Vehicle control method and vehicle
By acquiring accelerator pedal and navigation data and combining weighted processing to determine engine control factors, the problem that existing engine start-stop systems cannot adapt to driver habits and future routes has been solved, achieving personalized engine control and improved energy-saving performance.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- GREAT WALL MOTOR CO LTD
- Filing Date
- 2026-01-22
- Publication Date
- 2026-04-24
AI Technical Summary
Existing engine start-stop systems make judgments based on the vehicle's current state parameters, which cannot adapt to driver habits and future driving routes, resulting in a contradiction between energy-saving effects and driving experience.
By acquiring accelerator pedal parameters and navigation data, driver habit parameters and power demand parameters are determined. These parameters are then combined with weighted processing to obtain engine control factors, thereby determining engine operating conditions and performing target control.
It enables personalized adaptation of engine control methods, enhances the driver's driving experience, and optimizes the engine start-stop strategy under different operating conditions, thereby improving energy efficiency.
Smart Images
Figure CN121912959A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of vehicle control technology, and in particular to a vehicle control method and a vehicle. Background Technology
[0002] Currently, engine start-stop systems mainly make simple start-stop decisions based on the vehicle's current state parameters (such as vehicle speed, battery SOC, etc.).
[0003] However, judging engine start / stop based on the vehicle's current state parameters may not be suitable for driver habits and future driving routes. Summary of the Invention
[0004] In view of this, the purpose of this application is to propose a vehicle control method and a vehicle to solve the problem that the engine start / stop judgment based on the current state parameters of the vehicle cannot adapt to the driver's habits and future driving routes.
[0005] To achieve the above objectives, this application provides a vehicle control method, comprising: Obtain accelerator pedal parameters, and determine driver habit parameters based on the accelerator pedal parameters, wherein the driver habit parameters are the parameters of the influence of driver habits on the engine; Obtain navigation data and determine power demand parameters based on the navigation data, wherein the power demand parameters are parameters that affect the engine; The engine control factor is determined based on the driver habit parameters and the power demand parameters, wherein the engine control factor is the combined influence factor of the driver habit parameters and the power demand parameters on the engine; Based on the engine control factors, the engine operating condition is determined, the target control mode corresponding to the engine operating condition is determined, and the engine is controlled according to the target control mode.
[0006] Based on the same inventive concept, this application also provides a vehicle including an electronic device, the electronic device including a memory, a processor and a computer program stored in the memory and executable by the processor, the processor implementing the method described above when executing the computer program.
[0007] As described above, the vehicle control method and vehicle provided in this application acquire accelerator pedal parameters and determine driver habit parameters based on these parameters. These driver habit parameters represent the impact of driver habits on the engine. This allows for accurate determination of driver habit parameters based on the accelerator pedal parameters, reflecting the degree of influence of driver habits on the engine. Navigation data is acquired, and power demand parameters are determined based on this data. These power demand parameters represent the impact of power demand on the engine. This allows for accurate determination of power demand parameters for future driving routes, reflecting the degree of influence of future driving routes on the engine. An engine control factor is determined based on the driver habit parameters and power demand parameters. This engine control factor is a combined influence of both driver habit parameters and power demand parameters on the engine, comprehensively considering the impact of driver habits and future driving routes. Based on the engine control factor, the engine operating condition is determined, and the corresponding target control method is determined. The engine is then controlled according to this target control method. This target control method adapts to driver habits and future driving routes, thereby improving the driver's driving experience. Attached Figure Description
[0008] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0009] Figure 1 This is a flowchart of a vehicle control method according to an embodiment of this application; Figure 2 This is a schematic diagram of the vehicle control device according to an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation
[0010] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.
[0011] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.
[0012] In related technologies, current engine start-stop systems mainly make simple start-stop decisions based on the vehicle's current state parameters (such as vehicle speed, battery SOC, etc.).
[0013] This approach in related technologies has the following problems: (1) Lack of consideration for the driver’s individual habits makes it impossible to implement an engine control strategy that adapts to the driver.
[0014] (2) Lack of foresight regarding future driving routes, making it impossible to adjust engine status in advance.
[0015] (3) There is a contradiction between energy saving effect and driving experience.
[0016] Based on the above, the embodiments of this application will be described in detail below with reference to the accompanying drawings.
[0017] The vehicle control method proposed in the embodiments of this application is applied to the vehicle controller.
[0018] like Figure 1 As shown, the method includes: Step 101: Obtain accelerator pedal parameters, and determine driver habit parameters based on the accelerator pedal parameters, wherein the driver habit parameters are the parameters of the influence of driver habits on the engine.
[0019] In specific implementation, the accelerator pedal parameters are the relevant parameters of the accelerator pedal collected. These parameters include at least one of the following: accelerator pedal depth, duration corresponding to the accelerator pedal depth, accelerator pedal force, operating voltage, operating current, and output signal linearity accuracy. In this embodiment, the preferred accelerator pedal parameters are accelerator pedal depth and duration corresponding to the accelerator pedal depth.
[0020] Driver habit parameters are parameters that reflect the impact of driver habits on the engine. Driver habit parameters can reflect the degree to which driver habits affect engine operation (starting or stopping).
[0021] Specifically, accelerator pedal operation is determined based on accelerator pedal parameters, and driver habit parameters are determined based on accelerator pedal operation. Accelerator pedal operation refers to parameters related to accelerator pedal operation that reflect driver habits, including accelerator pedal operation frequency and average accelerator pedal depth.
[0022] Step 102: Obtain navigation data and determine power demand parameters based on the navigation data, wherein the power demand parameters are the parameters that affect the engine.
[0023] In practice, navigation data refers to the data set used to provide users with location information and route planning services. The planned route is determined based on the navigation data, along with the power demand parameters for that route.
[0024] Power demand parameters are parameters that reflect the impact of power demand on the engine. Power demand parameters can demonstrate the degree to which the power parameters required for the future driving route affect the engine's operation (starting or stopping).
