CN109866733B - Automatic defogging system and method - Google Patents
Automatic defogging system and method Download PDFInfo
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- CN109866733B CN109866733B CN201910242125.8A CN201910242125A CN109866733B CN 109866733 B CN109866733 B CN 109866733B CN 201910242125 A CN201910242125 A CN 201910242125A CN 109866733 B CN109866733 B CN 109866733B
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Abstract
The invention aims to provide an automatic demisting system and a method capable of actively learning user behaviors, wherein the system divides the execution of automatic demisting into four different automatic states, monitors and learns the current actions of user intervention in automatic demisting when entering the automatic state 1, the automatic state 2 and the automatic state 3, records and counts, and automatically sets the default demisting actions in the automatic state 1, the automatic state 2 or the automatic state 3 as the actions which are accustomed to by a user if the user is determined to repeat the same intervention actions for a plurality of times. The invention sets multi-gear automatic fog prevention or defogging and actively learns the user behavior in the automatic defogging process, so that the automatic defogging is more intelligent and can adapt to different users, different vehicles, different regions or different seasons.
Description
Technical Field
The invention belongs to the technical field of automobile air conditioners, and particularly relates to antifogging or defogging of an automobile.
Background
The existing automobile air conditioner demisting technology is mainly divided into two types, wherein one type mainly depends on whether a user observes that fog is generated or not at present, and demisting is manually started; another method detects the relative humidity and temperature of the wet air near the window glass by a sensor, calculates the probability of easy fogging and executes automatic defogging. However, if the existing automatic defogging technology is not well calibrated before the vehicle leaves the factory, the problems of opening in advance or delaying to open and the like exist, and most of the existing automatic defogging technology only sets a threshold value for opening and closing, so sudden opening caused by fluctuation of moisture content of air in the vehicle can bring a sharp feeling to a user, and the technology is not intelligent and humanized enough.
Disclosure of Invention
The invention aims to provide an automatic demisting system and method capable of actively learning user behaviors, wherein the user behaviors are actively learned in the automatic demisting execution process by setting a multi-gear automatic anti-fogging or demisting strategy, so that automatic demisting is more intelligent, and the system and method can be suitable for different users, different vehicles, different regions or different seasons.
The technical scheme of the system and the method is as follows:
the automatic demisting method capable of actively learning user behaviors includes that execution of automatic demisting is divided into four different automatic states, namely an automatic state 1 adopting maximum gear air volume demisting, an automatic state 2 adopting middle gear air volume demisting, an automatic state 3 adopting minimum gear air volume demisting and an automatic state 4 only opening the external circulation of the automobile without blowing air.
When entering the automatic state 1, the automatic state 2 and the automatic state 3, the user will be monitored and learned to intervene the current automatic defogging action, and record and count, if the user is determined to repeat the same intervening action for many times, the default defogging action in the automatic state 1, the automatic state 2 or the automatic state 3 is automatically set as the action the user is accustomed to.
The value of the intermediate gear in the automatic state 2 is variable, a default value of the intermediate gear is given in the initial state, for example, the maximum air volume gear is 8 gears, then the initial intermediate gear can be given as 4 gears, and then the system automatically adapts to the frequently used gear between the maximum gear and the minimum gear according to the habit of the user.
The automatic defogging method comprises the following steps that the automatic defogging state is entered according to a vehicle calibrated fogging threshold and user behavior learning in various automatic states, the front windshield temperature and humidity detection module can detect the surface temperature T of the front windshield and the dew point Td of wet air near the front windshield in real time, the air conditioner control module judges which automatic state the automatic defogging is entered according to the fact that the difference value of the T and the Td is compared with preset thresholds P1, P2, P3 and P4, and the specific method comprises the following steps:
a. and when T-Td is less than or equal to P1, entering an automatic state 1, adjusting an internal and external circulation actuator to an external circulation, adjusting an air blowing mode to full defrosting, turning on a compressor, driving an air blower to perform defogging at the maximum gear air volume, and executing a self-learning process 1, wherein P1 is a fogging starting threshold value calibrated by the vehicle.
