Vehicle energy management method, system and computer-readable storage medium

Abstract

The present application provides a vehicle energy management method, system and computer-readable storage medium, which belongs to the field of new energy vehicle technology. The embodiment of the present application can use the cloud platform to accurately determine whether the vehicle is traveling on the target accustomed route when the vehicle does not turn on navigation, and then determine the minimum remaining power of the vehicle when it is determined that the vehicle is traveling on the target accustomed route, and send the minimum remaining power and the navigation information and speed correction coefficient of the vehicle on the target accustomed route to the vehicle; the vehicle can perform targeted predictive energy management on each speed section of the target accustomed route by comprehensively considering the navigation information of the target accustomed route, the speed correction coefficient and the user's driving habits. In this way, through the collaboration of the cloud, the vehicle and the user, the energy-saving effect of the vehicle on the target accustomed route can be improved while satisfying the user's personalized driving habits, thereby effectively alleviating the user's range anxiety and improving the user's driving experience.

Description

Technical Field

[0001] The present application relates to the field of new energy vehicle technology, and in particular to a vehicle energy management method, system and computer-readable storage medium. Background Art

[0002] In related technologies, the energy management strategy for hybrid vehicles is usually to formulate different energy consumption models based on various driving modes and power modes for control. Energy management is limited to a few fixed modes, and the energy-saving effect is poor. Some companies combine energy management and navigation for predictive energy management, achieving better energy consumption levels based on fixed energy management.

[0003] However, in actual use, especially when commuting frequently, the vehicle's onboard navigation is usually not turned on. At this time, navigation-based predictive energy management will not achieve the expected energy-saving effect. Summary of the invention

[0004] The present application provides a vehicle energy management method, system and computer-readable storage medium to solve the current problem that it is difficult to achieve effective predictive energy management when the vehicle's onboard navigation is not turned on.

[0005] In order to solve the above problems, this application adopts the following technical solutions:

[0006] In a first aspect, an embodiment of the present application provides a vehicle energy management method, which is applied to a vehicle, and the method includes:

[0007] When the navigation function of the vehicle is not turned on, uploading the driving information of the vehicle to the cloud platform, so that the cloud platform determines the minimum remaining power of the vehicle when the vehicle is traveling on a target accustomed route based on the driving information, and sends the minimum remaining power and the navigation information and vehicle speed correction coefficient of the vehicle on the target accustomed route to the vehicle;

[0008] Determining, based on the speed correction coefficient of the target accustomed route and the navigation information, the predicted driving power consumption of the vehicle in a plurality of speed sections of the target accustomed route and the predicted driving time of the vehicle on the target accustomed route;

[0009] Based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle, the energy management strategy corresponding to the vehicle in each of the plurality of speed sections is determined.

[0010] In one embodiment of the present application, the navigation information includes segment distances and reference driving times of multiple navigation segments of the target accustomed route;

[0011] The step of determining the predicted driving power consumption of the vehicle in a plurality of speed sections of the target accustomed route based on the speed correction coefficient of the target accustomed route and the navigation information comprises:

[0012] Determining the navigation vehicle speed of each navigation section based on the section distance and reference driving time of each navigation section;

[0013] Based on the vehicle speed correction coefficient, the navigation vehicle speed of each navigation section is corrected to obtain the predicted vehicle speed of the vehicle in each navigation section;

[0014] Based on the predicted vehicle speed of each navigation section, the plurality of navigation sections are divided into a plurality of vehicle speed sections; wherein different vehicle speed sections correspond to different vehicle speed ranges;

[0015] Based on the power consumption information per 100 kilometers of the vehicle at various vehicle speeds, the predicted driving power consumption of the vehicle in the plurality of vehicle speed sections is determined.

[0016] In one embodiment of the present application, the step of determining the predicted driving time of the vehicle on the target habitual route based on the speed correction coefficient of the target habitual route and the navigation information includes:

[0017] Determining the driving time of each navigation section based on the section distance and predicted vehicle speed of the vehicle on each navigation section;

[0018] The sum of the driving time of each navigation section is determined as the predicted driving time of the vehicle on the target accustomed route.

[0019] In one embodiment of the present application, the plurality of vehicle speed sections include a low-speed section, a medium-speed section and a high-speed section; the predicted driving power consumption includes a low-speed section driving power consumption corresponding to the low-speed section, a medium-speed section driving power consumption corresponding to the medium-speed section, and a high-speed section driving power consumption corresponding to the high-speed section;

[0020] The step of determining the energy management strategy corresponding to each of the plurality of speed sections of the vehicle based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle comprises:

[0021] Determining predicted accessory power consumption based on the predicted driving duration and the accessory power;

[0022] Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption, the low-speed section driving power consumption, the medium-speed section driving power consumption and the high-speed section driving power consumption as a first power difference;

[0023] Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption, the low-speed section driving power consumption, and the medium-speed section driving power consumption as a second power difference;

[0024] Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption and the low-speed section driving power consumption as a third power difference;

[0025] Based on the first power difference, the second power difference and the third power difference, energy management strategies corresponding to the vehicle in each of the plurality of speed sections are determined.

[0026] In one embodiment of the present application, the step of determining the energy management strategy corresponding to each of the vehicle in the plurality of speed sections based on the first power difference, the second power difference and the third power difference includes:

[0027] When the first electric quantity difference is greater than an upper threshold of a preset hysteresis interval, determining that the energy management strategy of the vehicle in the low-speed section, the medium-speed section and the high-speed section is a pure electric drive strategy; the hysteresis interval is a closed interval consisting of a lower threshold and an upper threshold;

[0028] When the first power difference is within the hysteresis interval, or when the first power difference is less than the lower limit threshold and the second power difference is greater than the upper limit threshold, determining that the energy management strategy of the vehicle in the low-speed section and the medium-speed section is a pure electric drive strategy, and determining that the energy management strategy of the vehicle in the high-speed section is a fuel drive strategy;

[0029] When the second power difference is within the hysteresis interval, or when the second power difference is less than the lower limit threshold and the third power difference is greater than the upper limit threshold, the energy management strategy of the vehicle on the low-speed section is determined to be the pure electric drive strategy, the energy management strategy of the vehicle on the medium-speed section is determined to be the fuel drive strategy, and the energy management strategy of the vehicle on the high-speed section is determined to be the fuel drive power generation strategy;

[0030] When the third electrical charge difference is within the hysteresis interval, or when the third electrical charge difference is less than the lower limit threshold, the energy management strategy of the vehicle in the low-speed section is determined to be the pure electric drive strategy, and the energy management strategy of the vehicle in the medium-speed section and the high-speed section is determined to be the fuel-driven power generation strategy.

[0031] In an embodiment of the present application, the method further includes:

[0032] When the first power difference enters or exits the hysteresis interval, or when the second power difference enters or exits the hysteresis interval, or when the third power difference enters or exits the hysteresis interval, the energy management strategy of the previous moment is maintained.

[0033] In an embodiment of the present application, the method further includes:

[0034] In the case where the energy management strategy is determined to be the pure electric drive strategy, determining the minimum remaining power as the target remaining power of the vehicle;

[0035] In the case where the energy management strategy is determined to be the fuel driving strategy, determining the current remaining power as the target remaining power of the vehicle;

[0036] When it is determined that the energy management strategy is the fuel-driven power generation strategy, a preset maximum remaining power is determined as the target remaining power of the vehicle.

[0037] In the second aspect, based on the same inventive concept, the embodiment of the present application provides another vehicle energy management method, which is applied to a cloud platform, and the method includes:

[0038] Acquire driving information uploaded by the vehicle when the navigation function is not turned on, and determine whether the vehicle is traveling on a target accustomed route based on the driving information;

[0039] When it is determined that the vehicle is traveling on the target accustomed route, determining a minimum remaining power of the vehicle;

[0040] The minimum remaining power, navigation information of the vehicle on the target accustomed route, and a speed correction coefficient are sent to the vehicle, so that the vehicle determines the predicted driving power consumption of the vehicle in multiple speed sections of the target accustomed route and the predicted driving time of the vehicle on the target accustomed route based on the speed correction coefficient and navigation information of the target accustomed route; and determines the energy management strategy corresponding to each of the multiple speed sections of the vehicle based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle.

[0041] In one embodiment of the present application, the driving information includes the departure time, the origin location and the current driving route of the vehicle;

[0042] The step of determining whether the vehicle is traveling on a target accustomed route based on the driving information includes:

[0043] Based on the departure time and the origin location, determining at least one pending habitual route from a plurality of user habitual routes; the plurality of user habitual routes are determined based on the historical driving routes of the vehicle;

[0044] Determining a similarity between the current driving route and at least one of the pending accustomed routes;

[0045] The undetermined habitual route with the highest similarity is determined as the target habitual route, and when the similarity of the target habitual route is greater than a similarity threshold, it is determined that the vehicle is traveling on the target habitual route.

[0046] In one embodiment of the present application, the user's usual route includes a departure time tag and a departure location tag;

[0047] The step of determining at least one pending common route from a plurality of common routes of the user based on the departure time and the origin location comprises:

[0048] For any user's usual route, when the departure time is within the time range indicated by the departure time tag and the origin location is within the area range indicated by the origin location tag, the user's usual route is determined to be the pending usual route.

[0049] In an embodiment of the present application, the step of determining the minimum remaining power of the vehicle includes:

[0050] Determining the charging habits of the vehicle and the charging location of the target habitual route;

[0051] When the charging habit is a frequent charging type and charging locations exist at both the origin and the destination of the target habitual route, a preset reference remaining power is determined as the minimum remaining power for the vehicle to arrive at the destination and return to the origin;

[0052] In a case where the charging habit is the regular charging type and a charging location exists only at the origin of the target habitual route, determining the sum of the reference remaining power and the first preset remaining power as the minimum remaining power for the vehicle to reach the destination;

[0053] When the charging habit is the regular charging type and there is a charging location only at the destination of the target habitual route, the reference remaining power is determined as the minimum remaining power for the vehicle to arrive at the destination, and the sum of the reference remaining power and the first preset remaining power is determined as the minimum remaining power for the vehicle to return to the origin;

[0054] In a case where the charging type is an irregular charging type or an occasional charging type, a sum of the reference remaining power and a second preset remaining power is determined as a minimum remaining power for the vehicle to arrive at the destination.