[0025] Specifically, road parameters within a preset distance ahead of the vehicle are determined based on navigation data, and power demand parameters are determined based on these road parameters. Road parameters refer to road-related parameters within a preset distance ahead of the vehicle on the planned route.
[0026] Step 103: Determine the engine control factor based on the driver habit parameters and the power demand parameters, wherein the engine control factor is the combined influence factor of the driver habit parameters and the power demand parameters on the engine.
[0027] In practice, the engine control factor is the combined influence of driver habit parameters and power demand parameters on the engine. The engine control factor can reflect the degree of influence of driver habits and the power parameters required for future driving routes on engine operation (starting or stopping).
[0028] The engine control factor is obtained by weighting the driver's habit parameters and power demand parameters. In some schemes, to make the engine control factor more accurate, a fusion parameter is determined based on the driver's habit parameters and power demand parameters, and the engine control factor is obtained by weighting the driver's habit parameters, power demand parameters, and fusion parameter.
[0029] Step 104: Determine the engine operating condition based on the engine control factor, determine the target control mode corresponding to the engine operating condition, and control the engine according to the target control mode.
[0030] In practical implementation, engine operating conditions refer to the scenarios in which engine power is required. Engine operating conditions can include: high-demand operating conditions, medium-demand operating conditions, and low-demand operating conditions.
[0031] Different engine operating conditions correspond to different target control methods. Specifically, when the engine is operating under high demand, a first target control method is determined, and the engine is controlled according to this method. When the engine is operating under medium demand, a second target control method is determined, and the engine is controlled according to this method. When the engine is operating under low demand, a third target control method is determined, and the engine is controlled according to this method.
[0032] The above scheme obtains accelerator pedal parameters and determines driver habit parameters based on these parameters. These driver habit parameters represent the impact of driver habits on the engine. This allows for accurate determination of driver habit parameters based on accelerator pedal parameters, reflecting the degree to which driver habits influence the engine. Navigation data is then obtained, and power demand parameters are determined based on this data. These power demand parameters represent the impact of power demand on the engine. This allows for accurate determination of power demand parameters for future driving routes, reflecting the degree to which future driving routes influence the engine. Engine control factors are determined based on the driver habit parameters and power demand parameters. These engine control factors are the combined influence of both driver habit parameters and power demand parameters on the engine, comprehensively considering the impact of driver habits and future driving routes. Based on these engine control factors, engine operating conditions are determined, and the corresponding target control method is identified. The engine is then controlled according to this target control method, ensuring that the engine's target control method adapts to driver habits and future driving routes, thereby improving the driver's driving experience.
[0033] In some embodiments, step 101 includes: Step 1011: Obtain the received accelerator pedal depth and the duration of the accelerator pedal depth.
[0034] In practice, accelerator pedal depth refers to the distance the accelerator pedal moves when the driver presses it, and the value ranges from 0 to 100%. Accelerator pedal depth duration refers to the time the driver presses the accelerator pedal and maintains that depth.
[0035] The accelerator pedal depth can be at least one, and each accelerator pedal depth corresponds to a duration. For example, the first accelerator pedal depth from minute 0 to minute 5 is 3%, the second accelerator pedal depth from minute 5 to minute 9 is 6%, and the third accelerator pedal depth from minute 9 to minute 15 is 10%. In the example above, the accelerator pedal depths include: a first accelerator pedal depth of 3%, a second accelerator pedal depth of 6%, and a third accelerator pedal depth of 10%. The duration of the first accelerator pedal depth of 3% is 5 minutes, the duration of the second accelerator pedal depth of 6% is 4 minutes, and the duration of the third accelerator pedal depth of 10% is 6 minutes.
[0036] Step 1012: Determine the accelerator pedal operation frequency based on the accelerator pedal depth and the duration.
[0037] In practice, the accelerator pedal operation frequency refers to the number of times the accelerator pedal is used per unit of time.
[0038] Specifically, the accelerator pedal depth can be at least one. Based on each accelerator pedal depth and its corresponding duration, the number of effective operations within a preset time range is determined from at least one accelerator pedal depth, and the ratio of the number of effective operations to the preset time range is used as the accelerator pedal operation frequency.
[0039] Step 1013: Determine the average accelerator pedal depth based on the accelerator pedal depth and the duration.
[0040] In practice, the average accelerator pedal depth refers to the average depth of at least one accelerator pedal pressed by the driver over a historical period. This historical period can be the time interval from when the vehicle is powered on to the current moment.
[0041] Specifically, the accelerator pedal depth can be at least one. The total accelerator pedal depth is determined based on the depth of each accelerator pedal and its corresponding duration, the total duration is determined based on the duration of each accelerator pedal depth, and the ratio of the total accelerator pedal depth to the total duration is taken as the average accelerator pedal depth.
[0042] Step 1014: Based on the pre-stored mapping relationship, determine the driver habit parameters corresponding to the accelerator pedal operation frequency and the average accelerator pedal depth; wherein, the mapping relationship is the correspondence between the accelerator pedal operation frequency, the average accelerator pedal depth and the driver habit parameters.
[0043] In practice, a mapping relationship between accelerator pedal operation frequency, average accelerator pedal depth, and driver habit parameters is pre-stored. Based on the pre-stored mapping relationship, the driver habit parameters corresponding to the accelerator pedal operation frequency and average accelerator pedal depth are determined.
[0044] For example, the pre-stored mapping relationships include: a first operating frequency and a first average depth corresponding to a first habitual parameter, a second operating frequency and a second average depth corresponding to a second habitual parameter, and a third operating frequency and a third average depth corresponding to a third habitual parameter. When the accelerator pedal operating frequency is the second operating frequency and the accelerator pedal average depth is the second average depth, the driver's habitual parameter is determined to be the second habitual parameter.
