Energy-saving control method of vehicle and vehicle

Abstract

The embodiment of the application relates to the technical field of vehicles, and discloses an energy-saving control method of a vehicle and the vehicle, the method comprising the following steps: after determining that a user has a parking rest intention, acquiring vehicle state information and current environment information of the vehicle; according to the current environment information and the vehicle state information, predicting a parking duration corresponding to a current parking scene; according to the parking duration and the vehicle state information, determining a target energy-saving strategy; wherein different energy-saving strategies correspond to different closed intelligent driving functions; and executing the target energy-saving strategy to control the vehicle to enter an energy-saving mode corresponding to the current parking scene. The technical scheme of the application can solve the problem of poor energy-saving control flexibility in the prior art.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, specifically to an energy-saving control method for vehicles and a vehicle. Background Technology

[0002] With the increasing popularity of new energy vehicles, users frequently encounter parking and rest scenarios in their daily use. For example, when shopping in a mall, making a short stop at a highway service area, or temporarily parking on the roadside in a residential area, users use vehicle functions such as seat adjustment, air conditioning control, and entertainment systems to meet their rest needs. However, during the period when the vehicle is parked and resting, the Advanced Driver Assistance System (ADAS) still needs to continue operating to maintain safety functions such as reversing radar, driver status monitoring, blind spot monitoring, and collision warning, so as not to affect subsequent driving safety.

[0003] Currently, a uniform energy-saving strategy is often adopted, which involves directly disabling some ADAS functions during parking and rest scenarios to reduce energy consumption. However, this approach cannot adapt to the different rest needs of various scenarios, making it difficult to achieve reasonable energy saving while ensuring the normal operation of ADAS safety functions. The energy-saving control method is rigid and lacks flexibility. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide an energy-saving control method and a vehicle to solve the problem of poor flexibility in energy-saving control in the prior art.

[0005] According to one aspect of the present invention, a vehicle energy-saving control method is provided, the method comprising:

[0006] After determining that the user intends to park and rest, obtain the vehicle's status information and the current environment information.

[0007] Based on the current environmental information and the vehicle status information, predict the parking duration corresponding to the current parking scenario;

[0008] Based on the parking duration and vehicle status information, a target energy-saving strategy is determined; wherein, different energy-saving strategies correspond to different intelligent driving functions being turned off;

[0009] The target energy-saving strategy is executed to control the vehicle to enter the energy-saving mode corresponding to the current parking scenario.

[0010] According to another aspect of the present invention, an energy-saving control device for a vehicle is provided, comprising:

[0011] The acquisition module is used to acquire vehicle status information and current environmental information after determining that the user intends to park and rest.

[0012] The prediction module is used to predict the parking duration corresponding to the current parking scenario based on the current environmental information and the vehicle status information.

[0013] The determination module is used to determine the target energy-saving strategy based on the parking duration and the vehicle status information; wherein, different energy-saving strategies correspond to different intelligent driving functions being turned off;

[0014] The execution module is used to execute the target energy-saving strategy to control the vehicle to enter the energy-saving mode corresponding to the current parking scenario.

[0015] According to another aspect of the present invention, an electronic device is provided, including: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus;

[0016] The memory is used to store at least one executable instruction that causes the processor to perform the operation of the energy-saving control method for the vehicle described above.

[0017] According to another aspect of the present invention, a vehicle is provided, comprising: a vehicle body and an electronic device, the electronic device being used to perform the energy-saving control method of the vehicle described above.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, the storage medium storing at least one executable instruction that causes an energy-saving control device of an electronic device / vehicle to perform the following operations:

[0019] After determining that the user intends to park and rest, obtain the vehicle's status information and the current environment information.

[0020] Based on the current environmental information and the vehicle status information, predict the parking duration corresponding to the current parking scenario;

[0021] Based on the parking duration and vehicle status information, a target energy-saving strategy is determined; wherein, different energy-saving strategies correspond to different intelligent driving functions being turned off;

[0022] The target energy-saving strategy is executed to control the vehicle to enter the energy-saving mode corresponding to the current parking scenario.

[0023] This invention collects vehicle status and environmental information after determining the user's intention to park and rest. Based on the vehicle status and environmental information, it predicts the parking duration corresponding to the current parking scenario. Combining the parking duration with the vehicle status, it matches and grades a target energy-saving strategy. Finally, it executes the target energy-saving strategy to put the vehicle into the energy-saving mode corresponding to the current parking scenario. This can replace the traditional uniform energy-saving control method and achieve differentiated and precise energy-saving control for different parking scenarios such as short-term parking and long-term rest. While ensuring the normal operation of the core safety functions of ADAS during parking and rest, it effectively reduces the ineffective energy consumption of the power battery, improves the flexibility and scenario adaptability of energy-saving control, and takes into account both the user's rest experience and the vehicle's range guarantee needs.

[0024] The above description is merely an overview of the technical solutions of the embodiments of the present invention. In order to better understand the technical means of the embodiments of the present invention and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0025] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0026] Figure 1 A flowchart of a first embodiment of the energy-saving control method for vehicles provided by the present invention is shown;

[0027] Figure 2 A flowchart of a second embodiment of the energy-saving control method for vehicles provided by the present invention is shown;

[0028] Figure 3 A schematic diagram of the structure of an electronic device provided by the present invention is shown;

[0029] Figure 4 A flowchart of a third embodiment of the energy-saving control method for vehicles provided by the present invention is shown;

[0030] Figure 5 A schematic diagram of an embodiment of the energy-saving control device for vehicles provided by the present invention is shown;

[0031] Figure 6 A schematic diagram of an embodiment of the electronic device provided by the present invention is shown. Detailed Implementation

[0032] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0033] Addressing the issue that existing energy-saving strategies that uniformly disable some ADAS functions during parking and rest scenarios are rigid and inflexible, failing to adapt to the differentiated rest needs of various parking scenarios such as short-term parking and long-term rest, and thus struggling to achieve reasonable energy saving while ensuring the normal operation of ADAS safety functions, the inventors recognized that the core reason for the poor energy-saving control effect lies in the failure of the strategy to dynamically adapt to the parking duration and vehicle status of the current parking scenario. Therefore, the inventors proposed identifying the parking duration corresponding to the current parking scenario by comprehensively considering the vehicle status and the current environmental information. Then, based on different parking durations such as short-term parking or long-term rest, and combined with the vehicle status, a differentiated energy-saving strategy is matched for the current parking scenario. This replaces a single, fixed energy-saving method, thereby achieving more precise and reasonable energy-saving control while ensuring the normal operation of ADAS safety functions, effectively improving the flexibility and scenario adaptability of energy-saving control in parking and rest scenarios.