b. And when the T-Td is more than P1 and less than or equal to P2, the system enters an automatic state 2, the system adjusts the internal and external circulation actuators to the external circulation, adjusts the blowing mode to the full defrosting mode, turns on the compressor, drives the blower to demist at the default air quantity of the middle gear, and executes a self-learning process 2, wherein P2 is the extremely easy fogging threshold value calibrated by the vehicle.
c. And when the T-Td is more than P2 and less than or equal to P3, the system enters an automatic state 3, the system adjusts the internal and external circulation actuators to the external circulation, adjusts the blowing mode to the full defrosting mode, turns on the compressor, drives the blower to demist at the minimum gear air volume, and executes a self-learning process 3, wherein P3 is a relatively easy fogging threshold value calibrated by the vehicle.
d. When the T-Td is more than P3 and less than or equal to P4, the system enters an automatic state 4, the system only adjusts the internal and external circulation actuators to the external circulation to enter the anti-fog mode, and P4 is the protection threshold value which is calibrated by the vehicle and is easy to fog.
Based on the above, when entering the automatic state 1, the automatic state 2 and the automatic state 3, the user can actively monitor and learn the action of the user intervening the current automatic demisting, record and count the action, and when the condition is met, the original default air volume gear, the action of starting the compressor and the like can be adjusted according to the behavior habituated to the user, and the specific method comprises the following steps:
a, entering an automatic state 1, actively learning whether a user reduces the air volume, and if the number of times that the user reduces the air volume to the X1 th gear is recorded and counted to be greater than a preset number X, setting the originally default maximum gear air volume of the automatic state 1 to be X1; further, actively learning, recording and counting whether the number of times N _ ACoff that the user manually closes the compressor in the state is larger than a preset number of times X, and if so, not forcibly opening the compressor in the automatic state 1.
b, entering an automatic state 2, actively learning whether the user adjusts the maximum air volume, recording the difference between the temperature T of the surface of the front windshield and the dew point Td of the wet air near the front windshield when the user manually adjusts the maximum air volume for the mth time by using a one-dimensional array P1_ update [ M ], namely P1_ update [ M ] is equal to T-Td, if the cumulative recording times are greater than a preset time M, carrying out statistical analysis on P1_ update [ M ], judging whether the standard difference of the data meets an expected set standard difference, and if the cumulative recording times are met, replacing the threshold P1 entering the automatic state 1 by the mean value of P1_ update [ M ]; further, actively learning whether the air volume is increased by the user, but the air volume is not increased to the maximum, if the number of times that the air volume is increased to the X2 th gear by the user is recorded and counted to be greater than the preset number of times X, the system sets the original default middle gear air volume in the automatic state 2 to be the X2 gear; further, actively learning whether the air volume is reduced by the user but not reduced to the minimum, if the number of times that the air volume is reduced to the X3 th gear by the user is recorded and counted to be greater than the preset number of times X, the system sets the original default middle gear air volume in the automatic state 2 to be the X2 gear; further, actively learning whether the user is adjusted to the minimum air volume, recording the difference between the temperature T of the surface of the front windshield and the dew point Td of the humid air near the front windshield when the user manually adjusts the minimum air volume for the ith time by using a one-dimensional array P3_ update [ i ], namely P3_ update [ i ] is equal to T-Td, if the accumulated recording times are greater than the preset times M, carrying out statistical analysis on P3_ update [ M ], judging whether the standard difference of the data of the front windshield meets the expected set standard difference, and if the accumulated recording times are met, replacing the threshold P3 entering the automatic state 3 by the mean value of P3_ update [ M ]; further, actively learning, recording and counting whether the number of times N _ ACoff that the user manually closes the compressor in the state is larger than a preset number of times X, and if so, not forcibly opening the compressor in the automatic state 1.
