Vehicle air conditioner comfort level control method and system and medium

Abstract

The invention belongs to the technical field of automobile air conditioner control, and particularly relates to a vehicle air conditioner comfort control method and system and a medium. The vehicle air conditioner comfort control method comprises the steps that comfort signals of similar vehicles in the using state are obtained; acquiring a sunlight intensity correction standard; obtaining vehicle monomer data deviating from a normal state according to the comfort level signal in the use state of the same kind of vehicles through a preset reinforcement learning algorithm; and optimizing the single vehicle data deviating from the normal state through a preset optimization algorithm and a sunlight intensity correction standard. The method solves the problems that deviation occurs in control of the air conditioner in the vehicle, and the comfort experience of a user is poor.

Description

Technical Field

[0001] The present invention belongs to the technical field of automobile air-conditioning control, and in particular relates to a vehicle air-conditioning comfort control method, system and medium. Background Art

[0002] Vehicle air conditioning plays a vital role in ensuring the comfort of passengers during travel. Ideally, vehicle air conditioning can maintain the comfort level inside the vehicle regardless of the external weather conditions. For vehicle air conditioning control, sunlight is one of the factors that has the greatest impact on the heat load inside the vehicle. When a vehicle is parked in direct sunlight, the temperature inside the vehicle will rise rapidly, resulting in an increase in heat load.

[0003] Modern vehicles usually use various sensors to collect environmental conditions and adjust the output of vehicle air conditioning according to environmental conditions. Among these sensors, sunlight sensors are particularly important for accurately evaluating the heat load caused by solar radiation. This sensor is usually installed on the inside of the windshield of the passenger compartment to detect the intensity of incident sunlight.

[0004] The accuracy of the sunlight sensor may be affected by various factors, such as the location of the sunlight sensor, the condition of the windshield, and modifications made by the owner, which may affect the sensor's ability to accurately measure sunlight intensity. The accuracy of the sunlight sensor is greatly affected by the windshield. If the customer applies film or protective film to the windshield, or if dust or debris accumulates on the windshield, the sensor value will be biased, resulting in distortion in the calculation of the heat load in the vehicle, and ultimately the relevant control of the vehicle air conditioning will be biased, affecting the user's comfort experience.

[0005] Additionally, environmental conditions and geographic location can vary significantly, affecting the intensity and angle of sunlight exposure, creating challenges in ensuring vehicle air conditioning comfort. Summary of the invention

[0006] In view of the shortcomings of the prior art described above, an object of the present invention is to provide a vehicle air conditioning comfort control method, system and medium, which solve the problem of deviation in vehicle air conditioning control and poor user comfort experience.

[0007] To achieve the above purpose, the present invention adopts the following technical solution.

[0008] A first aspect of the present invention provides a vehicle air conditioning comfort control method, comprising: Obtain the comfort signal of similar vehicles under usage status; Get the sunlight intensity correction standard; The comfort signals of the same type of vehicles under the use state are used to obtain the vehicle single body data that deviates from the normal state through a preset reinforcement learning algorithm; The vehicle unit data that deviates from the normal state is optimized through a preset optimization algorithm and sunlight intensity correction standard.

[0009] As an optional implementation, the comfort signal includes at least one or more of ambient temperature, vehicle interior temperature, sunlight intensity, vehicle geographic coordinates, vehicle air conditioning settings, air conditioning outlet temperature, air conditioning outlet air volume, and air conditioning internal and external circulation status.

[0010] As an optional implementation manner, the obtaining of the comfort signal of the same type of vehicle in use state includes: Obtaining comfort signals under the use status of each vehicle; The vehicle usage status is classified based on preset evaluation principles to obtain comfort signals under the usage status of similar vehicles; the preset evaluation principles at least include geographical location, season, weather conditions, usage time, number of passengers, driving speed and air conditioning usage mode.

[0011] As an optional implementation manner, the step of obtaining vehicle monomer data deviating from a normal state by using a preset reinforcement learning algorithm for the comfort signal of the same type of vehicle in use state includes: Select Convolutional Neural Network or Clustering Algorithm as the preset reinforcement learning algorithm; The environmental conditions and settings are used as input parameters of the preset reinforcement learning algorithm, and the temperature inside the vehicle is used as the output parameter of the preset reinforcement learning algorithm to obtain the vehicle unit data that deviates from the normal state.