[0055] In a third aspect, based on the same inventive concept, an embodiment of the present application provides a vehicle energy management device, which is applied to a vehicle, and the device includes:

[0056] an information uploading module, for uploading the driving information of the vehicle to the cloud platform when the navigation function of the vehicle is not turned on, so that the cloud platform can determine the minimum remaining power of the vehicle when it is determined that the vehicle is traveling on a target accustomed route based on the driving information, and send the minimum remaining power and the navigation information and vehicle speed correction coefficient of the vehicle on the target accustomed route to the vehicle;

[0057] a parameter prediction module, for determining, based on a speed correction coefficient of the target accustomed route and navigation information, a predicted driving power consumption of the vehicle in a plurality of speed sections of the target accustomed route and a predicted driving time of the vehicle on the target accustomed route;

[0058] A strategy determination module is used to determine the energy management strategy corresponding to the vehicle in each of the multiple speed sections based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle.

[0059] In a fourth aspect, based on the same inventive concept, the embodiment of the present application provides another vehicle energy management device, which is applied to a cloud platform, and the device includes:

[0060] A route determination module, used to obtain driving information uploaded by the vehicle when the navigation function is not turned on, and determine whether the vehicle is traveling on a target accustomed route based on the driving information;

[0061] An information determination module, configured to determine a minimum remaining power of the vehicle when it is determined that the vehicle is traveling on the target accustomed route;

[0062] The information sending module is used to send the minimum remaining power and the navigation information and speed correction coefficient of the vehicle on the target accustomed route to the vehicle, so that the vehicle can determine the predicted driving power consumption of the vehicle in multiple speed sections of the target accustomed route and the predicted driving time of the vehicle on the target accustomed route based on the speed correction coefficient and navigation information of the target accustomed route; and determine the energy management strategy corresponding to each of the multiple speed sections of the vehicle based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle.

[0063] In a fifth aspect, based on the same inventive concept, an embodiment of the present application provides a vehicle energy management system, the system comprising a vehicle and a cloud platform;

[0064] The vehicle is used to upload the driving information of the vehicle to the cloud platform when the navigation function of the vehicle is not turned on;

[0065] The cloud platform is used to determine the minimum remaining power of the vehicle when it is determined that the vehicle is traveling on a target accustomed route based on the driving information, and send the minimum remaining power and navigation information and a speed correction coefficient of the vehicle on the target accustomed route to the vehicle;

[0066] The vehicle is used to determine the predicted driving power consumption of the vehicle in multiple speed sections of the target accustomed route and the predicted driving time of the vehicle in the target accustomed route based on the speed correction coefficient of the target accustomed route and the navigation information; and determine the energy management strategy corresponding to each of the multiple speed sections of the vehicle based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle.

[0067] In the sixth aspect, based on the same inventive concept, an embodiment of the present application provides a computer-readable storage medium on which an executable program is stored. When the executable program is executed by a processor, it implements a vehicle energy management method proposed in the first aspect of the present application or another vehicle energy management method proposed in the second aspect of the present application.

[0068] Compared with the prior art, this application has the following advantages:

[0069] The embodiment of the present application provides a vehicle energy management method, by uploading the driving information of the vehicle to the cloud platform when the navigation function of the vehicle is not turned on, so that the cloud platform can determine the minimum remaining power of the vehicle when the vehicle is determined to be traveling on the target accustomed route based on the driving information, and send the minimum remaining power and the navigation information and speed correction coefficient of the vehicle on the target accustomed route to the vehicle; the vehicle can determine the predicted driving power consumption of the vehicle on multiple speed sections of the target accustomed route and the predicted driving time of the vehicle on the target accustomed route based on the speed correction coefficient and navigation information of the target accustomed route, and determine the energy management strategy corresponding to each of the vehicle in the multiple speed sections based on the predicted driving power consumption, predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle. The implementation of the present application can use the cloud platform to accurately identify the target accustomed route when the vehicle does not turn on navigation, and then by comprehensively considering the navigation information of the target accustomed route, the speed correction coefficient and the user's driving habits, it can perform targeted predictive energy management on each speed section of the target accustomed route. In this way, through the collaboration of cloud, vehicle and people, the energy-saving effect of the vehicle on the target driving route can be improved while meeting the user's personalized car usage habits, thereby effectively alleviating the user's range anxiety and improving the user's car experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0071] Figure 1 is a flowchart of the steps of a vehicle energy management method in one embodiment of the present application;

[0072] Figure 2 is a flowchart of another vehicle energy management method in one embodiment of the present application;

[0073] Figure 3 This is a functional module diagram of a vehicle energy management device in one embodiment of the present application;

[0074] Figure 4 It is a functional module diagram of another vehicle energy management device in one embodiment of the present application;

[0075] Figure 5 It is a structural diagram of a vehicle energy management system in one embodiment of the present application. DETAILED DESCRIPTION

[0076] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0077] It should be noted that, in order to improve the driving range and relieve the users' driving range anxiety, the current new energy vehicles are usually equipped with energy management strategies to reduce the energy consumption of the vehicle. Hybrid vehicles can use the engine and power battery as power sources, thereby improving fuel efficiency and reducing emissions. Compared with traditional gasoline or diesel vehicles, they are more environmentally friendly and energy-saving, and therefore have developed rapidly.

[0078] Since hybrid vehicles are equipped with both an engine and a power battery as power sources, hybrid vehicles usually have multiple driving modes or multiple power modes. Therefore, in the related art, in the design stage of energy management strategy, different energy consumption models are usually formulated for various driving modes or various power modes for control, and energy management is only a few fixed modes. It is impossible to achieve optimal energy consumption for people with different driving route requirements, so the energy saving effect is poor and it is difficult to meet the energy saving needs of users.

[0079] Some companies combine energy management and navigation. After the vehicle starts destination navigation, the navigation system can provide future road conditions information, allowing the vehicle to perform predictive energy management based on navigation information such as speed, distance, slope, etc., and achieve better energy consumption levels based on fixed energy management.

[0080] However, the above technologies all have certain limitations. In actual use, especially when commuting frequently, the vehicle's onboard navigation is usually not turned on. If the navigation is not turned on, the predictive energy management function cannot be activated, and the future road condition information cannot be accurately obtained, making it difficult for the vehicle to achieve accurate and effective predictive energy management.

[0081] In view of the current problem that it is difficult to achieve effective predictive energy management when the vehicle's onboard navigation is not turned on, this application aims to provide a vehicle energy management method that can use the cloud platform to accurately identify the target accustomed route when the vehicle does not turn on the navigation, and then by comprehensively considering the navigation information of the target accustomed route, the speed correction coefficient and the user's driving habits, it can perform targeted predictive energy management on each speed section of the target accustomed route. In this way, through the collaboration of the cloud, the vehicle and the user, the energy-saving effect of the vehicle on each speed section of the target accustomed route can be improved while satisfying the user's personalized driving habits, thereby effectively improving the user's driving experience.

[0082] Reference Figure 1 , shows a vehicle energy management method of the present application, applied to a vehicle, the method may include the following steps:

[0083] S101: When the navigation function of the vehicle is not turned on, the vehicle's driving information is uploaded to the cloud platform, so that the cloud platform can determine the vehicle's minimum remaining power based on the driving information when the vehicle is traveling on a target accustomed route, and send the minimum remaining power and the vehicle's navigation information and speed correction factor on the target accustomed route to the vehicle.

[0084] It should be noted that the execution subject of this embodiment is a control unit or controller in the vehicle with data processing, network communication and program running functions, such as ECU (Electronic Control Unit), VCU (Vehicle Control Unit), etc. The following description will be based on the ECU of the vehicle as the execution subject, and this embodiment does not impose specific restrictions on the type of execution subject. Among them, the vehicle can be a pure electric vehicle or a hybrid vehicle.

[0085] In this embodiment, the vehicle is equipped with a vehicle networking module, which is connected to the cloud platform through a cloud signal input interface, and the ECU can exchange data with the cloud platform through the vehicle networking module. The cloud platform can statistically analyze the vehicle's habitual route library, charging habits, and charging locations on the target habitual route based on the historical information uploaded by the vehicle.

[0086] In the specific implementation, the ECU will upload the historical driving data of the vehicle to the cloud platform through the Internet of Vehicles module. The cloud platform will count the historical driving routes with the most repeated trips within a preset period based on the historical driving data, and then obtain a habitual route library containing at least one user's habitual route. Specifically, the route with a vehicle's repeated trip frequency greater than the threshold can be determined as the user's habitual route.

[0087] In the specific implementation, the ECU will also upload the vehicle's historical charging location information and historical charging information to the cloud platform through the Internet of Vehicles module. Based on the historical charging location information and historical charging information, the cloud platform can determine the vehicle's charging habits and the charging location of each user's usual route; and then determine the vehicle's minimum remaining power based on the charging habits and the charging location of the target usual route. Among them, charging habits are used to characterize the user's charging behavior preferences for the vehicle, which can specifically include regular charging types, irregular charging types, or occasional charging types; the minimum remaining power represents the minimum remaining power that can meet the vehicle's driving needs on the target usual route.

[0088] In this embodiment, after obtaining the vehicle's usual route library, the cloud platform will request the navigation data of the user's usual route from the map provider whenever it detects that the vehicle is traveling on any user's usual route, and calculate the navigation speed of each navigation section of the user's usual route based on the navigation data; then compare the navigation speed with the actual speed of the vehicle on the user's usual route to determine the speed difference value of each navigation section; finally, determine the speed correction coefficient of the vehicle based on the speed difference value of each navigation section. It should be noted that the cloud platform will correct the speed correction coefficient of each user's usual route at preset intervals to ensure the accuracy and real-time performance of the speed correction coefficient.