[0034] The execution subject of this invention embodiment can be an electronic device with processing capabilities, such as an existing controller in a vehicle or a separately set controller. The controller can be an electronic control unit (ECU), a microcontroller unit (MCU), etc., and this invention embodiment is not limited thereto.

[0035] Figure 1 A flowchart of a first embodiment of the energy-saving control method for vehicles provided by the present invention is shown. Figure 1 As shown, the method includes the following steps:

[0036] Step 110: After determining that the user intends to park and rest, obtain the vehicle status information and the current environment information.

[0037] For example, the intention to rest in a parked vehicle refers to the user's intention to rest or temporarily stay in the vehicle when it is parked.

[0038] Vehicle status information consists of parameters that reflect the status of the vehicle's gear position, body components, and electrical equipment. For example, it may include information such as the parking gear signal, seat back angle, seat belt buckle status, air conditioning operating mode and fan speed, vehicle entertainment system on / off status, remaining battery charge, and duration of no driving operation.

[0039] The current environmental information includes information about the vehicle's internal and external environment and time, such as parking location, current time, ambient light intensity, and ambient temperature.

[0040] In one example, the electronic device can first collect information such as parking gear position, seat belt status, and seat angle through the vehicle's communication bus. Combined with the vehicle-machine interaction commands, it can determine whether the user intends to park and rest. After confirming the intention, it can read vehicle status information such as seat adjustment angle, air conditioning mode, and remaining battery power in real time through the vehicle sensor module. At the same time, it can identify the parking position through the vehicle positioning module, obtain the current time through the vehicle clock, and collect external environmental parameters through light and temperature sensors to obtain the current environmental information.

[0041] Specifically, in response to the user's active triggering of the rest mode, it is determined that the user intends to park and rest; or, if the vehicle status information is determined to meet the preset parking and rest conditions, it is determined that the user intends to park and rest.

[0042] The conditions for parking and resting include the vehicle being parked and meeting any of the following: the seatbelt is unbuckled, the seat back is adjusted to a preset resting angle, the air conditioning is in low fan speed and constant temperature mode, the in-vehicle entertainment system is off, and there is no driving operation after parking for a preset duration. Rest mode is a working mode specifically designed for in-vehicle rest scenarios and can be actively activated by the user via the in-vehicle system, buttons, or voice commands.

[0043] For example, when the electronic device detects that a user actively activates the rest mode via a touch button, physical button, or voice command on the vehicle's infotainment system, it can directly determine that the user intends to rest while parked. Alternatively, it can first determine if the vehicle is in parked (P) gear. If parking is enabled, it can further detect if at least one of the following conditions is met: the seatbelt is unfastened, the seatback is adjusted to a resting angle of 100° or higher, the air conditioning is on low fan speed constant temperature mode, the infotainment system is turned off, or there has been no driving operation for more than 5 consecutive minutes after parking. If these conditions are met, a 3-minute anti-shake timer is initiated. If there is no change in the status after the timer ends, the user's intention to rest while parked is confirmed. The anti-shake timer logic uses a 3-minute delay trigger mechanism. For example, after detecting that the user has unfastened their seatbelt, this state must be maintained for 3 minutes without any other reverse operation (such as refastening) to confirm the rest intention. This mechanism avoids accidental triggering of the energy-saving mode due to brief operations (such as temporarily adjusting the seat).

[0044] After determining the intent, the electronic device can collect vehicle status information such as seat angle, air conditioning mode, and remaining battery power through the communication bus, and obtain environmental information such as parking position, current time, light and temperature through the positioning module, clock and environmental sensors.

[0045] By combining user-initiated rest mode activation with automatic vehicle status determination of parking rest conditions, a dual intent recognition method is implemented. On the one hand, it can quickly respond when the user clearly has a rest need, ensuring the user's active control over the vehicle's energy-saving mode and improving ease of use and interactive experience. On the other hand, it can automatically identify potential parking rest intentions based on the actual vehicle status when the user does not actively operate, avoiding energy waste caused by the user forgetting to manually activate the mode. This effectively improves the accuracy and reliability of parking rest intention recognition and reduces false triggering and missed triggering.

[0046] Step 120: Based on the current environmental information and vehicle status information, predict the parking duration corresponding to the current parking scenario.

[0047] For example, the current parking scenario is the type of parking scenario, such as a shopping mall parking garage, a highway service area, a roadside parking lot in a residential area, or nighttime parking. The parking duration is the duration for which the vehicle is expected to remain parked and resting.

[0048] In one example, the electronic device can first identify the current parking scenario based on the current environment information, and then retrieve historical parking data from the database that has a similarity greater than a preset threshold to the current parking scenario. The average of the historical parking durations in the historical parking data is then used as the parking duration corresponding to the current parking scenario.

[0049] In another example, the electronic device has a pre-set prediction model, which is trained based on historical parking data. The training data can be environmental data from the historical parking data, and the training labels are the historical parking durations. The current environmental information can then be input into the prediction model to output the parking duration corresponding to the current parking scenario. It should be noted that this embodiment of the invention does not limit the type of prediction model; for example, it can be a neural network model.

[0050] Step 130: Determine the target energy-saving strategy based on parking duration and vehicle status information.

[0051] For example, the target energy-saving strategy is an energy-saving solution that adapts to the current parking scenario, parking duration, and vehicle battery level.

[0052] Intelligent driving functions refer to the vehicle's ADAS (Advanced Driver Assistance Systems) functions. Different energy-saving strategies correspond to different degrees of disabling non-essential intelligent driving functions, while core safety functions remain enabled at all times. In other words, different energy-saving strategies correspond to different disabled intelligent driving functions. For example, energy-saving strategies can be set to three levels: mild, moderate, and severe energy saving. Each energy-saving strategy corresponds to different disabled intelligent driving functions. It should be noted that the embodiments of this invention do not limit the content of the energy-saving strategies. For example, Table 1 provides an example of an energy-saving strategy provided by an embodiment of this invention.