[0012] As an optional implementation, the optimizing of the vehicle monomer data deviating from the normal state by using a preset optimization algorithm and a sunlight intensity correction standard includes: Select a preset optimization algorithm; The sunlight intensity correction standard is optimized based on a preset optimization algorithm, so that vehicles that deviate from the normal state can return to a reasonable response according to the optimized sunlight intensity correction standard.

[0013] As an optional implementation, the vehicle air conditioning comfort control method further includes reading other faults of the vehicle that deviate from a normal state.

[0014] As an optional implementation, the vehicle air conditioning comfort control method further includes collecting vehicle unit data of vehicles that deviate from a normal state within a preset number of days to determine whether the deviation persists; If a deviation occurs in two or more classification domains with similar sunlight intensity correction standards, update the sunlight intensity correction standard.

[0015] A second aspect of the present invention provides a vehicle air conditioning comfort control system, comprising: A first acquisition unit, at least used to acquire a comfort signal of a vehicle of the same type in a usage state; A second acquisition unit is used to at least acquire a sunlight intensity correction standard; A data acquisition unit, at least used to obtain vehicle single body data deviating from a normal state by using a preset reinforcement learning algorithm to obtain the comfort signal of the same type of vehicle under the use state; The optimization execution unit is at least used to optimize the vehicle unit data that deviates from the normal state through a preset optimization algorithm and a sunlight intensity correction standard.

[0016] As an optional implementation, the vehicle air conditioning comfort control system further includes a standard updating unit, the standard updating unit being used at least to collect vehicle unit data of vehicles deviating from a normal state within a preset number of days to determine whether the deviation persists; If a deviation occurs in two or more classification domains with similar sunlight intensity correction standards, update the sunlight intensity correction standard.

[0017] As an optional implementation, the vehicle air conditioning comfort control system further includes a state classification unit, which is at least used for: Obtaining comfort signals under the use status of each vehicle; The vehicle usage status is classified based on preset evaluation principles to obtain comfort signals under the usage status of similar vehicles. The preset evaluation principles at least include geographical location, season, weather conditions, usage time, number of passengers, driving speed and air conditioning usage mode.

[0018] A third aspect of the present invention provides an electronic device, comprising: At least one processor; and at least one memory in communication with the processor, wherein: the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the steps of the method described in the first aspect of the present invention.

[0019] A fourth aspect of the present invention provides a readable storage medium storing a computer program, wherein the computer program is executed by a processor to perform the steps of the method described in the first aspect of the present invention.

[0020] In summary, compared with the prior art, the present invention includes at least one of the following beneficial technical effects: 1. The present invention improves the precise comfort control of air conditioners of different vehicles by classifying the comfort signals of different types of vehicle usage status; 2. The present invention optimizes the vehicle data that deviates from the normal state by means of a preset reinforcement learning algorithm and a preset optimization algorithm. It has high control intelligence and technical stability, and improves the user's comfort experience by specifically correcting the air conditioning comfort problem of a single vehicle or a single batch of vehicles; 3. The present invention can intelligently correct the accuracy of the sunlight sensor online while the customer is using the vehicle, thereby ensuring the accuracy of the thermal load calculation inside the vehicle and providing the customer with a more uniform comfort guarantee experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 It is a flow chart of a vehicle air conditioning comfort control method in a specific embodiment of the present invention.

[0023] Figure 2 It is a schematic diagram of the OTA operation of a vehicle air conditioning comfort control method in a specific embodiment of the present invention.

[0024] Figure 3 It is a flow chart of another vehicle air conditioning comfort control method in a specific embodiment of the present invention.

[0025] Figure 4 It is a flow chart of another vehicle air conditioning comfort control method in a specific embodiment of the present invention.

[0026] Figure 5 It is a flow chart of another vehicle air conditioning comfort control method in a specific embodiment of the present invention.

[0027] Figure 6 It is a block diagram of a vehicle air conditioning comfort control system in a specific embodiment of the present invention.

[0028] Figure 7 FIG. 1 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application. In addition, it should be understood that the specific implementation methods described herein are only used to illustrate and explain the present application, and are not used to limit the present application.