c, entering an automatic state 3, actively learning whether the air volume is closed by a user, recording the difference between the temperature T of the surface of the front windshield and the dew point Td of the wet air near the front windshield when the air volume is manually adjusted to the maximum air volume for the jth time by the user by using a one-dimensional array P4_ update [ j ], namely P4_ update [ j ] ═ T-Td, if the accumulated recording times are more than a preset time M, carrying out statistical analysis on P4_ update [ M ], judging whether the standard difference of the data of the front windshield meets an expected set standard difference, and if the accumulated recording times are met, replacing the threshold P4 entering the automatic state 4 by using the mean value of P4_ update [ M ]; further, actively learning whether the air volume is increased by the user, but the air volume is not increased to the maximum, if the number of times that the air volume is increased to the X4 th gear by the user is recorded and counted to be greater than the preset number of times X, the system sets the originally default minimum air volume in the automatic state 3 to be X4 gear; further, actively learning, recording and counting whether the number of times N _ ACoff that the user manually closes the compressor in the state is larger than a preset number of times X, and if so, not forcibly opening the compressor in the automatic state 1.
In addition, the user behaviors are periodically learned under various automatic states, and in a learning period, the recorded times do not reach the preset times, the times of the learning content are automatically cleared, and the counting of a new period is entered again.
Meanwhile, the learning behaviors in various automatic states are permanently continuous, the learning contents such as the air quantity gear and the like can be covered, for example, if the original air quantity gear successfully replaces the original default set value, the recorded times are automatically reset, the learning can be continued, and if the conditions are met again, the air quantity gear learned to the habit of the user last time can be replaced by a new round of habit of the user. The design is mainly used for continuously tracking the user behavior by taking the user as a starting point and avoiding the problems of easiness in vehicle dominance or air conditioner air volume attenuation and the like.
The invention provides an automatic demisting system capable of actively learning user behaviors, which mainly comprises: the system comprises a front windshield temperature and humidity detection module, an air conditioner control module, an internal and external circulation actuator, an air blowing mode actuator, a compressor, a blower and the like.
The front windshield temperature and humidity detection module is used for detecting the surface temperature T of the front windshield and the dew point Td of the wet air near the front windshield in real time and transmitting detection signals to the air conditioner control module.
The air conditioner control module is used for comparing the difference value of the T and the Td with preset threshold values P1, P2, P3 and P4 and judging whether the automatic demisting enters the corresponding automatic demisting states 1,2, 3 and 4 or not; when the system enters an automatic state 1, an automatic state 2 and an automatic state 3, monitoring and actively learning the action of user intervention for the current automatic demisting, recording and counting, and if the repeated intervention action of the user is determined to meet the set condition, automatically setting the original default demisting action in the current automatic state as the action which is used by the user; the automatic states 1,2 and 3 are demisting states with different wind ranges, and the automatic state N is an automatic state of opening the circulation outside the vehicle without blowing air; the thresholds P1, P2, P3 and P4 are the fog thresholds of different degrees marked by the vehicle; and the internal and external circulation actuator and the blowing mode actuator are used for executing an automatic state 1, an automatic state 2, an automatic state 3 or an automatic state 4 after receiving a control signal of the air conditioner control module.
By adopting the technical scheme, the automatic defogging method has the multi-gear automatic antifogging or defogging function, and can actively learn the user behavior in the execution of the automatic defogging process, so that the defogging operation habit of the user is automatically used, the automatic defogging is more intelligent and humanized, and the automatic defogging method is suitable for different users, different vehicles, different regions or different seasons, and is an efficient and intelligent automatic defogging method.
Drawings
FIG. 1 is a system architecture diagram of an automatic defogging system;
FIG. 2 is a flowchart illustrating an implementation of an automatic defogging method for actively learning user behavior;
FIG. 3 is a self-learning flow of an automatic defogging method in an automatic state 1 for actively learning user behavior;
FIG. 4 is a self-learning flow of an automatic defogging method in an automatic state 2 for actively learning user behavior;
FIG. 5 is a self-learning flow of the automatic defogging method in the automatic state 3 for actively learning user behavior.
Detailed Description
The invention is further described with reference to the following figures and specific examples.
The architecture of the system according to the present invention is shown in fig. 1, and the method according to the present invention is further explained below with reference to specific embodiments.
