CN117002221B - Intelligent control method and system for automobile air conditioner capable of achieving information intercommunication - Google Patents
Intelligent control method and system for automobile air conditioner capable of achieving information intercommunication Download PDFInfo
- Publication number
- CN117002221B CN117002221B CN202311287224.0A CN202311287224A CN117002221B CN 117002221 B CN117002221 B CN 117002221B CN 202311287224 A CN202311287224 A CN 202311287224A CN 117002221 B CN117002221 B CN 117002221B
- Authority
- CN
- China
- Prior art keywords
- automobile
- vehicle
- air
- air quality
- sensor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000005286 illumination Methods 0.000 claims abstract description 42
- 238000004378 air conditioning Methods 0.000 claims abstract description 40
- 230000005855 radiation Effects 0.000 claims abstract description 34
- 230000004927 fusion Effects 0.000 claims abstract description 33
- 230000008859 change Effects 0.000 claims abstract description 25
- 238000012544 monitoring process Methods 0.000 claims abstract description 21
- 238000011156 evaluation Methods 0.000 claims abstract description 20
- 230000007613 environmental effect Effects 0.000 claims abstract description 19
- 230000033228 biological regulation Effects 0.000 claims abstract description 18
- 238000003908 quality control method Methods 0.000 claims abstract description 15
- 230000001105 regulatory effect Effects 0.000 claims abstract description 9
- 238000005057 refrigeration Methods 0.000 claims abstract description 8
- 238000001303 quality assessment method Methods 0.000 claims abstract description 5
- WSFSSNUMVMOOMR-UHFFFAOYSA-N Formaldehyde Chemical compound O=C WSFSSNUMVMOOMR-UHFFFAOYSA-N 0.000 claims description 57
- 239000011159 matrix material Substances 0.000 claims description 30
- 238000004891 communication Methods 0.000 claims description 22
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 claims description 20
- 238000001816 cooling Methods 0.000 claims description 13
- 230000003993 interaction Effects 0.000 claims description 13
- 230000036760 body temperature Effects 0.000 claims description 10
- 229910002092 carbon dioxide Inorganic materials 0.000 claims description 10
- 239000001569 carbon dioxide Substances 0.000 claims description 10
- 230000006870 function Effects 0.000 claims description 10
- 238000009423 ventilation Methods 0.000 claims description 9
- 230000001877 deodorizing effect Effects 0.000 claims description 7
- 238000004887 air purification Methods 0.000 claims description 6
- 238000005259 measurement Methods 0.000 claims description 6
- 230000001276 controlling effect Effects 0.000 claims description 5
- 230000008569 process Effects 0.000 claims description 5
- 238000000605 extraction Methods 0.000 claims description 4
- 238000000354 decomposition reaction Methods 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 claims description 3
- 239000003344 environmental pollutant Substances 0.000 claims description 3
- 238000011049 filling Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 238000010606 normalization Methods 0.000 claims description 3
- 231100000719 pollutant Toxicity 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 238000001179 sorption measurement Methods 0.000 claims description 3
- 230000001954 sterilising effect Effects 0.000 claims description 3
- 238000004659 sterilization and disinfection Methods 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 230000008447 perception Effects 0.000 claims description 2
- 238000005457 optimization Methods 0.000 claims 1
- 238000005265 energy consumption Methods 0.000 abstract description 4
- 238000013461 design Methods 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 3
- 238000010438 heat treatment Methods 0.000 description 3
- 239000013618 particulate matter Substances 0.000 description 3
- 206010021143 Hypoxia Diseases 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000004332 deodorization Methods 0.000 description 2
- 238000004134 energy conservation Methods 0.000 description 2
- 239000007789 gas Substances 0.000 description 2
- 230000002452 interceptive effect Effects 0.000 description 2
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 description 1
- 206010039203 Road traffic accident Diseases 0.000 description 1
- 230000004913 activation Effects 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 229910002091 carbon monoxide Inorganic materials 0.000 description 1
- 239000012141 concentrate Substances 0.000 description 1
- 239000000110 cooling liquid Substances 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 238000007499 fusion processing Methods 0.000 description 1
- 230000017525 heat dissipation Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000013441 quality evaluation Methods 0.000 description 1
- 230000000306 recurrent effect Effects 0.000 description 1
- 239000003507 refrigerant Substances 0.000 description 1
- 239000002918 waste heat Substances 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60H—ARRANGEMENTS OF HEATING, COOLING, VENTILATING OR OTHER AIR-TREATING DEVICES SPECIALLY ADAPTED FOR PASSENGER OR GOODS SPACES OF VEHICLES
- B60H1/00—Heating, cooling or ventilating [HVAC] devices
- B60H1/00642—Control systems or circuits; Control members or indication devices for heating, cooling or ventilating devices
- B60H1/00735—Control systems or circuits characterised by their input, i.e. by the detection, measurement or calculation of particular conditions, e.g. signal treatment, dynamic models
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60H—ARRANGEMENTS OF HEATING, COOLING, VENTILATING OR OTHER AIR-TREATING DEVICES SPECIALLY ADAPTED FOR PASSENGER OR GOODS SPACES OF VEHICLES
- B60H1/00—Heating, cooling or ventilating [HVAC] devices
- B60H1/00642—Control systems or circuits; Control members or indication devices for heating, cooling or ventilating devices
- B60H1/00735—Control systems or circuits characterised by their input, i.e. by the detection, measurement or calculation of particular conditions, e.g. signal treatment, dynamic models
- B60H1/00764—Control systems or circuits characterised by their input, i.e. by the detection, measurement or calculation of particular conditions, e.g. signal treatment, dynamic models the input being a vehicle driving condition, e.g. speed
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60H—ARRANGEMENTS OF HEATING, COOLING, VENTILATING OR OTHER AIR-TREATING DEVICES SPECIALLY ADAPTED FOR PASSENGER OR GOODS SPACES OF VEHICLES
- B60H1/00—Heating, cooling or ventilating [HVAC] devices
- B60H1/00642—Control systems or circuits; Control members or indication devices for heating, cooling or ventilating devices
- B60H1/00735—Control systems or circuits characterised by their input, i.e. by the detection, measurement or calculation of particular conditions, e.g. signal treatment, dynamic models
- B60H1/008—Control systems or circuits characterised by their input, i.e. by the detection, measurement or calculation of particular conditions, e.g. signal treatment, dynamic models the input being air quality
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60H—ARRANGEMENTS OF HEATING, COOLING, VENTILATING OR OTHER AIR-TREATING DEVICES SPECIALLY ADAPTED FOR PASSENGER OR GOODS SPACES OF VEHICLES
- B60H1/00—Heating, cooling or ventilating [HVAC] devices
- B60H1/00642—Control systems or circuits; Control members or indication devices for heating, cooling or ventilating devices