[0089] In this embodiment, when the vehicle enters the driving state, if the ECU detects that the navigation function of the vehicle is not turned on, the driving information will be uploaded to the cloud platform in real time during the driving process of the vehicle. The cloud platform will determine whether the vehicle is driving on the target accustomed route based on the driving information.

[0090] In a specific implementation, the driving information includes the vehicle's departure time, origin location, and current driving route. The cloud platform will first determine at least one pending accustomed route from multiple user accustomed routes based on the departure time and origin location. The pending accustomed route represents a route that conforms to the user's travel habits from the time dimension and the location dimension. Then, during the vehicle's driving process, as the current driving route continues to extend, the cloud platform will calculate the similarity between the current driving route and at least one pending accustomed route in real time. Finally, the pending accustomed route with the highest similarity is determined as the target accustomed route, and when the similarity of the target accustomed route is greater than the similarity threshold, it is determined that the vehicle is driving on the target accustomed route.

[0091] Exemplarily, the user has three routes with address a as the starting point, among which user route A is a commuting route to the company, user route B is a route home to the home address, and user route C is a tourist route to a tourist area. Among them, user routes A and B depart from 7 to 8 in the morning, and user route C departs from 8 to 9 in the morning. If the cloud platform detects that the starting location of the vehicle is address a and the departure time is 7:20, it is preliminarily determined that the user may go to the company or to the home address, and then the pending routes are determined to be user routes A and user routes B; as the vehicle travels, the current route continues to extend. If the cloud platform detects that the current route is consistent with user route A, it is finally determined that the vehicle is traveling on user route A.

[0092] In this embodiment, after determining that the vehicle is traveling on the target accustomed route, the cloud platform will request navigation information of the target accustomed route from the map provider, and package the navigation information, the vehicle speed correction factor and the minimum remaining power into a data packet and then transparently transmit it to the TSP (Telematics Service Provider). The TSP encapsulates the data packet and sends the data packet to the vehicle according to the remote control protocol with the vehicle. After receiving the data packet, the vehicle will perform data verification on the data packet, and after the verification is successful, the data in the data packet will be converted into a CAN (Controller Area Network) signal. After parsing the data packet, the ECU can perform targeted predictive energy management on the target accustomed route based on the parsed minimum remaining power, navigation information and vehicle speed correction factor of the target accustomed route.

[0093] S102: Determine, based on the speed correction coefficient of the target accustomed route and the navigation information, the predicted driving power consumption of the vehicle on multiple speed sections of the target accustomed route and the predicted driving time of the vehicle on the target accustomed route.

[0094] In this embodiment, the ECU can predict the predicted speed of the vehicle in each navigation section according to the speed correction coefficient of the vehicle in the target accustomed route, and then divide the multiple navigation sections into multiple speed sections.

[0095] It should be noted that the speed section represents a set of navigation sections corresponding to a certain speed range of the vehicle. For example, multiple speed sections can be set as low-speed sections (corresponding speed range is 0km / h≤V≤30km / h), medium-speed sections (corresponding speed range is 30km / h<V≤60km / h) and high-speed sections (corresponding speed range is V>60km / h), and the target accustomed route has five navigation sections a, b, c, d, and e. Based on the predicted speed of the vehicle, the ECU knows that the predicted speed of the vehicle in navigation sections a and c is between 0 and 30km / h, and then determines that the low-speed sections include a and c; similarly, it can be determined that the medium-speed sections include b and e, and the high-speed section includes d.

[0096] In this embodiment, the ECU can accurately calculate the predicted vehicle speed based on the vehicle speed correction coefficient and navigation information, and thus accurately predict the predicted driving power consumption and the predicted driving time; at the same time, by dividing multiple navigation sections into different vehicle speed sections, targeted energy management of different vehicle speed sections can be achieved.

[0097] S103: Based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle, determine the energy management strategy corresponding to the vehicle in multiple speed sections.

[0098] It should be noted that the vehicle's power consumption specifically includes the vehicle's driving power consumption and the accessory power consumption of the vehicle's accessories, among which the accessory power consumption includes air conditioning power consumption, high-voltage line loss power consumption and low-voltage power consumption. Therefore, the ECU can determine the vehicle's predicted accessory power consumption by obtaining the vehicle's accessory power and predicted driving time, and then combine the predicted driving power consumption issued by the cloud platform to predict the vehicle's full vehicle power consumption on the target accustomed route.

[0099] In this embodiment, the ECU can determine the available remaining power that can be consumed by the vehicle based on the current remaining power and the minimum remaining power of the vehicle, and then, based on the available remaining power and the power consumption of the whole vehicle, the ECU can match the corresponding energy management strategy for each speed route to perform energy management. In this way, through the collaboration of the cloud, the vehicle and the human, the energy-saving effect of the vehicle on the target accustomed route can be effectively improved on the premise of meeting the personalized car-using habits of the user, ensuring that the vehicle can meet the driving needs of the user on the target accustomed route, thereby effectively alleviating the user's range anxiety and improving the user's car-using experience.

[0100] In a feasible implementation manner, the navigation information includes the segment distances and reference driving times of multiple navigation segments of the target accustomed route; the step of determining the predicted driving power consumption of the vehicle in multiple speed segments of the target accustomed route based on the speed correction coefficient of the target accustomed route and the navigation information in S102 may specifically include the following sub-steps:

[0101] S102-1: Determine the navigation vehicle speed of each navigation section based on the section distance and reference driving time of each navigation section.

[0102] In this embodiment, the navigation information of the target accustomed route provided by the map provider is usually determined based on the driving data provided by other vehicles on the target accustomed route. In other words, the reference driving time is calculated and statistically analyzed based on the driving time of other vehicles on the target accustomed route.

[0103] In a specific implementation, the ECU can calculate the navigation vehicle speed of each navigation section according to the section distance and the reference driving time, and generate a navigation information table as shown in Table 1.

[0104] Table 1 Navigation information table

[0105]

[0106] It should be noted that step_cal_T represents the navigation step. When step_cal_T is 0, it means that the vehicle travels 40 meters at a speed of 6 km / h in the first navigation section. Then when step_cal_T is 1, it means that the vehicle travels 800 meters at a speed of 30 km / h in the second navigation section, and so on, until the last navigation section.

[0107] S102-2: Based on the vehicle speed correction coefficient, the navigation vehicle speed of each navigation section is corrected to obtain the predicted vehicle speed of the vehicle in each navigation section.

[0108] In a specific implementation, the predicted vehicle speed of the vehicle on each navigation section may be determined according to the product of the navigation vehicle speed and the vehicle speed correction coefficient.

[0109] In this embodiment, in order to improve the accuracy of the predicted vehicle speed for each navigation section, the cloud platform can also count the speed correction coefficient corresponding to each navigation section, and then for any navigation section, correct the navigation speed of the navigation section according to the speed correction coefficient corresponding to the navigation section, and then obtain the predicted vehicle speed for the navigation section.

[0110] In this embodiment, according to the predicted vehicle speed of each navigation section, the section distances of the navigation sections with the same predicted vehicle speed are summed up to generate a predicted vehicle speed-distance comparison table as shown in Table 2.

[0111] Table 2 Predicted speed-distance comparison table

[0112]

[0113] It should be noted that, taking the predicted vehicle speed of 60 km / h as an example, the distance corresponding to the predicted vehicle speed is S10, and S10 represents the sum of the section distances of all navigation sections with a predicted vehicle speed of 60 km / h.

[0114] S102-3: Divide the plurality of navigation sections into a plurality of speed sections based on the predicted vehicle speed of each navigation section.

[0115] In this embodiment, it is taken into account that the vehicle has different energy consumption characteristics at different vehicle speeds, that is, when driving at low speeds, battery drive is usually used because the drive motor is more efficient at low speeds, which can reduce fuel consumption and emissions; when driving at high speeds, fuel drive is usually used because the engine is more efficient and more powerful at high loads and high speeds.

[0116] In this implementation, different vehicle speed sections correspond to different vehicle speed ranges, and the plurality of navigation sections may be divided into a plurality of vehicle speed sections according to a plurality of preset vehicle speed ranges.

[0117] Specifically, let the predicted speed be V, then multiple speed sections can be set, including low-speed sections (corresponding speed range is 0km / h≤V≤30km / h), medium-speed sections (corresponding speed range is 30km / h<V≤60km / h) and high-speed sections (corresponding speed range is V>60km / h). The ECU will classify all navigation sections with predicted speeds between 0 and 30km / h (including 0km / h and 30km / h) as low-speed sections; all navigation sections with predicted speeds between 30 and 60km / h (excluding 30km / h and including 60km / h) as medium-speed sections; and all navigation sections with predicted speeds > 60km / h as high-speed sections.

[0118] S102-4: Based on the vehicle's 100-kilometer power consumption information at various vehicle speeds, determine the predicted driving power consumption of the vehicle in multiple speed sections.

[0119] In this embodiment, the power consumption information of the vehicle at various vehicle speeds can be determined according to the dynamic calculation formula and the power economy simulation results. Referring to Table 3, the power consumption information of a vehicle of a certain model at various vehicle speeds is shown.

[0120] Table 3 Electricity consumption per 100 kilometers

[0121]

[0122] It should be noted that the unit of vehicle speed in Table 3 is km / h, and the unit of power consumption per 100 kilometers is Kwh / 100km. Taking a vehicle speed of 50km / h as an example, its corresponding driving power consumption is 15Kwh / 100km, which means that the power consumed for driving 100 kilometers at a speed of 50km / h is 15Kwh.

[0123] It should be further explained that Table 3 is only an example of the electricity consumption information per 100 kilometers at some vehicle speeds. In actual use, the vehicle speed-electricity consumption curve can be fitted based on the electricity consumption information per 100 kilometers at multiple preset vehicle speeds obtained from the test. The vehicle speed-electricity consumption curve represents the electricity consumption information per 100 kilometers at each vehicle speed.

