A hybrid vehicle real-time energy distribution method and device

Abstract

The application discloses a hybrid vehicle real-time energy distribution method and device, determines a traffic scene where a vehicle is located according to a current position of the vehicle, obtains driving information of a vehicle speed, acceleration and brake frequency, determines a current driving style of the vehicle according to the traffic scene where the vehicle is located and the vehicle driving information, and selects a charging and discharging strategy from multiple charging and discharging strategies according to the current driving style of the vehicle and the traffic scene where the vehicle is located, wherein the multiple charging and discharging strategies have different charging target battery state of charge (SOC) and discharging target SOC. The application introduces the position information of the vehicle and the current driving information of the vehicle, judges the current driving style and the traffic scene, selects the charging and discharging strategy of the current vehicle, realizes different energy distribution modes under different driving styles and traffic scenes, and achieves the effect of flexible energy distribution.

Description

Technical Field

[0001] This application relates to the field of automotive control, specifically to a method and apparatus for real-time energy distribution in hybrid electric vehicles. Background Technology

[0002] With the development of automotive technology, hybrid vehicles have attracted great attention in the automotive industry and become a key focus of automotive research and development. Hybrid vehicles use an internal combustion engine and an electric motor as hybrid power sources, combining the advantages of a fuel engine (good power, fast response, and long operating time) with the benefits of an electric motor (no pollution and low noise), thus showing promising development prospects.

[0003] The state of charge (SOC) of a battery, also known as the remaining capacity, is the ratio of the amount of electricity that the battery can actually provide in its current state to the amount of electricity that it can provide when fully charged.

[0004] Most existing hybrid electric vehicles employ energy strategies based on simple, fixed rules: when the battery charge falls below a certain discharge target SOC, they enter parallel charging mode; when the battery charge exceeds a certain charging SOC, they return to pure electric driving mode. This simple, fixed energy allocation rule fails to accommodate different driving styles and traffic scenarios, resulting in significant variations in energy consumption under different driving styles and traffic conditions. This leads to unreasonable energy distribution and a poor driving experience. Summary of the Invention

[0005] In view of this, this application provides a real-time energy distribution method and device for plug-in hybrid electric vehicles, which solves the problem that fixed-rule energy management methods cannot adjust the target SOC of charging / discharging according to the current driving style and traffic scenario, and achieves the purpose of intelligently managing the vehicle's energy distribution method according to driving style and traffic scenario.

[0006] To address the above problems, the technical solutions provided in this application are as follows:

[0007] In a first aspect of this application, a real-time energy distribution method for a plug-in hybrid electric vehicle is provided, the method comprising:

[0008] Determine the traffic scenario in which the vehicle is located based on its current position;

[0009] Obtain vehicle driving information, including information on vehicle speed, acceleration, and braking frequency;

[0010] The current driving style of the vehicle is determined based on the traffic scenario in which the vehicle is located and the vehicle's driving information;

[0011] Based on the vehicle's current driving style and the traffic scenario in which the vehicle is located, a charging and discharging strategy is selected from multiple charging and discharging strategies; the multiple charging and discharging strategies have different target battery state of charge (SOC) and target discharge SOC.

[0012] In one possible implementation, the charging and discharging strategy includes: monitoring the battery SOC; when the SOC is higher than the target charging SOC, entering pure electric driving mode and starting to discharge; when the SOC is lower than the target discharging SOC, starting the engine to charge; and when the SOC is between the target charging SOC and the target discharging SOC, maintaining the current charging state or discharging state.

[0013] In one possible implementation, the method further includes:

[0014] Obtain the vehicle's travel duration;

[0015] If the travel duration is not greater than the preset duration, then the current driving style of the vehicle is determined to be the preset default style;

[0016] If the travel duration exceeds a preset duration, then determining the vehicle's current driving style based on the traffic scenario and the vehicle's driving information includes:

[0017] Based on the traffic scenario and driving information of the vehicle within a preset time period before the current moment, determine the vehicle's current driving style.

[0018] In one possible implementation, the traffic scenario in which the vehicle is located includes: non-highway sections in urban areas, non-highway sections in suburban areas, and highway sections.

[0019] In one possible implementation, the vehicle's current driving style includes: aggressive, normal, and calm.