[0053] Table 1 Energy Saving Strategies

[0054]

[0055] Core safety features may include, for example, reversing radar, driving recorder, driver status monitoring, and panoramic imaging; advanced driving features may include, for example, adaptive cruise control, lane keeping assist, automatic parking, and Navigate on Autopilot (NOA); major driving features may include, for example, intelligent following, traffic signal recognition, and pedestrian and vehicle recognition; and basic intelligent driving assistance features may include, for example, blind spot monitoring, collision warning, and lane departure warning.

[0056] In one example, the electronic device can prioritize executing the battery level determination logic. If the remaining battery level in the vehicle status information is lower than a preset threshold (e.g., 30%), the heavy energy-saving strategy is directly set as the target energy-saving strategy. If the battery level is within the normal range (e.g., greater than or equal to 30%), then based on the predicted parking time and the mapping relationship between the preset parking time and energy-saving strategies, light, medium, or heavy energy-saving strategies are matched respectively. Different strategies correspond to a progressively increasing number of unnecessary intelligent driving functions being turned off, thereby determining the final adapted target energy-saving strategy. For example, Table 2 illustrates a mapping relationship between an energy-saving strategy and parking time and the remaining battery level provided by an embodiment of the present invention.

[0057] Table 2. Mapping relationship between energy-saving strategies, parking duration, and remaining battery charge.

[0058]

[0059] It should be noted that the above mapping relationship is only an example, and the embodiments of the present invention do not limit this mapping relationship. Electronic devices can determine the target energy-saving strategy based on the predicted parking duration and vehicle status information, combined with a preset energy-saving strategy mapping relationship (as shown in Table 2). For example, if the predicted parking duration is ≥2 hours, a heavy energy-saving strategy is matched, disabling advanced driving functions (such as adaptive cruise control) and primary driving functions (such as intelligent following), retaining only core safety functions (such as reversing radar). This strategy matching logic dynamically adjusts the start / stop state of intelligent driving functions through software instructions, requiring no hardware modification and reducing control complexity.

[0060] Step 140: Execute the target energy-saving strategy to control the vehicle to enter the energy-saving mode corresponding to the current parking scenario.

[0061] For example, the energy-saving mode is a low-power mode in which the vehicle operates according to a target energy-saving strategy. It reduces parking energy consumption by shutting down unnecessary intelligent driving functions via software commands without cutting off sensor power. It should be noted that the intelligent driving function control uses a software switch control method. During the energy-saving process, only the relevant functional logic is shut down, without cutting off sensor power; that is, the sensors are switched to a low-power mode. It also supports quick wake-up, allowing intelligent driving functions to be quickly restored without affecting the user experience. Furthermore, it ensures the normal availability of core safety functions throughout the entire control process, balancing energy saving and driving safety.

[0062] In one example, the electronic device can generate corresponding ADAS power-saving control commands based on the target energy-saving strategy and send them to the ADAS controller. The controller selectively disables unnecessary auxiliary functions at the corresponding level according to the command requirements, while retaining core safety functions such as reversing radar and driver status monitoring, so that the vehicle enters an energy-saving mode that matches the current parking scenario, while maintaining a continuous power supply to the basic sensing components.

[0063] Optionally, during the operation of energy-saving mode, the electronic device can continuously monitor the actual parking time. If the actual parking time exceeds the predicted parking time, it will automatically switch to a higher level of energy-saving strategy. For example, when the predicted parking time is 1.5 hours, a medium energy-saving strategy will be matched and executed. If the actual parking time exceeds 2 hours, it will automatically switch to a heavy energy-saving strategy. This achieves dynamic adaptation of energy-saving strategies, further optimizes energy consumption control during parking rest, and balances energy-saving effect with user experience.

[0064] Optionally, when the electronic device receives a user-triggered command to exit the rest mode, or when the electronic device detects a clear driving intention from the user, such as engaging P gear, fastening the seatbelt, or pressing the accelerator, it triggers the exit from the energy-saving mode and initiates a recovery mechanism to quickly close the energy-saving mode and simultaneously restore the user's original intelligent driving function configuration. After the recovery is complete, it returns to the aforementioned step 110 to restart the control process, including determining the parking rest intention and subsequent parking duration prediction and energy-saving strategy matching. At the same time, the electronic device saves the actual parking duration data of this parking rest to the database in real time, updates historical parking scenarios and corresponding duration data, and provides more accurate historical data support that is in line with user habits for the similarity calculation of the current parking scenario and the determination of the initial parking duration, further optimizing the accuracy of subsequent energy-saving control.

[0065] In this embodiment, after determining the user's intention to park and rest, vehicle status and environmental information are collected. Based on the vehicle status and environmental information, the parking duration corresponding to the current parking scenario is predicted. Combined with the parking duration and vehicle status, a target energy-saving strategy is matched and graded. Finally, the target energy-saving strategy is executed to make the vehicle enter the energy-saving mode corresponding to the current parking scenario. This can replace the traditional uniform energy-saving control method and achieve differentiated and precise energy-saving control for different parking scenarios such as short-term parking and long-term rest. While ensuring the normal operation of ADAS core safety functions during parking and rest, it effectively reduces the ineffective energy consumption of the power battery, improves the flexibility and scenario adaptability of energy-saving control, and takes into account both the user's rest experience and the vehicle's range guarantee needs.

[0066] Figure 2 A flowchart of a second embodiment of the energy-saving control method for vehicles provided by the present invention is shown. Figure 2 As shown, the method includes the following steps:

[0067] Step 210: After determining that the user intends to park and rest, obtain the vehicle status information and the current environment information.

[0068] It should be noted that this step is similar to step 110 mentioned above, and will not be repeated here.

[0069] Step 220: Determine the current parking scenario based on the environmental parameters, current time, and parking location information in the current environment information.

[0070] For example, as mentioned above, the current environmental information may include environmental parameters, current time, parking location, etc. Environmental parameters are parameters characterizing the internal and external environmental conditions of the vehicle, such as interior brightness, external light intensity, ambient temperature, and weather conditions. The current time is the real-time time obtained by the electronic device and can be used to classify time periods. Parking location information is the specific attribute of the vehicle's parking location, such as shopping mall parking garages, highway service areas, roadside parking in residential areas, and company parking lots. The current parking scenario is a category of vehicle rest and usage scenarios; different scenarios correspond to different parking duration characteristics and energy consumption requirements, such as shopping mall rest scenarios, highway service area rest scenarios, temporary nighttime stops in residential areas, and company lunch break scenarios.