[0045] In some scenarios, to facilitate finding the driver's habit parameters corresponding to the frequency of accelerator pedal operation and the average depth of accelerator pedal, the pre-stored mapping relationship can be a mapping relationship table, as shown in Table 1.
[0046] Table 1 Mapping Relationship Table
[0047] Based on the mapping table above, the driver's habit parameters corresponding to the accelerator pedal operation frequency and average accelerator pedal depth can be determined. For example, when the accelerator pedal operation frequency is 10 times / min and the average accelerator pedal depth is 30%, the driver's habit parameter is 0.45. As another example, when the accelerator pedal operation frequency is 15 times / min and the average accelerator pedal depth is 60%, the driver's habit parameter is 0.80.
[0048] In addition, the pre-stored mapping relationship can be the correspondence between the accelerator pedal operation frequency range, the average accelerator pedal depth range, and driver habit parameters. Specifically, the accelerator pedal operation frequency range to which the accelerator pedal operation frequency belongs is determined, and the average accelerator pedal depth range to which the average accelerator pedal depth belongs is determined; based on the pre-stored mapping relationship, the driver habit parameters corresponding to the accelerator pedal operation frequency range and the average accelerator pedal depth range are determined.
[0049] For example, the pre-stored mapping relationships include: a first operating frequency range and a first average depth range corresponding to a first habitual parameter; a second operating frequency range and a second average depth range corresponding to a second habitual parameter; and a third operating frequency range and a third average depth range corresponding to a third habitual parameter. When the accelerator pedal operating frequency belongs to the third operating frequency range and the accelerator pedal average depth belongs to the third average depth range, then the driver's habitual parameter is determined to be the third habitual parameter.
[0050] Following step 1014, the method further includes: determining the driver habit type based on driver habit parameters. Specifically, the driver habit type corresponding to the driver habit parameters is determined based on a pre-stored correspondence, wherein the pre-stored correspondence is the correspondence between driver habit parameters and driver habit types.
[0051] For example, pre-stored mappings include: driver habit parameters Corresponding to the economy model, driver's habit parameters Corresponding to the standard model, driver's habitual parameters Corresponding to the sporty type. When the driver's habit parameter is between 0.1 and 0.3, the driver's habit is determined to be low-frequency, shallow pressing of the accelerator pedal with priority on fuel economy, i.e., the driver's habit type is economy; when the driver's habit parameter is between 0.4 and 0.6, the driver's habit is determined to be balanced between fuel economy and responsiveness of the accelerator pedal, i.e., the driver's habit type is standard; when the driver's habit parameter is between 0.7 and 1.0, the driver's habit is determined to be high-frequency, deep pressing of the accelerator pedal with priority on power response, i.e., the driver's habit type is sporty.
[0052] The above method obtains the received accelerator pedal depth and its duration. The accelerator pedal operation frequency is determined based on the depth and duration. The average accelerator pedal depth is also determined based on the depth and duration. This allows the accelerator pedal operation frequency and average depth to comprehensively and accurately reflect driver habits. Based on a pre-stored mapping relationship, driver habit parameters corresponding to the accelerator pedal operation frequency and average depth are determined; where the mapping relationship is the correspondence between the accelerator pedal operation frequency, average depth, and driver habit parameters. This allows for accurate determination of driver habit parameters based on the accelerator pedal operation frequency and average depth, and enables the determination of the driver's influence on the engine based on these driver habits.
[0053] In some embodiments, step 1012 includes: Step 1012A: In response to determining that the accelerator pedal depth is greater than a preset depth threshold and the duration is greater than a preset duration, a valid operation is recorded.
[0054] In practice, if the accelerator pedal depth exceeds a preset depth threshold and the duration exceeds a preset duration, a valid operation is recorded. If the accelerator pedal depth changes, the validity of the operation is reassessed based on the new accelerator pedal depth.
[0055] For example, if the duration of the first accelerator pedal depth of 3% is 5 minutes, the duration of the second accelerator pedal depth of 6% is 4 minutes, and the duration of the third accelerator pedal depth of 10% is 6 minutes, with a preset depth threshold of 5% and a preset duration of 1 second, then the second accelerator pedal depth of 6% is recorded as one valid operation, and the third accelerator pedal depth of 10% is recorded as one valid operation.
[0056] Step 1012B: Count the number of valid operations within a preset time range, and use the ratio of the number of valid operations to the preset time range as the accelerator pedal operation frequency.
[0057] In practice, the preset time range refers to a pre-set time period, and the preset time window can be a pre-set time window. For example, the preset time range can be between 15 and 30 minutes, and the preset time range can be 15 minutes.
[0058] The number of valid operations within a preset time range is counted, and the ratio of the number of valid operations to the preset time range is used as the accelerator pedal operation frequency. ,in, This refers to the frequency of accelerator pedal operation. The number of valid operations within a preset time range. This is a preset time range.
[0059] For example, within a preset time range of 15 minutes, the duration of the first accelerator pedal depth at 3% is 5 minutes, the duration of the second accelerator pedal depth at 6% is 4 minutes, and the duration of the third accelerator pedal depth at 10% is 6 minutes. A valid operation is recorded when the second accelerator pedal depth reaches 6%, and a valid operation is recorded when the third accelerator pedal depth reaches 10%. In the above example, there are 2 valid operations, so the accelerator pedal operation frequency is determined to be 0.13 times / min.
[0060] The above scheme records a valid operation when the accelerator pedal depth exceeds a preset depth threshold and the duration exceeds a preset duration. This method accurately identifies valid accelerator pedal operations by determining if the pedal depth exceeds the preset depth threshold, and avoids incorrectly identifying short-term accidental pedal presses as valid operations by determining if the duration of the pedal depth exceeds the preset duration. Statistically counting the number of valid operations within a preset time range and using the ratio of the number of valid operations to the preset time range as the accelerator pedal operation frequency accurately determines the accelerator pedal operation frequency, which precisely reflects the driver's habits.