As shown in fig. 1, the system mainly includes: the system comprises a front windshield temperature and humidity detection module 1, an air conditioner control module 2, an internal and external circulation actuator 3, an air blowing mode actuator 4, a compressor 5, a blower 6 and the like. The method of the invention divides the execution of automatic demisting into four different automatic states, namely an automatic state 1 adopting maximum gear air volume demisting, an automatic state 2 adopting middle gear air volume demisting, an automatic state 3 adopting minimum gear air volume demisting and an automatic state 4 only opening the circulation outside the vehicle without blowing. The method is implemented as follows:
(1) the front windshield temperature and humidity detection module detects the surface temperature T of the front windshield and the dew point Td of the wet air near the front windshield in real time and transmits detection signals to the air conditioner control module;
(2) the air conditioner control module compares the difference value of the T and the Td with preset threshold values P1, P2, P3 and P4 to judge whether the automatic demisting enters the corresponding automatic demisting states 1,2, 3 and 4; the automatic states 1,2 and 3 are demisting states with different wind ranges, and the automatic state 4 is an automatic state of opening the circulation outside the vehicle without blowing air; the thresholds P1, P2, P3 and P4 are fog thresholds which are calibrated by the vehicle and have different degrees of fog, and the protection threshold which is calibrated by the vehicle and is easy to fog is taken as an initial value;
(3) the internal and external circulation actuator and the blowing mode actuator execute automatic states 1,2, 3 and 4 after receiving a control signal of the air conditioner control module, the air conditioner control module monitors and actively learns the action of user intervention in the current automatic demisting, records and counts, and if the repeated intervention action of the user is determined to meet the set condition, the originally default demisting action in the current automatic state is automatically set as the action which is used by the user.
In the method, when the system enters the automatic state 1, the automatic state 2 and the automatic state 3, the system monitors and learns the current automatic demisting actions interfered by the user, records and counts the actions, and if the user is determined to repeat the same interference actions for many times, the default demisting actions in the automatic state 1, the automatic state 2 or the automatic state 3 are automatically set as the actions used by the user.
In the method, the entering of the automatic defogging state depends on a vehicle calibrated fogging threshold and learning of user behaviors in various automatic states, the front windshield temperature and humidity detection module 1 can detect the temperature T of the surface of a front windshield and the dew point Td of wet air near the front windshield in real time, and the air conditioner control module 2 judges which automatic state the automatic defogging enters according to the fact that the difference value of the T and the Td is compared with preset thresholds P1, P2, P3 and P4.
As shown in fig. 2, for example, the vehicle in this embodiment has been calibrated to have P1 ═ 2.8 ℃, P2 ═ 3.5 ℃, P3 ═ 4.6 ℃, P4 ═ 5.5 ℃, the maximum air volume gear of the vehicle air conditioner is 8, the minimum gear is 1, and the default intermediate gear is 4, and the specific method is as follows:
a. when T-Td is less than or equal to 2.8 ℃, entering an automatic state 1, adjusting an internal and external circulation actuator 3 to an external circulation, adjusting an air blowing mode actuator 4 to a full defrosting state, turning on a compressor 5, driving an air blower 6 to demist with maximum gear air volume, and executing a self-learning process 1 by the system;
b. when T-Td is more than 2.8 and less than or equal to 3.5, the system enters an automatic state 2, the system adjusts an internal and external circulation actuator 3 to an external circulation actuator, adjusts a blowing mode actuator 4 to a full defrosting mode, turns on a compressor 5, drives a blower 6 to demist with the air quantity of a middle gear, and executes a self-learning process 2;
c. when T-Td is more than 3.5 and less than or equal to 4.6, the system enters an automatic state 3, the system adjusts the internal and external circulation actuator 3 to the external circulation, adjusts the blowing mode actuator 4 to the full defrosting, turns on the compressor 5, drives the blower 6 to demist with the minimum gear air volume, and executes a self-learning process 3;
d. when T-Td is more than 4.6 and less than or equal to 5.5, the system enters an automatic state 4, and only adjusts the internal and external circulation actuators 3 to external circulation to enter antifogging preparation;