[0030] It should be noted that the description order of the following embodiments is not intended to limit the preferred order of the embodiments of the present application. In addition, in the following embodiments, the description of each embodiment has its own emphasis, and for parts not described in detail in one embodiment, reference can be made to the relevant description of other embodiments.

[0031] like Figure 1 As shown, the first aspect of the present invention provides a vehicle air conditioning comfort control method, comprising the following steps.

[0032] Step S100: Acquire a comfort signal of a similar vehicle under usage status, wherein the comfort signal includes at least one or more of ambient temperature, vehicle interior temperature, sunlight intensity, vehicle geographic coordinates, vehicle air conditioning settings, air conditioning outlet temperature, air conditioning outlet air volume, and air conditioning internal and external circulation status.

[0033] like Figure 2 As shown, the general Over The Air (OTA) delivery procedure includes: the vehicle collects relevant data through the on-board system and uploads the data to the cloud. The cloud diagnoses and intelligently corrects the uploaded data, and sends the optimized data or instructions to the vehicle through OTA, thereby realizing intelligent control of designated vehicle functions.

[0034] For example, the comfort signal can be collected and uploaded to the cloud at a fixed frequency, such as once per second, and participate in the cloud analysis.

[0035] Specifically, the comfort signal includes but is not limited to the contents shown in the present invention, and all relevant parameters, signals, data or information that can be used to characterize comfort can be covered by the comfort signal listed in the present invention.

[0036] Specifically, the interior temperature provides real-time information about the current temperature inside the vehicle, which can be used to adjust the air conditioning system accordingly.

[0037] Specifically, sunlight intensity affects the temperature inside the vehicle and plays a key role in adjusting the vehicle air conditioning system to maintain the optimal cabin temperature.

[0038] Specifically, the vehicle's geographic coordinates affect the environmental conditions to which the vehicle is exposed.

[0039] Specifically, the vehicle air conditioning settings include but are not limited to the temperature, fan speed and operating mode (such as cooling, heating, defrosting) set by the user, and the vehicle air conditioning settings can provide information about the user's comfort preferences.

[0040] Specifically, the air outlet temperature and the air outlet air volume of the air conditioner provide the air conditioning system performance.

[0041] Specifically, the air conditioning internal and external circulation state reflects information about the air circulation mode of the vehicle air conditioning system (for example, whether the system draws in fresh air from the outside or circulates air in the vehicle).

[0042] Comfort signals may be collected and categorized based on preset evaluation criteria, including but not limited to geographic location, season, weather conditions, time of use, number of passengers, driving speed, and air conditioning usage patterns.

[0043] like Figure 3 As shown, in step S100, the step of obtaining the comfort signal of the same type of vehicle in use state includes: Step S110: Acquire the comfort signal of each vehicle under the use status; Step S120: Classify the vehicle usage status based on preset evaluation principles to obtain comfort signals under the usage status of similar vehicles; the preset evaluation principles at least include geographical location, season, weather conditions, usage time, number of passengers, driving speed and air conditioning usage mode.

[0044] Specifically, obtaining the usage status of similar vehicles is conducive to achieving comfort control for vehicles in the same usage status. Generally speaking, the usage status of each vehicle can be evaluated based on the parameters included in the comfort signal, and the usage status of each vehicle can be classified into categories.

[0045] For example, geographic location helps to accurately analyze and optimize the air conditioning comfort control of vehicles in different geographical conditions.

[0046] For example, Season helps to accurately analyze and optimize the vehicle's air conditioning comfort control under different seasonal conditions.

[0047] For example, weather conditions help to accurately analyze and optimize the vehicle's air conditioning comfort control in different weather conditions.

[0048] For example, time of use helps to accurately analyze and optimize the vehicle's air conditioning comfort control at different times of the day.

[0049] For example, the number of passengers helps to accurately analyze and optimize the vehicle's air conditioning comfort control under different passenger load conditions.

[0050] For example, driving speed helps to accurately analyze and optimize the vehicle's air conditioning comfort control at different driving speeds.

[0051] For example, air conditioning usage patterns help to accurately analyze and optimize the vehicle's air conditioning comfort control under different air conditioning usage patterns.