[0061] In some embodiments, step 1013 includes: Step 1013A: For each accelerator pedal depth, perform the following: multiply the accelerator pedal depth with the corresponding duration to obtain the product parameter corresponding to the accelerator pedal depth.
[0062] In practice, the depth of each accelerator pedal is multiplied by its corresponding duration to obtain the product parameter corresponding to that accelerator pedal depth. For the first The product parameter corresponding to each accelerator pedal depth For the first The depth of the accelerator pedal For the first The duration of each accelerator pedal depth.
[0063] Step 1013B: Summing up the product parameters corresponding to all accelerator pedal depths to obtain the total accelerator pedal depth, and summing up all durations to obtain the total duration.
[0064] In practice, the total accelerator pedal depth is obtained by summing the product parameters corresponding to all accelerator pedal depths. This represents the total accelerator pedal depth. For the first The product parameter corresponding to each accelerator pedal depth.
[0065] The total duration is obtained by summing all durations. Total duration For the first The duration of each accelerator pedal depth.
[0066] Step 1013C: The ratio of the total accelerator pedal depth to the total duration is taken as the average accelerator pedal depth.
[0067] In practice, the ratio of total accelerator pedal depth to total duration is used as the average accelerator pedal depth. ,in, This represents the average depth of the accelerator pedal. This represents the total accelerator pedal depth. Total duration.
[0068] For example, the duration of the first accelerator pedal depth (3%) is 5 minutes, the duration of the second accelerator pedal depth (6%) is 4 minutes, and the duration of the third accelerator pedal depth (10%) is 6 minutes. In the above examples, the average accelerator pedal depth... .
[0069] The above scheme involves performing the following steps for each accelerator pedal depth: multiplying the accelerator pedal depth by its corresponding duration to obtain a product parameter. Summing these product parameters for all accelerator pedal depths yields the total accelerator pedal depth, and summing these parameters for all durations yields the total duration. The ratio of the total accelerator pedal depth to the total duration is then used as the average accelerator pedal depth. This accurately determines the average accelerator pedal depth, which precisely reflects the driver's habits.
[0070] In some embodiments, step 102 includes: Step 1021: Obtain navigation data and determine at least one road parameter within a preset distance ahead of the vehicle based on the navigation data.
[0071] In practice, a planned route is determined based on navigation data, and at least one road parameter is determined within a preset distance ahead of the vehicle based on the planned route. The road parameter refers to road-related parameters within the preset distance ahead of the vehicle on the planned route. Road parameters include at least one of the following: gradient, curvature, road type, and congestion level.
[0072] For example, the preset distance can be in the range of 1km to 3km, and the preset distance can be set to 2km. When the preset distance is 2km, at least one road parameter within 2km ahead of the vehicle is determined based on navigation data.
[0073] Step 1022: Determine the road factor corresponding to each road parameter; wherein, the road factor is the influence factor of the road parameter on the power demand.
[0074] In practical implementation, the road factor is the influence factor of the road parameter on power demand. Specifically, when the road parameters are slope, curvature, road type, and congestion level, the slope factor is determined based on the slope within a preset distance in front of the vehicle, the curvature factor is determined based on the curvature within a preset distance in front of the vehicle, the road type factor is determined based on the road type within a preset distance in front of the vehicle, and the congestion level factor is determined based on the congestion level within a preset distance in front of the vehicle.
[0075] Among them, the slope factor refers to the factor that affects the power demand, the curvature factor refers to the factor that affects the power demand, the road type factor refers to the factor that affects the power demand, and the congestion factor refers to the factor that affects the congestion level.
[0076] Step 1023: Weight the road factors corresponding to all road parameters to obtain the power demand parameters.
[0077] In practice, the weights corresponding to each road factor are retrieved, and the power demand parameters are obtained by weighting the road factors corresponding to all road parameters based on the weights corresponding to each road factor.
[0078] When the road parameters are slope, curvature, road type, and congestion level, the power demand parameters are obtained by weighting the slope factor, curvature factor, road type factor, and congestion level factor. ,in, For power demand parameters, This is the first weight corresponding to the slope factor. For slope factor, This is the second weight corresponding to the curvature factor. For curvature factor, The third weight corresponding to the road type factor. For road type factors, This is the fourth weight corresponding to the crowding factor. This represents the crowding level factor. In some scenarios, the first, second, third, and fourth weights can be pre-defined; for example, the first weight... Second weight Third weight Fourth weight .
[0079] The above method acquires navigation data and determines at least one road parameter within a preset distance ahead of the vehicle. A road factor is then determined for each road parameter; this road factor represents the influence of that road parameter on power demand. The power demand parameters are obtained by weighting the road factors corresponding to all road parameters, accurately determining the power demand parameters and reflecting the degree of impact of the future driving route on the engine.
[0080] In some embodiments, the road parameters include at least one of the following: slope, curvature, road type, and congestion level; step 1022 includes: Step 1022A: Determine the ramp type based on the slope and determine the slope factor corresponding to the ramp type.
[0081] In practice, the slope types include uphill and downhill types. Specifically, in response to determining that the slope type is uphill, the slope factor is determined to be the first slope factor corresponding to the uphill type; in response to determining that the slope type is downhill, the slope factor is determined to be the second slope factor corresponding to the downhill type; wherein, the first slope factor is greater than the second slope factor, that is, the power demand of the vehicle is high when going uphill and low when going downhill.
[0082] For example, the first slope factor is 0.8 and the second slope factor is 0.3. When the slope within a preset distance in front of the vehicle is uphill, the slope factor is set to 0.8; when the slope within a preset distance in front of the vehicle is downhill, the slope factor is set to 0.3.
[0083] And / or, in step 1022B, determine the number of curves based on the curvature, and determine the curvature factor corresponding to the number of curves.