- B60H1/00814—Control systems or circuits characterised by their output, for controlling particular components of the heating, cooling or ventilating installation
- B60H1/00821—Control systems or circuits characterised by their output, for controlling particular components of the heating, cooling or ventilating installation the components being ventilating, air admitting or air distributing devices
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60H—ARRANGEMENTS OF HEATING, COOLING, VENTILATING OR OTHER AIR-TREATING DEVICES SPECIALLY ADAPTED FOR PASSENGER OR GOODS SPACES OF VEHICLES
- B60H1/00—Heating, cooling or ventilating [HVAC] devices
- B60H1/00642—Control systems or circuits; Control members or indication devices for heating, cooling or ventilating devices
- B60H1/00814—Control systems or circuits characterised by their output, for controlling particular components of the heating, cooling or ventilating installation
- B60H1/00878—Control systems or circuits characterised by their output, for controlling particular components of the heating, cooling or ventilating installation the components being temperature regulating devices
Landscapes
- Physics & Mathematics (AREA)
- Thermal Sciences (AREA)
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Air-Conditioning For Vehicles (AREA)
- Air Conditioning Control Device (AREA)
Abstract
The invention discloses an intelligent control method and system of an automobile air conditioner capable of communicating information, and relates to the technical field of air conditioner regulation and control, wherein the control method comprises the following steps: a plurality of sensors are distributed in the automobile to sense the environmental parameters in the automobile in real time; monitoring an air quality index in the vehicle in real time, carrying out quality assessment on the air quality index, and formulating an air quality control measure in the vehicle based on an assessment result; predicting the running speed change of the automobile in the future time by utilizing a speed prediction model, and predicting the refrigerating capacity requirement of the engine based on the running speed change; sensing the illumination radiation intensity outside the automobile in real time; fusing the data acquired by the sensors; and the frequency of the frequency converter is regulated through PID based on the fusion result so as to control the air flow and the refrigeration efficiency of the air conditioning system and realize the self-adaptive regulation and control of the environmental parameters in the vehicle. According to the invention, the air quality index in the vehicle is monitored in real time, and the working mode of the air conditioning system is adjusted in a targeted manner according to the evaluation result, so that the energy consumption is reduced.
Description
Technical Field
The invention relates to the technical field of air conditioner regulation and control, in particular to an intelligent control method and system of an automobile air conditioner capable of achieving information intercommunication.
Background
An automotive air conditioner is a system for adjusting the temperature and humidity in a vehicle equipped on the vehicle, which provides a comfortable driving environment by refrigerating or heating air and controlling the flow direction and speed of air, and adjusts the temperature in the vehicle by refrigerating with a compressor and heating with a heat exchanger, and when refrigerating, the compressor compresses and condenses the refrigerant into liquid, and then releases heat through an evaporator, cooling the air in the vehicle, and when heating, the heat exchanger heats the cooling liquid by using the waste heat of an engine and blows the hot air into the vehicle by a fan.
The intelligent control of vehicle air conditioner can provide more comfortable driving experience according to driver and passenger's demand automatically regulated temperature, humidity and air flow direction, need not manual adjustment, and the driver can concentrate on driving more, and the passenger also can enjoy more comfortable riding environment, helps reducing the fuel consumption of vehicle simultaneously to produce less influence to the environment. Due to the special working environment of automobiles, the control of automobile air conditioners is mainly represented by the following aspects:
(1) The automobile has the advantages that the volume of the automobile carriage is small, the proportion of the occupied area of the automobile window is relatively large, and the automobile window is easily subjected to direct sunlight, so that the temperature in the carriage is high, and in addition, the temperature in the carriage is also influenced by human body heat dissipation and the radiant heat of an engine, so that the heat load of an automobile air conditioner is large;
(2) When the engine is driven, the refrigerating performance of the automobile air conditioner is related to the running speed of the automobile, the cooling capacity of the automobile is large at high speed, and the cooling capacity of the automobile is small at low speed;
(3) Because the space in the automobile is small, oxygen deficiency and high carbon dioxide concentration are extremely easy to cause in the closed space, carbon monoxide in automobile engine exhaust gas and dust on a road easily enter the carriage, and air turbidity in the automobile is caused.
For the problems in the related art, no effective solution has been proposed at present.
Disclosure of Invention
The invention mainly aims to provide an intelligent control method and system for an automobile air conditioner capable of communicating information, so as to overcome the technical problems existing in the prior art.
For this purpose, the invention adopts the following specific technical scheme:
according to one aspect of the invention, there is provided an intelligent control method of an air conditioner for a vehicle capable of communicating information, the control method comprising the steps of:
s1, distributing a plurality of sensors in an automobile, sensing environment parameters in the automobile in real time, and uploading the environment parameters in the automobile to a central control unit;
s2, monitoring the air quality index in the vehicle in real time, carrying out quality assessment on the air quality index, and formulating air quality control measures in the vehicle based on an assessment result;
s3, predicting the running speed change of the automobile in the future time by using a speed prediction model, and predicting the refrigerating capacity requirement of the engine based on the running speed change;
s4, sensing the illumination radiation intensity outside the automobile in real time, and judging whether the working mode of the air conditioning system needs to be adjusted or not according to the illumination radiation intensity;
s5, carrying out data interaction and collaborative management on each sensor and a central control unit through a communication interface, and fusing data acquired by each sensor;
s6, adjusting the frequency of the frequency converter through PID based on the fusion result to control the air flow and the refrigeration efficiency of the air conditioning system, and realizing the self-adaptive regulation and control of the environmental parameters in the vehicle.