[0052] For example, the geographical location can be obtained based on the administrative region, such as vehicles in Shanghai belong to the same geographical location; the season can be divided according to the solar terms, such as vehicles in autumn belong to the same season; the weather conditions can be divided based on the weather forecast, such as vehicles with cloudy weather belong to the same weather; the use time can be divided based on the use time, such as vehicles with a use time of 8 am belong to the same use time; the number of passengers can be obtained based on the seat sensing signal, such as vehicles with 4 passengers belong to the same number of passengers; the driving speed can be divided based on the vehicle speed, such as vehicles with an average speed of 30-60 km / h within 1 hour belong to the same driving speed; the air conditioning use mode can be obtained based on the air conditioning sensor signal, such as vehicles in cooling mode belong to the same air conditioning use mode. Therefore, one or more vehicles with a geographical location of Shanghai, a season of autumn, cloudy weather, a use time of 8 am, a number of passengers of 4, a driving speed of 30-60 km / h, and an air conditioning use mode of cooling mode are in the same type of vehicle use state.

[0053] Here, in this way, the vehicle air conditioning comfort control method designed by the present invention can be kept in a unified processing category, which is beneficial to ensuring the uniformity of customer comfort.

[0054] Step S200: Obtain a sunlight intensity correction standard; specifically, the sunlight intensity correction standard can be used as a reference for adjusting the vehicle air-conditioning system according to the sunlight intensity. It can be presented in the form of a sunlight intensity correction table, a sunlight intensity calibration (table) or a sunlight intensity correction standard table. The sunlight intensity correction standard can be preset or dynamically adjusted according to real-time data.

[0055] In one application scenario, the sunlight intensity correction standard can be obtained by engineering based on actual engineering tests. The specific content of the sunlight intensity correction standard includes but is not limited to the in-vehicle temperature, the air-conditioning outlet temperature, and the corresponding sunlight intensity correction calibration amounts, etc. Technical personnel in this field can design and process according to the actual sunlight intensity correction standard.

[0056] Step S300: obtaining vehicle unit data that deviates from a normal state through a preset reinforcement learning algorithm using the comfort signal of the same type of vehicle in use.

[0057] Specifically, the vehicle monomer data deviating from the normal state can be determined by setting a threshold value corresponding to the normal vehicle monomer data. When the vehicle monomer data exceeds the threshold value of the normal vehicle monomer data, it indicates that the vehicle monomer data is the vehicle monomer data deviating from the normal state. The vehicle monomer data includes but is not limited to the predicted or controlled vehicle interior temperature, the actual vehicle interior temperature, and the difference between the predicted or controlled vehicle interior temperature and the actual vehicle interior temperature. The vehicle monomer data is used to identify vehicles that significantly deviate from the normal state and may require further analysis and optimization.

[0058] like Figure 4 As shown, specifically, in step S300, the comfort signal of the same type of vehicle in use state is used to obtain the vehicle monomer data deviating from the normal state through a preset reinforcement learning algorithm, including: Step S310: Select a convolutional neural network or a clustering algorithm as a preset reinforcement learning algorithm; Step S320: Using the comfort signal of similar vehicles in use as the input parameter of the preset reinforcement learning algorithm, using the in-vehicle temperature and the air-conditioning outlet temperature as the output parameters of the preset reinforcement learning algorithm, and obtaining the vehicle unit data that deviates from the normal state.

[0059] Specifically, CNN is a deep learning algorithm that is widely used in the fields of image processing and computer vision. In the present invention, CNN can be used to analyze comfort signals and identify vehicles that deviate significantly from normal conditions; clustering algorithms can help us discover vehicle individual data that deviates from normal conditions by discovering the inherent structure and rules of the data.

[0060] Specifically, through a preset reinforcement learning method, individual vehicle data that deviates from the normal state is obtained based on the comfort signal. The reinforcement learning method can use a convolutional neural network (CNN) algorithm to analyze the comfort signal and identify vehicles that significantly deviate from the normal state. The input of this reinforcement learning process includes but is not limited to ambient temperature, sunlight intensity, vehicle geographic coordinates, air conditioning settings, air outlet temperature, air outlet air volume, and internal and external circulation status, and the output includes a prediction or control strategy for the temperature inside the vehicle.

