CN102865649B - Secondary fuzzy control-based multi-objective adjusting method of air quality inside carriage - Google Patents
Secondary fuzzy control-based multi-objective adjusting method of air quality inside carriage Download PDFInfo
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- CN102865649B CN102865649B CN201210359446.4A CN201210359446A CN102865649B CN 102865649 B CN102865649 B CN 102865649B CN 201210359446 A CN201210359446 A CN 201210359446A CN 102865649 B CN102865649 B CN 102865649B
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
- Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating
Abstract
The invention relates to a secondary fuzzy control-based multi-objective adjusting method of air quality inside a carriage. Temperature, concentration of carbon dioxide and humidity inside the carriage are mixed and adjusted by adopting secondary fuzzy control; and contradiction of three parameters is solved; in primary fuzzy control, three scheme parameters are output after comparison of information of a single parameter with prior information in a databank; and in secondary fuzzy control, a multi-objective optimization adjustment scheme is output after coordinating the contradiction of the three scheme parameters. With the adoption of the secondary fuzzy control-based multi-objective adjusting method, a plurality of mutually conflictive parameters, such as in-car temperature, in-car carbon dioxide concentration and in-car humidity can be mixed and adjusted at the same time, and sensitivity of adjustment is increased through a negative feedback mode.
Description
Technical field
The invention belongs to heating and ventilation project air-conditioning technique field, particularly relate to a kind of air in a car compartment quality multiple target control method based on secondary fuzzy control.
Background technology
The air-conditioned train of China adopts start and stop compressor to regulate the method for refrigerating capacity to carry out the adjusting of air themperature at present, adopts the fresh air supply mode of fixing resh air requirement to regulate the gas concentration lwevel of air in car.In the time that the volume of the flow of passengers is larger, car internal loading changes greatly, and temperature regulates and seems slower, and gas concentration lwevel exceeds standard, and in-car air quality is not good, affects passenger's physical and mental health.People have proposed many measures that improve in-car air quality for this reason, but all more unilateral.What have focuses on ventilation, has but ignored the requirement that meets passenger's thermal comfort, and the requirement that has well met thermal comfort having but cannot ensure the unobstructed of ventilation in car.Therefore, how to apply multiobject optimization method, control isoparametric the stablizing of humidity in vehicle interior temperature, the interior gas concentration lwevel of car, car is that air-conditioned train air quality regulates the matter of utmost importance running into simultaneously.The author has proposed the theory based on fuzzy control, the method for taking resh air requirement and refrigerating capacity comprehensive automation to regulate, and the concentration of carbon dioxide in control car, maintains the stable of vehicle interior temperature.Document and the patent of some train air conditionings are disclosed before this.For example, in paper " the automatic adjusting of train air-conditioning resh air requirement and refrigerating capacity ", propose to adopt the way of resh air requirement and refrigerating capacity comprehensive adjustment, inflexible problem that before having overcome, fixing resh air requirement causes.Paper " use of variable refrigerant volume air-conditioning system on train sleeper carriage " has adopted converter technique to regulate ventilation, and the ability of refrigeration is enhanced, and has simplified Electronic Control and dynamical system.Paper " Adaptive Fuzzy Control and the PLC application in central air conditioner system control " has applied to the method for fuzzy control in the middle of the control of central air-conditioning, has improved the flexibility of controlling.Above document has all proposed some control methods to train air quality, still, also cannot control the stable of gas concentration lwevel in vehicle interior temperature, car, the interior multiple parameters of humidity of car simultaneously.In controlling these parameters, main limitation is problem conflicting between parameter, and the present invention adopts the method for secondary fuzzy control to complete multiobject optimization.
Summary of the invention
Technical problem to be solved by this invention is to provide a kind of air in a car compartment quality multiple target control method based on secondary fuzzy control, can mix adjusting to the multiple conflicting parameters of humidity in gas concentration lwevel, car in vehicle interior temperature, car simultaneously.