[0124] In a specific implementation, according to the 100km power consumption information of the vehicle at various speeds shown in Table 3 and the predicted speed-distance comparison table shown in Table 2, by multiplying the 100km power consumption and the distance at the same speed, the predicted driving power consumption of the corresponding distance at each predicted speed can be obtained. Referring to Table 4, the predicted driving power consumption of the vehicle at each predicted speed is shown.

[0125] Table 4 Predicted vehicle speed-predicted driving power consumption comparison table

[0126]

[0127] It should be noted that the unit of the predicted vehicle speed in Table 4 is km / h, and the unit of the predicted driving power consumption is Kwh. Taking the predicted vehicle speed of 60km / h as an example, its corresponding driving power consumption is W60, which means that the power consumed by all navigation sections with a predicted vehicle speed of 60km / h is W60.

[0128] In this embodiment, Table 4 is integrated according to the vehicle speed ranges corresponding to the low-speed section, the medium-speed section and the high-speed section, so as to obtain the predicted driving power consumption of each vehicle speed section shown in Table 5.

[0129] Table 5 Vehicle speed section-predicted driving power consumption comparison table

[0130]

[0131] It should be noted that the unit of the predicted driving power consumption in Table 5 is Kwh. Taking the low-speed section as an example, the corresponding predicted driving power consumption is ∑E_req_low, which means that the power consumed by all navigation sections with a predicted vehicle speed of 5~30km / h is ∑E_req_low.

[0132] In this embodiment, in order to facilitate subsequent calculations for energy management, the predicted driving power consumption can also be converted from the form of Kwh to the form of SOC (State of Charge) according to the conversion relationship between the remaining power and the power consumption. Referring to Table 6, the conversion relationship between the remaining power and the power consumption of a battery with a rated power of 62Kwh is shown.

[0133] Table 6 Electricity Conversion Table

[0134]

[0135] For example, if the predicted driving power consumption of a vehicle on a low-speed section is 22 Kwh, the predicted driving power consumption can be converted into 30%, indicating that the vehicle will consume 30% of the battery power on the low-speed section.

[0136] In this embodiment, the ECU can accurately calculate the predicted driving power consumption of each vehicle speed section through the above operations, thereby facilitating targeted energy management of each vehicle speed section.

[0137] In a feasible implementation manner, the step of determining the predicted driving time of the vehicle on the target accustomed route based on the speed correction coefficient of the target accustomed route and the navigation information in S102 may specifically include the following sub-steps:

[0138] S102-5: Determine the driving time of each navigation section based on the section distance and predicted vehicle speed of the vehicle on each navigation section.

[0139] In this embodiment, after calculating the predicted vehicle speed of each navigation section, the ECU may divide the section distance of each navigation section by the corresponding predicted vehicle speed to obtain the section travel time of each navigation section.

[0140] S102-6: Determine the sum of the driving time of each navigation section as the predicted driving time of the vehicle on the target accustomed route.

[0141] In this embodiment, by calculating the predicted driving time of the vehicle on the target accustomed route, the predicted accessory power consumption can be accurately calculated.

[0142] It should be noted that if the vehicle speed correction coefficient is a single coefficient set for the entire target accustomed route, in order to improve calculation efficiency, the predicted driving time of the target accustomed route can be calculated directly based on the vehicle speed correction coefficient and the reference driving time of the target accustomed route provided by the navigation information; if the vehicle speed correction coefficient includes multiple coefficients set for each navigation section, the predicted driving time of the vehicle on the target accustomed route can be calculated according to S102-5~S102-6.

[0143] It should be further explained that by using the vehicle's ECU to execute steps S102-1 to S102-6, the computing pressure of the cloud platform can be effectively alleviated, and the cloud platform can be effectively prevented from having insufficient computing power and untimely response when providing energy management services to a large number of vehicles that do not have navigation functions enabled at the same time.

[0144] In a feasible implementation manner, the plurality of vehicle speed sections include a low-speed section, a medium-speed section, and a high-speed section; the predicted driving power consumption includes a low-speed section driving power consumption corresponding to the low-speed section, a medium-speed section driving power consumption corresponding to the medium-speed section, and a high-speed section driving power consumption corresponding to the high-speed section; S103 may specifically include the following sub-steps:

[0145] S103 - 1 : Determine predicted accessory power consumption based on predicted driving time and accessory power.

[0146] In the present embodiment, the predicted accessory power indicates the amount of power consumed by the vehicle accessories per unit time.

[0147] In a specific implementation, the ECU can determine the vehicle's accessory power at regular intervals based on the vehicle's average power in a preset period before the current moment. For example, the average power of the previous 10 minutes can be selected as the vehicle's accessory power; and then the predicted accessory power consumption is calculated based on the product of the accessory power and the predicted driving time.

[0148] S103-2: Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption, the low-speed section driving power consumption, the medium-speed section driving power consumption and the high-speed section driving power consumption as the first power difference.

[0149] In this implementation, the first power difference can be calculated according to the following formula:

[0150] △E_PEM_1=E_current-E_min_PEM-∑E_req_ACC-∑E_req_low-∑E_req_mid-∑E_req_high (1);

[0151] Among them, △E_PEM_1 represents the first power difference; E_current represents the current remaining power; E_min_PEM represents the minimum remaining power; ∑E_req_ACC represents the predicted accessory power consumption; ∑E_req_low represents the driving power consumption in low-speed sections; ∑E_req_mid represents the driving power consumption in medium-speed sections; ∑E_req_high represents the driving power consumption in high-speed sections.

[0152] It should be noted that if △E_PEM_1≥0, it means that the current remaining power of the vehicle can meet the driving needs of the vehicle on low-speed sections, medium-speed sections and high-speed sections at the same time; if △E_PEM_1<0, it means that the current remaining power of the vehicle cannot meet the driving needs of the vehicle on low-speed sections, medium-speed sections and high-speed sections at the same time.

[0153] S103-3: Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption, the low-speed section driving power consumption and the medium-speed section driving power consumption as the second power difference.

[0154] In this implementation, the second power difference can be calculated according to the following formula:

[0155] △E_PEM_2=E_current-E_min_PEM-∑E_req_ACC-∑E_req_low-∑E_req_mid (2);

[0156] Wherein, ΔE_PEM_2 represents the second electrical quantity difference.

[0157] It should be noted that if △E_PEM_2≥0, it means that the current remaining power of the vehicle can meet the driving needs of the vehicle on low-speed sections and medium-speed sections at the same time; if △E_PEM_2<0, it means that the current remaining power of the vehicle cannot meet the driving needs of the vehicle on low-speed sections and medium-speed sections at the same time.

[0158] S103-4: Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption and the low-speed section driving power consumption as a third power difference.

[0159] In this implementation, the third power difference can be calculated according to the following formula:

[0160] △E_PEM_3=E_current-E_min_PEM-∑E_req_ACC-∑E_req_low (3);

[0161] Wherein, △E_PEM_3 represents the third electrical quantity difference.

[0162] It should be noted that if △E_PEM_3≥0, it means that the current remaining power of the vehicle can meet the driving needs of the vehicle on low-speed roads; if △E_PEM_3<0, it means that the current remaining power of the vehicle cannot meet the driving needs of the vehicle on low-speed roads.

[0163] S103-5: Based on the first power difference, the second power difference and the third power difference, determine the energy management strategies corresponding to the vehicle in the multiple speed sections.

[0164] In this embodiment, by analyzing the first power difference, the second power difference and the third power difference, it is possible to effectively determine which speed sections the vehicle's current remaining power can meet the driving requirements of, and then formulate corresponding energy management strategies for each speed section to perform predictive energy management.

[0165] In a specific implementation, S103-5 may specifically include the following sub-steps:

[0166] S103-5-1: When the first power difference is greater than the upper threshold of the preset hysteresis interval, determine that the energy management strategy of the vehicle in the low-speed section, the medium-speed section and the high-speed section is a pure electric drive strategy.

[0167] It should be noted that the hysteresis interval is a closed interval consisting of a lower threshold and an upper threshold. For example, the hysteresis interval can be set to [-1%, 1%], that is, the lower threshold can be set to -1% and the upper threshold can be set to 1%.

[0168] In this embodiment, by setting a hysteresis interval, the first power difference, the second power difference or the third power difference can be allowed to fluctuate within a certain range, thereby effectively avoiding frequent adjustments to the energy management strategy during driving.

[0169] In this embodiment, if the ECU detects that the first power difference is greater than the upper limit threshold of the hysteresis interval, it means that the vehicle has sufficient remaining power to support the vehicle's driving needs in various speed sections, and then determines that the vehicle's energy management strategy in each speed section is a pure electric drive strategy.

[0170] It should be noted that the pure electric drive strategy refers to a strategy of using a power battery as a power source and a drive motor to drive the vehicle.

[0171] S103-5-2: When the first charge difference is within the hysteresis interval, or when the first charge difference is less than the lower limit threshold and the second charge difference is greater than the upper limit threshold, determine that the energy management strategy of the vehicle in low-speed sections and medium-speed sections is a pure electric drive strategy, and determine that the energy management strategy of the vehicle in high-speed sections is a fuel drive strategy.

[0172] It should be noted that the fuel driving strategy refers to a strategy of using fuel as a power source to drive the vehicle using an engine.

[0173] In this embodiment, if the ECU detects that the first power difference is in the hysteresis interval, it means that the remaining power of the vehicle can only support the driving needs of the vehicle in various speed sections to a certain extent. At this time, due to the uncertainty of the vehicle's driving state and the inevitable calculation errors, it may cause the vehicle to be unable to drive according to the pure electric drive strategy in all sections. Therefore, if the ECU detects that the first power difference is in the hysteresis interval, it will allocate a pure electric drive strategy to low-speed sections and medium-speed sections, and allocate a fuel drive strategy to high-speed sections. In this way, it can ensure that the vehicle has sufficient remaining power to support the vehicle's driving needs in low-speed sections and medium-speed sections; at the same time, it can meet the vehicle's driving needs in high-speed sections. Since the engine is more efficient at high speeds, it can improve energy saving while ensuring the high power requirements of the vehicle.