[0061] Exemplarily, the CNN is configured to process the comfort signal in a hierarchical manner, wherein lower layers of the network are responsible for detecting simple features in the comfort signal, while higher layers of the network are responsible for detecting more complex features, thereby obtaining vehicle unit data that deviates from a normal state.

[0062] For example, after learning and analyzing the input and output parameters, the air outlet temperature and the interior temperature under some working conditions can be obtained, such as an ambient temperature of 35°C and 200w sunlight. After learning, most vehicles can reach an interior temperature of 25°C and an air-conditioning outlet temperature of 10°C after being started for 10 minutes under normal circumstances. However, the interior temperature of some vehicles can reach 30°C and the air-conditioning outlet temperature can reach 20°C. Based on this, it is judged that the vehicle is a deviated vehicle.

[0063] Step S400: Optimizing the vehicle unit data that deviates from the normal state through a preset optimization algorithm and a sunlight intensity correction standard.

[0064] like Figure 5 As shown, in step S400, the vehicle monomer data deviating from the normal state is optimized by using a preset optimization algorithm and a sunlight intensity correction standard, including: Step S410: Select a preset optimization algorithm; Step S420: Optimize the sunlight intensity correction standard based on a preset optimization algorithm, so that the vehicle that deviates from the normal state returns to a reasonable response according to the optimized sunlight intensity correction standard.

[0065] For example, the clustering algorithm identifies that under summer conditions, the cooling time for a vehicle set to 25AUTO should be 15 minutes to reach a stable state. The cooling time for a certain vehicle is 30 minutes, which is much longer than normal. Excluding other problems and analyzing phenomena such as the air outlet temperature, it is believed that the sunlight sensor is too small. By using a preset optimization algorithm, the calibration amount of the sunlight correction intensity correction standard is increased so that the sunlight intensity of the vehicle tends to be normal. After correction, the cooling time is optimized to 18 minutes, and it is now considered that the optimized sunlight correction calibration amount is available.

[0066] In an application scenario of the present invention, for the identified deviated vehicle, after excluding other sensor failures and other problems, it can be considered that the cause is the sunlight sensor deviation (that is, the actual sunlight value exceeds 200w). At this time, the preset optimization algorithm is used to optimize the sunlight intensity correction standard, such as correcting the sunlight at this time from 200w to 600w. At this time, the interior temperature and the air outlet temperature of the deviated vehicle under this working condition can be restored to the normal range. For example, the interior temperature can reach 27°C and the air outlet temperature can reach 13°C after 10 minutes of starting. At this time, it can be considered that the special calibration for this vehicle has been completed.

[0067] This method helps to improve the accuracy and consistency of the thermal load calculation in the vehicle, thereby improving the comfort of the vehicle air conditioning.

[0068] In one embodiment of the present invention, the vehicle air conditioning comfort control method further includes reading other faults of the vehicle that deviate from a normal state.

[0069] Specifically, the purpose of reading other faults of the vehicle that deviate from the normal state is to ensure that all related sensors are not faulty, all related signals are valid, there are no thermal management-related after-sales system diagnostic error issues, and performance issues, etc.

[0070] Specifically, this method can be used to determine whether there are other conditions that may cause comfort deviations. For example, the vehicle's mechanical or electrical systems may have faults that affect the performance of the air conditioning system. These faults may include, but are not limited to, air conditioning compressor problems, refrigerant leaks, electrical faults, or sensor faults. By reading these faults, the method may be able to identify and resolve issues that are not directly related to sunlight intensity but may still affect the vehicle's air conditioning comfort.

[0071] In an application scenario of the present invention, a vehicle fault is read by using a diagnostic tool or software, and the diagnostic tool or software may be configured to communicate with an on-board diagnostic system of the vehicle to retrieve a fault code or other diagnostic information.

[0072] In one application scenario of the present invention, by comparing fault data with comfort signals or vehicle individual data that deviates from the normal state, if the comparison result shows that the comfort deviation is caused by these faults, then the vehicle individual data that deviates from the normal state corresponding to these faults are not suitable for the vehicle air conditioning comfort control method provided by the present invention.

