remaining power threshold, and plan a path with a first density of the distribution of charging stations passed by for the target vehicle;

[0151] When the charging probability is between the first charging probability threshold and the second charging probability threshold, control the operating mode of the range extender of the target vehicle based on the magnitude relationship between the remaining power and multiple remaining power thresholds, and plan a path with a second density of the distribution of charging stations passed by for the target vehicle. The multiple remaining power thresholds at least include: a fourth remaining power threshold greater than the third remaining power threshold;

[0152] When the charging probability is less than the second charging probability threshold, control the operating mode of the range extender of the target vehicle based on the magnitude relationship between the remaining power and the fifth remaining power threshold, and plan a path with a third density of the distribution of charging stations passed by for the target vehicle. The fifth remaining power threshold is greater than the fourth remaining power threshold and the third remaining power threshold;

[0153] The third density is less than the first density, and the first density is less than the second density.

[0154] As an implementation manner of the present application, the control module 102 is configured to control the operation mode of the range extender of the target vehicle based on the magnitude relationship between the remaining power and the fifth remaining power threshold when the charging probability is less than the second charging probability threshold, including:

[0155] When the charging probability is less than the second charging probability threshold, control the range extender to start until the remaining power is greater than the fifth remaining power threshold, and control the consumption of the battery power according to the acceleration requirement of the target vehicle.

[0156] As an implementation manner of the present application, the control module 102 is configured to control the operation mode of the range extender of the target vehicle based on the magnitude relationship between the remaining power and multiple remaining power thresholds when the charging probability is between the first charging probability threshold and the second charging probability threshold, including:

[0157] When the charging probability is between the first charging probability threshold and the second charging probability threshold, control the range extender to turn off when the remaining power is greater than the fourth remaining power threshold, and control the operation mode of the range extender when the remaining power is less than or equal to the fourth remaining power threshold according to the magnitude relationship between the vehicle speed of the target vehicle and the vehicle speed threshold and the magnitude relationship between the remaining power and multiple remaining power thresholds. The multiple remaining power thresholds at least include: the third remaining power threshold and the fourth remaining power threshold.

[0158] As an implementation manner of the present application, the control module 102 is configured to control the operation mode of the range extender of the target vehicle based on the magnitude relationship between the remaining power and the third remaining power threshold when the charging probability is greater than the first charging probability threshold, including:

[0159] When the charging probability is greater than the first charging probability threshold, control the range extender to turn off when the remaining power is greater than the third remaining power threshold, and control the range extender to start when the remaining power is less than the third remaining power threshold until the remaining power is greater than the third remaining power threshold.

[0160] As an implementation manner of the present application, the prediction module 101 is specifically configured to perform the following steps:

[0161] Obtain the current trip information of the target vehicle, including: destination, estimated destination SOC, estimated arrival time, current date, and the number of times charged this week; and, obtain the historical charging information of the target vehicle, including: historical charging SOC, historical charging time, historical charging location, usage duration, total number of charges, and number of charges per week;

[0162] According to the historical charging information, statistically analyze the probability distribution information and corresponding weights of the target vehicle in multiple dimensions; the probability distribution information in multiple dimensions includes: SOC probability distribution, time period probability distribution, location probability distribution, and calculate the current remaining charging probability;

[0163] Based on the current trip information of the target vehicle and the probability distribution information in multiple dimensions, determine the target probability of each dimension;

[0164] Based on the target probability of each dimension and the corresponding weight, predict the charging probability of the target vehicle.

[0165] Based on the same inventive concept, an embodiment of the present application provides a readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps in the vehicle control method described in any of the above embodiments of the present application.

[0166] Based on the same inventive concept, an embodiment of the present application provides an electronic device, refer to Figure 5 , Figure 5 is a schematic diagram of an electronic device proposed in an embodiment of the present application. The electronic device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps in the vehicle control method described in any of the above embodiments of the present application.

[0167] Regarding the device in the above embodiments, the specific manner in which each module performs operations has been described in detail in the embodiments related to the method, and will not be elaborated here.

[0168] The above are only preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0169] For the method embodiments, for simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and components involved are not necessarily essential to the present application.

[0170] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, an apparatus, or a computer program product. Therefore, the embodiments of the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the embodiments of the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0171] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of methods, terminal devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, as well as the combination of processes and / or blocks in the flowchart and / or block diagram. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal devices generate a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0172] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0173] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable terminal device provide steps for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0174] Although the preferred embodiments of the embodiments of the present application have been described, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concept. Therefore, the present application is interpreted to include the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present application.

[0175] Finally, it should also be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or terminal device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or terminal device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or terminal device comprising the said element.

[0176] The vehicle control method, device and storage medium provided in the present application have been introduced in detail above. Specific examples are used in this text to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A vehicle control method, characterized in that, Including: During the driving of the target vehicle, predicting the charging probability of the target vehicle according to the travel information and historical charging information of the target vehicle; Controlling the operation mode of the range extender of the target vehicle according to the magnitude relationship between the charging probability and at least one charging probability threshold, and planning a driving path covering a charging station for the target vehicle.

