Cabin temperature adjusting method based on climate and storage medium

Abstract

The invention discloses a climate-based cabin temperature adjusting method and a storage medium, and the method comprises the steps: obtaining the current information of a target vehicle, and the current information comprises the current position, the current parking time, the current environment temperature and the current date; a preset model is adopted to generate push information and push time based on the current information, and the push information is output to a mobile terminal based on the battery state of the target vehicle; the mobile terminal responds to the push information to start an instruction generation unit, and the instruction generation unit responds to a confirmation instruction input by a user to generate an extreme mode starting instruction based on the push information; the vehicle-mounted terminal operates an extreme mode in response to the extreme mode starting instruction, and the vehicle-mounted terminal outputs an adjustment completion prompt to the mobile terminal in response to the completion state of the extreme mode; and in response to the getting-on state of the user, the vehicle-mounted terminal adjusts the vehicle-mounted terminal air conditioner to enter a low-power mode.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent vehicle cabin adjustment under extreme climate conditions, and in particular to a climate-based cabin temperature adjustment method and storage medium. Background Art

[0002] Through the applicant's insight into user needs, it was found that car owners in some areas have to park their vehicles for a long time in extreme climate environments for at least 4 months each year. In parts of Guangdong, Guangxi Zhuang Autonomous Region, and Hainan Province south of the Tropic of Cancer, the summer lasts for more than 7 months each year; in the northern region north of the Qinling Mountains, there are more than 4 months of cold winter each year. The Xinjiang Uygur Autonomous Region and parts of the three northeastern provinces enter winter in October and last until April of the following year, with winter lasting 6 months; in the central region with more suitable temperatures, Sichuan and Chongqing, Central China, North China, and the Yangtze River Delta, there are at least 2 months of hot summer and 2 months of low winter temperatures. After a vehicle has been parked for a long time in the hot summer sun, the temperature inside the vehicle can reach over 60 degrees; after being parked for a long time in snowy weather, in addition to being cold inside the vehicle, there are also problems such as frosted windshield that is difficult to remove.

[0003] Taking the Jetta as an example, analysis of mass production data shows that over a third of Jetta owners commute daily to a fixed location. They spend over a third of their annual time in extreme climates, enduring intense heat and cold inside their vehicles and manually managing frosted windshields and rearview mirrors. With existing solutions, users, caught up in their busy daily commutes, need to remember when to turn on the car's air conditioning on their phones and manually adjust parameters like temperature and air volume. This inherently high barrier to entry means users often forget to use the system, ultimately abandoning it most of the time. Summary of the Invention

[0004] To solve at least one aspect of the above problems, the present invention provides a climate-based cabin temperature adjustment method, comprising: obtaining current information of a target vehicle, the current information including the current location, the current parking time, the current ambient temperature and the current date; using a preset model to generate push information and push time based on the current information, and outputting the push information to a mobile terminal based on the battery status of the target vehicle; the mobile terminal starts an instruction generation unit in response to the push information, and the instruction generation unit generates an extreme mode start instruction based on the push information in response to a confirmation instruction input by the user; the vehicle terminal runs the extreme mode in response to the extreme mode start instruction, and the vehicle terminal outputs an adjustment completion prompt to the mobile terminal in response to the completion status of the extreme mode; the vehicle terminal adjusts the vehicle terminal air conditioner to enter a low power mode in response to the user's boarding status.

[0005] Preferably, the step of using a preset model to generate push information and push time based on the current information also includes: setting extreme mode activation conditions, the extreme mode activation conditions include ambient temperature thresholds, parking time thresholds, regional thresholds and date thresholds, the push information includes quick cooling mode activation prompts and quick heating mode activation prompts, the extreme mode activation conditions include extreme cold conditions and extreme hot conditions, the preset model generates a quick cooling mode activation prompt based on the current information according to the extreme cold conditions, and the preset model generates a quick heating mode activation prompt based on the current information according to the extreme hot conditions; the preset model determines the commuting time and extreme mode time based on the historical operating data of the target vehicle, the commuting time includes working time and getting off work time, and the preset model determines the push time based on the commuting time and the extreme mode time.