[0084] In practice, the presence of a curve is determined based on the curvature. Specifically, if the curvature is greater than a preset curvature threshold, a curve is identified, and the number of curves within a preset distance ahead of the vehicle is counted. If the number of curves falls within a first range, a first curvature factor is determined; if the number of curves falls within a second range, a second curvature factor is determined. Wherein, the first range is smaller than the second range, and the first curvature factor is greater than the second curvature factor; that is, the more curves within a preset distance ahead of the vehicle, the lower the power demand.
[0085] For example, the first curvature factor is 0.8 when the first number range is 0 to 3; the second curvature factor is 0.6 when the second number range is 4 to 6; and the third curvature factor is 0.4 when the third number range is 7 to 9. If the number of curves determined based on the curvature within a preset distance in front of the vehicle is 2, then the curvature factor is 0.8; if the number of curves determined based on the curvature within a preset distance in front of the vehicle is 5, then the curvature factor is 0.6; and if the number of curves determined based on the curvature within a preset distance in front of the vehicle is 8, then the curvature factor is 0.4.
[0086] And / or, in step 1022C, based on a pre-stored first correspondence, determine the road type factor corresponding to the road type; wherein, the first correspondence is the correspondence between road type and road type factor.
[0087] In practice, the first correspondence includes road type factors corresponding to different road types. Based on the first correspondence, the road type factor corresponding to the road type within a preset distance ahead of the vehicle is determined.
[0088] For example, the first correspondence includes: a road type factor of 0.8 for highways, 0.5 for suburban roads, and 0.3 for urban roads. When the road type within a preset distance ahead of the vehicle is a highway, the road type factor is determined to be 0.8; when the road type within a preset distance ahead of the vehicle is a suburban road, the road type factor is determined to be 0.5; and when the road type within a preset distance ahead of the vehicle is an urban road, the road type factor is determined to be 0.3.
[0089] And / or, in step 1022D, based on a pre-stored second correspondence, determine the congestion factor corresponding to the congestion level; wherein, the second correspondence is the correspondence between the congestion level and the congestion factor.
[0090] In practice, the second correspondence includes congestion level factors corresponding to different user levels. Based on the second correspondence, the congestion level factor corresponding to the congestion level within a preset distance ahead of the vehicle is determined.
[0091] For example, the second correspondence includes: a road type factor of 0.2 for congested roads, 0.6 for slow-moving roads, and 1.0 for unobstructed roads. When the road type within a preset distance ahead of the vehicle is a congested road, the road type factor is determined to be 0.2; when the road type within a preset distance ahead of the vehicle is a slow-moving road, the road type factor is determined to be 0.6; and when the road type within a preset distance ahead of the vehicle is an unobstructed road, the road type factor is determined to be 1.0.
[0092] The above scheme determines the slope type and corresponding slope factor based on the gradient, accurately reflecting the impact of slope on power demand. Similarly, it determines the number of curves and corresponding curvature factor based on curvature, accurately reflecting the impact of curvature on power demand. Based on a pre-stored first correspondence, it determines the road type factor corresponding to the road type; this first correspondence accurately determines the road type factor, reflecting the impact of road type on power demand. Finally, based on a pre-stored second correspondence, it determines the congestion level factor corresponding to the congestion level; this second correspondence accurately determines the congestion level factor, reflecting the impact of congestion level on power demand.
[0093] In some embodiments, step 103 includes: Step 1031: Multiply the driver habit parameters and the power demand parameters to obtain fused parameters.
[0094] In practice, the fusion parameter refers to the parameter that integrates the influence of driver habit parameters and power demand parameters on engine operation.
[0095] The fused parameters are obtained by multiplying the driver's habit parameters and power demand parameters. These are fusion parameters. For parameters that are familiar to drivers, These are the power demand parameters.
[0096] Step 1032: The driver habit parameters, the power demand parameters, and the fusion parameters are weighted to obtain the engine control factor.
[0097] In practice, the system retrieves the first weight corresponding to the power demand parameter, the second weight corresponding to the driver habit parameter, and the third weight corresponding to the fused parameter. Based on the first, second, and third weights, the driver habit parameter, power demand parameter, and fused parameter are weighted to obtain the engine control factor. , in, For engine control factors, As the first weight, For parameters that are familiar to drivers, As the second weight, For power demand parameters, As the third weight, These are the fusion parameters. In some scenarios, the first, second, and third weights can be pre-defined; for example, the first weight... Second weight Third weight .
[0098] The above method involves multiplying driver habit parameters and power demand parameters to obtain fused parameters. These fused parameters comprehensively reflect the influence of both parameters on engine operation. Weighting the driver habit parameters, power demand parameters, and fused parameters yields the engine control factor, making it more accurate.
[0099] In some embodiments, step 104 includes: Step 1041: In response to determining that the engine control factor is greater than the first parameter threshold, the engine operating condition is determined to be a high-demand operating condition, and the first target control mode corresponding to the high-demand operating condition is determined to be starting the engine preparation function and prohibiting the engine from stopping.
[0100] In practical implementation, the first parameter threshold This can be a pre-set maximum engine power demand. When the engine control factor exceeds the first parameter threshold ( When the threshold value is 0, it indicates a high demand on engine power, thus classifying the engine operating condition as a high-demand condition. For example, the first parameter threshold... ,when When the engine power demand is high, the engine operating condition is determined to be a high-demand condition.
[0101] When the engine is in a high-demand condition, the primary target control method for this condition is to start the engine and prevent it from stopping. This allows the engine to start in advance and continue running in high-demand scenarios, ensuring that the engine can meet the power requirements of the driver's habits and future driving routes.
[0102] Alternatively, in step 1042, in response to determining that the engine control factor is less than or equal to a first parameter threshold and greater than or equal to a second parameter threshold, the engine operating condition is determined to be a medium demand operating condition, and the second target control method corresponding to the medium demand scenario is to control the engine based on the received engine control command; wherein, the first parameter threshold is greater than the second parameter threshold.