based on the above, when entering the automatic state 1, the automatic state 2 and the automatic state 3, the user can be actively monitored and learned to intervene the action of the current automatic demisting, and the record and the statistics are carried out, when the conditions are met, the actions of originally defaulted air volume gear, starting the compressor 5 and the like can be adjusted according to the behavior of the habit of the user, and the specific method comprises the following steps:
as shown in fig. 3, entering the automatic state 1, actively learning whether the air volume is reduced by the user, and if it is recorded and counted that the number of times that the air volume is reduced to the X1 th gear by the user is greater than the preset number X, the system will set the originally default maximum gear air volume in the automatic state 1 to be the X1 gear; for example, in one learning period, it is recorded that 50 times of adjustment of the air volume gear to 6 gear in the automatic state 1 by the user is performed, and from 51 st time, the maximum air volume gear in the automatic state 1 is automatically set to 6 gear. Further, actively learning, recording and counting whether the number of times N _ ACoff that the user manually closes the compressor 5 in the state is greater than a preset number of times X, and if so, not forcibly opening the compressor 5 in the automatic state 1; for example, in a learning cycle, the system records that 50 times of actions of manually turning off the compressor are performed by the user in the automatic state 1, and the compressor is not forcibly turned on any more when the system enters the automatic state 1 next time.
As shown in fig. 4, the automatic state 2 is entered, whether the user adjusts the maximum air volume is actively learned, the difference between the temperature T of the front windshield surface and the dew point Td of the humid air near the front windshield when the user manually adjusts the maximum air volume M times is recorded by a one-dimensional array P1_ update [ M ], that is, P1_ update [ M ] is T-Td, if the cumulative recording times is greater than the preset times M, the P1_ update [ M ] is statistically analyzed to determine whether the standard deviation of the present group of data meets the expected set standard deviation, and if so, the threshold P1 entered into the automatic state 1 is replaced by the mean value of P1_ update [ M ].
In the invention, the expected standard deviation is set for ensuring that the data recorded each time is stable and reliable, so that the fluctuation and the variation between the measurements are avoided and eliminated, and the expected standard deviation can be obtained by testing and counting in a vehicle in advance; for example, for 20 tests of the vehicle in the present embodiment, the P1_ test at the time of just fogging is measured as [2.8,3.4,3.2,1.9,2.3,2.4,2.6,2.6,3.1,2.4 ] T-Td]Counting the data to obtain the standard deviation sigmatestIf the standard deviation expected by the vehicle model is 0.5, if the subsequent user uses the system in one learning period, the system records and counts 20 times of maximum gear air volume in the automatic state 2, and the maximum gear air volume corresponds to the group of data P1_ update [20 ]]Standard deviation of (a)update<σtestWhen the data is equal to 0.5, the set of data P1_ update [20 ] is used]Replaces the default value of 2.8 for P1.
Further, in the automatic state 2, whether the air volume is adjusted to be the maximum or not is actively learned, if the number of times that the air volume is adjusted to the X2 th gear is recorded and counted by the user to be larger than the preset number X, the system sets the original default middle gear air volume in the automatic state 2 to be the X2 gear.
Further in the automatic state 2, actively learning whether the air volume is reduced by the user but not reduced to the minimum, if the number of times that the air volume is reduced to the X3 th gear by the user is recorded and counted to be greater than the preset number X, the system sets the original default middle gear air volume in the automatic state 2 to be the X2 gear; in summary, the value of the intermediate gear is variable, a default value of the intermediate gear is given in an initial state, for example, the maximum air flow gear is 8 gears, the initial intermediate gear can be given as 4 gears, and then the system automatically adapts to the frequently used gears between the maximum gear and the minimum gear according to the habit of the user.
Further, in the automatic state 2, whether the user is adjusted to the minimum air volume is actively learned, the difference between the temperature T of the surface of the front windshield and the dew point Td of the wet air near the front windshield when the user is adjusted to the minimum air volume manually for the ith time is recorded by using a one-dimensional array P3_ update [ i ], namely P3_ update [ i ] is equal to T-Td, if the cumulative recording frequency is greater than the preset frequency M, the P3_ update [ M ] is subjected to statistical analysis, whether the standard difference of the data meets the expected set standard difference is judged, and if the data meets the preset frequency M, the threshold P3 entering the automatic state 3 is replaced by the mean value of the P3_ update [ M ].