[0174] In this embodiment, if the ECU detects that the first power difference is less than the lower limit threshold and the second power difference is greater than the upper limit threshold, it means that the vehicle has sufficient remaining power to support the vehicle's driving needs on low-speed sections and medium-speed sections, and then determines that the vehicle's energy management strategy on low-speed sections and medium-speed sections is a pure electric drive strategy, and determines that the vehicle's energy management strategy on high-speed sections is a fuel drive strategy.

[0175] S103-5-3: When the second charge difference is within the hysteresis interval, or when the second charge difference is less than the lower limit threshold and the third charge difference is greater than the upper limit threshold, the energy management strategy of the vehicle on the low-speed section is determined to be a pure electric drive strategy, the energy management strategy of the vehicle on the medium-speed section is determined to be a fuel drive strategy, and the energy management strategy of the vehicle on the high-speed section is determined to be a fuel-driven power generation strategy.

[0176] It should be noted that the fuel-driven power generation strategy refers to a strategy of using fuel as a power source to drive the vehicle using an engine and using the engine to drive a drive motor to charge a power battery.

[0177] In this embodiment, if the ECU detects that the second power difference is within the hysteresis interval, or the second power difference is less than the lower limit threshold and the third power difference is greater than the upper limit threshold, it means that the current remaining power of the vehicle can only fully meet the driving needs of the vehicle on low-speed sections. In order to ensure that the vehicle has sufficient remaining power, a fuel-driven power generation strategy will be allocated for high-speed sections, so that the vehicle can use the engine to drive the drive motor to charge the power battery on the high-speed section.

[0178] S103-5-4: When the third power difference is within the hysteresis interval, or when the third power difference is less than the lower limit threshold, the energy management strategy of the vehicle in the low-speed section is determined to be a pure electric drive strategy, and the energy management strategy of the vehicle in the medium-speed section and the high-speed section is determined to be a fuel-driven power generation strategy.

[0179] In this embodiment, if the ECU detects that the third power difference is within the hysteresis interval, the current remaining power of the vehicle may not be able to meet the driving needs of all low-speed sections; if the ECU detects that the third power difference is less than the lower limit threshold, it means that the current remaining power of the vehicle is low and can no longer meet the driving needs of all low-speed sections. At this time, in order to ensure the energy-saving effect at low speed, a pure electric drive strategy will be allocated to the low-speed section; at the same time, in order to prevent the current remaining power of the vehicle from further decreasing below the minimum remaining power, a fuel-driven power generation strategy will be allocated to the medium-speed section and the high-speed section, so that the vehicle can charge the power battery in both the medium-speed section and the high-speed section.

[0180] It should be noted that since low-speed sections are usually distributed in different sections of the target route, even if the third power difference is less than the lower limit threshold, since the vehicle can charge the power battery in both medium-speed sections and high-speed sections, the power battery can be replenished in time, so that the drive motor can be used for driving in each low-speed section, thereby ensuring the energy-saving effect.

[0181] In this embodiment, more speed sections can be divided according to actual needs. For example, the target accustomed route can be divided into low-speed sections, medium-low-speed sections, medium-speed sections, medium-high-speed sections and high-speed sections, and then the above five speed sections are matched with corresponding energy management strategies to achieve more sophisticated predictive energy management. This embodiment does not impose specific restrictions on the number of speed sections.

[0182] In a feasible implementation manner, in order to avoid frequent adjustment of the energy management strategy during driving, the vehicle energy management method may further include the following steps:

[0183] S104: When the first power difference enters or exits the hysteresis interval, or when the second power difference enters or exits the hysteresis interval, or when the third power difference enters or exits the hysteresis interval, maintain the energy management strategy of the previous moment.

[0184] It should be noted that the first power difference, the second power difference and the third power difference are dynamically changing parameters. For example, the first power difference, the second power difference and the third power difference can be set to be updated at preset time intervals, and then the energy management strategy of the vehicle in each speed section can be updated according to the updated power differences.

[0185] In this embodiment, considering that the first power difference, the second power difference and the third power difference may frequently enter or exit the hysteresis interval when they fluctuate, thus leading to frequent adjustment of the energy management strategy. Therefore, if the ECU detects that any of the first power difference, the second power difference and the third power difference enters or exits the hysteresis interval, the energy management strategy at the previous moment will be maintained.

[0186] Exemplarily, taking the first charge difference as an example, when the first charge difference is greater than the upper limit threshold of the hysteresis interval, it will be determined that the vehicle's energy management strategies in low-speed sections, medium-speed sections and high-speed sections are all pure electric drive strategies; at the next strategy update moment, the first charge difference decreases and enters the hysteresis interval from a state greater than the upper limit threshold. At this time, the ECU will not change the energy management strategy of the high-speed section from a pure electric drive strategy to a fuel drive strategy, but will continue to keep the energy management strategy of the high-speed section as a pure electric drive strategy.

[0187] In a feasible implementation manner, the vehicle energy management method may further include the following steps:

[0188] S105: When the energy management strategy is determined to be the pure electric drive strategy, the minimum remaining power is determined as the target remaining power of the vehicle.

[0189] In this embodiment, when the ECU is executing the pure electric drive strategy, it will use the minimum remaining power as the target remaining power of the vehicle for energy management. That is, before the current remaining power of the vehicle drops to the minimum remaining power, the drive motor will be controlled to drive the vehicle alone.

[0190] S106: When the energy management strategy is determined to be the fuel driving strategy, the current remaining power is determined as the target remaining power of the vehicle.

[0191] In this embodiment, the ECU will use the current remaining power as the target remaining power of the vehicle for energy management during the execution of the fuel driving strategy. That is, the vehicle will always be in a state of reaching the target remaining power, at which time the engine will be controlled to drive the vehicle alone.

[0192] S107: When the energy management strategy is determined to be the fuel-driven power generation strategy, a preset maximum remaining power is determined as the target remaining power of the vehicle.

[0193] In this embodiment, when the ECU is executing the fuel-driven power generation strategy, it will use the highest remaining power as the target remaining power of the vehicle for energy management. That is to say, while controlling the engine to drive the vehicle, it will also control the engine to drive the drive motor to charge the power battery. At this time, the highest remaining power will be used as the charging target of the power battery, and the drive motor will be controlled to charge the power battery.

[0194] In an example, the predicted vehicle speed is defined as V, the target remaining power is defined as SOC_PEM_tgt, the minimum remaining power is defined as E_min_PEM, the maximum remaining power is defined as SOC_tgtmax, the hysteresis interval is defined as [TSHmax, TSHmin], and multiple speed sections are defined including low-speed sections (corresponding to a speed range of 0km / h≤V≤30km / h), medium-speed sections (corresponding to a speed range of 30km / h<V≤60km / h) and high-speed sections (corresponding to a speed range of V>60km / h). Based on the first power difference, the second power difference and the third power difference, the following energy management and SOC management can be implemented:

[0195] (1) If after initialization, △E_PEM_1>TSHmax.

[0196] Low-speed sections (0km / h≤V≤30km / h): execute pure electric drive strategy; SOC_PEM_tgt=SOC_min_PEM.

[0197] Medium-speed sections (30km / h<V≤60km / h): implement pure electric drive strategy; SOC_PEM_tgt=SOC_min_PEM.

[0198] High-speed sections (V>60km / h): implement pure electric drive strategy; SOC_PEM_tgt=SOC_min_PEM.

[0199] (2) If TSHmin≤△E_PEM_1≤TSHmax, or, △E_PEM_1<TSHmin and △E_PEM_2>TSHmax.

[0200] Low-speed sections (0km / h≤V≤30km / h): execute pure electric drive strategy; SOC_PEM_tgt=SOC_min_PEM.

[0201] Medium-speed sections (30km / h<V≤60km / h): implement pure electric drive strategy; SOC_PEM_tgt=SOC_min_PEM.

[0202] High-speed section (V>60km / h): execute fuel driving strategy; SOC_PEM_tgt=SOC_tgtcurrent.

[0203] It should be noted that when △E_PEM_1 enters or exits the hysteresis interval, the energy management strategy of the previous moment is maintained; if △E_PEM_1 is in the hysteresis interval after initialization, the energy management strategy of situation (2) is executed.

[0204] (3) If TSHmin≤△E_PEM_2≤TSHmax, or, △E_PEM_2<TSHmin and △E_PEM_3>TSHmax.

[0205] Low-speed sections (0km / h≤V≤30km / h): execute pure electric drive strategy; SOC_PEM_tgt=SOC_min_PEM.

[0206] Medium-speed section (30km / h<V≤60km / h): execute fuel driving strategy; SOC_PEM_tgt=SOC_tgtcurrent.

[0207] High-speed section (V>60km / h): Execute the fuel-driven power generation strategy; SOC_PEM_tgt=SOC_tgtmax.

[0208] It should be noted that when △E_PEM_2 enters or exits the hysteresis interval, the energy management strategy of the previous moment is maintained; if △E_PEM_2 is in the hysteresis interval after initialization, the energy management strategy of situation (3) is executed.

[0209] (4) If TSHmin≤△E_PEM_3≤TSHmax, or, △E_PEM_3<TSHmin.

[0210] Low-speed sections (0km / h≤V≤30km / h): execute pure electric drive strategy; SOC_PEM_tgt=SOC_min_PEM.

[0211] Medium-speed section (30km / h<V≤60km / h): implement fuel-driven power generation strategy; SOC_PEM_tgt=SOC_tgtmax.

[0212] High-speed section (V>60km / h): Execute the fuel-driven power generation strategy; SOC_PEM_tgt=SOC_tgtmax.

[0213] It should be noted that when △E_PEM_3 enters or exits the hysteresis interval, the energy management strategy of the previous moment is maintained; if △E_PEM_3 is located in the hysteresis interval after initialization, the energy management strategy of situation (4) is executed.