Optionally, the distributing a plurality of sensors inside the automobile, sensing the environmental parameters inside the automobile in real time, and uploading the environmental parameters inside the automobile to the central control unit comprises the following steps:
s11, disposing an infrared sensor in a seat area in the automobile, wherein the infrared sensor is used for sensing the body temperature of a passenger;
s12, deploying an air quality sensor in the automobile, wherein the air quality sensor is used for monitoring an air quality index in the automobile;
s13, deploying an illumination sensor at the vehicle-mounted terminal, wherein the illumination sensor is used for sensing illumination radiation intensity;
s14, uploading the passenger body temperature, the air quality index and the illumination radiation intensity to the central control unit respectively.
Optionally, the real-time monitoring of the air quality index in the vehicle and the quality evaluation thereof, and the making of the air quality control measure in the vehicle based on the evaluation result comprise the following steps:
s21, monitoring an air quality index in the vehicle in real time by using an air quality sensor, and constructing a topological structure based on the air quality index;
the air quality index is hour granularity information, and at least comprises carbon dioxide concentration, formaldehyde concentration and PM2.5 concentration;
s22, calculating and generating a corresponding adjacency matrix, a degree matrix and a Laplace matrix according to the topological structure, and normalizing the air quality index by utilizing a MIN-MAX algorithm;
s23, constructing an air quality prediction model based on the air quality index after normalization processing;
s24, respectively building a global assembly and a local assembly by utilizing an air quality prediction model, and fusing the outputs of the global assembly and the local assembly;
s25, defining a loss function and a root mean square error, taking the input of the local assembly and the global assembly as filling data, and respectively calculating index prediction values of air quality indexes;
s26, comparing the index predicted value with an air quality standard limit value, and carrying out grade evaluation on the air quality index based on a comparison result;
and S27, formulating an in-vehicle air quality control measure based on the grade evaluation result.
Optionally, the building of the global assembly comprises the steps of:
performing Laplace transformation based on the adjacent matrix to generate a feature matrix, and extracting spatial features in the feature matrix;
the time sequence after the space feature extraction is used as the input of the GRU to acquire the time feature, and the output of the global component is calculated;
and calling the custom GG cell class, and converting the cell state output value into GRU output dimension which is the same as the label vector through the full connection layer.
Optionally, the in-vehicle quality control measures comprise ventilation, air purification, deodorization, formaldehyde removal and optimized air supply;
the ventilation is used for accelerating the ventilation of dirty air;
the air purification is used for purifying the air in the vehicle by utilizing a filtering sterilization technology;
the deodorizing and formaldehyde removing device is used for reducing the concentration of formaldehyde and peculiar smell substances by utilizing a vehicle-mounted deodorizing and formaldehyde removing device and an adsorption and decomposition principle;
the optimized air supply is used for preferentially adjusting the air inlet mode of the air conditioning system so as to reduce the input of external pollutants into the vehicle.
Optionally, the expression of the feature matrix is:
in the method, in the process of the invention,representing a feature matrix;
a representation matrix;
representing the self-connecting adjacency matrix.
Optionally, the method for predicting the running speed change in the future time of the automobile by using the speed prediction model and predicting the engine refrigerating capacity requirement based on the running speed change comprises the following steps:
s31, dividing the driving road sections according to the curve radius and the longitudinal slope gradient in the driving road sections of the automobile, and taking the starting point and the ending point of each road section as linear characteristic points for predicting the driving speed of the automobile;
the division of the driving road section comprises dividing the driving road section of the automobile into a straight line section, a longitudinal slope section, a flat curve section and a curved slope combined section;
s32, acquiring the speed of an adjacent road section joined by the current road section, taking the speed as the initial running speed of the adjacent road section, and respectively measuring and calculating the running speed of the automobile according to the type of each road section;
s33, respectively integrating the automobile running speeds of all road sections, and predicting the automobile running speed in a future time period by utilizing an IHSDM model;
s34, judging the refrigerating capacity requirement of the engine based on a prediction result of the running speed of the automobile;
s35, if the running speed of the automobile is high, the air conditioner refrigerating capacity is high; if the vehicle is traveling at a low speed, the air conditioning cooling capacity is low.
Optionally, the data interaction and collaborative management of each sensor and the central control unit through the communication interface, and the fusion of the data collected by each sensor includes the following steps:
s51, designing a communication interface matched with each sensor, wherein the communication interface comprises a serial port, an SPI and an I2C, and ensuring that each sensor is in data intercommunication with a central control unit through the communication interface;
s52, uploading the data acquired by each sensor to a central control unit according to the requirements of each sensor and a communication protocol; the data collected by each sensor comprises the passenger body temperature, the air quality index and the illumination radiation intensity;
s53, carrying out interaction and collaborative management on data acquired by each sensor by utilizing a central control unit;
s54, fusing the data acquired by each sensor by using a data fusion algorithm.
Optionally, the fusing the data collected by each sensor by using the data fusion algorithm includes the following steps:
s541, modeling data acquired by each sensor by using a BPA function in a D-S evidence theory;
s542, calculating a weighted Deng entropy based on the weighted credibility entropy, and performing non-deterministic measurement on each group of BPA functions;
s543, calculating the weight of each sensor data source according to the non-deterministic measurement result;
s544, performing data fusion by using a Dempster evidence combination rule, and regulating and controlling the air conditioning system based on a data fusion result.
According to another aspect of the invention, an intelligent control system of the automobile air conditioner capable of communicating information is provided, and the system comprises an environment parameter acquisition module, an air index evaluation module, a driving speed prediction module, an illumination radiation sensing module, a data fusion module and an intelligent regulation and control module;
the environment parameter acquisition module is used for distributing a plurality of sensors in the automobile, sensing the environment parameters in the automobile in real time and uploading the environment parameters in the automobile to the central control unit;
the air index evaluation module is used for monitoring the air quality index in the vehicle in real time, evaluating the quality of the air quality index, and formulating air quality control measures in the vehicle based on the evaluation result;
the running speed prediction module is used for predicting running speed change in the future time of the automobile by using a speed prediction model and predicting the cooling capacity requirement of the engine in the automobile based on the running speed change;
the illumination radiation sensing module is used for sensing the illumination radiation intensity outside the automobile in real time and judging whether the working mode of the air conditioning system needs to be adjusted according to the illumination radiation intensity;
the data fusion module is used for carrying out data interaction and collaborative management on each sensor and the central control unit through the communication interface, and fusing the data acquired by each sensor;
the intelligent regulation and control module is used for regulating the frequency of the frequency converter through PID based on the fusion result so as to control the air flow and the refrigeration efficiency of the air conditioning system and realize the self-adaptive regulation and control of the environmental parameters in the vehicle.