[0006] Preferably, the step of outputting push information based on the battery status of the target vehicle also includes: the preset model determines the extreme mode operating energy consumption based on the historical operating data of the target vehicle; the preset model outputs push information based on the extreme mode adjustment energy consumption and the battery status, wherein the battery status includes the current power level, charging status and scheduled charging plan, and the push information is output when the current power level is greater than the extreme mode operating energy consumption, and the push information is output when the current power level is less than the extreme mode operating energy consumption and the charging status and the scheduled charging plan meet the extreme mode operating energy consumption.

[0007] Preferably, the extreme mode activation condition also includes a response weight, and the response weight includes a first-level response weight, a second-level response weight and a third-level response weight. The first-level response weight is greater than the second-level response weight, and the second-level response weight is greater than the third-level response weight. The temperature threshold weight and the parking time threshold weight are the first-level response weight, the temperature threshold weight is the second-level response weight, and the regional threshold weight is the third-level response weight.

[0008] Preferably, the preset model also receives the current information in response to a start instruction input by a user.

[0009] Preferably, the extreme mode includes a quick heating mode and a quick cooling mode. When the push information is a quick cooling mode prompt, the vehicle-computer end responds to the extreme mode start instruction to run the quick cooling mode. When the push information is a quick heating mode prompt information, the vehicle-computer end responds to the extreme mode start instruction to run the quick heating mode.

[0010] Preferably, the quick cooling mode includes turning on the air conditioner, setting the lowest temperature, setting the maximum air volume, turning on the external circulation, and turning on the seat ventilation.

[0011] Preferably, the quick heating mode includes turning on the air conditioner, the highest temperature, the largest air volume, turning on the internal circulation, turning on the seat heating, turning on the front windshield defrosting, turning on the rear windshield defrosting, and turning on the exterior rearview mirror heating.

[0012] Preferably, the low power mode also includes a summer temperature maintenance mode and a winter temperature maintenance mode.

[0013] In another aspect, a computer-readable storage medium is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program executes any of the above methods for adjusting cabin temperature based on climate.

[0014] The climate-based cabin temperature adjustment method of this embodiment has the following beneficial effects: by predicting the user's commute time and integrating factors such as the real-time temperature of the user's parking location, parking duration, battery charge, and charging schedule, it ultimately determines whether to push a reminder to the user's mobile phone to start the air conditioning in advance. If the user confirms the request, the in-car air conditioning is remotely activated at full cooling / heating power with a single click, creating a comfortable driving temperature for the user, solving defrosting issues, and improving driving safety. This provides a complete and effective solution for long-term, high-frequency, and repetitive scenarios and needs in extreme climates. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] To better understand the above and other objects, features, advantages, and functions of the present invention, reference may be made to the embodiments shown in the accompanying drawings. Like reference numerals in the accompanying drawings refer to like components. Those skilled in the art should understand that the accompanying drawings are intended to schematically illustrate preferred embodiments of the present invention and have no limiting effect on the scope of the present invention. The components in the drawings are not drawn to scale.

[0016] Figure 1 A flow chart of a method for adjusting cabin temperature based on climate according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0017] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0018] As used herein, the term "including" and its variations represent open inclusion, i.e., "including but not limited to." Unless otherwise stated, the term "or" means "and / or." The term "based on" means "based at least in part on." The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment." The term "another embodiment" means "at least one additional embodiment." The terms "first," "second," etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0019] In order to at least partially solve one or more of the above problems and other potential problems, the embodiments of the present disclosure provide a cabin temperature adjustment method based on climate, such as Figure 1 As shown, the operating terminal of the climate-based cabin temperature adjustment method includes a cloud, a mobile phone, and a vehicle computer. The cloud and the vehicle computer are connected in real-time communication to obtain information output by the vehicle computer. The cloud and the mobile phone are connected in real-time communication, and the mobile phone and the vehicle computer are connected in communication. The mobile phone and the vehicle computer are identified and matched by user codes. The cloud uses user codes to realize data identification and matching between the mobile phone and the vehicle computer. The climate-based cabin temperature adjustment method includes the following steps:

[0020] Step S1, obtaining the current information of the target vehicle, including the current location, current parking time, current ambient temperature and current date.