Further in the automatic state 2, actively learning, recording and counting whether the number of times N _ ACoff that the user manually turns off the compressor 5 in the state is greater than the preset number of times X, and if so, in the automatic state 1, the compressor 5 is not forcibly turned on any more.
As shown in fig. 5, the automatic state 3 is entered, whether the user turns off the air volume is actively learned, a one-dimensional array P4_ update [ j ] is used to record the difference between the temperature T of the front windshield surface and the dew point Td of the humid air near the front windshield when the user manually adjusts the maximum air volume j, that is, P4_ update [ j ] is equal to T-Td, if the cumulative recording number is greater than the preset number M, the P4_ update [ M ] is statistically analyzed to determine whether the standard deviation of the present group of data meets the expected set standard deviation, and if so, the threshold P4 entered into the automatic state 4 is replaced by the mean value of P4_ update [ M ].
Further, in the automatic state 3, whether the air volume is adjusted to be the maximum or not is actively learned, if the number of times that the air volume is adjusted to be the X4 th gear is recorded and counted by the user to be larger than the preset number X, the system sets the originally default minimum air volume in the automatic state 3 to be the X4 gear.
Further in the automatic state 3, actively learning, recording and counting whether the number of times N _ ACoff that the user manually turns off the compressor 5 in the state is greater than the preset number of times X, and if so, in the automatic state 1, the compressor 5 is not forcibly turned on any more.
In addition, the user behaviors are periodically learned under various automatic states, and in a learning period, the recorded times do not reach the preset times, the times of the learning content are automatically cleared, and the counting of a new period is entered again.
Meanwhile, the learning behaviors in various automatic states are permanently continuous, the learning contents such as the air quantity gear and the like can be covered, for example, if the original air quantity gear successfully replaces the original default set value, the recorded times are automatically reset, the learning can be continued, and if the conditions are met again, the air quantity gear learned to the habit of the user last time can be replaced by a new round of habit of the user. The design is mainly used for continuously tracking the user behavior by taking the user as a starting point and avoiding the problems of easiness in vehicle dominance or air conditioner air volume attenuation and the like.
Claims (6)
1. An automatic defogging method is characterized by being applied to an automatic defogging system, wherein the system comprises a front windshield temperature and humidity detection module, an air conditioner control module, an internal and external circulation actuator, a blowing mode actuator, a compressor and a blower; the method comprises the following steps:
(1) the front windshield temperature and humidity detection module detects the surface temperature T of the front windshield and the dew point Td of the wet air near the front windshield in real time and transmits detection signals to the air conditioner control module;
(2) the air conditioner control module compares the difference value of the T and the Td with preset threshold values P1, P2, P3 and P4 to judge whether automatic demisting enters corresponding demisting automatic states 1,2, 3 and 4, wherein the automatic states 1,2 and 3 adopt different air volume demisting states, the automatic state 1 adopts the maximum air volume demisting state, the automatic state 2 adopts the middle gear air volume demisting state, the automatic state 3 adopts the minimum air volume demisting state, and the automatic state 4 is an automatic state which does not blow air and only opens the cycle outside the vehicle; the preset thresholds P1, P2, P3 and P4 are fog thresholds of different degrees marked by the vehicle, and a protection threshold which is marked by the vehicle and is easy to fog is taken as an initial value of the preset thresholds, the preset threshold P1 is a fog starting threshold which is marked by the vehicle, P2 is an extremely easy fog threshold which is marked by the vehicle, and P3 and P4 are relatively easy fog thresholds which are marked by the vehicle, wherein P1 < P2 < P3 < P4;
(3) the internal and external circulation actuator and the blowing mode actuator execute automatic states 1,2, 3 and 4 after receiving a control signal of the air conditioner control module, monitor and actively learn the current automatic demisting action interfered by a user when executing the automatic states 1,2 and 3, record and count the actions, and automatically set the originally default demisting action in the current automatic state as the action habituated to the user if determining that the repeated interference action of the user meets the set condition;