The technical solution adopted for the present invention to solve the technical problems is: a kind of air in a car compartment quality multiple target control method based on secondary fuzzy control is provided, comprises the following steps:
1) gather air in a car compartment quality parameter information by the sensor node of the first data acquisition module, described air quality parameters comprises temperature parameter, gas concentration lwevel parameter, humidity parameter;
2) described the first data acquisition module is transferred to central processing module by the first transport module by air quality parameters;
3) described central processing module creates one-level fuzzy control list according to prior information;
4) after described central processing module is compared the data in the air quality parameters from the first data acquisition module and one-level fuzzy control list, export a scheme parameter, thereby obtain three scheme parameters based on temperature parameter, gas concentration lwevel parameter, humidity parameter respectively;
5) described three scheme parameters input secondary fuzzy control list, described secondary fuzzy control list regulates the contradiction between parameters, output multiple-objection optimization regulation scheme;
6) described central processing module, according to multiple-objection optimization regulation scheme, draws best control program, and by command to the air-conditioning adjustment module on train;
7) described air-conditioning adjustment module, according to the instruction of central processing module, regulates accordingly to air quality;
8) repeating step 1～7, thus air in a car compartment mass parameter is controlled to preset value.
Described central processing module comprises A/D converter, microprocessor, described A/D converter input connects the first transport module, output connects microprocessor, described microprocessor comprises one-level fuzzy controller, secondary fuzzy controller, described microprocessor also connects serial port module, and described serial port module is connection data storehouse also.
Described air-conditioning adjustment module comprises temperature adjustment module, gas concentration lwevel adjustment module, moisture adjustment module, described temperature adjustment module connects temperature controller, described gas concentration lwevel adjustment module connects scavenging air valve door switch, and described moisture adjustment module connects humidity controller.
In described step 5, temperature, gas concentration lwevel are paid the utmost attention in secondary fuzzy control, secondly just consider humidity.
The following step of the rear increase of described step 7: increase a feedback module, described feedback module comprises the second data acquisition module, the second transport module, and described the second data acquisition module is transferred to central processing module by the air quality parameters collecting by the second transport module; Described step 4 replaces with: by calculating parameter transformation rate from the air quality parameters of the first data acquisition module and the second data acquisition module, after described central processing module is compared the data in parameter transformation rate and one-level fuzzy control list, export a scheme parameter, thereby obtain three scheme parameters based on temperature parameter, gas concentration lwevel parameter, humidity parameter respectively.
In described step 5, secondary fuzzy control is paid the utmost attention to and is considered to regulate the parameter being changed significantly.
Described the first transport module, the second transport module are all taking CC2430 as core.
beneficial effect
The present invention has following beneficial effect compared to existing technology:
1, fuzzy control list is regulated for train air quality parameters, and adopts the method for secondary list, transparence parameter regulate in conflicting difficult point, realized and the mixing of multiple air quality parameters having been regulated simultaneously;
2, whole regulating system is simple in structure, realization is easy, resource occupation is few, and by degenerative mode, has increased the sensitivity regulating, and can reach more fast the regulating effect of wanting;
3, make the adjusting of air quality parameters there is stronger applicability and flexibility, especially met the performance requirement that on train, air quality regulates, for how to provide a comfortable air ambient by bus that effective solution is provided to passenger.
Brief description of the drawings
Fig. 1 is air-conditioning regulating system structured flowchart of the present invention;
Fig. 2 is secondary fuzzy control FB(flow block) of the present invention;
Fig. 3 is that the present invention does not adopt the simulation result while feedback;
Fig. 4 is that the present invention has adopted the simulation result after feedback;
Detailed description of the invention
Below in conjunction with specific embodiment, further set forth the present invention.Should be understood that these embodiment are only not used in and limit the scope of the invention for the present invention is described.In addition should be understood that those skilled in the art can make various changes or modifications the present invention after having read the content of the present invention's instruction, these equivalent form of values fall within the application's appended claims limited range equally.
As shown in Fig. 1～Fig. 2, the present invention includes the following step:
1) gather air in a car compartment quality parameter information by the sensor node of the first data acquisition module, described air quality parameters comprises temperature parameter, gas concentration lwevel parameter, humidity parameter;
2) described the first data acquisition module is transferred to central processing module by the first transport module by air quality parameters;
3) described central processing module creates one-level fuzzy control list according to prior information;
4) after described central processing module is compared the data in the air quality parameters from the first data acquisition module and one-level fuzzy control list, export a scheme parameter, thereby obtain three scheme parameters based on temperature parameter, gas concentration lwevel parameter, humidity parameter respectively;
5) described three scheme parameters input secondary fuzzy control list, described secondary fuzzy control list regulates the contradiction between parameters, output multiple-objection optimization regulation scheme;
6) described central processing module, according to multiple-objection optimization regulation scheme, draws best control program, and by command to the air-conditioning adjustment module on train;
7) described air-conditioning adjustment module, according to the instruction of central processing module, regulates accordingly to air quality;
8) repeating step 1～7, thus air in a car compartment mass parameter is controlled to preset value.