The beneficial effects of the invention are as follows:
1. according to the invention, through monitoring the air quality index in the vehicle in real time, problems are found in time, the air quality is improved, the riding comfort is improved, meanwhile, the air conditioning system is adjusted according to the evaluation result, the energy consumption waste is avoided, the energy conservation and the environmental protection are realized, the good air quality in the vehicle is beneficial to improving the driving safety and the attention, the fatigue degree is reduced, the refrigerating capacity is adjusted by predicting the change of the vehicle speed, the comfortable driving environment is provided, and the energy utilization efficiency is improved.
2. According to the invention, the air quality index in the vehicle is monitored in real time, and the air quality problem such as too high carbon dioxide concentration, excessive standard formaldehyde and other harmful gases can be found in time, so that measures are taken in time to improve the air quality, the riding comfort is improved, meanwhile, the working mode of an air conditioning system is pertinently adjusted according to the evaluation result by monitoring the air quality index in the vehicle in real time, the energy consumption is reduced, the energy conservation and environmental protection are realized, the good air quality in the vehicle is beneficial to improving the concentration and the reaction capability of a driver, the driving fatigue degree is reduced, and the driving safety is further improved.
3. According to the invention, the refrigerating capacity of the engine can be adjusted in advance by the air conditioning system through predicting the running speed change of the automobile, and the air conditioning system can be dynamically adjusted according to the running speed change, so that the air conditioning system is suitable for the refrigerating requirements under different running speeds, a more comfortable driving environment is provided, the occurrence of the situation of over-refrigerating or under-refrigerating is avoided, the energy utilization efficiency is improved, the proper temperature in the automobile is ensured, and the comfort and the attention of a driver are further improved.
4. According to the invention, the communication interface is arranged, so that the information intercommunication between the central control unit and each sensor can be realized, and the data such as the passenger body temperature, the air quality index, the illumination radiation intensity and the like can be fused and managed, so that the air conditioning system can intelligently adjust according to the requirements and the environment changes of passengers, more comfortable riding experience is provided, the data acquired by each sensor is fused and analyzed through the central control unit, the environment condition in the vehicle can be known more accurately, the working mode of the air conditioning system can be regulated more accurately, and the efficient utilization of energy is realized.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of an intelligent control method of an automotive air conditioner capable of communicating information according to an embodiment of the invention;
fig. 2 is a schematic block diagram of an intelligent control system for an air conditioner of a vehicle capable of communicating information according to an embodiment of the present invention.
In the figure:
1. an environmental parameter acquisition module; 2. an air index evaluation module; 3. a running speed prediction module; 4. an illumination radiation sensing module; 5. a data fusion module; 6. and an intelligent regulation module.
Detailed Description
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein.
As described in the background art, oxygen deficiency and too high carbon dioxide concentration are easily caused in a closed space, and the air quality in the vehicle cannot be evaluated in the prior art.
The invention is further described with reference to the accompanying drawings and the specific embodiments, as shown in fig. 1, the intelligent control method for the vehicle air conditioner capable of communicating information according to the embodiment of the invention comprises the following steps:
s1, distributing a plurality of sensors in an automobile, sensing environment parameters in the automobile in real time, and uploading the environment parameters in the automobile to a central control unit.
The method for monitoring the environment of the automobile comprises the following steps of:
s11, disposing an infrared sensor in a seat area in the automobile, wherein the infrared sensor is used for sensing the body temperature of a passenger;
and S12, deploying an air quality sensor in the automobile, wherein the air quality sensor is used for monitoring an air quality index in the automobile.
The air quality sensor includes a particulate matter sensor, a formaldehyde sensor and CO 2 A sensor, etc.
Particulate matter sensors are used to detect and measure particulate matter concentrations, such as PM2.5 and PM10, in the air in a vehicle.
The formaldehyde sensor is used for monitoring and measuring the formaldehyde content in the air in the vehicle.
CO 2 The sensor is used for monitoring and measuring carbon dioxide (CO) in the air in the vehicle 2 ) Concentration.
S13, deploying an illumination sensor at the vehicle-mounted terminal, wherein the illumination sensor is used for sensing illumination radiation intensity;
s14, uploading the passenger body temperature, the air quality index and the illumination radiation intensity to the central control unit respectively.
S2, monitoring the air quality index in the vehicle in real time, carrying out quality assessment on the air quality index, and formulating air quality control measures in the vehicle based on the assessment result.
The method comprises the following steps of monitoring the air quality index in the vehicle in real time, evaluating the air quality index in the vehicle, and formulating an air quality control measure in the vehicle based on an evaluation result:
s21, monitoring an air quality index in the vehicle in real time by using an air quality sensor, and constructing a topological structure based on the air quality index.
The air quality index is hour granularity information, and at least comprises carbon dioxide concentration, formaldehyde concentration and PM2.5 concentration.
S22, calculating and generating a corresponding adjacency matrix, a degree matrix and a Laplace matrix according to the topological structure, and normalizing the air quality index by utilizing a MIN-MAX algorithm;
s23, constructing an air quality prediction model based on the air quality index after normalization processing;
s24, building a global assembly and a local assembly respectively by using an air quality prediction model, and fusing the outputs of the global assembly and the local assembly.
Wherein the building of the global assembly comprises the following steps:
and carrying out Laplace transformation based on the adjacent matrix to generate a feature matrix, and extracting spatial features in the feature matrix.
The expression of the feature matrix is as follows:
in the method, in the process of the invention,representing a feature matrix;
a representation matrix;
representing the self-connecting adjacency matrix.