[0020] A second aspect of this application provides a real-time energy distribution device for a hybrid electric vehicle, characterized in that the device comprises:

[0021] The scene determination unit is used to determine the traffic scene in which the vehicle is located based on the vehicle's current position.

[0022] A driving information acquisition unit is used to acquire vehicle driving information, including information on vehicle speed, acceleration, and braking frequency.

[0023] The style determination unit is used to determine the current driving style of the vehicle based on the traffic scenario in which the vehicle is located and the vehicle's driving information;

[0024] The strategy selection unit is used to select a charging and discharging strategy from a variety of charging and discharging strategies based on the current driving style of the vehicle and the traffic scenario in which the vehicle is located; the variety of charging and discharging strategies have different target battery charge state of OC and target discharge state of OC.

[0025] A third aspect of this application provides an apparatus, the apparatus comprising: a processor and a memory;

[0026] The memory is used to store instructions;

[0027] The processor is configured to execute the instructions in the memory and perform the method described in the first aspect.

[0028] A fourth aspect of this application provides a computer-readable storage medium storing program code or instructions that, when run on a computer, cause the computer to perform the method described in the first aspect above.

[0029] Therefore, the embodiments of this application have the following beneficial effects:

[0030] According to the method provided in this application, by introducing the vehicle's location information and current driving information, the current driving style and traffic scenario are determined, and the current vehicle's charging and discharging strategy is selected, so as to achieve the effect of flexible energy allocation by using different energy distribution methods under different driving styles and traffic scenarios. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 A schematic flowchart of a real-time energy distribution method for a hybrid electric vehicle provided in this application embodiment;

[0033] Figure 2 A schematic diagram illustrating the differentiation of target SOC types based on driving style and traffic scenario provided in this application embodiment;

[0034] Figure 3 This is a schematic diagram of the target SOC-vehicle speed for charging and discharging provided in an embodiment of this application;

[0035] Figure 4 A logical framework diagram of the technical solution provided in the embodiments of this application;

[0036] Figure 5 A prediction window timeline diagram provided for embodiments of this application;

[0037] Figure 6 This is a schematic diagram of the target SOC-vehicle speed for intense charging and discharging provided in an embodiment of this application;

[0038] Figure 7 This is a schematic diagram of a typical charge / discharge target SOC-vehicle speed provided in an embodiment of this application;

[0039] Figure 8 This is a schematic diagram of the target SOC-vehicle speed for a calm charging and discharging process provided in an embodiment of this application.

[0040] Figure 9 This application provides a schematic diagram of nine types of target SOC-vehicle speed for charging and discharging, as shown in the embodiments of this application.

[0041] Figure 10 This is a schematic diagram of a real-time energy distribution device for a hybrid electric vehicle provided in an embodiment of this application. Detailed Implementation

[0042] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0043] The inventors discovered in their research that most existing hybrid electric vehicles' energy strategies are based on simple, fixed rules: when the battery charge falls below a certain discharge target SOC, it enters parallel charging mode; when the battery charge exceeds a certain charging SOC, it returns to pure electric driving mode. This simple, fixed energy allocation rule fails to accommodate different driving styles and traffic scenarios, resulting in significant differences in energy consumption under different driving styles and traffic conditions. This leads to unreasonable energy distribution and a poor driving experience.

[0044] Based on this, embodiments of this application provide a real-time energy distribution method for hybrid electric vehicles. The method determines the traffic scenario in which the vehicle is located based on its current position; acquires driving information such as vehicle speed, acceleration, and braking frequency; determines the vehicle's current driving style based on the traffic scenario and driving information; and selects a charging / discharging strategy from multiple charging / discharging strategies based on the current driving style and traffic scenario. These multiple charging / discharging strategies have different target battery state of charge (SOC) and target discharge SOC. This application, by introducing vehicle location information and current driving information, determines the current driving style and traffic scenario, and selects the current charging / discharging strategy, thereby enabling the use of different energy distribution methods under different driving styles and traffic scenarios, achieving a flexible energy distribution effect.

[0045] To facilitate understanding of the methods provided in the embodiments of this application, the following description will be provided in conjunction with the accompanying drawings.