[0214] In this embodiment, the cloud platform can be used to accurately identify the target accustomed route without turning on the navigation of the vehicle, and then by comprehensively considering the navigation information of the target accustomed route, the speed correction coefficient and the user's driving habits, targeted predictive energy management can be performed on each speed section of the target accustomed route. In this way, through the collaboration of the cloud, the vehicle and the user, the energy saving effect of the vehicle on each speed section of the target accustomed route can be improved while satisfying the user's personalized driving habits, thereby effectively improving the user's driving experience.

[0215] In the second aspect, based on the same inventive concept, refer to Figure 2 , the embodiment of the present application provides another vehicle energy management method, which is applied to a cloud platform. The method may include the following steps:

[0216] S201: Acquire driving information uploaded by the vehicle when the navigation function is not turned on, and determine whether the vehicle is traveling on a target accustomed route based on the driving information.

[0217] It should be noted that the execution subject of this embodiment is a cloud platform with data processing, network communication and program running functions, for example, the cloud platform can be a cloud server, a high-performance computing server or a distributed server, etc. The cloud platform can be connected to multiple certified vehicles to achieve energy management of multiple vehicles.

[0218] In this embodiment, the cloud platform will count the historical driving routes with the most repeated trips by the vehicle within a preset period based on the historical driving data of the vehicle, and then obtain a common route library containing at least one common route of the user. Specifically, the route with the number of repeated trips by the vehicle greater than the number threshold can be determined as the common route of the user.

[0219] In this embodiment, after obtaining the habitual route library of any vehicle, once the driving information uploaded by the vehicle without the navigation function turned on is obtained, the recognition of the habitual route will be triggered to determine whether the vehicle is traveling on the target habitual route.

[0220] S202: When it is determined that the vehicle is traveling on the target accustomed route, determine the minimum remaining power of the vehicle.

[0221] In the specific implementation, once the cloud platform determines that the vehicle is traveling on the target accustomed route, it will determine the vehicle's minimum remaining power based on the vehicle's charging habits and the charging location of the target accustomed route. The minimum remaining power refers to the minimum remaining power that can meet the vehicle's driving needs on the target accustomed route.

[0222] It should be noted that during the operation of the vehicle, the historical charging location information and historical charging information will be uploaded to the cloud platform. The cloud platform will determine the vehicle's charging habits and the charging location of each user's usual route based on the vehicle's historical charging location information and historical charging information; and then determine the vehicle's minimum remaining power based on the charging habits and the charging location of the target usual route. Among them, charging habits are used to characterize the user's charging behavior preferences for the vehicle, which can specifically include regular charging type, irregular charging type or occasional charging type.

[0223] S203: The minimum remaining power, navigation information of the vehicle on the target accustomed route, and the speed correction coefficient are sent to the vehicle, so that the vehicle can determine the predicted driving power consumption of the vehicle on multiple speed sections of the target accustomed route and the predicted driving time of the vehicle on the target accustomed route based on the speed correction coefficient and navigation information of the target accustomed route; and determine the energy management strategy corresponding to each of the multiple speed sections of the vehicle based on the predicted driving power consumption, predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle.

[0224] In this embodiment, in order to calculate the speed correction coefficient, the cloud platform will request the navigation data of the user's accustomed route from the map provider whenever it detects that the vehicle is traveling on any user's accustomed route, and calculate the navigation speed of each navigation section of the user's accustomed route based on the navigation data; then compare the navigation speed with the actual speed of the vehicle on the user's accustomed route to determine the speed difference value of each navigation section; finally, determine the speed correction coefficient of the vehicle based on the speed difference value of each navigation section. It should be noted that the cloud platform will correct the speed correction coefficient of each user's accustomed route every preset period to ensure the accuracy and real-time performance of the speed correction coefficient.

[0225] In this embodiment, after determining that the vehicle is traveling on the target accustomed route, the cloud platform will request navigation information of the target accustomed route from the map provider, and package the navigation information, the vehicle speed correction factor and the minimum remaining power into a data packet and then transparently transmit it to the TSP (Telematics Service Provider). The TSP encapsulates the data packet and sends the data packet to the vehicle according to the remote control protocol with the vehicle. After receiving the data packet, the vehicle will perform data verification on the data packet, and after the verification is successful, the data in the data packet will be converted into a CAN (Controller Area Network) signal. After parsing the data packet, the vehicle's ECU can perform targeted predictive energy management on the target accustomed route based on the parsed minimum remaining power, navigation information of the target accustomed route and the vehicle speed correction factor.

[0226] In this embodiment, the cloud platform can statistically analyze the vehicle's habitual route library, the speed correction coefficient of each user's habitual route and other information based on the historical information uploaded by the vehicle. Furthermore, when the vehicle's navigation function is not turned on, the cloud platform can accurately identify the target habitual route and accurately calculate the minimum remaining power. By sending the minimum remaining power and the vehicle's navigation information and speed correction coefficient on the target habitual route to the vehicle, the vehicle can perform targeted predictive energy management on each speed section of the target habitual route by comprehensively considering the navigation information of the target habitual route, the speed correction coefficient and the user's driving habits.

[0227] In a feasible implementation manner, the driving information includes the departure time, the origin location and the current driving route of the vehicle; the step of determining whether the vehicle is traveling on the target accustomed route based on the driving information in S201 may specifically include the following sub-steps:

[0228] S201-1: Determine at least one pending route from among a plurality of user's usual routes based on the departure time and the origin location.

[0229] In this embodiment, multiple user's usual routes are determined based on the historical driving routes of the vehicle. Since each user's usual route is a route that the user travels frequently and usually has a relatively stable departure time and origin location, the cloud platform will first select at least one pending usual route from multiple user's usual routes based on the departure time and origin location of the vehicle; and further determine a unique target usual route from at least one pending usual route based on the current driving route.

[0230] In a specific implementation, the user's usual route includes a departure time tag and a departure location tag. The departure time tag indicates the time range when the user usually departs from the user's usual route; the departure location tag indicates the area range when the user usually departs from the user's usual route.

[0231] For example, if the departure time label of a user's usual walking route is 7:00-7:30 in the morning, and the starting location label is a circular area with a radius of 150 meters and the target location as the center, it means that the user is accustomed to using a certain time between 7:00 and 7:30 as the departure time of the user's usual walking route, and is accustomed to using a certain place in the circular area as the starting location of the user's usual walking route.

[0232] In this embodiment, when the cloud platform is judging a pending habitual route, it can determine that the user's habitual route is a pending habitual route for any user's habitual route if the departure time is within the time range indicated by the departure time tag and the origin location is within the area range indicated by the origin location tag.

[0233] S201 - 2: Determine the similarity between the current driving route and at least one pending accustomed route.

[0234] In this embodiment, the cloud platform will update the current driving route in real time during the driving of the vehicle, and further update the similarity between the current driving route and at least one pending accustomed route in real time.

[0235] In a specific implementation, the cloud platform can solve the similarity between the current driving route and at least one pending habitual route based on algorithms such as Hausdorff distance and Longest Common Subsequence (LCSS). Specifically, the current driving route includes multiple position coordinates, and each user's habitual route includes multiple preset position coordinates; by using Hausdorff distance or LCSS, based on the multiple position coordinates of the current driving route and the multiple preset position coordinates of each pending habitual route, the similarity between the current driving route and each pending habitual route can be solved.

[0236] In specific implementations, the cloud platform can also build and train classification models such as KNN (K-Nearest Neighbors) and support vector machines by comparing the trajectory overlap between the actual complete driving route and the user's usual route as a label. The cloud platform can predict the destination of the vehicle and the predicted route to the destination by inputting the current driving route into the classification model, and then determine the similarity between the current driving route and at least one pending usual route based on the trajectory overlap between the predicted route and the user's usual route.

[0237] S201 - 3 : determining the undetermined accustomed route with the highest similarity as the target accustomed route, and determining that the vehicle is traveling on the target accustomed route when the similarity of the target accustomed route is greater than a similarity threshold.

[0238] In this embodiment, since there is only one target accustomed route, the cloud platform will first select the pending accustomed route with the highest similarity as the target accustomed route. If the similarity of the target accustomed route is greater than the similarity threshold, it means that the vehicle is traveling on the target accustomed route, thereby triggering energy management of the vehicle on the target accustomed route. It should be noted that by setting the similarity threshold, misjudgment can be effectively avoided.

[0239] In this embodiment, the cloud platform can accurately identify the target's usual route by comprehensively considering the vehicle's departure time, origin location and current driving route.

[0240] In a feasible implementation manner, the step of determining the minimum remaining power of the vehicle in S202 may specifically include the following sub-steps:

[0241] S202-1: Determine the charging habit of the vehicle and the charging position of the target habitual route.

[0242] In this embodiment, charging habits are used to characterize the user's preference for vehicle charging behavior, which may specifically include regular charging type, irregular charging type or occasional charging type; the charging location indicates the location where the vehicle can be charged on the target habitual route, which may specifically refer to the charging location of the origin and destination.

[0243] In this embodiment, the cloud platform can obtain the historical charging location information and historical charging information of the vehicle in a preset historical period; and determine the charging location of each user's usual route based on the historical charging location information; at the same time, determine the vehicle's charging habits based on the historical charging information.

[0244] In a specific implementation, the cloud platform can count the charging frequency of the vehicle at intervals, such as once a week, based on historical charging information, and determine the fluctuation amplitude of the charging frequency based on the continuous charging frequency. The cloud platform can determine that the charging habit is a frequent charging type when the historical charging information indicates that the charging frequency of the vehicle is greater than the first frequency threshold and the fluctuation amplitude of the charging frequency is less than the first amplitude threshold; when the charging frequency is less than the second frequency threshold, the charging habit is determined to be an occasional charging type; when the fluctuation amplitude of the charging frequency of the vehicle is greater than the second amplitude threshold, the charging habit is determined to be an irregular charging type. Among them, the first frequency threshold is greater than or equal to the second frequency threshold; the first amplitude threshold is less than or equal to the second amplitude threshold.