the method for performing active learning after entering the automatic state 2 comprises the following steps: entering an automatic state 2, actively learning whether the user adjusts the maximum air volume, recording the difference between the temperature T of the surface of the front windshield and the dew point Td of the humid air near the front windshield when the user manually adjusts the maximum air volume for the mth time by using a one-dimensional array P1_ update [ M ], namely P1_ update [ M ] = T-Td, if the accumulated recording times are more than a preset time M, carrying out statistical analysis on P1_ update [ M ], judging whether the standard difference of the data meets an expected set standard difference, and if the accumulated recording times are met, replacing the threshold P1 entering the automatic state 1 by the mean value of P1_ update [ M ]; the expected set standard deviation is set for ensuring that the data recorded each time are stable and reliable, so that fluctuation and variation between measurements are avoided and eliminated, and the expected set standard deviation is obtained by testing and counting in a vehicle in advance; further, actively learning whether the air volume is increased by the user, but the air volume is not increased to the maximum, if the number of times that the air volume is increased to the X2 th gear by the user is recorded and counted to be greater than the preset number of times X, the system sets the original default middle gear air volume in the automatic state 2 to be the X2 gear; further, actively learning whether the air volume is reduced by the user but not reduced to the minimum, if the number of times that the air volume is reduced to the X3 th gear by the user is recorded and counted to be greater than the preset number of times X, the system sets the original default middle gear air volume in the automatic state 2 to be the X2 gear; further, actively learning whether the user is adjusted to the minimum air volume, recording the difference between the temperature T of the surface of the front windshield and the dew point Td of the humid air near the front windshield when the user manually adjusts the minimum air volume for the ith time by using a one-dimensional array P3_ update [ i ], namely P3_ update [ i ] = T-Td, if the accumulated recording times are greater than the preset times M, carrying out statistical analysis on P3_ update [ M ], judging whether the standard difference of the data of the front windshield meets the expected set standard difference, and if so, replacing the threshold P3 entering the automatic state 3 by the mean value of P3_ update [ M ]; further, actively learning, recording and counting whether the number of times N _ ACoff that the user manually closes the compressor in the state is larger than a preset number of times X, and if so, in the automatic state 2, the compressor is not forcibly opened any more.
2. The automatic defogging method according to claim 1, wherein the method for the air conditioning control module to determine which automatic state the automatic defogging enters is:
a. when T-Td is less than or equal to P1, entering an automatic state 1, adjusting an internal and external circulation actuator to an external circulation, adjusting a blowing mode to a full defrosting mode, turning on a compressor, driving a blower to demist with the maximum gear air volume, and executing an active learning process;
b. when the T-Td is more than P1 and less than or equal to P2, the automatic state 2 is entered, the internal and external circulation actuators are adjusted to the external circulation, the blowing mode is adjusted to the full defrosting mode, the compressor is started, the blower is driven to demist with the default air quantity of the middle gear, and the active learning process is executed;
c. when T-Td is more than P2 and less than or equal to P3, the automatic state 3 is entered, the internal and external circulation actuators are adjusted to be external circulation, the blowing mode is adjusted to be full defrosting, the compressor is started, the blower is driven to carry out demisting by the minimum gear air volume, and an active learning process is executed;
d. when the T-Td is more than P3 and less than or equal to P4, the automatic state 4 is entered, and only the inner and outer circulation actuators are adjusted to the outer circulation to enter the anti-fog preparation.
3. The automatic defogging method according to claim 1, wherein the active learning after entering the automatic state 1 is performed by:
entering an automatic state 1, actively learning whether the air volume is reduced by a user, and if the number of times that the air volume is reduced to the X1 th gear by the user is recorded and counted to be greater than a preset number of times X, setting the originally default maximum gear air volume of the automatic state 1 to be a X1 gear; further, actively learning, recording and counting whether the number of times N _ ACoff that the user manually closes the compressor in the state is larger than a preset number of times X, and if so, not forcibly opening the compressor in the automatic state 1.