Described central processing module comprises A/D converter, microprocessor, described A/D converter input connects the first transport module, output connects microprocessor, described microprocessor comprises one-level fuzzy controller, secondary fuzzy controller, described microprocessor also connects serial port module, and described serial port module is connection data storehouse also.
Described air-conditioning adjustment module comprises temperature adjustment module, gas concentration lwevel adjustment module, moisture adjustment module, described temperature adjustment module connects temperature controller, described gas concentration lwevel adjustment module connects scavenging air valve door switch, and described moisture adjustment module connects humidity controller.
In described step 5, temperature, gas concentration lwevel are paid the utmost attention in secondary fuzzy control, secondly just consider humidity.
The following step of the rear increase of described step 7: increase a feedback module, described feedback module comprises the second data acquisition module, the second transport module, and described the second data acquisition module is transferred to central processing module by the air quality parameters collecting by the second transport module; Described step 4 replaces with: by calculating parameter transformation rate from the air quality parameters of the first data acquisition module and the second data acquisition module, after described central processing module is compared the data in parameter transformation rate and one-level fuzzy control list, export a scheme parameter, thereby obtain three scheme parameters based on temperature parameter, gas concentration lwevel parameter, humidity parameter respectively.
In described step 5, secondary fuzzy control is paid the utmost attention to and is considered to regulate the parameter being changed significantly.
Described the first transport module, the second transport module are all taking CC2430 as core.
The first transport module of the present invention, the second transport module all adopt the mode of wireless transmission, their exploitation adopts TinyOS system, programming language is nesC, and described the first transport module, the second transport module have built a WSN network air quality parameters collecting is transmitted.
One-level fuzzy control list not only by current the first data collecting module collected to air quality parameters form, also introduce negative-feedback, make central processing module become dual input from single input, calculate the interconversion rate of parameter, and to whole system, remain single input, original one dimension parameter list is configured to two-dimensional parameter list.
Below by setting up fuzzy control table and fuzzy controller, data acquisition, Fuzzy Processing, the present invention is specifically set forth in four aspects of adjusting feedback:
1, set up fuzzy control table and fuzzy controller
What the present invention proposed is a kind of air in a car compartment quality multiple target control method based on secondary fuzzy control.First to set up the one-level fuzzy control table of each parameter, as shown in table 1.
Secondly determine that one-level fuzzy controller is the model of one two input one output, wherein two inputs are respectively air-conditioning system parameter error E and parameter error rate Ec, and output is valve opening U.The model of the blur tool case that this method adopts is Mamdani type.Parameter E1 in this method, E2, E3 and parameter error rate Ec1, Ec2, Ec3 is representation temperature, humidity, gas concentration lwevel and their deviation ratio respectively.The fuzzy subset's of input E and Ec and output U domain is { 6 ,-5 ,-4,-3 ,-2 ,-1,0,1,2,3,4,5,6}, the membership function curve of each fuzzy quantity is triangle, and for each fuzzy quantity chosen seven Linguistic Values in negative large, negative, negative little, zero, just little, center, honest, for programming conveniently, abridge and represent { NB NM NS ZE PS PM PB} with English alphabet.
Then set up secondary fuzzy control list, the main object of secondary fuzzy control list is to solve the contradictory problems regulating between temperature and gas concentration lwevel, by this parameters, transparent.In the time of this two parameters contradiction, first by ventilation module regulation of carbon dioxide concentration, and adjusting temperature by a small margin, when gas concentration lwevel reach standard 70% time, mainly regulate temperature, regulate and ventilate by a small margin.The method can be saved the energy, and within the time faster, reaches all more suitable targets of temperature and gas concentration lwevel, pays the utmost attention to after temperature and gas concentration lwevel, just considers humidity.
2, data acquisition
Data acquisition, by the sensor collection of the first data acquisition module and the second data acquisition module, in this example, is carried out the analog input to data by the simulink environment under matlab software.In order to carry out Fuzzy processing, input variable must be carried out to obfuscation, input variable to be varied to corresponding fuzzy subset's domain, this will be multiplied by corresponding coefficient input quantity, and this coefficient is called as quantizing factor conventionally.Here the quantizing factor of inputting E is set as ke, and the quantizing factor of Ec is set as kec.In addition, the output quantity after fuzzy control, can not directly act on controlled device, also must be by its sharpening, be transformed in the receptible basic domain of controlled device, and this will scale factor ku.Three gain modules in Fig. 2 provide respectively quantizing factor ke, kec, and scale factor ku.Be ke=0.1, kec=0.001, ku=0.8.