[0021] Specifically, the cloud obtains current information by connecting to the target vehicle, where Figure 1 As shown, the current location (i.e., the user's location) is marked by the latitude and longitude coordinates of the target vehicle, and the current location comes from the positioning system data of the vehicle terminal; the current parking duration (parking time) is the time interval from the last power-off of the vehicle terminal to the moment of obtaining the current information; the current ambient temperature (the current temperature outside the vehicle) is the ambient temperature of the target vehicle's location; the current date (i.e., the season in which the user is located) is the date corresponding to the moment of obtaining the current information.

[0022] Step S2: Generate push information and push time based on current information using a preset model, and output push information to the mobile terminal based on the battery status of the target vehicle.

[0023] Specifically, the training method of the preset model includes: constructing an extreme mode training set, adding labels to the vehicle operation data of the extreme mode training set, including extreme cold conditions, extreme hot conditions, commuting time, extreme mode time consumption, push time, extreme mode energy consumption, battery status and push message output time, etc. Through the training of the extreme mode training set, the preset model can complete autonomous learning to generate push information and push time based on the current information of the target vehicle, and determine whether to output push information based on the battery status of the target vehicle. In some embodiments, the preset model is an AI large model set in the cloud. For example, the preset model uses the Alibaba Qwen2.5 large model. The preset model uses the vehicle system to record the time information and location information of the user's historical vehicle use, stores the time information and location information in the database, analyzes the historical data in the database according to a preset time period, and identifies the user's travel pattern information, wherein the travel pattern information includes travel time, travel location and travel frequency.

[0024] In some embodiments, the step of using a preset model to generate push information and push time based on current information also includes: step S201, setting the extreme mode activation conditions, the extreme mode activation conditions include ambient temperature threshold, parking time threshold, regional threshold and date threshold, the push information includes a quick cooling mode activation prompt and a quick heating mode activation prompt, the extreme mode activation conditions include extreme cold conditions and extreme hot conditions, the preset model generates a quick cooling mode activation prompt based on the current information according to the extreme cold conditions, and the preset model generates a quick heating mode activation prompt based on the current information according to the extreme hot conditions.

[0025] The ambient temperature threshold for extremely cold conditions is less than or equal to 5°C, the parking time threshold is greater than or equal to 2 hours, the regional threshold is north of the Tropic of Cancer, and the date threshold is January-March and October-December. The ambient temperature threshold for extremely hot conditions is greater than or equal to 30°C, the parking time threshold is greater than or equal to 2 hours, all cities, and the date threshold is June-August. The preset model evaluates the current information of the target vehicle based on the extremely cold conditions. For example, when the current location, current parking time, current ambient temperature and current date in the current information of the target vehicle are within the threshold interval corresponding to the extremely cold conditions, the preset model generates a prompt to turn on the quick heating mode; when the current location, current parking time, current ambient temperature and current date in the current information of the target vehicle are within the threshold interval corresponding to the extremely hot conditions, the preset model generates a prompt to turn on the quick cooling mode. In another embodiment, the thresholds for the extreme mode activation conditions can be set according to the actual usage requirements of the target vehicle.

[0026] In some embodiments, the extreme mode activation condition also includes a response weight, which includes a first-level response weight, a second-level response weight, and a third-level response weight. The first-level response weight is greater than the second-level response weight, the second-level response weight is greater than the third-level response weight, the temperature threshold weight and the parking time threshold weight are the first-level response weight, the temperature threshold weight is the second-level response weight, and the regional threshold weight is the third-level response weight.