4. The automatic defogging method according to claim 1, wherein the method of performing active learning after entering the automatic state 3 is:
entering an automatic state 3, actively learning whether the air volume is closed by a user, if so, recording the difference between the temperature T of the surface of the front windshield and the dew point Td of the wet air near the front windshield when the air volume is manually closed by the user for the jth time by using a one-dimensional array P4_ update [ j ], namely P4_ update [ j ] = T-Td, if the accumulated recording time is more than a preset time M, carrying out statistical analysis on P4_ update [ M ], judging whether the standard difference of the data of the front windshield meets an expected set standard difference, and if so, replacing the threshold P4 entering the automatic state 4 by using the mean value of P4_ update [ M ]; if not, actively learning whether the air volume is increased by the user, but is not increased to the maximum, if the number of times that the air volume is increased to the X4 th gear by the user is recorded and counted to be greater than the preset number X, the system sets the originally default minimum air volume in the automatic state 3 to be X4 gear; further, actively learning, recording and counting whether the number of times N _ ACoff that the user manually closes the compressor in the state is larger than a preset number of times X, and if so, not forcibly opening the compressor in the automatic state 3.
5. The method according to any one of claims 1-4, wherein: aiming at that the active learning user behaviors under various automatic states are periodic, in a learning period, if the recorded times do not reach the preset times, the times of the learning content are automatically reset, and the counting of a new period is entered again;
further, in the active learning process under various automatic states, when a certain item of learning content under a certain automatic state is successfully replaced, the recording times are automatically reset, the learning is continued, and if the conditions are met again, the replacement is performed again.
6. A system for implementing the automatic defogging method as recited in any one of claims 1 to 5, wherein said system comprises: the system comprises a front windshield temperature and humidity detection module, an air conditioner control module, an internal and external circulation actuator, a blowing mode actuator, a compressor and a blower;
the front windshield temperature and humidity detection module is used for detecting the surface temperature T of the front windshield and the dew point Td of the wet air near the front windshield in real time and transmitting detection signals to the air conditioner control module; the air conditioner control module is used for comparing the difference value of the T and the Td with preset threshold values P1, P2, P3 and P4 and judging whether the automatic demisting enters the corresponding demisting automatic states 1,2, 3 and 4 or not; when the system enters an automatic state 1, an automatic state 2 and an automatic state 3, monitoring and actively learning the action of user intervention for the current automatic demisting, recording and counting, and if the repeated intervention action of the user is determined to meet the set condition, automatically setting the original default demisting action in the current automatic state as the action which is used by the user; the automatic states 1,2 and 3 are demisting states with different wind ranges, and the automatic state 4 is an automatic state of opening the circulation outside the vehicle without blowing air; the preset thresholds P1, P2, P3 and P4 are the fog thresholds of different degrees marked by the vehicle; and the internal and external circulation actuator and the blowing mode actuator are used for executing an automatic state 1, an automatic state 2, an automatic state 3 or an automatic state 4 after receiving a control signal of the air conditioner control module.
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| CN110978951B (en) * | 2019-12-17 | 2021-06-11 | 重庆超力电器有限责任公司 | Demisting control method and device and automobile |
| CN111497555B (en) * | 2020-04-24 | 2022-05-17 | 重庆长安汽车股份有限公司 | Heating method for automobile air conditioner |
| CN112158166B (en) * | 2020-09-30 | 2023-03-28 | 重庆长安汽车股份有限公司 | Control method for automatic demisting of automobile and automobile |
| CN113370746B (en) * | 2021-06-30 | 2022-05-27 | 一汽奔腾轿车有限公司 | Demisting closed-loop control system of pure electric vehicle heat pump system and control method thereof |
| CN114290873B (en) * | 2021-12-27 | 2024-01-12 | 重庆长安汽车股份有限公司 | Automobile air conditioner control method and system capable of automatically adapting to user habit and automobile |
| CN114475523A (en) * | 2022-02-24 | 2022-05-13 | 重庆长安新能源汽车科技有限公司 | Automatic defogging control method and system, vehicle and storage medium |
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