[0103] In practical implementation, the second parameter threshold This can be a pre-set minimum engine power requirement. When the engine control factor is less than or equal to the first parameter threshold and greater than or equal to the second parameter threshold (…), When the threshold value is 0, it indicates that the engine's power demand is normal, and the engine operating condition is determined to be a medium demand condition. For example, the first parameter threshold value... The second parameter threshold ,when When the power demand of the engine is normal, the engine operating condition is determined to be a medium demand condition.
[0104] When the engine is operating under medium demand conditions, the second target control method corresponding to medium demand conditions is determined to be to control the engine based on the received engine control commands. This method can control the engine to start or stop according to the needs of the vehicle, thereby meeting the power requirements of the vehicle.
[0105] Alternatively, in step 1043, in response to determining that the engine control factor is less than the second parameter threshold, the engine operating condition is determined to be a low-demand operating condition, and the third target control method corresponding to the low-demand scenario is determined to be to control the engine to stop running after receiving a deceleration command.
[0106] In specific implementation, when the engine control factor is less than the second parameter threshold ( When the threshold value is set to 0, it indicates a low demand on the engine's power, thus defining the engine operating condition as a low-demand condition. For example, the second parameter threshold... ,when When the power demand on the engine is low, the engine operating condition is determined to be a low-demand operating condition.
[0107] When the engine is operating under low demand conditions, the third target control method corresponding to the low demand conditions is to control the engine to stop running after receiving a deceleration command. This can stop the engine in advance when anticipating deceleration occurs in the low demand scenario, thereby achieving energy saving while meeting the vehicle's power demand.
[0108] Specifically, when the engine operating condition is determined to be a low-demand condition, upon receiving a deceleration command, the engine is controlled to stop running, and the engine is kept in a stopped state for a target duration, which is longer than a preset shutdown duration. In this way, when the engine operating condition is low-demand, after controlling the engine to stop running, the engine shutdown time can be extended, thereby maximizing energy savings when engine demand is low.
[0109] The above scheme determines the engine operating condition as follows: When the engine control factor is greater than the first parameter threshold, the engine operating condition is identified as a high-demand condition. The first target control method for this high-demand condition is to activate the engine preparation function and prevent the engine from stopping. This allows the engine to start in advance and continue running under high demand conditions, ensuring it meets the power requirements of the driver's habits and future driving routes. When the engine control factor is less than or equal to the first parameter threshold but greater than or equal to the second parameter threshold, the engine operating condition is identified as a medium-demand condition. The second target control method for this medium-demand condition is to control the engine based on received engine control commands. Here, the first parameter threshold is greater than the second parameter threshold, allowing the engine to start or stop according to the vehicle's overall needs, thus meeting the vehicle's power requirements. When the engine control factor is less than the second parameter threshold, the engine operating condition is identified as a low-demand condition. The third target control method for this low-demand condition is to stop the engine upon receiving a deceleration command. This allows the engine to stop in advance when anticipated deceleration occurs under low demand conditions, achieving energy savings while meeting the vehicle's power requirements.
[0110] In some embodiments, step 1041 includes: Step 1041A: Determine the target location of the engine under high demand conditions within a preset distance in front of the vehicle.
[0111] Step 1041B: Obtain the vehicle's current location in real time and determine the relative distance between the current location and the target location.
[0112] Step 1041C: In response to determining that the relative distance is less than or equal to a preset distance threshold, the engine preparation function is activated.
[0113] In practice, the target location is the location where the vehicle's engine has a high demand, and the current location is the vehicle's current position.
[0114] When the engine is in a high-demand condition, it means that the vehicle has a high demand on the engine when it is driving to the target location ahead. By activating the engine preparation function, the engine can be started in advance before the vehicle reaches the target location where the engine demand is high, so that the vehicle can meet the high engine demand at the target location.
[0115] Specifically, after determining that the engine operating condition is a high-demand condition, the engine preparation function is activated when the relative distance between the current position and the target position is less than or equal to a preset distance threshold. In this way, when the vehicle is close to the target position, the engine preparation function is activated in advance to ensure that the engine can meet the high-demand operating conditions of the target position.
[0116] For example, the preset distance threshold can be set between 100m and 200m. When the preset distance threshold is 100m, it means that the engine preparation function can be started in advance when the vehicle is 100m away from the target location of the high-demand working condition.
[0117] The above method determines the target location for high engine demand conditions within a preset distance ahead of the vehicle. The vehicle's current position is acquired in real time, and the relative distance between the current position and the target position is determined. When the relative distance is less than or equal to a preset distance threshold, the engine preparation function is activated. This allows the engine preparation function to be activated in advance when the vehicle is about to reach the target location for high engine demand conditions, ensuring that the engine can meet the high operating requirements of the target location.
[0118] It should be noted that the method in this embodiment can be executed by a single device, such as a computer or server. The method can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.
[0119] It should be noted that the above description describes some embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0120] Based on the same inventive concept, corresponding to any of the above embodiments, this application also provides a vehicle control device.
[0121] refer to Figure 2 The vehicle control device includes: The first parameter determination module 201 is configured to acquire accelerator pedal parameters and determine driver habit parameters based on the accelerator pedal parameters, wherein the driver habit parameters are parameters on the influence of driver habits on the engine. The second parameter determination module 202 is configured to acquire navigation data and determine power demand parameters based on the navigation data, wherein the power demand parameters are parameters that affect the engine. The factor determination module 203 is configured to determine an engine control factor based on the driver habit parameters and the power demand parameters, wherein the engine control factor is the combined influence factor of the driver habit parameters and the power demand parameters on the engine; The engine control module 203 is configured to determine the engine operating condition based on the engine control factor, determine the target control mode corresponding to the engine operating condition, and control the engine according to the target control mode.