[0027] Specifically, by setting response weights at each level, a push message is generated when the target vehicle's current information does not fully meet various thresholds, and pre-cooling or pre-heating adjustments are further implemented based on the push message. For example, by setting response weights, even if neither the region nor the season meets the extreme mode activation conditions, the target vehicle can still be pre-heated or pre-cooled in the event of extreme cold or heat. In other words, by setting response weights for the extreme mode activation conditions, the target vehicle's adaptability to extreme weather can be increased.

[0028] In step S202 , the preset model determines the commuting time and the extreme mode time according to the historical operation data of the target vehicle. The commuting time includes the time when going to work and the time when leaving get off work. The preset model determines the push time according to the commuting time and the extreme mode time.

[0029] Specifically, the historical operating data of the target vehicle includes power-on time, power-off time and location information. The preset model determines the parking time and parking location of the target vehicle based on the historical operating data, and further determines the commuting time based on the parking location and parking time frequency of the historical operating data. For example, the frequency of parking at a fixed location at a fixed time exceeding the fixed time is greater than or equal to a specified number of times per week, and the corresponding locations of home and company are determined by the time corresponding to the parking time, and further determine the working time, off-work time, and commuting time based on the power-on time and power-off time corresponding to the locations of home and company.

[0030] The target vehicle's historical operating data also includes energy consumption information, including the duration of rapid heating and cooling modes. The preset model determines the duration of extreme mode based on this energy consumption information. The preset model determines the push notification time based on the commute time and the duration of extreme mode. For example, if the extreme mode duration is 10 minutes and the commute times are 8:00 and 17:00, the preset model can determine the push notification time based on the target vehicle's current information. For example, the push notification time is 7:50 before the start of the workday and 16:50 before the end of the workday.

[0031] In some embodiments, the step of outputting push information based on the battery status of the target vehicle also includes: step S203, the preset model determines the extreme mode operating energy consumption based on the historical operating data of the target vehicle; the preset model outputs push information based on the extreme mode adjusted energy consumption and battery status, wherein the battery status includes the current power, charging status and scheduled charging plan, and the push information is output when the current power is greater than the extreme mode operating energy consumption, and the push information is output when the current power is less than the extreme mode operating energy consumption and the charging status and scheduled charging plan meet the extreme mode operating energy consumption.

[0032] Specifically, the historical operating data of the target vehicle includes air conditioning cooling energy consumption and air conditioning heating energy consumption. The preset model determines the energy consumption of the rapid cooling mode based on the air conditioning cooling energy consumption, determines the energy consumption of the rapid heating mode based on the air conditioning heating energy consumption, and further evaluates the energy consumption requirements of the vehicle based on the current state of the target vehicle to determine whether the current battery state of the target vehicle can support the extreme operation mode of the vehicle-side. The extreme operation energy consumption of the vehicle includes the energy consumption of the rapid cooling mode or the energy consumption of the commuting distance, or the energy consumption of the rapid heating mode and the energy consumption of the commuting distance. For example, the push is only performed when the target vehicle has sufficient battery power; if the battery power of the target vehicle is insufficient and not charging, the push is abandoned; if the battery power of the target vehicle is insufficient, but it is currently charging, and the power is sufficient to support the remote cooling and heating service before the estimated departure time, the push continues. In another embodiment, the preset model also includes a preset power threshold. For example, the preset power threshold is 20%. When the current battery power of the target vehicle is less than 20%, the push information is rejected.

[0033] In some embodiments, the method further includes a preset model receiving current information in response to a start instruction input by a user.

[0034] Specifically, when a user requests rapid heating or cooling of a target vehicle, they activate the preset model through a startup command, activating the target vehicle's rapid heating or cooling function. By setting startup commands for the preset models and increasing the startup conditions for the preset models, computing costs can be reduced, improving cloud-based operational efficiency and adapting to the needs of a large number of vehicles.