And taking the time sequence after the spatial feature extraction as the input of the GRU to acquire the time feature, and calculating the output of the global component.
It should be noted that, a GRU model (variant of the recurrent neural network RNN) is created by using TensorFlow, pyTorch or other deep learning framework, and the time sequence after the spatial feature extraction is used as the input of the GRU, where the input of the GRU is a feature vector of a time step sequence, and the feature vector of each time step is used as the input of the GRU and is transferred to the next time step in each time step iteration.
And calling the custom GG cell class, and converting the cell state output value into GRU output dimension which is the same as the label vector through the full connection layer.
In the GRU model, GG cells (variants of GRU) are used as the cell types of GRU, a full-connection layer is added after the GRU model is output, the output value of the unit state is converted into the same dimension as the label vector, and an activation function and parameter setting are selected for conversion operation.
S25, defining a loss function and a root mean square error, taking the input of the local assembly and the global assembly as filling data, and respectively calculating index prediction values of air quality indexes;
s26, comparing the index predicted value with the air quality standard limit value, and carrying out grade assessment on the air quality index based on the comparison result.
It should be noted that this step mainly includes the following aspects: standard limits for different air quality classes (the index range for each class is determined based on actual conditions and air quality related criteria) are defined, for example, air quality is classified into excellent, good, light, medium, heavy and heavy pollution classes.
Comparing the predicted value with the standard limit value of each air quality level, if the predicted value is less than or equal to the standard limit value of the priority level, then the predicted value is evaluated as the priority level, and so on.
The air quality index is rated according to the rating of the predicted value, and the rating can be represented by numbers (such as 1 for excellent, 2 for good, 3 for light pollution, etc.).
And S27, formulating an in-vehicle air quality control measure based on the grade evaluation result.
Wherein, the quality control measures in the vehicle comprise ventilation, air purification, deodorization, formaldehyde removal and optimized air supply;
the ventilation is used for accelerating the ventilation of dirty air;
the air purification is used for purifying the air in the vehicle by utilizing a filtering sterilization technology;
the deodorizing and formaldehyde removing device is used for reducing the concentration of formaldehyde and peculiar smell substances by utilizing a vehicle-mounted deodorizing and formaldehyde removing device and an adsorption and decomposition principle;
the optimized air supply is used for preferentially adjusting the air inlet mode of the air conditioning system so as to reduce the input of external pollutants into the vehicle.
S3, predicting the running speed change of the automobile in the future time by using a speed prediction model, and predicting the refrigerating capacity requirement of the engine based on the running speed change.
The method for predicting the running speed change of the automobile in the future time by utilizing the speed prediction model and predicting the refrigerating capacity requirement of the engine based on the running speed change comprises the following steps of:
s31, dividing the driving road sections according to the curve radius and the longitudinal slope gradient in the driving road sections of the automobile, and taking the starting point and the ending point of each road section as linear characteristic points for predicting the driving speed of the automobile.
The division of the driving road section comprises dividing the driving road section of the automobile into a straight line section, a longitudinal slope section, a flat curve section and a curved slope combined section.
S32, acquiring the speed of an adjacent road section joined by the current road section, taking the speed as the initial running speed of the adjacent road section, and respectively measuring and calculating the running speed of the automobile according to the type of each road section;
s33, respectively integrating the automobile running speeds of all the road sections, and predicting the automobile running speed in a future time period by using the IHSDM model.
It should be noted that IHSDM (Interactive Highway Safety Design Model) is an interactive highway safety design model for evaluating and predicting the influence of highway design on traffic safety, and the IHSDM model evaluates the influence of different designs on traffic safety by estimating probability and severity of occurrence of traffic accidents based on data of geometric design of highway, traffic flow, vehicle speed, road environment, etc.
S34, judging the refrigerating capacity requirement of the engine based on a prediction result of the running speed of the automobile;
s35, if the running speed of the automobile is high, the air conditioner refrigerating capacity is high; if the vehicle is traveling at a low speed, the air conditioning cooling capacity is low.
S4, sensing the illumination radiation intensity outside the automobile in real time, and judging whether the working mode of the air conditioning system needs to be adjusted or not according to the illumination radiation intensity.
It should be noted that, by using the illumination sensor or other related sensors, the illumination radiation intensity data outside the automobile can be obtained, and these data can be transmitted to the control unit of the air conditioning system in real time to analyze and judge, and the air conditioning system automatically adjusts the working mode according to the preset strategy according to the magnitude and the variation trend of the illumination radiation intensity.
For example, in the case of higher intensity of illumination radiation, the air conditioning system may choose to reduce the cooling power, or adjust the fan speed, to reduce the energy consumption, while in the case of lower intensity of illumination radiation, the air conditioning system may provide a stronger cooling effect to meet the comfort needs of the passengers.
S5, carrying out data interaction and collaborative management on each sensor and a central control unit through a communication interface, and fusing data acquired by each sensor;
the method for carrying out data interaction and collaborative management on each sensor and the central control unit through the communication interface and fusing the data acquired by each sensor comprises the following steps:
s51, designing a communication interface matched with each sensor, wherein the communication interface comprises a serial port, an SPI and an I2C, and ensuring that each sensor is in data intercommunication with a central control unit through the communication interface;
s52, uploading the data acquired by each sensor to a central control unit according to the requirements of each sensor and a communication protocol; the data collected by each sensor comprises the passenger body temperature, the air quality index and the illumination radiation intensity;
s53, carrying out interaction and collaborative management on data acquired by each sensor by utilizing a central control unit;
s54, fusing the data acquired by each sensor by using a data fusion algorithm.
The data fusion algorithm is used for fusing the data acquired by the sensors, and the method comprises the following steps.
S541, modeling data acquired by each sensor by using a BPA function in the D-S evidence theory.
It should be noted that D-S evidence theory (Dempster-Shafer Evidence Theory), also called DST theory or evidence theory, is an inference method for dealing with uncertainty and imperfection, in which a BPA (Basic Probability Assignment) function is used to model data collected by each sensor, and a BPA function represents confidence or uncertainty of a proposition.
S542, calculating weighted Deng entropy based on the weighted credibility entropy, and performing nondeterministic measurement on each group of BPA functions.