[0122] In some embodiments, the first parameter determining module 201 includes: The acquisition unit is configured to acquire the received accelerator pedal depth and the duration of the accelerator pedal depth; The operation frequency determination unit is configured to determine the accelerator pedal operation frequency based on the accelerator pedal depth and the duration. An average depth determination unit is configured to determine the average depth of the accelerator pedal based on the accelerator pedal depth and the duration. The first parameter determination unit is configured to determine the driver habit parameters corresponding to the accelerator pedal operation frequency and the average accelerator pedal depth based on a pre-stored mapping relationship; wherein, the mapping relationship is the correspondence between the accelerator pedal operation frequency, the average accelerator pedal depth and the driver habit parameters.
[0123] In some embodiments, the operating frequency determination unit includes: The valid operation recording subunit is configured to record a valid operation in response to determining that the accelerator pedal depth is greater than a preset depth threshold and the duration is greater than a preset duration. The operation frequency determination subunit is configured to count the number of valid operations within a preset time range and use the ratio of the number of valid operations to the preset time range as the accelerator pedal operation frequency.
[0124] In some embodiments, the average depth determination unit includes: The product processing subunit is configured to perform the following for each accelerator pedal depth: multiply the accelerator pedal depth with the corresponding duration to obtain the product parameter corresponding to the accelerator pedal depth; The summation subunit is configured to sum the product parameters corresponding to all accelerator pedal depths to obtain the total accelerator pedal depth, and to sum all durations to obtain the total duration. The average depth determination subunit is configured to use the ratio of the total accelerator pedal depth to the total duration as the average accelerator pedal depth.
[0125] In some embodiments, the second parameter determining module 202 includes: The road parameter determination unit is configured to acquire navigation data and determine at least one road parameter within a preset distance ahead of the vehicle based on the navigation data. The road factor determination unit is configured to determine the road factor corresponding to each road parameter; wherein the road factor is the influence factor of the road parameter on the power demand; The second parameter determination unit is configured to perform weighted processing on the road factors corresponding to all road parameters to obtain the power demand parameters.
[0126] In some embodiments, the road parameters include at least one of the following: slope, curvature, road type, and congestion level; The road factor determination unit includes: A slope factor determination subunit is configured to determine the ramp type based on the slope, and to determine the slope factor corresponding to the ramp type; and / or, A curvature factor determination subunit is configured to determine the number of curves based on the curvature, and to determine the curvature factor corresponding to the number of curves; and / or, A road type factor determination subunit is configured to determine the road type factor corresponding to the road type based on a pre-stored first correspondence; wherein, the first correspondence is the correspondence between road types and road type factors; and / or, The congestion factor determination subunit is configured to determine the congestion factor corresponding to the congestion level based on a pre-stored second correspondence; wherein the second correspondence is the correspondence between the congestion level and the congestion factor.
[0127] In some embodiments, the factor determination module 203 includes: The fusion parameter determination unit is configured to multiply the driver habit parameters and the power demand parameters to obtain fusion parameters. The factor determination unit is configured to perform weighted processing on the driver habit parameters, the power demand parameters, and the fusion parameters to obtain the engine control factor.
[0128] In some embodiments, the engine control module 203 includes: The first target control mode determination unit is configured to, in response to determining that the engine control factor is greater than a first parameter threshold, determine that the engine operating condition is a high-demand condition, and determine that the first target control mode corresponding to the high-demand condition is to start the engine preparation function and prohibit the engine from stopping; or... The second target control mode determination unit is configured to, in response to determining that the engine control factor is less than or equal to a first parameter threshold and greater than or equal to a second parameter threshold, determine that the engine operating condition is a medium demand operating condition, and determine that the second target control mode corresponding to the medium demand scenario is to control the engine based on the received engine control command; wherein, the first parameter threshold is greater than the second parameter threshold; or... The third target control mode determination unit is configured to determine the engine operating condition as a low-demand condition in response to determining that the engine control factor is less than the second parameter threshold, and to determine the third target control mode corresponding to the low-demand scenario as controlling the engine to stop running after receiving a deceleration command.
[0129] In some embodiments, the first target control mode determination unit includes: The target location determination subunit is configured to determine the target location of the engine under high demand conditions within a preset distance in front of the vehicle. The relative distance determination subunit is configured to acquire the vehicle's current position in real time and determine the relative distance between the current position and the target position; The engine preparation start-up subunit is configured to activate the engine preparation function in response to determining that the relative distance is less than or equal to a preset distance threshold.
[0130] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing this application, the functions of each module can be implemented in one or more software and / or hardware.
[0131] The apparatus of the above embodiments is used to implement the corresponding vehicle control method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.
[0132] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle control method described in any of the above embodiments.
[0133] Figure 3 This embodiment illustrates a more specific hardware structure of an electronic device. The device may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.
[0134] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.
[0135] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.
[0136] The input / output interface 1030 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components within the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.
[0137] The communication interface 1040 is used to connect the communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB (Universal Serial Bus), network cable, etc.) or wireless means (such as mobile network, WIFI (Wireless Fidelity), Bluetooth, etc.).
[0138] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.
[0139] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.
[0140] The electronic devices described above are used to implement the corresponding vehicle control methods in any of the foregoing embodiments and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.
[0141] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the vehicle control method as described in any of the above embodiments.
[0142] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random-access memory (SRAM), dynamic random-access memory (DRAM), other types of random-access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital video disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.
[0143] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the vehicle control method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.
[0144] Based on the same inventive concept, corresponding to any of the above embodiments, this application also provides a computer program product, including computer program instructions. When the computer program instructions are run on a computer, the computer causes the computer to execute the vehicle control method as described in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.
[0145] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a vehicle, including the vehicle control device, or electronic device, or storage medium in the above embodiments, wherein the vehicle device implements the vehicle control method described in any of the above embodiments.