[0035] In step S3, the mobile terminal activates the instruction generation unit in response to the push information, and the instruction generation unit generates an extreme mode activation instruction based on the push information in response to the confirmation instruction input by the user.

[0036] Specifically, if Figure 1As shown, the cloud pushes a message to the user's mobile phone, asking them whether to enable the rapid cooling / heating service for parking in extreme weather conditions. If the user confirms, they can activate the maximum power rapid cooling or heating mode with a single click. The mobile terminal is equipped with a command generation unit. The command generation unit generates a rapid cooling mode activation command based on the received rapid cooling mode activation prompt and confirmation command. The command generation unit also generates a rapid heating mode activation command based on the received rapid heating mode activation prompt and confirmation command.

[0037] In step S4, the vehicle computer terminal operates the extreme mode in response to the extreme mode start instruction, and the vehicle computer terminal outputs an adjustment completion prompt to the mobile terminal in response to the completion status of the extreme mode.

[0038] Specifically, the vehicle computer receives an extreme mode activation command via the mobile terminal and, in response to the extreme mode activation command, operates in extreme mode. In some embodiments, the vehicle computer further includes a monitoring unit that, in response to the activation of extreme mode by the vehicle computer, outputs the vehicle status in real time, including the progress of extreme mode activation. The mobile terminal receives the vehicle status in real time via a connection to the vehicle computer, allowing the user to monitor the progress of cooling / heating on the mobile phone.

[0039] In some embodiments, the extreme mode includes a quick heating mode and a quick cooling mode. When the push information is a quick cooling mode prompt, the vehicle computer responds to the extreme mode start instruction to run the quick cooling mode. When the push information is a quick heating mode prompt information, the vehicle computer responds to the extreme mode start instruction to run the quick heating mode.

[0040] In some embodiments, the rapid cooling mode includes turning on the air conditioning, setting the lowest temperature, setting the highest air volume, enabling external circulation, and enabling seat ventilation. In some embodiments, the rapid heating mode includes turning on the air conditioning, setting the highest temperature, setting the highest air volume, enabling internal circulation, enabling seat heating, enabling front window defrost, enabling rear window defrost, and enabling exterior mirror heating. Those skilled in the art will appreciate that in other embodiments, the rapid cooling and heating modes may also operate other vehicle-side devices based on actual needs.

[0041] In step S5, the vehicle-side air conditioner is adjusted to enter a low-power mode in response to the user's vehicle-boarding status.

[0042] Specifically, if Figure 1 As shown, the vehicle computer also includes a state maintenance unit. This unit detects the user's entry status by connecting to the vehicle door lock and, in response, adjusts the vehicle computer's air conditioning to low-power mode. This maintains the temperature after the user unlocks the vehicle and enters the vehicle. That is, after the user unlocks the vehicle and enters the vehicle, the air conditioning switches from maximum power to a lower power mode to maintain the vehicle's interior temperature, while also improving comfort and energy efficiency.

[0043] In some embodiments, the low power mode also includes a summer temperature maintenance mode and a winter temperature maintenance mode.

[0044] Specifically, the temperature maintenance tasks in summer temperature maintenance mode include: keeping the air conditioner on, adjusting the temperature to 25 degrees, adjusting the air volume to level 3, and adjusting the seat ventilation to level 1. The temperature maintenance tasks in winter temperature maintenance mode include: keeping the air conditioner on, adjusting the temperature to 19 degrees, adjusting the air volume to level 3, adjusting to external circulation, adjusting the seat heating to level 1, keeping the front window defrost on, keeping the rear window defrost on, and keeping the exterior mirror heating on.

[0045] In another aspect, a computer-readable storage medium is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program executes any of the above methods for adjusting cabin temperature based on climate.