It should be noted that, the weighted Deng entropy is an information entropy measurement method for multi-attribute decision, which considers the weights of attributes, in which each attribute has different importance or weight, and the weighted Deng entropy obtains the weighted entropy of the attribute by multiplying the weight of the attribute with the information entropy of the attribute value.
Note that the expression of the weighted Deng entropy is:
in the method, in the process of the invention,Xrepresenting an identification framework;
Arepresenting a set of events in an identification framework;
mrepresenting a basic probability distribution;
lbrepresenting a data set;
represents the weighted Deng entropy, wherein,dthe weight is represented by a weight that,wrepresenting accuracy.
S543, calculating the weight of each sensor data source according to the non-deterministic measurement result;
s544, performing data fusion by using a Dempster evidence combination rule, and regulating and controlling the air conditioning system based on a data fusion result.
It should be noted that the Dempster evidence combination rule, also called Dempster-Shafer evidence theory, is a method for reasonably combining evidence from different sources, which is based on probability theory and evidence theory, can process information of uncertainty and incompleteness, and provides an effective data fusion way.
S6, adjusting the frequency of the frequency converter through PID based on the fusion result to control the air flow and the refrigeration efficiency of the air conditioning system, and realizing the self-adaptive regulation and control of the environmental parameters in the vehicle.
It should be noted that, based on the fusion result, the frequency of the frequency converter is adjusted by the PID to control the air flow and the refrigeration efficiency of the air conditioning system, and the implementation of the adaptive regulation and control of the environmental parameters in the vehicle includes the following steps:
taking the fused data as a comprehensive result of the environment parameters in the vehicle, and setting an expected value of the environment parameters in the vehicle according to the requirements of passengers and the environment requirements, for example, setting an ideal temperature range;
comparing the fusion result with an expected value, and calculating to obtain an error value which represents the difference between the actual output and the expected output;
calculating the output of the controller according to the error value by a PID control algorithm, wherein the PID control algorithm comprises three parts, namely a proportion (P), an integral (I) and a derivative (D), which are respectively used for responding to the size of the error, the total amount of accumulated error and the rate of error change;
the output of the PID controller is used as an input signal, the frequency of the frequency converter is controlled to adjust the air flow and the refrigerating efficiency of the air conditioning system, and the frequency converter can control the fan speed and the working frequency of the compressor of the air conditioning system, so that the air flow and the refrigerating efficiency are adjusted;
the fusion result and the actual environment parameters are continuously monitored, and the parameters of the PID controller are adjusted according to the feedback information, so that an air conditioning system can be adaptively adjusted, and a stable and comfortable in-vehicle environment is achieved.
As shown in fig. 2, according to another embodiment of the present invention, there is further provided an intelligent control system for an air conditioner of an automobile capable of communicating information, the system including an environmental parameter acquisition module 1, an air index evaluation module 2, a traveling speed prediction module 3, an illumination radiation perception module 4, a data fusion module 5 and an intelligent regulation module 6;
the environment parameter acquisition module 1 is used for distributing a plurality of sensors in the automobile, sensing the environment parameters in the automobile in real time and uploading the environment parameters in the automobile to the central control unit;
the air index evaluation module 2 is used for monitoring the air quality index in the vehicle in real time, evaluating the quality of the air quality index, and formulating air quality control measures in the vehicle based on the evaluation result;
the running speed prediction module 3 is used for predicting running speed change in the future time of the automobile by using a speed prediction model and predicting the cooling capacity requirement of the engine in the automobile based on the running speed change;
the illumination radiation sensing module 4 is used for sensing illumination radiation intensity outside the automobile in real time and judging whether the working mode of the air conditioning system needs to be adjusted according to the illumination radiation intensity;
the data fusion module 5 is used for carrying out data interaction and collaborative management on each sensor and the central control unit through the communication interface, and fusing the data acquired by each sensor;
the intelligent regulation and control module 6 is used for regulating the frequency of the frequency converter through PID based on the fusion result so as to control the air flow and the refrigeration efficiency of the air conditioning system and realize the self-adaptive regulation and control of the environmental parameters in the vehicle.
In summary, by means of the above technical scheme of the present invention, various environmental parameters in the vehicle, such as temperature, humidity, etc., are sensed in real time by the plurality of sensors in the vehicle, and the data are uploaded to the central control unit, and the air quality in the vehicle is monitored, and evaluated, corresponding control measures are formulated, and the vehicle speed prediction model is utilized to predict the vehicle speed change, further predict the cooling requirement of the engine, and meanwhile, whether the air conditioner working mode needs to be adjusted is judged by sensing the external illumination intensity, each sensor performs data interaction and collaborative management with the central control unit, fusion processing is performed on the collected data, and finally, the frequency converter is controlled by the PID algorithm according to the data fusion result, and the air flow and the cooling efficiency of the air conditioning system are adjusted, so that the self-adaptive regulation of the environmental parameters in the vehicle is realized. In general, the intelligent control system utilizes central control to intelligently regulate and control an air conditioning system through real-time sensing and data fusion of various parameters inside and outside the vehicle, so as to realize accurate management of the environment inside the vehicle.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (6)
1. An intelligent control method of an automobile air conditioner capable of communicating information is characterized by comprising the following steps:
s1, distributing a plurality of sensors in an automobile, sensing environment parameters in the automobile in real time, and uploading the environment parameters in the automobile to a central control unit;
s2, monitoring the air quality index in the vehicle in real time, carrying out quality assessment on the air quality index, and formulating air quality control measures in the vehicle based on an assessment result;
s3, predicting the running speed change of the automobile in the future time by using a speed prediction model, and predicting the refrigerating capacity requirement of the engine based on the running speed change;
s4, sensing the illumination radiation intensity outside the automobile in real time, and judging whether the working mode of the air conditioning system needs to be adjusted or not according to the illumination radiation intensity;