[0071] In one example, the electronic device can determine the parking location type based on the parking location information in the current environment and a map database, such as "XX shopping mall underground parking garage" or "XX highway service area parking lot"; it can also classify the current time period based on the current time, such as weekday lunch break, weekend outing, or nighttime; and it can supplement scene features based on environmental parameters such as light intensity and ambient temperature, such as "air conditioning on for constant temperature in hot weather" or "low light environment at night". The electronic device combines the above three dimensions of information to determine the current parking scene, which could be, for example, "shopping mall underground parking garage + weekend outing + high temperature constant temperature environment".

[0072] Step 230: Determine the initial parking duration based on the current parking scenario.

[0073] For example, the initial parking duration is a basic estimated parking duration matched with the current parking scenario.

[0074] In one example, the electronic device retrieves all historical parking data that match the current parking scenario from the database. If there are multiple sets of historical data for the same scenario, outliers with abnormal durations are removed, and the remaining valid historical parking data are statistically calculated. The arithmetic mean of all valid durations is taken as the initial parking duration. If there is no historical parking data that matches the current parking scenario in the database, a preset default initial duration, such as 1 hour, is used as the initial parking duration corresponding to the current parking scenario.

[0075] Specifically, for each historical parking scenario in the preset database, the similarity between the current parking scenario and the historical parking scenario is calculated to obtain the target historical parking scenario that matches the current parking scenario; the initial parking duration is determined based on the parking duration corresponding to the target historical parking scenario.

[0076] The preset database is a storage unit for historical parking data, containing records of multiple historical parking scenarios and the corresponding actual parking duration for each scenario. Historical parking scenarios are parking situations that have occurred in the past, formed by integrating parking location, time, and environmental parameters. Target historical parking scenarios are those that have a similarity to the current parking scenario that reaches a preset threshold and can be used as a reference for parking duration.

[0077] For example, an electronic device can iterate through each set of historical parking scenarios stored in a preset database, comparing the current parking scenario with each historical parking scenario from three dimensions: parking location, current time period, and environmental parameters. Weighted calculations are then performed (e.g., 40% for location, 30% for time period, and 30% for environmental parameters) to obtain the similarity scores between each pair of scenarios. Historical parking scenarios with a similarity score greater than or equal to a preset threshold (e.g., 80%) are selected as target historical parking scenarios. If multiple target historical parking scenarios exist, the historical parking durations corresponding to all target historical parking scenarios are extracted. After removing abnormal duration data that deviates from the mean by ±30%, the average of the remaining valid duration data is calculated, and this average is determined as the initial parking duration for the current parking scenario. If no historical parking scenario in the database meets the similarity requirement, a preset 1 hour is directly used as the initial parking duration. Alternatively, the median of the parking durations corresponding to the target historical parking scenarios can be used as the initial parking duration. Alternatively, the data distribution can be determined by calculating the coefficient of variation of the remaining valid time data. When the coefficient of variation is higher than a preset threshold, the median is selected, and when it is lower than the threshold, the average value is selected. This ensures that the initial parking time matches the user's actual rest needs and provides a reliable benchmark for the accurate matching of subsequent energy-saving strategies.

[0078] The similarity calculation can be performed by weighted comparison of three dimensions: parking location (40%), time period (30%), and environmental parameters (30%). For example, if the current scene and the historical scene have a matching degree of 80% in location, 70% in time period, and 85% in environmental parameters, then the overall similarity is (80%×40%)+(70%×30%)+(85%×30%)=79.5%. When the similarity is ≥80%, it is determined to match the target historical parking scene, ensuring that only high-confidence data is used for prediction and avoiding interference from low-relevance historical data.

[0079] Step 240: Correct the initial parking duration based on the vehicle status information to obtain the parking duration corresponding to the current parking scenario.

[0080] For example, the correction process is a calculation process that combines the vehicle's real-time status information to adjust the initial parking duration, thereby optimizing the accuracy of the initial duration and making it more in line with the user's current actual rest needs.

[0081] Vehicle status information is the core basis for reflecting users' real-time rest behavior, and is used to distinguish between rest tendencies and temporary stop behaviors.

[0082] In one example, the electronic device can be corrected using a preset state duration lookup table. This table pre-configured with duration offsets corresponding to different vehicle state combinations. When it detects that the seat is adjusted to a resting angle and sleep mode is activated, the corresponding duration offset is directly added to the initial parking duration. When it detects that the user frequently operates the vehicle's infotainment system without adjusting the seat, the corresponding duration offset is directly subtracted from the initial parking duration and then adjusted to a fixed time precision to obtain the final parking duration for the current parking scenario. For example, when sleep mode is activated in the vehicle status information, the initial parking duration is increased by 30%; when the vehicle status information indicates only a brief seat adjustment, 50% of the initial parking duration is taken as the parking duration.

[0083] In another example, a correction coefficient is determined based on the vehicle status information; the initial parking duration is then corrected based on the correction coefficient to obtain the parking duration corresponding to the current parking scenario.

[0084] The correction factor is a numerical coefficient determined based on the user's current vehicle operation status, used to amplify or reduce the initial parking duration. Vehicle status information includes parameters that reflect the user's desire to rest, such as seat back adjustment angle, seat belt status, air conditioning operating mode, vehicle infotainment system operation behavior, and whether sleep mode is activated.

[0085] In some possible implementations, the electronic device can first determine the overall category of the vehicle's status information. For example, it can be divided into rest-oriented and temporary-stop states. For instance, if the vehicle status information includes a seat back angle ≥100°, seatbelt unfastened and no frequent vehicle system operation, vehicle system sleep mode activated, and air conditioning running at low fan speed and constant temperature, the overall vehicle status information can be classified as a rest-oriented state, indicating that the user has a need for a longer rest period. If the vehicle status information includes a seat back angle <100°, only brief seat adjustment, frequent touches of the vehicle system after unfastening the seatbelt, and short periods of inactivity after parking, the overall vehicle status information can be classified as a temporary-stop state, indicating that the user has a need for a temporary stop. Then, the electronic device determines the corresponding correction coefficient based on the overall category of the vehicle status information, multiplies the initial parking time by the correction coefficient to obtain the corrected duration, and finally normalizes the corrected duration to a 10-minute precision to obtain the final parking time corresponding to the current parking scenario.