[0046] See Figure 1 This figure is a schematic flowchart of a real-time energy distribution method for a hybrid electric vehicle provided in an embodiment of this application. Figure 1 As shown, the method may include:

[0047] Step 101: Determine the traffic scenario in which the vehicle is located based on its current position.

[0048] In this embodiment, the vehicle's current traffic scenario is determined by incorporating the vehicle's navigation location information. Specifically, the traffic scenario can include: non-highway urban areas, non-highway suburbs, and high-speed areas. It should be noted that more traffic scenarios can be defined based on the vehicle's specific driving environment; this is merely one possible implementation method and does not impose any limitations on the specific division of traffic scenarios.

[0049] Step 102: Obtain vehicle driving information, which includes information on vehicle speed, acceleration, and braking frequency.

[0050] Step 103: Determine the current driving style of the vehicle based on the traffic scene in which the vehicle is located and the vehicle driving information.

[0051] In this embodiment, the current driving style of the vehicle is determined based on the current traffic scenario and driving information. Specifically, the driving style may include: aggressive, normal, and calm. It should be noted that no limitation is made on the classification of driving styles here.

[0052] Step 104: Select one charging and discharging strategy from a variety of charging and discharging strategies based on the vehicle's current driving style and the traffic scenario in which the vehicle is located.

[0053] In this embodiment, multiple charging and discharging strategies have different target SOCs for charging and discharging. Specifically, when driving styles include aggressive, normal, and calm driving, and traffic scenarios include urban non-highway sections, suburban non-highway sections, and high-speed sections, combining each driving style and traffic scenario yields nine different charging and discharging strategies. These nine different strategies correspond to nine different target SOCs for charging and discharging. See also Figure 2 This figure is a schematic diagram illustrating the differentiation of target SOC types based on driving style and traffic scenario according to an embodiment of this application. Figure 2 As shown, each target SOC type corresponds to a charging and discharging strategy. The nine target SOC types are labeled as 1-9 for ease of subsequent explanation.

[0054] In some possible implementations, the charging and discharging strategy includes: monitoring the battery SOC; when the SOC is higher than the target charging SOC, entering pure electric driving mode and starting to discharge; when the SOC is lower than the target discharging SOC, starting the engine to charge; and when the SOC is between the target charging SOC and the target discharging SOC, maintaining the current charging state or discharging state.

[0055] like Figure 3 The schematic diagram of the target SOC-vehicle speed provided in the embodiment of this application shows the target SOC for charging and discharging, as well as the difference between the target SOC and the target SOC, with vehicle speed as the horizontal axis and target SOC as the vertical axis.

[0056] The following example uses a plug-in hybrid electric vehicle (PHEV) with a battery capacity of 16.5 kWh, a maximum usable range of 90%-10%, and a vehicle weight of 1830 kg to illustrate the rules for determining the maximum / minimum charging and discharging targets. It is known that this PHEV consumes 17 kWh / 100 km of pure electric power under the New European Driving Cycle (NEDC) test. To ensure that a fully charged EV can cover a typical commuting distance of 50 km, the maximum charging target is set at approximately 40% SOC. Simultaneously, to prevent the battery level from dropping beyond its usable range, the minimum discharging target is set at approximately 20%. The specific charging and discharging target SOC can be flexibly adjusted according to different traffic scenarios and driving styles.

[0057] In some possible implementations, the method further includes:

[0058] Obtain the vehicle's travel duration;

[0059] If the travel duration is not greater than the preset duration, then the current driving style of the vehicle is determined to be the preset default style;

[0060] If the travel duration exceeds a preset duration, then determining the vehicle's current driving style based on the traffic scenario and the vehicle's driving information includes:

[0061] Based on the traffic scenario and driving information of the vehicle within a preset time period before the current moment, determine the vehicle's current driving style.

[0062] The following section, with reference to the accompanying drawings and specific embodiments, details how to determine the current driving style of a vehicle:

[0063] See Figure 4 This diagram is a logical framework diagram of the technical solution provided in the embodiments of this application. Figure 4 As shown in this embodiment, during the user's travel time T1, a charging / discharging strategy is selected according to a pre-set default driving style, which can be set to normal. After the user's travel time T1, the driving style type is determined based on the location information and driving signals from the historical time T1, and it is estimated that the driving style will remain unchanged for the next time T2. The Hybrid Control Unit (HCU) obtains the location information for the next time T2 and determines the traffic scenario type for the next time T2. Thus, the driving style and traffic scenario type for the next time T2 are predicted, and the charging / discharging strategy type is predicted based on the driving style and traffic scenario type, achieving the goal of flexibly adjusting the target SOC for charging and discharging. T1 and T2 can be adjusted according to the vehicle's HCU data processing capabilities and actual effects, with reference values ​​of T1 = 200s and T2 = 60s.