[0073] In one embodiment of the present invention, the vehicle air conditioning comfort control method further includes collecting vehicle unit data of vehicles that deviate from a normal state within a preset number of days to determine whether the deviation persists; If a deviation occurs in two or more classification domains with similar sunlight intensity correction criteria, the sunlight intensity correction criteria are updated.

[0074] Specifically, the present invention determines whether the deviation persists by collecting vehicle unit data that deviates from the normal state for a preset number of days, such as 5 days. The new standard can be released through OTA, thereby ensuring that the affected vehicles can quickly match the effective sunlight intensity correction standard, thereby efficiently improving the comfort of the vehicle air conditioning.

[0075] In one application scenario of the present invention, a new sunlight intensity correction standard is issued to a specific customer or customer group.

[0076] For example, new standards may be released to customers who use their vehicles in Shanghai, or to customer groups who use their vehicles in spring and autumn. This targeted release of new standards may allow for more personalized and effective vehicle air conditioning comfort control.

[0077] For example, the invention also involves issuing new standards to customers using vehicles in Shanghai, the vehicle uploads data to the cloud, the cloud performs calculations and finds that there is a deviation in comfort, when the season enters summer, the cloud will continue to find sunlight intensity problems and may find that a consistent correction is needed. The cloud can push new calibrations to customers individually.

[0078] This helps ensure that customers experience a uniform level of comfort, and through personalized standard updates, the performance of the vehicle's air conditioning system can be optimized more effectively, thereby improving the overall user experience.

[0079] like Figure 6 As shown, the second aspect of the present invention provides a vehicle air conditioning comfort control system, comprising: A first acquisition unit 51 is at least used to acquire a comfort signal of a vehicle of the same type in a usage state; A second acquisition unit 52 is used to at least acquire a sunlight intensity correction standard; The data acquisition unit 53 is at least used to obtain the vehicle unit data deviating from the normal state by using the comfort signal of the same type of vehicle in the use state through a preset reinforcement learning algorithm; The optimization execution unit 54 is at least used to optimize the vehicle unit data that deviates from the normal state through a preset optimization algorithm and a sunlight intensity correction standard.

[0080] Please continue reading Figure 6 , In one embodiment of the present invention, the vehicle air conditioning comfort control system further includes a standard updating unit 55, the standard updating unit 55 is at least used to collect vehicle monomer data of vehicles deviating from the normal state within a preset number of days, and determine whether the deviation persists; If a deviation occurs in two or more classification domains with similar sunlight intensity correction standards, update the sunlight intensity correction standard.

[0081] Specifically, if it is determined that there are deviations between two or more classification domains and they have similar sunlight intensity correction standards, then an update of the standards may be made. The update may include revisions to existing standards to reduce or eliminate the deviations, or the introduction of new standards to better suit the specific conditions of these classification domains.

[0082] Please continue reading Figure 6 In one embodiment of the present invention, the vehicle air conditioning comfort control system further includes a state classification unit 56, and the state classification unit 56 is at least used for: Obtaining comfort signals under the use status of each vehicle; The vehicle usage status is classified based on preset evaluation principles to obtain comfort signals under the usage status of similar vehicles. The preset evaluation principles at least include geographical location, season, weather conditions, usage time, number of passengers, driving speed and air conditioning usage mode.

[0083] like Figure 7 As shown, the third aspect of the present invention provides an electronic device, including: At least one processor; and at least one memory in communication with the processor, wherein: the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the steps of the method described in any one of the above embodiments.

[0084] A fourth aspect of the present invention discloses a readable storage medium storing a computer program, wherein the computer program is executed by a processor to perform the steps of the method described in any one of the above embodiments.

[0085] Computer-readable storage media may include: any entity or device capable of carrying a computer program, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), and a software distribution medium, etc. A computer program includes a computer program code. The computer program code may be in source code form, object code form, an executable file, or some intermediate form, etc. A computer-readable storage medium may include: any entity or device capable of carrying a computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), and a software distribution medium, etc.

[0086] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0087] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, apparatus or device (such as a computer-based system, a system including a processing module, or other system that can fetch instructions from an instruction execution system, apparatus or device and execute instructions), or used in combination with these instruction execution systems, apparatuses or devices.