3, Fuzzy Processing
Fuzzy controller is the core of this Fuzzy Processing, and its control law is to obtain by the experience of imitating artificial control and accumulate by staff.The effect of the control law of fuzzy controller is utilizing the obtained accurate state of COMPUTER DETECTION control procedure to carry out obfuscation, thereby change the input message of fuzzy controller into, then make fuzzy reasoning and decision-making according to the method for human brain, the output quantity of controlled device, finally utilize de-fuzzy accurately to be measured again, it is acted in controlled device.So the process of fuzzy controller is generally that the synthetic algorithm imitation human brain that utilizes fuzzy reasoning afterwards of input and output obfuscation makes a policy.In the present invention, adopt secondary fuzzy control, first order fuzzy control draws three preconditioning schemes by the parameter of obtaining, the place that second level fuzzy control is contradictory according to possibility in the middle of preconditioning scheme, according to the priori of oneself and demand, makes and is more conducive to own object selection.In this example, main consideration, in the time of temperature and gas concentration lwevel conflict, is first considered ventilation, considers and then the control of temperature, and such selection is conducive to save the energy, on the train of limited energy.Because three parameter kp, the ki, the kd that control are in the effect difference of three parameters of different time, and these three parameters also exist the relation of being mutually related each other, so in design fuzzy controller, must consider in the effect of three parameters of different time and inter-related relation each other for the adjusting of parameter of controller.Now set up following rule, be respectively used to three parameter kp of change control device, ki, kd.The fuzzy reasoning table of three parameters is respectively as shown in table 2, table 3, table 4.
4, regulate feedback
After the processing of secondary fuzzy controller, obtain a multiple-objection optimization regulation scheme, calling air-conditioning adjustment module regulates, temperature controller, the humidity controller of air-conditioning adjustment module and change air valve and start to act on simultaneously, and carry out negative-feedback after output, by parameter Resurveys such as temperature, humidity and gas concentration lwevels after regulating, feed back to the input of one-level fuzzy controller, proceed to regulate.Fig. 3, Fig. 4 have represented respectively not adopt and adopt feedback simulation result afterwards.From Fig. 3, Fig. 4, after adopting feedback, can be adjusted to faster the effect needing.
If following table 1 is one-level fuzzy control specification table; Table 2 is the fuzzy reasoning table of kp; Table 3 is the fuzzy reasoning table of ki; Table 4 is the fuzzy reasoning table of kd.
Table 1: one-level fuzzy control rule table
The fuzzy reasoning table of table 2:kp
The fuzzy reasoning table of table 3:ki
The fuzzy reasoning table of table 4:kd
Claims (7)
1. the air in a car compartment quality multiple target control method based on secondary fuzzy control, is characterized in that, comprises the following steps:
1) gather air in a car compartment quality parameter information by the sensor node of the first data acquisition module, described air quality parameters comprises temperature parameter, gas concentration lwevel parameter, humidity parameter;
2) described the first data acquisition module is transferred to central processing module by the first transport module by air quality parameters;
3) described central processing module creates one-level fuzzy control list according to prior information;
4) after described central processing module is compared the data in the air quality parameters from the first data acquisition module and one-level fuzzy control list, export a scheme parameter, thereby obtain three scheme parameters based on temperature parameter, gas concentration lwevel parameter, humidity parameter respectively;
5) described three scheme parameters input secondary fuzzy control list, described secondary fuzzy control list regulates the contradiction between parameters, output multiple-objection optimization regulation scheme;
6) described central processing module, according to multiple-objection optimization regulation scheme, draws best control program, and by command to the air-conditioning adjustment module on train;
7) described air-conditioning adjustment module, according to the instruction of central processing module, regulates accordingly to air quality;
8) repeating step 1～7, thus air in a car compartment mass parameter is controlled to preset value.
2. a kind of air in a car compartment quality multiple target control method based on secondary fuzzy control as claimed in claim 1, it is characterized in that: described central processing module comprises A/D converter, microprocessor, described A/D converter input connects the first transport module, output connects microprocessor, described microprocessor comprises one-level fuzzy controller, secondary fuzzy controller, described microprocessor also connects serial port module, and described serial port module is connection data storehouse also.