[0064] Figure 5 This is a prediction window timeline diagram provided in the embodiments of this application, such as... Figure 5 As shown, during the T1 time window after the start of the trip, the default driving style is used because there is not enough data to determine the driving style. When the travel time is equal to T1, the first prediction of driving style and traffic scenario is made at M1. After the driving style and traffic scenario type in the T2 time window after M1 are determined, the power control is performed according to the corresponding charging and discharging strategy.

[0065] Furthermore, in one possible implementation, driving style and traffic scenario can be dynamically predicted in real time at every moment Mi after M1 until the end of the trip. In this embodiment, it is assumed that a person's commute route is 15 minutes on highway + 10km in urban area, the driving style is normal, and the person is driving a PHEV vehicle with a battery capacity of 16.5kWh, a maximum battery availability range of 90%-10%, and a vehicle weight of 1830kg. Under the low battery condition, the charging and discharging situation during commuting is analyzed using the prediction method described above. T1 and T2 are set according to the reference values ​​of 200s / 60s. After 200 seconds of driving, if the vehicle is first determined to be on a highway and in a normal driving style, a charging and discharging strategy of target SOC type 6 is selected. Charging begins when the battery level drops below 28%. If charging is performed at an average power of 8kW, the battery level increases by 0.8% SOC per minute. After 10 minutes, the battery level reaches 36%. Once the vehicle enters a non-highway urban area at this charge level, the system determines in real time whether it is in a non-highway urban area and in a normal driving style, corresponding to a target SOC estimation type of 5. The engine will only start when the battery level drops to 21%. According to NEDC energy consumption estimates, the discharging process can cover 12km of urban mileage, reducing the number of engine starts in urban areas and the chance of operating in uneconomical areas.

[0066] The following is a detailed description of the nine target SOC types corresponding to the nine charging and discharging strategies in the embodiments of this application:

[0067] Target SOC Type 1: When the vehicle driving style is aggressive and the traffic scenario is urban (non-highway), the corresponding target SOC estimation type is 1. In this case, ordinary plug-in hybrid electric vehicles are easily affected by the driver's aggressive driving style, resulting in frequent engine start-stop, increasing fuel consumption and leading to a poor driving experience. When managing energy based on driving style and traffic scenario type, the charge-discharge SOC difference can be increased to avoid frequent engine start-stop. When the SOC drops below the target charging SOC limit, the engine starts, entering charging mode until the SOC is charged to the higher charging target SOC_ctyp1. When the SOC is higher than the charging target SOC_ctyp1, the vehicle enters pure electric driving mode until the SOC drops to the discharging target SOC_dtyp1, such as... Figure 6 As shown.

[0068] Target SOC Type 2: This applies when the vehicle is driven aggressively in suburban, non-highway traffic conditions. In this case, to prevent the battery level from dropping too low during pure electric driving under aggressive conditions, the discharge target SOC can be increased relative to Target SOC Type 1. When the SOC exceeds the charging target SOC_ctyp2, the vehicle enters pure electric driving mode until the SOC drops to the discharge target SOC_dtyp2. At this point, SOC_ctyp2 = SOC_ctyp1, and SOC_dtyp2 > SOC_dtyp1. Figure 6 As shown.

[0069] Target SOC Type 3: This applies when the vehicle is driven aggressively in a high-speed environment. In this case, the engine can operate better in its high-efficiency range, simultaneously increasing both the charging and discharging target SOC compared to Target SOC Type 2, thus increasing engine operating opportunities. When the SOC exceeds the charging target SOC_ctyp3, the vehicle enters pure electric driving mode until the SOC drops to the discharging target SOC_dtyp3. At this point, SOC_ctyp3 > SOC_ctyp2 and SOC_dtyp3 > SOC_dtyp2, as shown below. Figure 6 As shown.