[0245] S202-2: When the charging habit is a regular charging type and charging locations exist at both the origin and destination of the target habitual route, a preset reference remaining power is determined as the minimum remaining power for the vehicle to arrive at the destination and return to the origin.

[0246] In this embodiment, if the cloud platform detects that the charging habit is a frequent charging type and there are charging locations at both the origin and destination of the target accustomed route, it means that the user usually charges the vehicle at the origin and destination. At this time, the vehicle can be allowed to consume more power while traveling on the target accustomed route. Therefore, whether going to the destination or returning to the origin, the baseline remaining power can be determined as the minimum remaining power.

[0247] It should be noted that the target commuting route is usually a commuting route. Therefore, it is necessary to consider the battery status of the vehicle at the origin and destination to ensure the battery demand of the vehicle to and from the target commuting route.

[0248] S202-3: When the charging habit is a regular charging type and a charging location exists only at the starting point of the target habitual route, a sum of a reference remaining power and a first preset remaining power is determined as a minimum remaining power for the vehicle to arrive at the destination.

[0249] In this embodiment, if the cloud platform detects that the charging habit is a frequent charging type and there is only a charging location at the starting point of the target common route, it means that the user can only charge the vehicle at the starting point. At this time, in order to ensure that the vehicle has enough power to return after reaching the destination, the cloud platform will determine the sum of the baseline remaining power and the first preset remaining power as the minimum remaining power for the vehicle to reach the destination.

[0250] S202-4: When the charging habit is the regular charging type and there is a charging location only at the destination of the target route, the baseline remaining power is determined as the minimum remaining power for the vehicle to arrive at the destination, and the sum of the baseline remaining power and the first preset remaining power is determined as the minimum remaining power for the vehicle to return to the starting point.

[0251] In this embodiment, if the cloud platform detects that the charging habit is a frequent charging type and there is only a charging location at the destination of the target accustomed route, it means that the user can only charge the vehicle at the destination. At this time, in order to ensure that the vehicle has enough power to travel the next time after returning, the cloud platform will determine the sum of the baseline remaining power and the first preset remaining power as the minimum remaining power of the vehicle returning to the starting point; since the destination of the target accustomed route can charge the vehicle, the baseline remaining power can be directly determined as the minimum remaining power of the vehicle to reach the destination.

[0252] S202-5: When the charging type is an irregular charging type or an occasional charging type, a sum of the reference remaining power and the second preset remaining power is determined as a minimum remaining power for the vehicle to arrive at the destination.

[0253] In this embodiment, if the cloud platform detects that the charging type is irregular or occasional, it cannot guarantee whether the user will charge the vehicle at the origin and destination. At this time, in order to ensure that the vehicle has enough power to travel back and forth on the target route, the cloud platform will determine the sum of the baseline remaining power and the second preset remaining power as the minimum remaining power for the vehicle to reach the destination.

[0254] In this embodiment, by comprehensively considering the charging habits of the vehicle and the charging locations at the origin and destination, a suitable minimum remaining power can be determined for the vehicle, thereby effectively avoiding the situation where the remaining power of the vehicle is too low to drive the vehicle on the target route.

[0255] In the third aspect, based on the same inventive concept, refer to Figure 3 The embodiment of the present application provides a vehicle energy management device 300, which is applied to a vehicle. The vehicle energy management device 300 includes:

[0256] The information uploading module 301 is used to upload the driving information of the vehicle to the cloud platform when the navigation function of the vehicle is not turned on, so that the cloud platform can determine the minimum remaining power of the vehicle when it is determined that the vehicle is traveling on the target accustomed route based on the driving information, and send the minimum remaining power and the navigation information and speed correction coefficient of the vehicle on the target accustomed route to the vehicle;

[0257] A parameter prediction module 302, for determining a predicted driving power consumption of the vehicle on a plurality of speed sections of the target accustomed route and a predicted driving time of the vehicle on the target accustomed route based on a speed correction coefficient of the target accustomed route and navigation information;

[0258] The strategy determination module 303 is used to determine the energy management strategy corresponding to the vehicle in multiple speed sections based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle.

[0259] It should be noted that the specific implementation of the vehicle energy management device 300 in the embodiment of the present application refers to the specific implementation of the vehicle energy management method proposed in the first aspect of the embodiment of the present application, and will not be repeated here.

[0260] In the fourth aspect, based on the same inventive concept, refer to Figure 4 , the embodiment of the present application provides another vehicle energy management device 400, which is applied to a cloud platform. The vehicle energy management device 400 includes:

[0261] The route determination module 401 is used to obtain the driving information uploaded by the vehicle when the navigation function is not turned on, and determine whether the vehicle is traveling on the target accustomed route based on the driving information;

[0262] An information determination module 402 is used to determine the minimum remaining power of the vehicle when it is determined that the vehicle is traveling on the target accustomed route;

[0263] The information sending module 403 is used to send the minimum remaining power and the navigation information and speed correction coefficient of the vehicle on the target accustomed route to the vehicle, so that the vehicle can determine the predicted driving power consumption of the vehicle in multiple speed sections of the target accustomed route and the predicted driving time of the vehicle on the target accustomed route based on the speed correction coefficient and navigation information of the target accustomed route; and determine the energy management strategy corresponding to the vehicle in multiple speed sections based on the predicted driving power consumption, predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle.

[0264] It should be noted that the specific implementation of the vehicle energy management device 400 of the embodiment of the present application refers to the specific implementation of the vehicle energy management method proposed in the second aspect of the embodiment of the present application, and will not be repeated here.

[0265] In the fifth aspect, based on the same inventive concept, refer to Figure 5 , an embodiment of the present application provides a vehicle energy management system 500, the system comprising a vehicle 501 and a cloud platform 502;

[0266] The vehicle 501 is used to upload the driving information of the vehicle 501 to the cloud platform 502 when the navigation function of the vehicle 501 is not turned on;

[0267] The cloud platform 502 is used to determine the minimum remaining power of the vehicle 501 when it is determined based on the driving information that the vehicle 501 is traveling on the target accustomed route, and send the minimum remaining power and the navigation information and the speed correction coefficient of the vehicle 501 on the target accustomed route to the vehicle 501;

[0268] Vehicle 501 is used to determine the predicted driving power consumption of vehicle 501 in multiple speed sections of the target accustomed route and the predicted driving time of vehicle 501 in the target accustomed route based on the speed correction coefficient of the target accustomed route and the navigation information; and determine the energy management strategy corresponding to vehicle 501 in multiple speed sections based on the predicted driving power consumption, predicted driving time, minimum remaining power, and current remaining power and accessory power of vehicle 501.

[0269] It should be noted that the specific implementation of the vehicle energy management system 500 of the embodiment of the present application refers to the specific implementation of a vehicle energy management method proposed in the first aspect of the embodiment of the present application and another vehicle energy management method proposed in the second aspect, which will not be repeated here.

[0270] In the sixth aspect, based on the same inventive concept, an embodiment of the present application provides a computer-readable storage medium on which an executable program is stored. When the executable program is executed by a processor, it implements a vehicle energy management method proposed in the first aspect of the present application or another vehicle energy management method proposed in the second aspect of the present application.

[0271] It should be noted that the specific implementation of the computer-readable storage medium in the embodiment of the present application refers to the specific implementation of a vehicle energy management method proposed in the first aspect of the embodiment of the present application and another vehicle energy management method proposed in the second aspect, which will not be repeated here.

[0272] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may 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.) containing computer-usable program codes.

[0273] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0274] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1A function specified in one or more boxes.

[0275] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0276] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0277] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0278] The vehicle energy management method, system and computer-readable storage medium provided by the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A vehicle energy management method, characterized in that: Applied to a vehicle, the method comprises: When the navigation function of the vehicle is not turned on, uploading the driving information of the vehicle to the cloud platform, so that the cloud platform determines the minimum remaining power of the vehicle when the vehicle is traveling on a target accustomed route based on the driving information, and sends the minimum remaining power and the navigation information and vehicle speed correction coefficient of the vehicle on the target accustomed route to the vehicle; Determining, based on the speed correction coefficient of the target accustomed route and the navigation information, the predicted driving power consumption of the vehicle in a plurality of speed sections of the target accustomed route and the predicted driving time of the vehicle on the target accustomed route; Determining energy management strategies corresponding to each of the plurality of speed sections for the vehicle based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle; The plurality of vehicle speed sections include a low-speed section, a medium-speed section and a high-speed section; the predicted driving power consumption includes a low-speed section driving power consumption corresponding to the low-speed section, a medium-speed section driving power consumption corresponding to the medium-speed section, and a high-speed section driving power consumption corresponding to the high-speed section; The step of determining the energy management strategy corresponding to each of the plurality of speed sections of the vehicle based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle comprises: Determining predicted accessory power consumption based on the predicted driving duration and the accessory power; Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption, the low-speed section driving power consumption, the medium-speed section driving power consumption and the high-speed section driving power consumption as a first power difference; Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption, the low-speed section driving power consumption, and the medium-speed section driving power consumption as a second power difference; Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption and the low-speed section driving power consumption as a third power difference; Determining energy management strategies corresponding to the vehicle in each of the plurality of speed sections based on the first power difference, the second power difference and the third power difference; Among them, the first power difference is used to indicate whether the current remaining power can simultaneously meet the driving needs of the vehicle on the low-speed section, the medium-speed section and the high-speed section; the second power difference is used to indicate whether the current remaining power can simultaneously meet the driving needs of the vehicle on the low-speed section and the medium-speed section; the third power difference is used to indicate whether the current remaining power can simultaneously meet the driving needs of the vehicle on the low-speed section.