[0086] In some possible implementations, the parameters in the vehicle status information are classified to obtain vehicle status information with rest tendency marking and vehicle status information with temporary stop marking; wherein, the vehicle status information with different markings has different weight coefficients; and correction coefficients are determined based on the weight coefficients corresponding to the vehicle status information with rest tendency marking and the vehicle status information with temporary stop marking.

[0087] The classification process involves categorizing the collected vehicle status information according to the strength of the user's willingness to rest. Vehicle status information tagged with "rest tendency" indicates a user's need for extended parking and rest. Vehicle status information tagged with "temporary stop" indicates a user's need for only a short stop and no need for extended rest. Weighting coefficients are pre-configured quantitative values ​​for different status information types, representing the degree of influence of that type of status on the determination of rest duration. For example, the seat back adjustment angle for "rest tendency" corresponds to 1.1, while the seat back adjustment angle for "temporary stop" corresponds to 0.9.

[0088] For example, the electronic device can first iterate through all parameters in the vehicle status information, and mark the status information such as adjusting the seat back to the preset rest angle, turning on the vehicle's sleep mode, setting the air conditioner to the rest constant temperature mode, and unfastening the seat belt without further operation as the rest tendency category. The status information such as not adjusting the seat to the rest angle, frequently operating the vehicle's system after parking, only briefly adjusting the seat, and not turning on the air conditioner in rest mode as the temporary stop category. Then, it can retrieve the weight coefficients of each type of status marked as rest tendency and the weight coefficients of each type of status marked as temporary stop from the database. Finally, it can perform a weighted fusion calculation of the comprehensive weight of the rest tendency category and the comprehensive weight of the temporary stop category. For example, the weighting ratio can be 60% for the rest tendency category and 40% for the temporary stop category. Finally, it can calculate the correction coefficient applicable to the current vehicle status.

[0089] For example, the current vehicle status information is: seat back adjusted to 105°, vehicle infotainment system in sleep mode, air conditioning set to rest / constant temperature mode, and there is slight operation of the vehicle infotainment system after parking. The electronic device first iterates through the parameters in the vehicle status information, marking the first three items as rest tendency category and the last item as temporary stop category; then it retrieves the preset weights, with the three weights for the rest tendency category being 1.1, 1.2, and 1.1 respectively. First, it calculates the comprehensive weight of this category, and takes the average of the three weights to obtain (1.1+1.2+1.1)÷3=1.13, while the weight of the temporary stop category is 0.9; then, it performs a weighted fusion calculation according to the ratio of 60% for the rest tendency category and 40% for the temporary stop category, and the correction coefficient = 1.13×0.6+0.9×0.4=1.038, finally obtaining a correction coefficient of 1.038. The corrected duration is regularized with a precision of 10 minutes. For example, if the corrected duration is 2 hours and 15 minutes, it is regularized to 2 hours and 20 minutes to ensure that the duration boundary of the strategy matching is clear and to reduce strategy switching caused by minor deviations.

[0090] Step 250: Determine the target energy-saving strategy based on parking duration and vehicle status information.

[0091] It should be noted that this step is similar to step 130 mentioned above, and will not be repeated here.

[0092] Step 260: Execute the target energy-saving strategy to control the vehicle to enter the energy-saving mode corresponding to the current parking scenario.

[0093] It should be noted that this step is similar to step 140 mentioned above, and will not be repeated here.

[0094] In this embodiment, after determining the user's intention to park and rest, vehicle status information and current environmental information are collected. Based on the environmental parameters, current time, and parking location in the current environmental information, the current parking scenario is determined. Then, the initial parking duration is determined based on the current parking scenario and corrected by combining the vehicle status information to obtain the final parking duration. Next, the target energy-saving strategy is matched according to the parking duration and vehicle status information. Finally, the strategy is executed to control the vehicle to enter the corresponding energy-saving mode. This can replace the traditional uniform energy-saving control method and achieve precise differentiated energy-saving control for different parking scenarios such as shopping malls, service areas, and residential areas, as well as different duration characteristics such as short-term parking and long-term rest. Under the premise of ensuring the normal operation of ADAS core safety functions, it effectively reduces the ineffective energy consumption of the power battery during parking and rest, improves the accuracy and scenario adaptability of vehicle energy-saving control, and takes into account both the user's rest experience and the vehicle's range guarantee needs.

[0095] Figure 3 A schematic diagram of the structure of an electronic device provided by the present invention is shown, such as... Figure 3 As shown, the electronic device includes a status acquisition module, a main control module, an ADAS controller, a user interaction module, and an intelligent driving memory module.

[0096] The status acquisition module is used to collect vehicle status information and data of the internal and external environment. The vehicle status information includes gear position, vehicle speed, remaining power battery charge, seat belt status, seat adjustment status, and air conditioning operation status. The data of the internal and external environment includes parking location, current time, and ambient brightness information, thus providing complete data support for subsequent rest intention determination, parking scene recognition, and parking duration prediction.

[0097] The intelligent driving memory module is used to record and store users' intelligent driving function usage habits, historical parking scenarios, and parking duration data corresponding to each scenario in real time, providing historical data reference for matching the current parking scenario and calculating the initial parking duration.

[0098] The user interaction module provides users with an interface for starting and stopping the rest mode, as well as an energy-saving selection interface, so that users can actively trigger the rest mode.

[0099] The main control module undertakes the core functions of rest mode management, parking rest intention determination, parking duration prediction, energy-saving strategy matching, control command sending, and memory recovery triggering. When determining the parking rest intention, the main control module can obtain the operation signal of the user actively triggering the rest mode through the user interaction module, or determine whether the preset parking rest conditions are met based on the vehicle status information collected by the status acquisition module, thereby determining whether the user has a parking rest intention. After determining the intention, the main control module determines the current parking scenario based on the environmental information collected by the status acquisition module, retrieves historical parking data in the intelligent driving memory module to calculate the initial parking duration, and then combines the vehicle status information to complete the duration correction to obtain the final parking duration. Then, based on the parking duration and vehicle status information, the target energy-saving strategy is determined and energy-saving control commands (ADAS power-saving mode commands) are issued. At the same time, the memory recovery operation can be triggered according to the scenario requirements.