[0070] Target SOC Type 4: When the vehicle driving style is normal and the traffic scenario is urban (non-highway), the target SOC type is 4. In this case, to reduce engine operating time, the charging target SOC is lowered compared to target SOC Type 1. When the SOC is higher than the charging target SOC_ctyp4, the vehicle enters pure electric driving mode until the SOC drops to the discharging target SOC_dtyp4. At this point, SOC_ctyp4 < SOC_ctyp1 and SOC_dtyp4 = SOC_dtyp1, as shown below. Figure 7 As shown.

[0071] Target SOC Type 5: This corresponds to Target SOC Type 5 when the vehicle's driving style is normal and the traffic scenario is suburban non-highway. In this case, to avoid the battery level dropping too low during pure electric driving, the discharge target SOC can be increased relative to Target SOC Type 4. When the SOC is higher than the charging target SOC_ctyp5, the vehicle enters pure electric driving mode until the SOC drops to the discharge target SOC_dtyp5. At this point, SOC_ctyp5 = SOC_ctyp4 and SOC_dtyp5 > SOC_dtyp4, see [link to relevant documentation]. Figure 7 .

[0072] Target SOC Type 6: This corresponds to Target SOC Type 6 when the vehicle's driving style is normal and the traffic scenario is high-speed. In this case, to increase engine operating opportunities, the target SOC for charging and discharging can be appropriately increased. When the SOC is higher than the charging target SOC_ctyp6, the vehicle enters pure electric driving mode until the SOC drops to the discharging target SOC_dtyp6. At this point, SOC_ctyp6 > SOC_ctyp5 and SOC_dtyp6 > SOC_dtyp5, see [link to relevant documentation]. Figure 7 .

[0073] Target SOC Type 7: When the vehicle driving style is calm and the traffic scenario is urban (non-highway), the target SOC type is 7. In this case, to reduce engine operating time, the charging target SOC can be further reduced relative to target SOC Type 4. When the SOC is higher than the charging target SOC_ctyp7, the vehicle enters pure electric driving mode until the SOC drops to the discharging target SOC_dtyp7. At this point, SOC_ctyp7 < SOC_ctyp4 and SOC_dtyp7 = SOC_dtyp4, see [link to relevant documentation]. Figure 8 .

[0074] Target SOC Type 8: This type of target SOC applies when the vehicle is driven in a calm mode and the traffic scenario is in suburban, non-highway areas. In this case, to prevent the battery level from dropping too low when the vehicle is driving in pure electric mode in suburban areas, the discharge target SOC can be increased relative to target SOC Type 7. When the SOC is higher than the charging target SOC_ctyp8, the vehicle enters pure electric driving mode until the SOC drops to the discharge target SOC_dtyp8. At this point, SOC_ctyp8 = SOC_ctyp7 and SOC_dtyp8 > SOC_dtyp7. See [link to documentation]. Figure 8 .

[0075] Target SOC Type 9: When the vehicle driving style is calm and the traffic scenario is high-speed, this corresponds to Target SOC estimation type 9. In this case, the vehicle speed is high, so the engine efficiency is high. To increase the engine's operating time, the same high charging target SOC and discharging target SOC can be maintained as in Target SOC Type 7. When the SOC is higher than the charging target SOC_ctyp9, the vehicle enters pure electric driving mode until the SOC drops to the discharging target SOC_dtyp9. At this point, SOC_ctyp9 > SOC_ctyp8 and SOC_dtyp9 > SOC_dtyp8, see [link to relevant documentation]. Figure 8 .

[0076] Will Figure 6 , Figure 7 and Figure 8 Integrating these into a single diagram yields a schematic diagram of the nine types of target SOC-vehicle speed for charging and discharging provided in the embodiments of this application, as shown below. Figure 9 As shown.

[0077] Based on the above method embodiments, this application provides a real-time energy distribution device for hybrid electric vehicles. See [link to relevant documentation]. Figure 10 This figure is a schematic diagram of a real-time energy distribution device for a hybrid vehicle provided in an embodiment of this application. Figure 10 As shown, the device may include:

[0078] Scene determination unit 201 is used to determine the traffic scene in which the vehicle is located based on the vehicle's current position;

[0079] The driving information acquisition unit 202 is used to acquire vehicle driving information, which includes information on vehicle speed, acceleration, and braking frequency.