[0046] While various embodiments of the present disclosure have been described above, the foregoing description is intended to be illustrative, non-exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is selected to best explain the principles of the embodiments, their practical applications, or technological improvements in the marketplace, or to enable others skilled in the art to understand this document.

Claims

1. A cabin temperature adjustment method based on climate, characterized in that: include: Obtaining current information of the target vehicle, including current location, current parking duration, current ambient temperature, and current date; Generate push information and push time based on the current information using a preset model, and output the push information to the mobile terminal based on the battery status of the target vehicle; The mobile terminal activates an instruction generation unit in response to the push information, and the instruction generation unit generates an extreme mode activation instruction based on the push information in response to a confirmation instruction input by the user; The vehicle computer terminal operates the extreme mode in response to the extreme mode start instruction, and the vehicle computer terminal outputs an adjustment completion prompt to the mobile terminal in response to a completion status of the extreme mode; The vehicle computer adjusts the vehicle air conditioner into low power mode in response to the user's getting in the vehicle.

2. The method according to claim 1, characterized in that The step of using a preset model to generate push information and push time based on the current information further includes: Setting extreme mode activation conditions, the extreme mode activation conditions including an ambient temperature threshold, a parking duration threshold, a regional threshold, and a date threshold; the pushed information including a quick cooling mode activation prompt and a quick heating mode activation prompt; the extreme mode activation conditions including an extremely cold condition and an extremely hot condition; the preset model generates a quick cooling mode activation prompt based on the current information according to the extremely cold condition; and the preset model generates a quick heating mode activation prompt based on the current information according to the extremely hot condition; The preset model determines the commuting time and the extreme mode time according to the historical operation data of the target vehicle, wherein the commuting time includes the time when going to work and the time when leaving get off work, and the preset model determines the push time according to the commuting time and the extreme mode time.

3. The method according to claim 2, characterized in that The step of outputting push information based on the battery status of the target vehicle further includes: The preset model determines the extreme mode operating energy consumption based on historical operating data of the target vehicle; The preset model adjusts the energy consumption according to the extreme mode and outputs push information according to the battery status, wherein the battery status includes the current power level, charging status and scheduled charging plan. Push information is output when the current power level is greater than the energy consumption of the extreme mode operation, and push information is output when the current power level is less than the energy consumption of the extreme mode operation and the charging status and the scheduled charging plan meet the energy consumption of the extreme mode operation.

4. The method according to claim 3, characterized in that The extreme mode activation condition also includes a response weight, which includes a first-level response weight, a second-level response weight, and a third-level response weight. The first-level response weight is greater than the second-level response weight, and the second-level response weight is greater than the third-level response weight. The temperature threshold weight and the parking time threshold weight are the first-level response weight, the temperature threshold weight is the second-level response weight, and the regional threshold weight is the third-level response weight.

5. The method according to claim 4, characterized in that The preset model also receives the current information in response to a start instruction input by a user.

6. The method according to claim 5, characterized in that The extreme modes include quick heating mode and quick cooling mode. When the push information is a quick cooling mode prompt, the vehicle computer responds to the extreme mode start instruction to run the quick cooling mode. When the push information is a quick heating mode prompt information, the vehicle computer responds to the extreme mode start instruction to run the quick heating mode.

7. The method according to claim 6, characterized in that The quick cooling mode includes turning on the air conditioner, the lowest temperature, the maximum air volume, turning on the external circulation, and turning on the seat ventilation.

8. The method according to claim 7, characterized in that The quick heating mode includes turning on the air conditioner, the highest temperature, the largest air volume, turning on the internal circulation, turning on the seat heating, turning on the front windshield defrost, turning on the rear windshield defrost, and turning on the exterior rearview mirror heating.

9. The method according to claim 1, characterized in that The low power mode also includes a summer temperature maintenance mode and a winter temperature maintenance mode.

10. A computer-readable storage medium, characterized in that The method comprises a computer program, which, when executed by a processor, executes the cabin temperature adjustment method based on climate according to any one of claims 1 to 9.

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