[0100] The ADAS controller receives energy-saving control commands from the main control module and executes corresponding control logic. It controls the vehicle's intelligent driving functions in stages through software switches and performs memory recovery operations for intelligent driving functions, ensuring the normal execution of energy-saving modes and subsequent function recovery.

[0101] Figure 4 A flowchart of a third embodiment of the energy-saving control method for vehicles provided by the present invention is shown. Figure 4 As shown, the method includes the following steps:

[0102] Step 310: System initialization.

[0103] Electronic devices load memory data from the intelligent driving memory module and prepare for predictions.

[0104] Step 320: Data collection and intent determination.

[0105] The electronic device collects vehicle status information and current environmental information based on the status acquisition module for subsequent prediction. Then, it performs dual trigger condition judgment based on the main control module. Whether the user actively enters the rest mode through the user interaction module or the vehicle automatically determines that it meets the parking rest conditions and completes the 3-minute anti-shake rest intention, the parking rest intention is confirmed. If neither is met, the data collection is returned.

[0106] Step 330: Parking duration prediction and strategy matching.

[0107] Electronic devices output predicted parking time through scene recognition, data matching, and time correction prediction. Then, they combine the predicted parking time with the remaining power of the vehicle's power battery to match the corresponding target energy-saving strategy. Furthermore, an automatic upgrade mechanism is set up for exceeding the predicted parking time, that is, when the actual parking time exceeds the predicted time, it automatically switches to a higher level of energy-saving strategy.

[0108] Step 340: Energy-saving control is executed.

[0109] The ADAS controller controls the intelligent driving function according to the predetermined target energy-saving strategy.

[0110] Step 350: Exit and Resume.

[0111] The electronic device determines whether exit conditions, such as active exit or detected driving intent, are met. If exit is not confirmed, the current energy-saving control state is maintained. If exit is confirmed, the energy-saving mode is turned off and the user's original intelligent driving function configuration is quickly restored. After configuration restoration, the system returns to step 320 to re-determine the parking rest intent. Simultaneously, the actual parking data can be saved to the intelligent driving memory module to update historical data. For example, the current parking scenario (e.g., shopping mall underground parking garage + weekend time + high-temperature environment), actual parking duration (e.g., 2 hours 15 minutes), and matching energy-saving strategy (e.g., moderate energy saving) can be used as a set of historical parking data and updated in the database. This data can subsequently be used for similarity calculation of the current parking scenario, determination of the initial parking duration, and correction processing.

[0112] This approach not only effectively improves the flexibility, accuracy, and adaptability of energy-saving control during parking and rest scenarios, achieving a balance between energy saving and safety, but also further reduces ineffective energy consumption during parking through data iteration and optimization, taking into account both user experience and vehicle range assurance.

[0113] Figure 5 A schematic diagram of an embodiment of the energy-saving control device for vehicles provided by the present invention is shown. Figure 5 As shown, the energy-saving control device 400 of the vehicle includes: an acquisition module 410, a prediction module 420, a determination module 430, and an execution module 440.

[0114] The acquisition module 410 is used to acquire vehicle status information and current environmental information after determining that the user intends to park and rest.

[0115] The prediction module 420 is used to predict the parking duration corresponding to the current parking scenario based on the current environmental information and vehicle status information.

[0116] The determination module 430 is used to determine the target energy-saving strategy based on the parking duration and vehicle status information; different energy-saving strategies correspond to different intelligent driving functions being turned off.

[0117] The execution module 440 is used to execute the target energy-saving strategy to control the vehicle to enter the energy-saving mode corresponding to the current parking scenario.

[0118] In one alternative embodiment, the prediction module 420 is used for:

[0119] Based on the environmental parameters, current time, and parking location information in the current environmental information, determine the current parking scenario;

[0120] Determine the initial parking duration based on the current parking scenario;

[0121] The initial parking duration is corrected based on the vehicle status information to obtain the parking duration corresponding to the current parking scenario.

[0122] In one alternative embodiment, the prediction module 420 is used for:

[0123] For each historical parking scenario in the preset database, the similarity between the current parking scenario and the historical parking scenario is calculated to obtain the target historical parking scenario that matches the current parking scenario.

[0124] The initial parking duration is determined based on the parking duration corresponding to the target historical parking scenarios.

[0125] In one alternative embodiment, the prediction module 420 is used for:

[0126] Use the average or median of the parking durations corresponding to the target historical parking scenarios as the initial parking duration.

[0127] In one alternative embodiment, the prediction module 420 is used for:

[0128] Determine the correction factor based on the vehicle status information;

[0129] The initial parking duration is corrected based on the correction coefficient to obtain the parking duration corresponding to the current parking scenario.

[0130] In one alternative embodiment, the prediction module 420 is used for:

[0131] The vehicle status information is classified and processed to obtain vehicle status information marked with rest tendency and vehicle status information marked with temporary stop; among them, the vehicle status information marked with different weight coefficients have different weight coefficients.

[0132] The correction coefficient is determined based on the weighting coefficients corresponding to the vehicle status information marked with rest tendency and the vehicle status information marked with temporary stop.

[0133] In one alternative approach, module 410 is obtained:

[0134] In response to a user's active triggering of the rest mode, it determines that the user intends to park and rest; or,

[0135] If the vehicle status information is determined to meet the preset parking and rest conditions, then it is determined that the user intends to park and rest.

[0136] In one alternative approach, the parking rest conditions include the vehicle being parked and meeting any of the following conditions: the seat belt is unbuckled, the seat back is adjusted to a preset resting angle, the air conditioning is in low fan speed constant temperature mode, the vehicle entertainment system is turned off, and there is no driving operation after parking for a preset duration.

[0137] As can be seen from the above, the energy-saving control device for vehicles provided in this embodiment of the invention can replace the traditional unified energy-saving control method, and achieve differentiated and precise energy-saving control for different parking scenarios such as short-term parking and long-term rest. While ensuring the normal operation of the core safety functions of ADAS during parking and rest, it effectively reduces the ineffective energy consumption of the power battery, improves the flexibility and scenario adaptability of energy-saving control, and takes into account both the user's rest experience and the vehicle's range guarantee needs.