[0080] Style determination unit 203 is used to determine the current driving style of the vehicle based on the traffic scene in which the vehicle is located and the vehicle driving information;

[0081] The strategy selection unit 204 is used to select a charging and discharging strategy from a variety of charging and discharging strategies based on the current driving style of the vehicle and the traffic scenario in which the vehicle is located; the variety of charging and discharging strategies have different target battery charge state of OC and target discharge state of OC.

[0082] It should be noted that the implementation of each unit in this embodiment can be found in the above method embodiment, and will not be repeated here.

[0083] In addition, this application embodiment also provides a device, the device including: a processor and a memory; the memory is used to store instructions; the processor is used to execute the instructions in the memory to execute the real-time energy distribution method for hybrid vehicles.

[0084] This application provides a computer-readable storage medium storing program code or instructions that, when run on a computer, cause the computer to execute the real-time energy distribution method for hybrid electric vehicles described above.

[0085] As can be seen, the embodiments of this application introduce the vehicle's location information and current driving information to determine the current driving style and traffic scenario, select the current vehicle's charging and discharging strategy, and realize the use of different energy distribution methods under different driving styles and traffic scenarios, thereby achieving the effect of flexible energy distribution.

[0086] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems or apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and relevant parts can be referred to the method section.

[0087] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0088] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0089] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0090] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A real-time energy distribution method for a hybrid electric vehicle, characterized in that, The method includes: Determine the traffic scenario in which the vehicle is located based on its current position; Obtain vehicle driving information, including information on vehicle speed, acceleration, and braking frequency; Obtain the vehicle's travel duration; if the travel duration is not greater than a preset duration, determine that the vehicle's current driving style is the preset default style; if the travel duration is greater than the preset duration, determine the vehicle's current driving style based on the traffic scenario and vehicle driving information within the preset duration before the current time. Based on the vehicle's current driving style and the traffic scenario, a charging / discharging strategy is selected from multiple charging / discharging strategies. These strategies have different target battery state of charge (SOC) for charging and target SOC for discharging. The charging / discharging strategy includes: monitoring the battery SOC; when the SOC is higher than the target SOC for charging, entering pure electric driving mode and starting to discharge; when the SOC is lower than the target SOC for discharging, starting the engine to charge; and when the SOC is between the target SOC for charging and the target SOC for discharging, maintaining the current charging or discharging state.

2. The method according to claim 1, characterized in that, The traffic scenarios in which the vehicle is located include: non-highway sections in urban areas, non-highway sections in suburban areas, and highway sections.

3. The method according to claim 1, characterized in that, The vehicle's current driving style includes: aggressive, normal, and calm.

4. A real-time energy distribution device for a hybrid electric vehicle, characterized in that, The device includes: The scene determination unit is used to determine the traffic scene in which the vehicle is located based on the vehicle's current position. A driving information acquisition unit is used to acquire vehicle driving information, including information on vehicle speed, acceleration, and braking frequency. A style determination unit is used to obtain the travel duration of the vehicle; if the travel duration is not greater than a preset duration, the current driving style of the vehicle is determined to be the preset default style; if the travel duration is greater than the preset duration, the current driving style of the vehicle is determined based on the traffic scene and vehicle driving information of the vehicle within the preset duration before the current time. The strategy selection unit is used to select a charging and discharging strategy from multiple charging and discharging strategies based on the vehicle's current driving style and the traffic scenario in which the vehicle is located. The multiple charging and discharging strategies have different target battery charge states (SOC) for charging and target discharge states (SOC). The charging and discharging strategy includes: monitoring the battery SOC; when the SOC is higher than the target charging SOC, entering pure electric driving and starting to discharge; when the SOC is lower than the target discharge SOC, starting the engine to charge; and when the SOC is between the target charging SOC and the target discharge SOC, maintaining the current charging state or discharging state.

5. A device, characterized in that, The device includes: a processor and a memory; The memory is used to store instructions; The processor is configured to execute the instructions in the memory to perform the method according to any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores program code or instructions that, when run on a computer, cause the computer to perform the method described in any one of claims 1-3.

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