3. a kind of air in a car compartment quality multiple target control method based on secondary fuzzy control as claimed in claim 1, it is characterized in that: described air-conditioning adjustment module comprises temperature adjustment module, gas concentration lwevel adjustment module, moisture adjustment module, described temperature adjustment module connects temperature controller, described gas concentration lwevel adjustment module connects scavenging air valve door switch, and described moisture adjustment module connects humidity controller.
4. a kind of air in a car compartment quality multiple target control method based on secondary fuzzy control as claimed in claim 1, is characterized in that: in described step 5, temperature, gas concentration lwevel are paid the utmost attention in secondary fuzzy control, secondly just considers humidity.
5. a kind of air in a car compartment quality multiple target control method based on secondary fuzzy control as claimed in claim 1, it is characterized in that, the following step of the rear increase of described step 7: increase a feedback module, described feedback module comprises the second data acquisition module, the second transport module, and described the second data acquisition module is transferred to central processing module by the air quality parameters collecting by the second transport module; Described step 4 replaces with: by calculating parameter transformation rate from the air quality parameters of the first data acquisition module and the second data acquisition module, after described central processing module is compared the data in parameter transformation rate and one-level fuzzy control list, export a scheme parameter, thereby obtain three scheme parameters based on temperature parameter, gas concentration lwevel parameter, humidity parameter respectively.
6. a kind of air in a car compartment quality multiple target control method based on secondary fuzzy control as claimed in claim 5, is characterized in that: in described step 5, secondary fuzzy control is paid the utmost attention to and regulated the parameter being changed significantly.
7. a kind of air in a car compartment quality multiple target control method based on secondary fuzzy control as described in claim 5 or 6, is characterized in that: described the first transport module, the second transport module are all taking CC2430 as core.
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Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103322643A (en) * | 2013-06-05 | 2013-09-25 | 苏州惠瑞自动化集成有限公司 | Automated air conditioning monitoring system |
| CN105588251B (en) * | 2014-10-20 | 2018-10-02 | 株式会社理光 | The method and apparatus for controlling air handling system |
| CN104730928A (en) * | 2015-04-14 | 2015-06-24 | 济南大学 | Method for controlling boiler water level of thermal power plant through fuzzy quantization factors |
| CN104930594A (en) * | 2015-06-24 | 2015-09-23 | 陈璟 | Air conditioner |
| CN105678429B (en) * | 2016-02-19 | 2019-04-16 | 西南交通大学 | A method of realizing the multidisciplinary multiple-objection optimization of electric automobile air-conditioning system |
| CN108302735B (en) * | 2016-09-30 | 2022-10-28 | 日本电气株式会社 | Apparatus and method for controlling air purification system |
| CN111174383B (en) * | 2018-10-24 | 2022-04-19 | 青岛海尔空调器有限总公司 | Control method and device of air conditioner cluster, air conditioner cluster and intelligent home system |
| CN110979366B (en) * | 2019-12-09 | 2021-09-10 | 交控科技股份有限公司 | Air conditioner control method and system for railway vehicle |
| CN111583672B (en) * | 2020-04-09 | 2021-11-12 | 江苏中科院智能科学技术应用研究院 | Intelligent traffic light control method, system and device |
| CN114216256B (en) * | 2021-12-22 | 2022-09-23 | 中国海洋大学 | Ventilation system air volume control method of off-line pre-training-on-line learning |
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| CN1727783A (en) * | 2004-07-26 | 2006-02-01 | 乐金电子(天津)电器有限公司 | Device for controlling indoor air quality through using ventilation system, and method |
| CN101865516A (en) * | 2010-06-02 | 2010-10-20 | 奇瑞汽车股份有限公司 | Device and method for controlling concentration of carbon dioxide in car |
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| JPH0464853A (en) * | 1990-07-04 | 1992-02-28 | Matsushita Seiko Co Ltd | Air conditioner |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN1727783A (en) * | 2004-07-26 | 2006-02-01 | 乐金电子(天津)电器有限公司 | Device for controlling indoor air quality through using ventilation system, and method |
| CN101865516A (en) * | 2010-06-02 | 2010-10-20 | 奇瑞汽车股份有限公司 | Device and method for controlling concentration of carbon dioxide in car |
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