[0138] Figure 6 The diagram shows a structural schematic of an embodiment of the electronic device provided by the present invention. The specific embodiments of the present invention do not limit the specific implementation of the electronic device.

[0139] like Figure 6 As shown, the electronic device may include: a processor 502, a communications interface 504, a memory 506, and a communications bus 508.

[0140] The processor 502, communication interface 504, and memory 506 communicate with each other via communication bus 508. Communication interface 504 is used to communicate with other network elements such as clients or other servers. The processor 502 executes program 510, specifically performing the relevant steps in the above-described embodiment of the energy-saving control method for vehicles.

[0141] Specifically, program 510 may include program code, which includes computer-executable instructions.

[0142] Processor 502 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The electronic device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or they may be processors of different types, such as one or more CPUs and one or more ASICs.

[0143] Memory 506 is used to store program 510. Memory 506 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0144] Specifically, program 510 can be called by processor 502 to cause the electronic device to perform the following operations:

[0145] After determining that the user intends to park and rest, obtain the vehicle's status information and the current environment information.

[0146] Based on the current environmental information and vehicle status information, predict the parking duration corresponding to the current parking scenario;

[0147] Based on parking duration and vehicle status information, a target energy-saving strategy is determined; different energy-saving strategies correspond to different intelligent driving functions being turned off.

[0148] Implement the target energy-saving strategy to control the vehicle to enter the energy-saving mode corresponding to the current parking scenario.

[0149] In one optional approach, the parking duration corresponding to the current parking scenario is predicted based on the current environmental information and vehicle status information, including:

[0150] Based on the environmental parameters, current time, and parking location information in the current environmental information, determine the current parking scenario;

[0151] Determine the initial parking duration based on the current parking scenario;

[0152] The initial parking duration is corrected based on the vehicle status information to obtain the parking duration corresponding to the current parking scenario.

[0153] In one alternative approach, the initial parking duration is determined based on the current parking scenario, including:

[0154] For each historical parking scenario in the preset database, the similarity between the current parking scenario and the historical parking scenario is calculated to obtain the target historical parking scenario that matches the current parking scenario.

[0155] The initial parking duration is determined based on the parking duration corresponding to the target historical parking scenarios.

[0156] In one alternative approach, the initial parking duration is determined based on the parking duration corresponding to the target historical parking scenario, including:

[0157] Use the average or median of the parking durations corresponding to the target historical parking scenarios as the initial parking duration.

[0158] In one optional approach, the initial parking duration is corrected based on vehicle status information to obtain the parking duration corresponding to the current parking scenario, including:

[0159] Determine the correction factor based on the vehicle status information;

[0160] The initial parking duration is corrected based on the correction coefficient to obtain the parking duration corresponding to the current parking scenario.

[0161] In one alternative approach, the correction factor is determined based on vehicle status information, including:

[0162] The vehicle status information is classified and processed to obtain vehicle status information marked with rest tendency and vehicle status information marked with temporary stop; among them, the vehicle status information marked with different weight coefficients have different weight coefficients.

[0163] The correction coefficient is determined based on the weighting coefficients corresponding to the vehicle status information marked with rest tendency and the vehicle status information marked with temporary stop.

[0164] In one alternative approach, determining that a user intends to park and rest includes:

[0165] In response to a user's active triggering of the rest mode, it determines that the user intends to park and rest; or,

[0166] If the vehicle status information is determined to meet the preset parking and rest conditions, then it is determined that the user intends to park and rest.

[0167] In one alternative approach, the parking rest conditions include the vehicle being parked and meeting any of the following conditions: the seat belt is unbuckled, the seat back is adjusted to a preset resting angle, the air conditioning is in low fan speed constant temperature mode, the vehicle entertainment system is turned off, and there is no driving operation after parking for a preset duration.

[0168] As can be seen from the above, the electronic device provided by the embodiments of the present invention can replace the traditional unified energy-saving control method and achieve differentiated and precise energy-saving control for different parking scenarios such as short-term parking and long-term rest. While ensuring the normal operation of the core safety functions of ADAS during parking and rest, it effectively reduces the ineffective energy consumption of the power battery, improves the flexibility and scenario adaptability of energy-saving control, and takes into account both the user's rest experience and the vehicle's range guarantee needs.

[0169] This invention provides a vehicle, including a vehicle body and an electronic device, which is used to perform the vehicle-based child safety status monitoring method in any of the above method embodiments.

[0170] This invention provides a computer-readable storage medium storing at least one executable instruction that, when executed on an energy-saving control device of an electronic device / vehicle, causes the energy-saving control device of the electronic device / vehicle to perform the energy-saving control method of the vehicle in any of the above-described method embodiments.

[0171] The executable instructions can be used to cause the energy-saving control device of the electronic device / vehicle to perform the following operations:

[0172] After determining that the user intends to park and rest, obtain the vehicle's status information and the current environment information.

[0173] Based on the current environmental information and vehicle status information, predict the parking duration corresponding to the current parking scenario;

[0174] Based on parking duration and vehicle status information, a target energy-saving strategy is determined; different energy-saving strategies correspond to different intelligent driving functions being turned off.

[0175] Implement the target energy-saving strategy to control the vehicle to enter the energy-saving mode corresponding to the current parking scenario.

[0176] In one optional approach, the parking duration corresponding to the current parking scenario is predicted based on the current environmental information and vehicle status information, including:

[0177] Based on the environmental parameters, current time, and parking location information in the current environmental information, determine the current parking scenario;

[0178] Determine the initial parking duration based on the current parking scenario;

[0179] The initial parking duration is corrected based on the vehicle status information to obtain the parking duration corresponding to the current parking scenario.

[0180] In one alternative approach, the initial parking duration is determined based on the current parking scenario, including:

[0181] For each historical parking scenario in the preset database, the similarity between the current parking scenario and the historical parking scenario is calculated to obtain the target historical parking scenario that matches the current parking scenario.

[0182] The initial parking duration is determined based on the parking duration corresponding to the target historical parking scenarios.