[0088] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A vehicle air conditioning comfort control method, characterized in that: include: Obtain the comfort signal of similar vehicles under usage status; Get the sunlight intensity correction standard; The comfort signals of the same type of vehicles under the use state are used to obtain the vehicle single body data that deviates from the normal state through a preset reinforcement learning algorithm; The vehicle unit data that deviates from the normal state is optimized through a preset optimization algorithm and sunlight intensity correction standard.

2. The vehicle air conditioning comfort control method according to claim 1, characterized in that: The comfort signal includes at least one or more of ambient temperature, vehicle interior temperature, sunlight intensity, vehicle geographic coordinates, vehicle air conditioning settings, air conditioning outlet temperature, air conditioning outlet air volume, and air conditioning internal and external circulation status.

3. The vehicle air conditioning comfort control method according to claim 2, characterized in that: The obtaining of the comfort signal of the same type of vehicle in use state comprises: Obtaining comfort signals under the use status of each vehicle; The vehicle usage status is classified based on preset evaluation principles to obtain comfort signals under the usage status of similar vehicles; the preset evaluation principles at least include geographical location, season, weather conditions, usage time, number of passengers, driving speed and air conditioning usage mode.

4. The vehicle air conditioning comfort control method according to claim 1, characterized in that: The step of obtaining vehicle single body data deviating from a normal state by using a preset reinforcement learning algorithm to obtain the comfort signal of the same type of vehicle in the use state includes: Select Convolutional Neural Network or Clustering Algorithm as the preset reinforcement learning algorithm; The comfort signals of similar vehicles in use are used as input parameters of the preset reinforcement learning algorithm, and the interior temperature and air-conditioning outlet temperature are used as output parameters of the preset reinforcement learning algorithm to obtain vehicle single body data that deviates from the normal state.

5. The vehicle air conditioning comfort control method according to claim 4, characterized in that: The optimization of the vehicle monomer data deviating from the normal state by using a preset optimization algorithm and a sunlight intensity correction standard includes: Select a preset optimization algorithm; The sunlight intensity correction standard is optimized based on a preset optimization algorithm, so that vehicles that deviate from the normal state can return to a reasonable response according to the optimized sunlight intensity correction standard.

6. The vehicle air conditioning comfort control method according to claim 4, characterized in that: Also included is reading of other faults of the vehicle that deviate from the normal state.

7. The vehicle air conditioning comfort control method according to claim 1, characterized in that: It also includes collecting vehicle individual data for a preset number of days for vehicles that deviate from a normal state to determine whether the deviation persists; If a deviation occurs in two or more classification domains with similar sunlight intensity correction standards, update the sunlight intensity correction standard.

8. A vehicle air conditioning comfort control system, characterized in that: include: A first acquisition unit, at least used to acquire a comfort signal of a vehicle of the same type in a usage state; A second acquisition unit is used to at least acquire a sunlight intensity correction standard; A data acquisition unit, at least used to obtain vehicle single body data deviating from a normal state by using a preset reinforcement learning algorithm to obtain the comfort signal of the same type of vehicle under the use state; The optimization execution unit is at least used to optimize the vehicle unit data that deviates from the normal state through a preset optimization algorithm and a sunlight intensity correction standard.

9. The vehicle air conditioning comfort control system according to claim 8, characterized in that: Also included is a standard updating unit, the standard updating unit being used at least to collect vehicle unit data of vehicles deviating from a normal state within a preset number of days to determine whether the deviation persists; If a deviation occurs in two or more classification domains with similar sunlight intensity correction standards, update the sunlight intensity correction standard.

10. The vehicle air conditioning comfort control system according to claim 8, characterized in that: It also includes a state classification unit, the state classification unit is at least used for: Obtaining comfort signals under the use status of each vehicle; The vehicle usage status is classified based on preset evaluation principles to obtain comfort signals under the usage status of similar vehicles. The preset evaluation principles at least include geographical location, season, weather conditions, usage time, number of passengers, driving speed and air conditioning usage mode.

11. An electronic device, characterized in that: include: at least one processor; And at least one memory communicatively connected to the processor, wherein: the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the steps of the vehicle air conditioning comfort control method as described in any one of claims 1-7.

12. A readable storage medium storing a computer program, characterized in that: The computer program is used by a processor to execute the steps of the vehicle air conditioning comfort control method as described in any one of claims 1-7.

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