[0146] The vehicles described in the above embodiments are used to implement the vehicle control method described in any of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.
[0147] It is understood that before using the technical solutions of the various embodiments in this application, users will be informed of the type, scope of use, and usage scenarios of the personal information involved in an appropriate manner, and user authorization will be obtained.
[0148] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose, based on the prompt message, whether to provide personal information to the software or hardware such as electronic devices, applications, servers, or storage media performing the operations described in this application.
[0149] As an optional but not limited implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.
[0150] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this application. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this application.
[0151] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.
[0152] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this application, and this also takes into account the fact that the details of the implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this application will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this application, it will be apparent to those skilled in the art that the embodiments of this application can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.
[0153] Although this application has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.
[0154] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this application.
Claims
1. A vehicle control method, characterized in that, The method includes: Obtain accelerator pedal parameters, and determine driver habit parameters based on the accelerator pedal parameters, wherein the driver habit parameters are the parameters of the influence of driver habits on the engine; Obtain navigation data and determine power demand parameters based on the navigation data, wherein the power demand parameters are parameters that affect the engine; The engine control factor is determined based on the driver habit parameters and the power demand parameters, wherein the engine control factor is the combined influence factor of the driver habit parameters and the power demand parameters on the engine; Based on the engine control factors, the engine operating condition is determined, the target control mode corresponding to the engine operating condition is determined, and the engine is controlled according to the target control mode.
2. The method according to claim 1, characterized in that, The process of acquiring accelerator pedal parameters and determining driver habit parameters based on these parameters includes: Obtain the received accelerator pedal depth and the duration of the accelerator pedal depth; The accelerator pedal operation frequency is determined based on the accelerator pedal depth and the duration. The average accelerator pedal depth is determined based on the accelerator pedal depth and the duration of the delay. Based on the pre-stored mapping relationship, the driver's habit parameters corresponding to the accelerator pedal operation frequency and the average accelerator pedal depth are determined; wherein, the mapping relationship is the correspondence between the accelerator pedal operation frequency, the average accelerator pedal depth and the driver's habit parameters.
3. The method according to claim 2, characterized in that, Determining the accelerator pedal operation frequency based on the accelerator pedal depth and the duration includes: In response to determining that the accelerator pedal depth is greater than a preset depth threshold and the duration is greater than a preset duration, a valid operation is recorded. The number of valid operations within a preset time range is counted, and the ratio of the number of valid operations to the preset time range is used as the accelerator pedal operation frequency.
4. The method according to claim 2, characterized in that, Determining the average accelerator pedal depth based on the accelerator pedal depth and the duration includes: For each accelerator pedal depth, perform the following: multiply the accelerator pedal depth by the corresponding duration to obtain the product parameter corresponding to the accelerator pedal depth; The total accelerator pedal depth is obtained by summing the product parameters corresponding to all accelerator pedal depths, and the total duration is obtained by summing all durations. The ratio of the total accelerator pedal depth to the total duration is taken as the average accelerator pedal depth.
5. The method according to claim 1, characterized in that, The process of acquiring navigation data and determining power demand parameters based on the navigation data includes: Acquire navigation data and determine at least one road parameter within a preset distance ahead of the vehicle based on the navigation data; Determine the road factor corresponding to each road parameter; wherein, the road factor is the influence factor of the road parameter on the power demand; The power demand parameters are obtained by weighting the road factors corresponding to all road parameters.
6. The method according to claim 5, characterized in that, The road parameters include at least one of the following: slope, curvature, road type, and congestion level; Determining the road factor corresponding to each road parameter includes: The ramp type is determined based on the slope, and the slope factor corresponding to the ramp type is determined; and / or, The number of curves is determined based on the curvature, and the curvature factor corresponding to the number of curves is determined; and / or, Based on a pre-stored first correspondence, the road type factor corresponding to the road type is determined; wherein, the first correspondence is the correspondence between road types and road type factors; and / or, Based on a pre-stored second correspondence, a congestion factor corresponding to the congestion level is determined; wherein, the second correspondence is the correspondence between the congestion level and the congestion factor.
7. The method according to claim 1, characterized in that, The step of determining the engine control factor based on the driver's habit parameters and the power demand parameters includes: The fusion parameters are obtained by multiplying the driver habit parameters and the power demand parameters. The engine control factor is obtained by weighting the driver habit parameters, the power demand parameters, and the fusion parameters.
8. The method according to claim 1, characterized in that, The process of determining the engine operating condition based on the engine control factor and determining the target control method corresponding to the engine operating condition includes: In response to determining that the engine control factor is greater than a first parameter threshold, the engine operating condition is determined to be a high-demand operating condition, and the first target control method corresponding to the high-demand operating condition is determined to be starting the engine preparation function and prohibiting the engine from stopping; or... In response to determining that the engine control factor is less than or equal to a first parameter threshold and greater than or equal to a second parameter threshold, the engine operating condition is determined to be a medium demand operating condition, and the second target control method corresponding to the medium demand scenario is determined to be controlling the engine based on the received engine control command; wherein, the first parameter threshold is greater than the second parameter threshold; or, In response to determining that the engine control factor is less than the second parameter threshold, the engine operating condition is determined to be a low-demand operating condition, and the third target control method corresponding to the low-demand scenario is determined to be to control the engine to stop running after receiving a deceleration command.
9. The method according to claim 8, characterized in that, The determination that the first target control method corresponding to the high-demand operating condition is to start the engine preparation function and prevent the engine from stopping includes: Determine the target location of the engine under high demand conditions within a preset distance in front of the vehicle; The vehicle's current location is acquired in real time, and the relative distance between the current location and the target location is determined. In response to determining that the relative distance is less than or equal to a preset distance threshold, the engine preparation function is activated.
10. A vehicle, characterized in that, The device includes an electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor, when executing the program, implements the method as claimed in any one of claims 1 to 9.