s5, carrying out data interaction and collaborative management on each sensor and a central control unit through a communication interface, and fusing data acquired by each sensor;
s6, adjusting the frequency of the frequency converter through PID based on the fusion result to control the air flow and the refrigeration efficiency of the air conditioning system, and realizing the self-adaptive regulation and control of the environmental parameters in the vehicle;
the method for real-time monitoring of the air quality index in the vehicle and quality assessment of the air quality index in the vehicle, and formulating the air quality control measure in the vehicle based on the assessment result comprises the following steps:
s21, monitoring an air quality index in the vehicle in real time by using an air quality sensor, and constructing a topological structure based on the air quality index;
the air quality index is hour granularity information, and at least comprises carbon dioxide concentration, formaldehyde concentration and PM2.5 concentration;
s22, calculating and generating a corresponding adjacency matrix, a degree matrix and a Laplace matrix according to the topological structure, and normalizing the air quality index by utilizing a MIN-MAX algorithm;
s23, constructing an air quality prediction model based on the air quality index after normalization processing;
s24, respectively building a global assembly and a local assembly by utilizing an air quality prediction model, and fusing the outputs of the global assembly and the local assembly;
s25, defining a loss function and a root mean square error, taking the input of the local assembly and the global assembly as filling data, and respectively calculating index prediction values of air quality indexes;
s26, comparing the index predicted value with an air quality standard limit value, and carrying out grade evaluation on the air quality index based on a comparison result;
s27, formulating an in-vehicle air quality control measure based on the grade evaluation result;
the building of the global assembly comprises the following steps:
performing Laplace transformation based on the adjacent matrix to generate a feature matrix, and extracting spatial features in the feature matrix;
the time sequence after the space feature extraction is used as the input of the GRU to acquire the time feature, and the output of the global component is calculated;
calling a custom GG cell class, and converting the cell state output value into GRU output dimension which is the same as the label vector through a full connection layer;
the measures for controlling the air quality in the vehicle comprise ventilation, air purification, deodorizing, formaldehyde removal and air supply optimization;
the ventilation is used for accelerating the ventilation of dirty air;
the air purification is used for purifying the air in the vehicle by utilizing a filtering sterilization technology;
the deodorizing and formaldehyde removing device is used for reducing the concentration of formaldehyde and peculiar smell substances by utilizing a vehicle-mounted deodorizing and formaldehyde removing device and an adsorption and decomposition principle;
the optimized air supply is used for preferentially adjusting an air inlet mode of the air conditioning system so as to reduce the input of external pollutants into the vehicle;
the expression of the feature matrix is as follows:
；
in the method, in the process of the invention,representing a feature matrix;
a representation matrix;
representing the self-connecting adjacency matrix.
2. The intelligent control method of the vehicle air conditioner capable of communicating information according to claim 1, wherein the distributed deployment of a plurality of sensors in the vehicle, the real-time sensing of the in-vehicle environmental parameters and the uploading of the in-vehicle environmental parameters to the central control unit comprises the following steps:
s11, disposing an infrared sensor in a seat area in the automobile, wherein the infrared sensor is used for sensing the body temperature of a passenger;
s12, deploying an air quality sensor in the automobile, wherein the air quality sensor is used for monitoring an air quality index in the automobile;
s13, deploying an illumination sensor at the vehicle-mounted terminal, wherein the illumination sensor is used for sensing illumination radiation intensity;
s14, uploading the passenger body temperature, the air quality index and the illumination radiation intensity to the central control unit respectively.
3. The intelligent control method for the vehicle air conditioner capable of communicating information according to claim 2, wherein the method for predicting the running speed change in the future time of the vehicle by using the speed prediction model and predicting the engine refrigerating capacity demand based on the running speed change comprises the following steps:
s31, dividing the driving road sections according to the curve radius and the longitudinal slope gradient in the driving road sections of the automobile, and taking the starting point and the ending point of each road section as linear characteristic points for predicting the driving speed of the automobile;
the division of the driving road section comprises dividing the driving road section of the automobile into a straight line section, a longitudinal slope section, a flat curve section and a curved slope combined section;
s32, acquiring the speed of an adjacent road section joined by the current road section, taking the speed as the initial running speed of the adjacent road section, and respectively measuring and calculating the running speed of the automobile according to the type of each road section;
s33, respectively integrating the automobile running speeds of all road sections, and predicting the automobile running speed in a future time period by utilizing an IHSDM model;
s34, judging the refrigerating capacity requirement of the engine based on a prediction result of the running speed of the automobile;
s35, if the running speed of the automobile is high, the air conditioner refrigerating capacity is high; if the vehicle is traveling at a low speed, the air conditioning cooling capacity is low.
4. The intelligent control method for the vehicle air conditioner capable of communicating information according to claim 3, wherein the steps of performing data interaction and collaborative management on each sensor and the central control unit through the communication interface, and fusing the data collected by each sensor comprise the following steps:
s51, designing a communication interface matched with each sensor, wherein the communication interface comprises a serial port, an SPI and an I2C, and ensuring that each sensor is in data intercommunication with a central control unit through the communication interface;
s52, uploading the data acquired by each sensor to a central control unit according to the requirements of each sensor and a communication protocol; the data collected by each sensor comprises the passenger body temperature, the air quality index and the illumination radiation intensity;
s53, carrying out interaction and collaborative management on data acquired by each sensor by utilizing a central control unit;
s54, fusing the data acquired by each sensor by using a data fusion algorithm.
5. The intelligent control method for the vehicle air conditioner capable of communicating information according to claim 4, wherein the data collected by each sensor is fused by using a data fusion algorithm, comprising the following steps:
s541, modeling data acquired by each sensor by using a BPA function in a D-S evidence theory;
s542, calculating a weighted Deng entropy based on the weighted credibility entropy, and performing non-deterministic measurement on each group of BPA functions;
s543, calculating the weight of each sensor data source according to the non-deterministic measurement result;
s544, performing data fusion by using a Dempster evidence combination rule, and regulating and controlling the air conditioning system based on a data fusion result.