2. The vehicle control method according to claim 1, wherein Controlling the operation mode of the range extender of the target vehicle according to the magnitude relationship between the charging probability and at least one charging probability threshold, and planning a driving path covering a charging station for the target vehicle, including: When the distance between the departure place and the destination of the target vehicle is less than a distance threshold, controlling the operation mode of the range extender of the target vehicle based on the magnitude relationship between the charging probability and the first charging probability threshold, and planning the charging station located at the destination as the charging station of the target vehicle; When the distance between the departure place and the destination of the target vehicle is greater than or equal to the distance threshold, controlling the operation mode of the range extender of the target vehicle based on the magnitude relationship between the charging probability and multiple charging probability thresholds, and planning a path passing through a charging station for the target vehicle, where the multiple charging probability thresholds at least include: a charging probability threshold less than the first charging probability threshold.

3. The vehicle control method according to claim 2, characterized in that When the distance between the departure place and the destination of the target vehicle is less than a distance threshold, controlling the operation mode of the range extender of the target vehicle based on the magnitude relationship between the charging probability and the first charging probability threshold, including: When the charging probability is greater than the first charging probability threshold, controlling the range extender to turn off when the remaining power is greater than the first remaining power threshold, and controlling the range extender to start when the remaining power is less than the first remaining power threshold until the remaining power is greater than the first remaining power threshold; When the charging probability is less than or equal to the first charging probability threshold, controlling the range extender to turn off when the remaining power is greater than the second remaining power threshold, and controlling the operation mode of the range extender when the remaining power is less than or equal to the second remaining power threshold according to the magnitude relationship between the vehicle speed of the target vehicle and the vehicle speed threshold and the magnitude relationship between the remaining power and multiple remaining power thresholds, where the multiple remaining power thresholds at least include: the first remaining power threshold and the second remaining power threshold.

4. The vehicle control method according to claim 2, wherein, When the distance between the departure place and the destination of the target vehicle is greater than or equal to the distance threshold, controlling the operation mode of the range extender of the target vehicle based on the magnitude relationship between the charging probability and multiple charging probability thresholds, and planning a path passing through a charging station for the target vehicle, including: When the charging probability is greater than the first charging probability threshold, controlling the operation mode of the range extender of the target vehicle based on the magnitude relationship between the remaining power and the third remaining power threshold, and planning a path with a first density of the distribution of charging stations passed by the target vehicle; When the charging probability is between the first charging probability threshold and the second charging probability threshold, based on the magnitude relationship between the remaining battery level and multiple remaining battery level thresholds, control the operating mode of the range extender of the target vehicle, and plan a path with a second density of charging station distribution density for the target vehicle. The multiple remaining battery level thresholds at least include: a fourth remaining battery level threshold greater than the third remaining battery level threshold; When the charging probability is less than the second charging probability threshold, based on the magnitude relationship between the remaining battery level and the fifth remaining battery level threshold, control the operating mode of the range extender of the target vehicle, and plan a path with a third density of charging station distribution density for the target vehicle. The fifth remaining battery level threshold is greater than the fourth remaining battery level threshold and the third remaining battery level threshold; The third density is less than the first density, and the first density is less than the second density.

5. The vehicle control method according to claim 4, wherein When the charging probability is less than the second charging probability threshold, based on the magnitude relationship between the remaining battery level and the fifth remaining battery level threshold, controlling the operating mode of the range extender of the target vehicle includes: When the charging probability is less than the second charging probability threshold, control the range extender to start until the remaining battery level is greater than the fifth remaining battery level threshold, and control the consumption of battery power according to the acceleration demand of the target vehicle.

6. The vehicle control method according to claim 4, wherein, When the charging probability is between the first charging probability threshold and the second charging probability threshold, based on the magnitude relationship between the remaining battery level and multiple remaining battery level thresholds, controlling the operating mode of the range extender of the target vehicle includes: When the charging probability is between the first charging probability threshold and the second charging probability threshold, control the range extender to turn off when the remaining battery level is greater than the fourth remaining battery level threshold, and control the operating mode of the range extender when the remaining battery level is less than or equal to the fourth remaining battery level threshold according to the magnitude relationship between the vehicle speed of the target vehicle and the vehicle speed threshold and the magnitude relationship between the remaining battery level and multiple remaining battery level thresholds. The multiple remaining battery level thresholds at least include: the third remaining battery level threshold and the fourth remaining battery level threshold.

7. The vehicle control method according to claim 4, characterized in that, When the charging probability is greater than the first charging probability threshold, based on the magnitude relationship between the remaining battery level and the third remaining battery level threshold, controlling the operating mode of the range extender of the target vehicle includes: When the charging probability is greater than the first charging probability threshold, control the range extender to turn off when the remaining battery level is greater than the third remaining battery level threshold, and control the range extender to start when the remaining battery level is less than the third remaining battery level threshold until the remaining battery level is greater than the third remaining battery level threshold.

8. The vehicle control method according to any one of claims 1-7, characterized in that Predict the charging probability of the target vehicle according to the travel information and historical charging information of the target vehicle, including: Obtain the current trip information of the target vehicle, including: destination, estimated destination SOC, estimated arrival time, current date, and the number of charges in this week; and, obtain the historical charging information of the target vehicle, including: historical charging SOC, historical charging time, historical charging location, usage duration, total number of charges, and number of charges per week; According to the historical charging information, count the probability distribution information and corresponding weights of the target vehicle in multiple dimensions; the probability distribution information in multiple dimensions includes: SOC probability distribution, time period probability distribution, location probability distribution, and calculate the current remaining charging probability; Based on the current trip information of the target vehicle and the probability distribution information in multiple dimensions, determine the target probability of each dimension; Predict the charging probability of the target vehicle based on the target probability of each dimension and the corresponding weight.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, implement the steps in the method according to any one of claims 1-8.

10. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, implement the steps in the method according to any one of claims 1-8.

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