[0183] In one alternative approach, the initial parking duration is determined based on the parking duration corresponding to the target historical parking scenario, including:

[0184] Use the average or median of the parking durations corresponding to the target historical parking scenarios as the initial parking duration.

[0185] In one optional approach, the initial parking duration is corrected based on vehicle status information to obtain the parking duration corresponding to the current parking scenario, including:

[0186] Determine the correction factor based on the vehicle status information;

[0187] The initial parking duration is corrected based on the correction coefficient to obtain the parking duration corresponding to the current parking scenario.

[0188] In one alternative approach, the correction factor is determined based on vehicle status information, including:

[0189] The vehicle status information is classified and processed to obtain vehicle status information marked with rest tendency and vehicle status information marked with temporary stop; among them, the vehicle status information marked with different weight coefficients have different weight coefficients.

[0190] The correction coefficient is determined based on the weighting coefficients corresponding to the vehicle status information marked with rest tendency and the vehicle status information marked with temporary stop.

[0191] In one alternative approach, determining that a user intends to park and rest includes:

[0192] In response to a user's active triggering of the rest mode, it determines that the user intends to park and rest; or,

[0193] If the vehicle status information is determined to meet the preset parking and rest conditions, then it is determined that the user intends to park and rest.

[0194] In one alternative approach, the parking rest conditions include the vehicle being parked and meeting any of the following conditions: the seat belt is unbuckled, the seat back is adjusted to a preset resting angle, the air conditioning is in low fan speed constant temperature mode, the vehicle entertainment system is turned off, and there is no driving operation after parking for a preset duration.

[0195] As can be seen from the above, the computer-readable storage medium provided in the embodiments of the present invention stores at least one executable instruction. When the executable instruction runs on the energy-saving control device of the electronic device / vehicle, it can replace the traditional unified energy-saving control method and achieve differentiated and precise energy-saving control for different parking scenarios such as short-term parking and long-term rest. While ensuring the normal operation of the core safety functions of ADAS during parking and rest, it effectively reduces the ineffective energy consumption of the power battery, improves the flexibility and scenario adaptability of energy-saving control, and takes into account both the user's rest experience and the vehicle's range guarantee needs.

[0196] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system, or other device. Furthermore, the embodiments of this invention are not directed to any particular programming language.

[0197] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. Similarly, for the sake of brevity and to aid in understanding one or more aspects of the invention, in the description of exemplary embodiments of the invention above, various features of the embodiments are sometimes grouped together in a single embodiment, figure, or description thereof. The claims, which follow the detailed description, are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0198] Those skilled in the art will understand that the modules in the device of the embodiment can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiment can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components, except that at least some of such features and / or processes or units are mutually exclusive.

[0199] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be construed as limiting the order of execution.

Claims

1. A method for energy-saving control of a vehicle, characterized in that, include: After determining that the user intends to park and rest, obtain the vehicle's status information and the current environment information. Based on the current environmental information and the vehicle status information, predict the parking duration corresponding to the current parking scenario; Based on the parking duration and vehicle status information, a target energy-saving strategy is determined; wherein, different energy-saving strategies correspond to different intelligent driving functions being turned off; The target energy-saving strategy is executed to control the vehicle to enter the energy-saving mode corresponding to the current parking scenario.

2. The method according to claim 1, characterized in that, The step of predicting the parking duration corresponding to the current parking scenario based on the current environmental information and the vehicle status information includes: Based on the environmental parameters, current time, and parking location information in the current environmental information, the current parking scenario is determined; Determine the initial parking duration based on the current parking scenario; The initial parking duration is corrected based on the vehicle status information to obtain the parking duration corresponding to the current parking scenario.

3. The method according to claim 2, characterized in that, The step of determining the initial parking duration based on the current parking scenario includes: For each historical parking scenario in the preset database, a similarity calculation is performed between the current parking scenario and the historical parking scenario to obtain a target historical parking scenario that matches the current parking scenario; The initial parking duration is determined based on the parking duration corresponding to the target historical parking scenario.

4. The method according to claim 3, characterized in that, The step of determining the initial parking duration based on the parking duration corresponding to the target historical parking scenario includes: The average or median of the parking durations corresponding to the target historical parking scenarios is used as the initial parking duration.

5. The method according to claim 2, characterized in that, The step of correcting the initial parking duration based on the vehicle status information to obtain the parking duration corresponding to the current parking scenario includes: Based on the vehicle status information, determine the correction coefficient; The initial parking duration is corrected based on the correction coefficient to obtain the parking duration corresponding to the current parking scenario.

6. The method according to claim 5, characterized in that, The step of determining the correction coefficient based on the vehicle status information includes: The vehicle status information is classified to obtain vehicle status information marked with rest tendency and vehicle status information marked with temporary stop; wherein, the vehicle status information marked with different weight coefficients has different weight coefficients. The correction coefficient is determined based on the weighting coefficients corresponding to the vehicle status information marked with a rest tendency and the vehicle status information marked with a temporary stop.

7. The method according to any one of claims 1-6, characterized in that, Determining whether a user intends to park and rest includes: In response to a user's active triggering of the rest mode, it determines that the user intends to park and rest; or, If the vehicle status information is determined to meet the preset parking and rest conditions, then it is determined that the user intends to park and rest.

8. The method according to claim 7, characterized in that, The parking rest conditions include the vehicle being parked and meeting any of the following conditions: the seat belt is unbuckled, the seat back is adjusted to a preset rest angle, the air conditioner is in low fan speed constant temperature mode, the vehicle entertainment system is turned off, and there is no driving operation after parking for a preset time.

9. An energy-saving control device for a vehicle, characterized in that, The device includes: The acquisition module is used to acquire vehicle status information and current environmental information after determining that the user intends to park and rest. The prediction module is used to predict the parking duration corresponding to the current parking scenario based on the current environmental information and the vehicle status information. The determination module is used to determine the target energy-saving strategy based on the parking duration and the vehicle status information; wherein, different energy-saving strategies correspond to different intelligent driving functions being turned off; The execution module is used to execute the target energy-saving strategy to control the vehicle to enter the energy-saving mode corresponding to the current parking scenario.

10. A vehicle, characterized in that, include: Vehicle body and electronic equipment; The electronic device is used to perform the energy-saving control method for the vehicle as described in any one of claims 1-8.

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