2. The vehicle energy management method according to claim 1, characterized in that: The navigation information includes the segment distances and reference driving times of multiple navigation segments of the target accustomed route; The step of determining the predicted driving power consumption of the vehicle in a plurality of speed sections of the target accustomed route based on the speed correction coefficient of the target accustomed route and the navigation information comprises: Determining the navigation vehicle speed of each navigation section based on the section distance and reference driving time of each navigation section; Based on the vehicle speed correction coefficient, the navigation vehicle speed of each navigation section is corrected to obtain the predicted vehicle speed of the vehicle in each navigation section; Based on the predicted vehicle speed of each navigation section, the plurality of navigation sections are divided into a plurality of vehicle speed sections; wherein different vehicle speed sections correspond to different vehicle speed ranges; Based on the power consumption information per 100 kilometers of the vehicle at various vehicle speeds, the predicted driving power consumption of the vehicle in the plurality of vehicle speed sections is determined.

3. The vehicle energy management method according to claim 2, characterized in that: The step of determining the predicted driving time of the vehicle on the target accustomed route based on the speed correction coefficient of the target accustomed route and the navigation information comprises: Determining the driving time of each navigation section based on the section distance and predicted vehicle speed of the vehicle on each navigation section; The sum of the driving time of each navigation section is determined as the predicted driving time of the vehicle on the target accustomed route.

4. The vehicle energy management method according to claim 1, characterized in that: The step of determining the energy management strategies corresponding to the vehicle in the plurality of speed sections based on the first power difference, the second power difference and the third power difference comprises: When the first electric quantity difference is greater than an upper threshold of a preset hysteresis interval, determining that the energy management strategy of the vehicle in the low-speed section, the medium-speed section and the high-speed section is a pure electric drive strategy; the hysteresis interval is a closed interval consisting of a lower threshold and an upper threshold; When the first power difference is within the hysteresis interval, or when the first power difference is less than the lower limit threshold and the second power difference is greater than the upper limit threshold, determining that the energy management strategy of the vehicle in the low-speed section and the medium-speed section is a pure electric drive strategy, and determining that the energy management strategy of the vehicle in the high-speed section is a fuel drive strategy; When the second power difference is within the hysteresis interval, or when the second power difference is less than the lower limit threshold and the third power difference is greater than the upper limit threshold, the energy management strategy of the vehicle on the low-speed section is determined to be the pure electric drive strategy, the energy management strategy of the vehicle on the medium-speed section is determined to be the fuel drive strategy, and the energy management strategy of the vehicle on the high-speed section is determined to be the fuel drive power generation strategy; When the third electrical charge difference is within the hysteresis interval, or when the third electrical charge difference is less than the lower limit threshold, the energy management strategy of the vehicle in the low-speed section is determined to be the pure electric drive strategy, and the energy management strategy of the vehicle in the medium-speed section and the high-speed section is determined to be the fuel-driven power generation strategy.

5. The vehicle energy management method according to claim 4, characterized in that: The method further comprises: When the first power difference enters or exits the hysteresis interval, or when the second power difference enters or exits the hysteresis interval, or when the third power difference enters or exits the hysteresis interval, the energy management strategy of the previous moment is maintained.

6. The vehicle energy management method according to claim 4, characterized in that: The method further comprises: In the case where the energy management strategy is determined to be the pure electric drive strategy, determining the minimum remaining power as the target remaining power of the vehicle; In the case where the energy management strategy is determined to be the fuel driving strategy, determining the current remaining power as the target remaining power of the vehicle; When it is determined that the energy management strategy is the fuel-driven power generation strategy, a preset maximum remaining power is determined as the target remaining power of the vehicle.

7. A vehicle energy management method, characterized in that: Applied to a cloud platform, the method includes: Acquire driving information uploaded by the vehicle when the navigation function is not turned on, and determine whether the vehicle is traveling on a target accustomed route based on the driving information; When it is determined that the vehicle is traveling on the target accustomed route, determining a minimum remaining power of the vehicle; The minimum remaining power, navigation information of the vehicle on the target accustomed route, and a speed correction coefficient are sent to the vehicle, so that the vehicle determines the predicted driving power consumption of the vehicle on multiple speed sections of the target accustomed route and the predicted driving time of the vehicle on the target accustomed route based on the speed correction coefficient and navigation information of the target accustomed route; and based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle, determines the energy management strategy corresponding to each of the multiple speed sections of the vehicle; The plurality of vehicle speed sections include a low-speed section, a medium-speed section and a high-speed section; the predicted driving power consumption includes a low-speed section driving power consumption corresponding to the low-speed section, a medium-speed section driving power consumption corresponding to the medium-speed section, and a high-speed section driving power consumption corresponding to the high-speed section; The step of determining the energy management strategy corresponding to each of the plurality of speed sections of the vehicle based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle comprises: Determining predicted accessory power consumption based on the predicted driving duration and the accessory power; Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption, the low-speed section driving power consumption, the medium-speed section driving power consumption and the high-speed section driving power consumption as a first power difference; Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption, the low-speed section driving power consumption, and the medium-speed section driving power consumption as a second power difference; Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption and the low-speed section driving power consumption as a third power difference; Determining energy management strategies corresponding to the vehicle in each of the plurality of speed sections based on the first power difference, the second power difference and the third power difference; Among them, the first power difference is used to indicate whether the current remaining power can simultaneously meet the driving needs of the vehicle on the low-speed section, the medium-speed section and the high-speed section; the second power difference is used to indicate whether the current remaining power can simultaneously meet the driving needs of the vehicle on the low-speed section and the medium-speed section; the third power difference is used to indicate whether the current remaining power can simultaneously meet the driving needs of the vehicle on the low-speed section.

8. The vehicle energy management method according to claim 7, characterized in that: The driving information includes the departure time, the origin location and the current driving route of the vehicle; The step of determining whether the vehicle is traveling on a target accustomed route based on the driving information includes: Based on the departure time and the origin location, determining at least one pending habitual route from a plurality of user habitual routes; the plurality of user habitual routes are determined based on the historical driving routes of the vehicle; Determining a similarity between the current driving route and at least one of the pending accustomed routes; The undetermined habitual route with the highest similarity is determined as the target habitual route, and when the similarity of the target habitual route is greater than a similarity threshold, it is determined that the vehicle is traveling on the target habitual route.

9. The vehicle energy management method according to claim 8, characterized in that: The user's usual route includes a departure time tag and a starting location tag; The step of determining at least one pending common route from a plurality of common routes of the user based on the departure time and the origin location comprises: For any user's usual route, when the departure time is within the time range indicated by the departure time tag and the origin location is within the area range indicated by the origin location tag, the user's usual route is determined to be the pending usual route.

10. The vehicle energy management method according to claim 7, characterized in that: The step of determining the minimum remaining power of the vehicle comprises: Determining the charging habits of the vehicle and the charging location of the target habitual route; When the charging habit is a frequent charging type and charging locations exist at both the origin and the destination of the target habitual route, a preset reference remaining power is determined as the minimum remaining power for the vehicle to arrive at the destination and return to the origin; In a case where the charging habit is the regular charging type and a charging location exists only at the origin of the target habitual route, determining the sum of the reference remaining power and the first preset remaining power as the minimum remaining power for the vehicle to reach the destination; When the charging habit is the regular charging type and there is a charging location only at the destination of the target habitual route, the reference remaining power is determined as the minimum remaining power for the vehicle to reach the destination, and the sum of the reference remaining power and the first preset remaining power is determined as the minimum remaining power for the vehicle to return to the origin; In a case where the charging type is an irregular charging type or an occasional charging type, a sum of the reference remaining power and a second preset remaining power is determined as a minimum remaining power for the vehicle to arrive at the destination.

11. A vehicle energy management system, characterized in that: The system includes a vehicle and a cloud platform; The vehicle is used to upload the driving information of the vehicle to the cloud platform when the navigation function of the vehicle is not turned on; The cloud platform is used to determine the minimum remaining power of the vehicle when it is determined that the vehicle is traveling on a target accustomed route based on the driving information, and send the minimum remaining power and navigation information and a speed correction coefficient of the vehicle on the target accustomed route to the vehicle; The vehicle is used to determine the predicted driving power consumption of the vehicle in multiple speed sections of the target accustomed route and the predicted driving time of the vehicle on the target accustomed route based on the speed correction coefficient of the target accustomed route and the navigation information; and determining energy management strategies corresponding to each of the plurality of speed sections for the vehicle based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle; The plurality of speed sections include a low-speed section, a medium-speed section and a high-speed section; The predicted driving power consumption includes the low-speed section driving power consumption corresponding to the low-speed section, the medium-speed section driving power consumption corresponding to the medium-speed section, and the high-speed section driving power consumption corresponding to the high-speed section; The step of determining the energy management strategy corresponding to each of the plurality of speed sections of the vehicle based on the predicted driving power consumption, the predicted driving time, the minimum remaining power, and the current remaining power and accessory power of the vehicle comprises: Determining predicted accessory power consumption based on the predicted driving duration and the accessory power; Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption, the low-speed section driving power consumption, the medium-speed section driving power consumption and the high-speed section driving power consumption as a first power difference; Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption, the low-speed section driving power consumption, and the medium-speed section driving power consumption as a second power difference; Determine the difference between the current remaining power and the minimum remaining power, the predicted accessory power consumption and the low-speed section driving power consumption as a third power difference; Determining energy management strategies corresponding to the vehicle in each of the plurality of speed sections based on the first power difference, the second power difference and the third power difference; Among them, the first power difference is used to indicate whether the current remaining power can simultaneously meet the driving needs of the vehicle on the low-speed section, the medium-speed section and the high-speed section; the second power difference is used to indicate whether the current remaining power can simultaneously meet the driving needs of the vehicle on the low-speed section and the medium-speed section; the third power difference is used to indicate whether the current remaining power can simultaneously meet the driving needs of the vehicle on the low-speed section.

12. A computer-readable storage medium having an executable program stored thereon, characterized in that: When the executable program is executed by a processor, the vehicle energy management method according to any one of claims 1 to 6 or the vehicle energy management method according to any one of claims 7 to 10 is implemented.

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