6. An intelligent control system of an automobile air conditioner capable of communicating information is used for realizing the intelligent control method of the automobile air conditioner capable of communicating information according to any one of claims 1-5, and is characterized in that the system comprises an environment parameter acquisition module (1), an air index evaluation module (2), a driving speed prediction module (3), an illumination radiation perception module (4), a data fusion module (5) and an intelligent regulation and control module (6);
the environment parameter acquisition module (1) is used for distributing a plurality of sensors in the automobile, sensing the environment parameters in the automobile in real time and uploading the environment parameters in the automobile to the central control unit;
the air index evaluation module (2) is used for monitoring the air quality index in the vehicle in real time, evaluating the air quality index, and formulating air quality control measures in the vehicle based on the evaluation result;
the running speed prediction module (3) is used for predicting running speed change in the future time of the automobile by using a speed prediction model and predicting the cooling capacity requirement of the engine in the automobile based on the running speed change;
the illumination radiation sensing module (4) is used for sensing the illumination radiation intensity outside the automobile in real time and judging whether the working mode of the air conditioning system needs to be adjusted or not according to the illumination radiation intensity;
the data fusion module (5) is used for carrying out data interaction and collaborative management on each sensor and the central control unit through the communication interface, and fusing the data acquired by each sensor;
the intelligent regulation and control module (6) is used for regulating the frequency of the frequency converter through PID based on the fusion result so as to control the air flow and the refrigeration efficiency of the air conditioning system and realize the self-adaptive regulation and control of the environmental parameters in the vehicle.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311287224.0A CN117002221B (en) | 2023-10-08 | 2023-10-08 | Intelligent control method and system for automobile air conditioner capable of achieving information intercommunication |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311287224.0A CN117002221B (en) | 2023-10-08 | 2023-10-08 | Intelligent control method and system for automobile air conditioner capable of achieving information intercommunication |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117002221A CN117002221A (en) | 2023-11-07 |
| CN117002221B true CN117002221B (en) | 2023-12-15 |
Family
ID=88573087
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311287224.0A Active CN117002221B (en) | 2023-10-08 | 2023-10-08 | Intelligent control method and system for automobile air conditioner capable of achieving information intercommunication |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117002221B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20070096321A (en) * | 2006-03-23 | 2007-10-02 | 주식회사 현대오토넷 | Air conditioner control system and method for car with the use of gps |
| CN105137895A (en) * | 2015-08-01 | 2015-12-09 | 湖南城市学院 | Internal environment monitoring and voice control system for passenger car |
| CN208789432U (en) * | 2018-03-27 | 2019-04-26 | 斑马网络技术有限公司 | Environment inside car adjusts device |
| CN110936786A (en) * | 2018-09-21 | 2020-03-31 | 联合汽车电子有限公司 | Air control system and method in vehicle |
| CN113071506A (en) * | 2021-05-20 | 2021-07-06 | 吉林大学 | Fuel cell automobile energy consumption optimization system considering cabin temperature |
| CN114074512A (en) * | 2020-08-13 | 2022-02-22 | 济南瑞青科技有限公司 | Fuel vehicle integrated management system |
-
2023
- 2023-10-08 CN CN202311287224.0A patent/CN117002221B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20070096321A (en) * | 2006-03-23 | 2007-10-02 | 주식회사 현대오토넷 | Air conditioner control system and method for car with the use of gps |
| CN105137895A (en) * | 2015-08-01 | 2015-12-09 | 湖南城市学院 | Internal environment monitoring and voice control system for passenger car |
| CN208789432U (en) * | 2018-03-27 | 2019-04-26 | 斑马网络技术有限公司 | Environment inside car adjusts device |
| CN110936786A (en) * | 2018-09-21 | 2020-03-31 | 联合汽车电子有限公司 | Air control system and method in vehicle |
| CN114074512A (en) * | 2020-08-13 | 2022-02-22 | 济南瑞青科技有限公司 | Fuel vehicle integrated management system |
| CN113071506A (en) * | 2021-05-20 | 2021-07-06 | 吉林大学 | Fuel cell automobile energy consumption optimization system considering cabin temperature |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117002221A (en) | 2023-11-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102981408B (en) | Running process modeling and adaptive control method for motor train unit | |
| Xie et al. | A Self-learning intelligent passenger vehicle comfort cooling system control strategy | |
| Khayyam | Adaptive intelligent control of vehicle air conditioning system | |
| Khayyam et al. | Intelligent energy management control of vehicle air conditioning via look-ahead system | |
| Chen et al. | Data-driven estimation of energy consumption for electric bus under real-world driving conditions | |
| CN105593040B (en) | For controlling the method and apparatus of circulation air operation in a motor vehicle | |
| CN109927709A (en) | A kind of route or travel by vehicle working condition determining method, energy management method and system | |
| CN105569707A (en) | Highway tunnel ventilation feedforward control method based on environmental forecasting | |
| CN108973998A (en) | A kind of heterogeneous vehicle platoon distribution energy-saving control method based on MPC | |
| CN111251819A (en) | Vehicle-mounted air conditioner intelligent adjusting method and system based on Internet of vehicles and big data | |
| CN103777631A (en) | Automatic driving control system and method | |
| CN113071506B (en) | Fuel cell automobile energy consumption optimization system considering cabin temperature | |
| CN105764736A (en) | Method and device for operating a vehicle | |
| CN110395245B (en) | Hybrid electric vehicle energy management system based on fixed route driving information | |
| Yan et al. | Co-optimization for fuel cell buses integrated with power system and air conditioning via multi-dimensional prediction of driving conditions | |
| Fayyazi et al. | Real-time self-adaptive Q-learning controller for energy management of conventional autonomous vehicles | |
| CN117002221B (en) | Intelligent control method and system for automobile air conditioner capable of achieving information intercommunication | |
| CN113276829B (en) | Vehicle running energy-saving optimization weight-changing method based on working condition prediction | |
| Wang et al. | Energy-efficient speed planner for connected and automated electric vehicles on sloped roads | |
| Amini et al. | Experimental validation of eco-driving and eco-heating strategies for connected and automated hevs | |
| Hajidavalloo et al. | NMPC-based integrated thermal management of battery and cabin for electric vehicles in cold weather conditions | |
| Yu et al. | A real-time robust ecological-adaptive cruise control strategy for battery electric vehicles | |
| CN117408360A (en) | Method, device and equipment for generating vehicle management strategy based on cloud domain interaction | |
| Guo et al. | Bilevel predictive control for hevs integrating energy and cabin thermal comfort | |
| Lindgärde et al. | Optimal vehicle control for fuel efficiency |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |