CN109050200A - A kind of control method of automobile heat pump air conditioner - Google Patents
A kind of control method of automobile heat pump air conditioner Download PDFInfo
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- CN109050200A CN109050200A CN201810957945.0A CN201810957945A CN109050200A CN 109050200 A CN109050200 A CN 109050200A CN 201810957945 A CN201810957945 A CN 201810957945A CN 109050200 A CN109050200 A CN 109050200A
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- compressor
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- 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
- B60H1/00357—Air-conditioning arrangements specially adapted for particular vehicles
- B60H1/00385—Air-conditioning arrangements specially adapted for particular vehicles for vehicles having an electrical drive, e.g. hybrid or fuel cell
- B60H1/00392—Air-conditioning arrangements specially adapted for particular vehicles for vehicles having an electrical drive, e.g. hybrid or fuel cell for electric vehicles having only electric drive means
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- 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
- B60H1/00271—HVAC devices specially adapted for particular vehicle parts or components and being connected to the vehicle HVAC unit
- B60H1/00278—HVAC devices specially adapted for particular vehicle parts or components and being connected to the vehicle HVAC unit for the battery
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- 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
- B60H1/00814—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
- B60H1/00899—Controlling the flow of liquid in a heat pump system
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Thermal Sciences (AREA)
- Mechanical Engineering (AREA)
- Life Sciences & Earth Sciences (AREA)
- Sustainable Development (AREA)
- Sustainable Energy (AREA)
- Air-Conditioning For Vehicles (AREA)
Abstract
The invention discloses a kind of control methods of automobile heat pump air conditioner, comprising: Step 1: obtaining evaporator outlet degree of superheat Δ T for the first BP neural network is inputted after evaporator parameter normalizatione, evaporator heat exchange amount QeAnd evaporator air side heat exchange amount Qair;Meanwhile the second BP neural network will be inputted after condenser parameter normalization, obtain condensator outlet degree of supercooling Δ Tc, condenser heat exchange amount QcAnd condenser air side heat exchange amount Qair,c;Step 2: calculating the heat exchange amount Δ Q that heat pump air conditioner needs to adjust;Step 3: being provided to the heat exchange amount Q of crew module to heat pump air conditioning systemneed, evaporator air side heat exchange amount QairAnd after heat pump air conditioning system needs the heat exchange amount △ Q that adjusts to carry out clustering, it is adjusted by the revolving speed of the duty when compressor of the duty ratio of cooling fan outside aperture to electric expansion valve, vehicle, interior cooling fan, make △ Q=0, and the general power of heat pump air conditioning system is minimum.The control method of automobile heat pump air conditioner provided by the invention, fast response time can preferably control energy consumption.
Description
Technical field
The invention belongs to automobile heat pump air conditioner control technology field, in particular to a kind of controlling party of automobile heat pump air conditioner
Method.
Background technique
Currently, air conditioning for automobiles lightweight, densification, intelligence, the development trend of energy-saving are obvious.As automatic air condition exists
Field of automobile air conditioner it is universal, driver no longer needs cumbersome to manually adjust crew module's temperature to meet driver and passenger couple
The requirement of comfort level.Driver only needs to set cockpit target temperature, and air-conditioner control system will automatically adjust, so that driving
It is consistent with target temperature to sail cabin temperature.Automobile air conditioner control system mainly passes through control compressor rotary speed, cooling fan rotation speed, electricity
Sub- expansion valve opening and inner-outer circulating air door state adjust cockpit temperature and determine whether there are fresh air injection crew module
To improve cabin air quality etc..
For electric car, compared with the system for non-independent air conditioner system (engine driving compressor of air conditioner) of orthodox car,
Electric automobile air-conditioning system uses the Air Conditioning System of motor-driven compressor, so that compressor of air conditioner is no longer by dynamical system
The constraint of state (orthodox car engine frequent start-stop etc.), more freely.Air-conditioner control system can carry out more intelligent
It adjusts.
For current automobile air conditioner control system, most of use pid control mode, be unable to satisfy air conditioning for automobiles
The requirement of this system changed with non-linear, time-varying and dynamic state of parameters of system.Cause air conditioning for automobiles to adjust crew module to relax
Appropriateness can not make timely response, hysteresis is strong, dynamic responding speed is slow.
In addition, batteries of electric automobile capacity is relatively limited, compressor, cooling fan and electric expansion valve consumption in air conditioning for automobiles
Electricity accounts for the 20%-30% of battery capacity.Air-conditioning system energy consumption has an important influence electric automobile during traveling mileage.
Therefore, design it is a kind of be enable to respond quickly, meeting crew module's comfort level simultaneously, automatically select air conditioning energy consumption most
Excellent heat pump air conditioner control system is very necessary.
Batteries of electric automobile state influences battery capacity huge.It needs to guarantee battery while guaranteeing temperature pleasant
In charge and discharge process, battery temperature remains at optimum range.
Summary of the invention
An object of the present invention is to provide a kind of control method of automobile heat pump air conditioner, uses BP neural network and gathers
Alanysis method combines, and is enable to respond quickly, and while meeting heating or refrigeration requires, control air conditioning energy consumption reaches most
It is excellent.
The second object of the present invention is to provide a kind of control method of automobile heat pump air conditioner, using radial base neural net pair
The aperture of battery flat electric expansion valve is adjusted, and the temperature of battery flat is made to be maintained at suitable range.
Technical solution provided by the invention are as follows:
A kind of control method of automobile heat pump air conditioner, comprising:
Step 1: by evaporator outlet temperature Teo, evaporator exit pressure Peo, evaporator temperature Tei, evaporator into
Mouth pressure Pei, evaporator inlet refrigerant flow q and vaporizer side air themperature TairThe first BP nerve net is inputted after normalization
Network obtains evaporator outlet degree of superheat Δ Te, evaporator heat exchange amount QeAnd evaporator air side heat exchange amount Qair;
Meanwhile by condensator outlet temperature Tco, condensator outlet pressure Pco, condenser inlet temperature Tci, condenser inlet
Pressure Pci, condenser inlet refrigerant flow qcAnd the air themperature T of condenserair,cThe 2nd BP nerve net is inputted after normalization
Network obtains condensator outlet degree of supercooling Δ Tc, condenser heat exchange amount QcAnd condenser air side heat exchange amount Qair,c;
Step 2: calculating the heat exchange amount Δ Q that heat pump air conditioner needs to adjust;
Δ Q=| Qneed|-|Qair| or Δ Q=| Qneed|-|Qair,c|;
Wherein, QneedThe heat exchange amount of crew module is provided to for heat pump air conditioning system;
Step 3: being provided to the heat exchange amount Q of crew module to heat pump air conditioning systemneed, evaporator air side heat exchange amount
QairAnd after heat pump air conditioning system needs the heat exchange amount △ Q that adjusts to carry out clustering, by adjust electric expansion valve aperture,
The revolving speed of the duty when compressor of the duty ratio of the outer cooling fan of vehicle, interior cooling fan is adjusted, and makes △ Q=0, and
The general power of heat pump air conditioning system is minimum.
Preferably, in said step 1, the hiding node layer of the first BP neural network is 8, the 2nd BP nerve net
The hidden layer number of nodes of network is 7.
Preferably, in the step 2, heat pump air conditioning system is provided to the heat exchange amount Q of crew moduleneedAre as follows:
Qneed=Qtotal-Qheat;
Wherein, QtotalFor total heat exchange amount inside vehicle occupant compartment, QheatFor the total heat duties for entering vehicle occupant compartment.
Preferably, total heat exchange amount Q inside vehicle occupant compartmenttotalAre as follows:
Qtotal=cp,air·ρair·V·(Tsetting-Tinside);
Wherein, TsettingFor driver's set temperature;cp,airFor air specific heat capacity;ρairFor atmospheric density;V is to multiply
Member's cabin product.
Preferably, the total heat duties Q into automobile passenger storehouseheatAre as follows:
Qheat=Qg+Qroof+Qside+Qbottom+Qperson+Qluggage+Qengine+Qskylight+Qwind;
Wherein, QgFor glass thermic load;QroofFor roof thermic load;QsideFor side wall thermic load;QbottomIt is negative for vehicle bottom heat
Lotus;QpersonFor occupant's thermic load;QluggageFor luggage compartment thermic load;QengmeFor piggyback pod thermic load;QskylightFor skylight
Thermic load;QwindFor fresh air and thermic load of leaking out.
Preferably, in the step 3, four class situations is divided into heat pump air conditioning system by clustering and are adjusted
Section, comprising:
The first kind increases electronic expansion valve opening as Δ Q > 0, until Δ Q=0;It is as Δ Q < 0, electronics is swollen
Swollen valve opening reduces, until Δ Q=0;
Second class increases electronic expansion valve opening as △ Q > 0, as evaporator outlet degree of superheat Δ TeReach 4.5
DEG C, stop the aperture for increasing electric expansion valve, adjusts the duty ratio of the outer cooling fan of vehicle and the duty ratio of interior cooling fan, directly
To △ Q=0, and interior cooling fan and the outer cooling fan of vehicle are optimal duty ratio;
As Δ Q < 0, electronic expansion valve opening is reduced, as evaporator outlet degree of superheat Δ TeReach 5.5 DEG C, stops
Reduce the aperture of electric expansion valve, the duty ratio of the outer cooling fan of vehicle and the duty ratio of interior cooling fan is adjusted, until △ Q=
0, and the outer cooling fan of vehicle and interior cooling fan are optimal duty ratio;
The aperture of electric expansion valve is increased to evaporator outlet degree of superheat Δ T as △ Q > 0 by third classeReach 4.5
℃;The duty of the duty ratio, interior cooling fan that adjust the outer cooling fan of vehicle simultaneously when compressor rotary speed, until △ Q=0,
And the general power of the outer cooling fan of vehicle, interior cooling fan and compressor is minimum;
As △ Q < 0, the aperture of electric expansion valve is decreased to evaporator outlet degree of superheat Δ TeReach 5.5 DEG C;Simultaneously
The duty of the duty ratio, interior cooling fan that adjust the outer cooling fan of vehicle when compressor rotary speed, until △ Q=0, and outside vehicle
The general power of cooling fan, interior cooling fan and compressor is minimum;
The aperture of electric expansion valve is increased to evaporator outlet degree of superheat Δ T as △ Q > 0 by the 4th classeReach 4.5
DEG C and adjust the duty ratio of the duty of the outer cooling fan of vehicle when interior cooling fan to maximum, while adjusting compressor and turning
Speed, until △ Q=0;
As △ Q < 0, expansion valve is decreased to evaporator outlet degree of superheat Δ TeReach 5.5 DEG C and adjusts cold outside vehicle
But the duty ratio of the duty of fan when interior cooling fan is to minimum, while adjusting compressor rotary speed, until △ Q=0.
Preferably, in second class, determine that the outer cooling fan of vehicle and the outer cooling fan of vehicle are optimal duty ratio
Objective function are as follows:
Wfan=U (k1·x2+k2·y2)
In formula, U is crest voltage, and x is the duty ratio of the outer cooling fan of vehicle, and y is the duty ratio of interior cooling fan, k1For
The inverse of the resistance of the outer cooling fan of vehicle, k2For the inverse of the resistance of interior cooling fan;
Work as WfanValue minimum when, corresponding x value is the optimal duty ratio of the outer cooling fan of vehicle, and corresponding y value is cold outside vehicle
But the optimal duty ratio of fan.
Preferably, in the third class, the general power of the outer cooling fan of vehicle, interior cooling fan and compressor are as follows:
Wtotal=A1(Wfan1+Wcompressor,1)+A2(Wfan2+Wcompressor,2)+A3Wcompressor,3;
In formula, (Wfan1+WCompressor, 1) it is that the outer cooling fan of vehicle is adjusted jointly with compressor, when reaching △ Q=0
The power of consumption, (Wfan2+WCompressor, 2) it is that interior cooling fan is adjusted jointly with compressor, disappear when reaching △ Q=0
The power of consumption, Wfan1For the maximum power of cooling fan outside vehicle, Wfan2For the maximum power of interior cooling fan;WCompressor, 3For
The separately adjustable power reached when △ Q=0 is consumed of compressor;
Adjust A1、A2And A3Make WtotalReach minimum value, obtains WtotalThe corresponding vehicle of minimum value outer cooling fan account for
The duty when compressor rotary speed of sky ratio, interior cooling fan.
Preferably, the electric expansion valve includes the first electric expansion valve and the second electric expansion valve;
When crew module needs heating, the first electric expansion valve is adjusted;
When crew module needs to freeze, the second electric expansion valve is adjusted.
Preferably, the control method of the automobile heat pump air conditioner further include: add automobile driving speed V, running car
Speed a, air-conditioning system general power Wtotal, battery flat temperature Tb, battery cooling line exchange heat before temperature value Tb1And battery cooling tube
Temperature value T after the heat exchange of roadb2Radial base neural net is inputted, the aperture of battery flat electric expansion valve is obtained.
The beneficial effects of the present invention are:
(1) control method of automobile heat pump air conditioner provided by the invention, using BP neural network and clustering method phase
In conjunction with, be enable to respond quickly, meet heating or refrigeration require while, control air conditioning energy consumption be optimal.
(2) control method of automobile heat pump air conditioner provided by the invention, using radial base neural net to battery flat electronics
The aperture of expansion valve is adjusted, and the temperature of battery flat can be made to be maintained at suitable range.
Detailed description of the invention
Fig. 1 is heat pump air conditioning system structural schematic diagram of the present invention.
Fig. 2 is the flow chart of the present invention for obtaining evaporator stage.
Fig. 3 is the flow chart of the present invention for obtaining condenser state.
Fig. 4 is crew module's seat arrangement schematic diagram of the present invention.
Fig. 5 is the flow chart for the heat exchange amount that calculating heat pump air conditioner of the present invention needs to adjust.
Fig. 6 is the flow chart that heat pump air conditioner state of the present invention and crew module's state carry out clustering.
Fig. 7 is heat pump air conditioning system control method schematic diagram of the present invention.
Fig. 8 is the method schematic diagram that optimal energy consumption is calculated in heat pump air conditioner third class control method of the present invention.
Fig. 9 is the schematic diagram of control battery flat equalized temperature of the present invention.
Specific embodiment
Present invention will be described in further detail below with reference to the accompanying drawings, to enable those skilled in the art referring to specification text
Word can be implemented accordingly.
The present invention provides a kind of control methods of automobile heat pump air conditioner.As shown in Figure 1, automobile heat pump air-conditioning system is main
By cooling fan 140, four-way valve outside the first temperature sensor 110, first pressure sensor 120, vehicle external heat exchanger 130, vehicle
150, second temperature sensor 210, second pressure sensor 220, compressor 230, third temperature sensor 310, third pressure
Sensor 320, gas-liquid separator 330, interior cooling fan 410, interior heat exchanger 420, the 4th temperature sensor the 430, the 4th
Pressure sensor 440, the first electric expansion valve 510, the first check valve 520, the 5th temperature sensor 530, the 5th pressure sensing
Device 540, second one-way valve 550, third check valve 560, the 4th check valve 570, the 6th temperature sensor 610, the 6th pressure pass
Sensor 620, the second electric expansion valve 630, chiller710, the 7th temperature sensor 720, the 8th temperature sensor 730, battery
740, battery flat electric expansion valve 750, the 9th temperature sensor 810, the tenth temperature sensor 820, first flowmeter 830 and
Two flowmeters 840 composition.
When vehicle occupant compartment needs to freeze, vehicle external heat exchanger 130 serves as condenser, and interior heat exchanger 420 serves as evaporation
Device;Detailed process are as follows: compressor 230- four-way valve 150- vehicle external heat exchanger 130- the second electric expansion valve 630- check valve 570-
Check valve 550- car heat exchanger 420- four-way valve 150- gas-liquid separator 330- compressor 230.210 He of second temperature sensor
Second pressure sensor 220 measures the temperature and pressure of the outlet of compressor 230 respectively, is considered as condenser inlet temperature and pressure;
First temperature sensor 110 and first pressure sensor 120 measure condensator outlet temperature and pressure respectively;6th temperature sensing
Device 610 and the 6th pressure sensor 620 measure 630 outlet temperature of the second electric expansion valve and pressure respectively, be considered as evaporator into
Mouth temperature and pressure;Third temperature sensor 310 and third pressure sensor 320 measure compressor inlet temperature and pressure, depending on
For evaporator outlet temperature and pressure;First flowmeter 830 measures condenser inner refrigerant flow;Second flowmeter 840 measures
Evaporator inner refrigerant flow;9th temperature sensor 810 measures condenser side wind-warm syndrome;The measurement of tenth temperature sensor 820 is steamed
Send out the air themperature of device side.
When vehicle occupant compartment needs heating, vehicle external heat exchanger serves as evaporator, and interior heat exchanger serves as condenser;Specifically
Process are as follows: compressor 230- four-way valve 150- car heat exchanger 420- the first electric expansion valve 510- the first check valve 520- third
Check valve 560- vehicle external heat exchanger 130- four-way valve 150- gas-liquid separator 330- compressor 230.Wherein, second temperature sensor
210, second pressure sensor 220 measures the temperature and pressure of compressor outlet respectively, is considered as condenser inlet temperature and pressure;
4th temperature sensor 430 and the 4th pressure sensor 440 measure condensator outlet temperature and pressure respectively;5th temperature sensing
Device 530 and the 5th pressure sensor 540 measure the temperature and pressure of the first expansion valve 510 outlet respectively, are considered as evaporator
Temperature and pressure;Third temperature sensor 310 and third pressure sensor 320 represent compressor inlet temperature and pressure, are considered as
Evaporator outlet temperature and pressure;First flowmeter 830 measures evaporator inner refrigerant flow;Second flowmeter 840 measures cold
Condenser inner refrigerant flow;The air themperature of 9th temperature sensor 810 measurement vaporizer side;Tenth temperature sensor 820 is surveyed
Measure the air themperature of condenser side.
7th temperature sensor 720 measures temperature before battery cooling line exchanges heat;8th temperature sensor 730 measures battery
Temperature after cooling line heat exchange.
As shown in Fig. 2, obtaining the process of evaporator stage by BP neural network are as follows: controller receives compressor inlet temperature
Spend sensor, Compressor Inlet Pressure sensor, expansion valve outlet temperature sensor, expansion valve outlet pressure sensor, flow
The measured value of sensor, vaporizer side temperature sensor, above-mentioned measured value respectively represent evaporator outlet temperature Teo, evaporator goes out
Mouth pressure Peo, evaporator temperature Tei, evaporator pressure Pei, refrigerant flow q, vaporizer side air themperature
Tair.By evaporator outlet temperature Teo, evaporator exit pressure Peo, evaporator temperature Tei, evaporator pressure Pei, system
Cryogen flow q, air themperature TairInput object is used as after being normalized, by evaporator outlet degree of superheat Δ Te, evaporator changes
Heat QeWith evaporator air side heat exchange amount QairAs output object, input layer node number 6, output layer node number is 3
It is a.Learnt using BP neural network, input 150 groups of sample datas, initial hidden layer node number is 1, and circulation is increased
Add, until the error that training obtains is less than setting error amount.By adjusting hidden layer node number, factor of momentum, learning rate,
Algorithm etc. is practised, is reduced to its absolute error within the scope of target error, i.e., BP neural network has trained.
Weight vector constantly is adjusted by minimizing loss function, defines loss function first (here using square error
Loss function), since the output layer of network has multiple output nodes, need the squared difference of each output node of output layer
Summation.
Obtain the loss function of each training examples are as follows:
Each layer connection weight is initialized, and learning rate and inertia coeffeicent are set;One group of sample characteristics is inputted, each layer section is calculated
Point output valve;Decline strategy according to gradient, parameter is adjusted with the negative gradient direction of objective function.
Right value update:
After constantly regulate, learning rate η=0.05, training objective error is 1 × 10-7, factor of momentum 0.95, hidden layer
Node number 8 best, wherein algorithm uses Levenberg-Marquardt algorithm.
By the evaporator outlet temperature T of Air-conditioning system sensor real-time measurementeo, evaporator exit pressure Peo, evaporator into
Mouth temperature Tei, evaporator pressure Pei, refrigerant flow q, vaporizer side air themperature Tair, inputted after normalization
In trained neural network, output layer parameter is subjected to renormalization, obtains evaporator outlet degree of superheat Δ Te, evaporator changes
Heat QeWith evaporator air side heat exchange amount Qair。
As shown in figure 3, obtaining the process and evaporator stage neural metwork training of condenser state by BP neural network
Process is substantially the same.Controller receive come the condensator outlet temperature sensor of condenser, condensator outlet pressure sensor,
Compressor exit temperature sensor, compressor delivery pressure sensor, condenser flow sensor, condenser side temperature sensor
Measured value, above-mentioned measured value respectively represents condensator outlet temperature Tco, condenser device outlet pressure Pco, condenser inlet temperature
Spend Tci, condenser inlet pressure Pci, refrigerant flow qc, condenser side air themperature Tair,c.Pass through condensator outlet temperature
Tco, condensator outlet pressure Pco, condenser inlet temperature Tci, condenser inlet pressure Pci, refrigerant flow qc, condenser survey
Air themperature Tair,cInput object is used as after being normalized, by condensator outlet degree of supercooling Δ Tc, condenser device heat exchange amount
QcWith condenser air side heat exchange amount Qair,cAs output object.Input layer node number 6, output layer node number are 3.
Initial hidden layer node number is 1, and circulation is increased, until the error that training obtains is less than setting error amount.Using BP mind
Learnt through network, by adjusting hidden layer node number, factor of momentum, learning rate, learning algorithm etc., makes its absolute error
It is reduced within the scope of target error.I.e. neural network has trained.
After constantly regulate, learning rate η=0.01, training objective error is 1 × 10-7, factor of momentum 0.9, hidden layer
Node number 7 best, wherein algorithm uses Levenberg-Marquardt algorithm.
By the condensator outlet temperature T of Air-conditioning system sensor real-time measurementco, condenser device outlet pressure Pco, condenser
Inlet temperature Tci, condenser inlet pressure Pci, refrigerant flow qc, condenser side air themperature Tair,c, inputted after normalization
In trained BP neural network, output layer parameter is subjected to renormalization, obtains condensator outlet degree of supercooling Δ Tc, it is cold
Condenser device heat exchange amount QcWith condenser air side heat exchange amount Qair,c。
Since personnel amount and physical trait difference in crew module cause to radiate thermic load not to crew module between each occupant
Together.As shown in figure 4, the seat bottom of position 910, position 920, position 930 is respectively installed a pressure sensor.Pass through pressure
Sensor perceives whether its position pressure is 0, judges whether each seat is occupied.And pass through pressure sensor senses
The difference of pressure, can reflect the physical trait of occupant, then calculate the corresponding thermic load of occupant of different physical traits.
As shown in figure 5, controller, which receives, comes from vehicle speed sensor, intensity of solar radiation sensor, crew module's temperature sensing
Device, vehicle external environment temperature sensor, the pressure sensor of position 910, the pressure sensor of position 920, position 930 pressure pass
The data that sensor, luggage compartment pressure sensor, piggyback pod temperature sensor, skylight air velocity transducer measure.The sensor
Measurement data respectively represent running car speed, into temperature, vehicle external environment in the intensity of solar radiation of crew module, crew module
Whether there is or not be put into article, crew module personnel number, temperature in piggyback pod, by skylight enter fresh air in crew module for temperature, luggage compartment
Amount.
Into the total heat duties Q in automobile passenger storehouseheatAre as follows:
Qheat=Qg+Qroof+Qside+Qbottom+Qperson+Qluggage+Qengine+Qskylight+Qwind;
Wherein, QgFor glass thermic load;QroofFor roof thermic load;QsideFor side wall thermic load;QbottomIt is negative for vehicle bottom heat
Lotus;QpersonFor occupant's thermic load;QluggageFor luggage compartment thermic load;QengmeFor piggyback pod thermic load;QskylightFor skylight
Thermic load;QwindFor fresh air and thermic load of leaking out.
According to people's normal type, generally between 40kg-100kg, therefore as pressure sensor record weight W < 40kg, write from memory
Think that 40kg, W > 100kg are defaulted as 100kg.
Qperson=Qdriver+Qcrew。
Rest part thermic load according to the mainstream calculation method of current crew module's heat exchange amount non-steady calculation method (dynamic
Conduct heat algorithm) it calculates.
Crew module's internal temperature T is measured by crew module's temperature sensorinside, calculate and needed inside vehicle occupant compartment
Total heat exchange amount Qtotal:
Qtotal=cp,air·ρair·V·(Tsetting-Tinside);
Wherein, TsettingFor driver's set temperature, cp,airFor air specific heat capacity;ρairFor atmospheric density;V is to multiply
Member's cabin product.
Later, the heat exchange amount Q that heat pump air conditioning system is provided to crew module is calculatedneed:
Qneed=Qtotal-Qheat;
Wherein, QtotalFor total heat exchange amount inside vehicle occupant compartment, QheatFor the total heat duties for entering vehicle occupant compartment.
It is thus possible to calculate the heat exchange amount Δ Q that heat pump air conditioner needs to adjust;Work as QneedWhen > 0, automobile member cabin needs to adopt
Warm up, at this time Δ Q=| Qneed|-|Qair|;
Work as QneedWhen < 0, automobile member cabin needs to freeze, at this time Δ Q=| Qneed|-|Qair,c|;
Wherein, QneedThe heat exchange amount of crew module is provided to for heat pump air conditioning system;Qair,cThe heat exchange of condenser air side
Amount.
Heat pump air conditioner control system needs to adjust electronic expansion valve opening, control cooling fan rotation speed dc motor pulse
Circulation duty ratio (abbreviation duty ratio below), compressor rotary speed make △ Q=0, and detailed process is as follows for adjusting.
Clustering, vehicle driving state and outdoor environment dynamic change are carried out to heat pump air conditioning system and crew module's state
Present over time and space it is non-linear, uncertain it is big, dynamic change is obvious, lead to heat pump air conditioning system and crew module's state
The range of variation is big and change rate is uncertain.In view of the above-mentioned problems, finding out its regularity using clustering methodology.Using occupant
Total heat exchange amount Q in cabintotal, thermic load Q in crew moduleheat, need to be supplied to the heat exchange amount of crew module by heat pump air conditioning system
Qneed, condenser air side heat exchange amount Qair,c, evaporator air side heat exchange amount Qair, heat pump air conditioning system need the heat exchange that adjusts
It measures △ Q to input as feature, due to having certain degree of overlapping between state each in characteristic item, characteristic item is used into principal component analysis
Method (hereinafter referred to as PCA) carries out dimensionality reduction first, as shown in fig. 6, process is as follows:
During dimensionality reduction mapping, there are mapping errors.Before carrying out dimensionality reduction to high dimensional feature, feature need to be done to it
It normalizes (feature normalization).This normalization operation includes:
(1) all features are allowed to possess similar scale, not so a feature is especially small, and a feature especially will affect greatly
The effect (feature scaling) of dimensionality reduction.
(2) zero-mean normalization (zero mean normalization).
Calculate the covariance matrix of sample characteristics, the characteristic value of covariance matrix and feature vector, dimensionality reduction calculates, according to tribute
It offers rate and carries out screening, reconstruct (reconstruction) (according to data reconstruction original data after dimensionality reduction), data convert.
Wherein three features are filtered out according to contribution degree to be clustered, and respectively need to be supplied to by heat pump air conditioning system
The heat exchange amount Q of crew moduleneed, evaporator air side heat exchange amount Qair, heat pump air conditioning system need the heat exchange amount △ Q that adjusts to carry out
Clustering.Here fuzzy C-mean algorithm (Fuzzy C-means) algorithm (hereinafter referred to as FCM) is used.Such as figure, measured according to experiment
The value of different lower three features of operating condition, totally 150 groups, each sample j belongs to the subordinating degree function μ of certain one kind iijIterative formula such as
Under:
Wherein, c is cluster centre number, ciIterative formula example it is as follows:
By the adjustment repeatedly of cluster centre number, effect is best when c=4, therefore by crew module's state and heat pump air conditioning system
State is divided into 4 classes and is controlled;It is meant to ensure that comfort level is best, energy consumption is optimal.
As shown in fig. 7, judgement is provided by heat pump air conditioning system when crew module and heat pump air conditioner state belong to the first kind
To the heat exchange amount Q of crew moduleneed。
If Qneed> 0, cockpit needs heating.At this point, vehicle external heat exchanger is as evaporator, interior heat exchanger is as condensation
Device, detailed process: compressor 230- four-way valve 150- car heat exchanger 420- the first electric expansion valve the first check valve of 510-
520- third check valve 560- vehicle external heat exchanger 130- four-way valve 150- gas-liquid separator 330- compressor 230.Judge heat pump sky
Adjusting system needs whether the heat exchange amount △ Q adjusted is equal to 0, if being equal to 0, current heat pump air conditioner state is just met under this state
Crew module's temperature requirement, so there is no need to adjust;If being not equal to 0, as △ Q > 0, then the increasing of 510 aperture of the first electric expansion valve is adjusted
Greatly, until △ Q=0;As △ Q < 0, adjusts 510 aperture of the first electric expansion valve and reduce, until Δ Q=0.
If Qneed< 0, crew module need to freeze.At this point, vehicle external heat exchanger is as condenser, interior heat exchanger is as evaporation
Device, detailed process are as follows: compressor 230- four-way valve 150- vehicle external heat exchanger 130- the second electric expansion valve 630- check valve 570-
Check valve 550- car heat exchanger 420- four-way valve 150- gas-liquid separator 330- compressor 230.Judge that heat pump air conditioning system needs
Whether the heat exchange amount Δ Q to be adjusted is equal to 0, if being equal to 0, current heat pump air conditioner state is just met for crew module's temperature under this state
Degree requires, and so there is no need to adjust;If being not equal to 0, as Δ Q > 0, then the increase of 630 aperture of the second electric expansion valve is adjusted, until Δ
Q=0;As Δ Q < 0, adjusts 630 aperture of the second electric expansion valve and reduce, until Δ Q=0.
When crew module and heat pump air conditioner state belong to the second class, judgement is supplied to crew module's by heat pump air conditioning system
Heat exchange amount Qneed。
If Qneed> 0, crew module need heating, and specific cyclic process is identical as the first kind.Judge that heat pump air conditioning system needs
Whether the heat exchange amount Δ Q to be adjusted is equal to 0, if being equal to 0, current heat pump air conditioner state is just met for crew module's temperature under this state
Degree requires, and so there is no need to adjust;As Δ Q > 0, while 510 aperture of the first electric expansion valve is increased, it need to consider that evaporator goes out
Temperature of making a slip of the tongue Δ TeWhether reach 4.5 DEG C, once reaching 4.5 DEG C, stops the aperture for increasing by the first electric expansion valve 510, pass through
Increase the duty ratio of the outer cooling fan of vehicle and the duty ratio of interior cooling fan, finds optimal energy consumption solution, be gradually adjusted to Δ Q=
0;As Δ Q < 0, while the first electric expansion valve 510 is reduced, evaporator outlet degree of superheat Δ T need to be consideredeWhether reach
5.5 DEG C, once reaching 5.5 DEG C, stop the aperture for reducing the first electric expansion valve 510, by reducing cooling fan duty outside vehicle
Than the duty ratio with interior cooling fan, optimal energy consumption solution is found, Δ Q=0 is gradually adjusted to.
If Qneed< 0, crew module need to freeze, and specific cyclic process is identical as the first kind.Judge that heat pump air conditioning system needs
Whether the heat exchange amount Δ Q to be adjusted is equal to 0, if being equal to 0, current heat pump air conditioner state is just met for crew module's temperature under this state
Degree requires, and so there is no need to adjust;As Δ Q > 0, while 630 aperture of the second electric expansion valve is increased, it need to consider that evaporator goes out
Temperature of making a slip of the tongue Δ TeWhether reach 4.5 DEG C, once reaching 4.5 DEG C, stops the aperture for increasing by the second electric expansion valve 630, pass through
The duty ratio for increasing vehicle outer cooling fan duty ratio and interior cooling fan, finds optimal energy consumption solution, is gradually adjusted to △ Q=0;
As △ Q < 0, while 630 aperture of the second electric expansion valve is reduced, evaporator outlet degree of superheat Δ T need to be consideredeWhether reach
To 5.5 DEG C, once reaching 5.5 DEG C, stop the aperture for reducing the second electric expansion valve 630, is accounted for by reducing cooling fan outside vehicle
Sky finds optimal energy consumption solution, is gradually adjusted to △ Q=0 than the duty ratio with interior cooling fan.
Belong to the second class for crew module and heat pump air conditioning system state to calculate optimal energy consumption solution detailed process is as follows: set
The voltage duty cycle for inputing to the dc motor of the outer cooling fan of control vehicle is x, crest voltage U=12V, records corresponding electricity
Flow Ix, wherein IxIt is related with x, by accordingly being tested to cooling fan outside vehicle, sum up corresponding formula:
Ix=12k1·x;
Obtain k1Value, k1For the inverse of the resistance of cooling fan outside vehicle.
If inputing to and controlling the voltage duty cycle of the dc motor of interior cooling fan is y, crest voltage U=12V,
Record corresponding current Iy, wherein IyIt is related with y, by accordingly being tested to interior cooling fan, sum up corresponding formula:
Iy=12k2·y;
Obtain k2Value, k2For the inverse of the resistance of interior cooling fan.
The general power of the outer cooling fan of vehicle and a certain moment consumption of interior cooling fan is obtained as a result, and formula is as follows:
Wfan=U (xIx+y·Iy(the k of)=121·x2+k2·y2);
Seek min (Wfan).Wherein, 0≤x≤x1(vehicle outer cooling fan meets direct current drive when △ Q is required when working independently
Machine duty ratio).0≤y≤y1(interior cooling fan meets dc motor duty ratio when △ Q is required when working independently), first
Given x=x1, y=0, calculating Wfan, hereafter x successively decreases by 5%, and y progressively increases by 5%, until y=y1.Export WfanMinimum value is corresponding
Duty ratio x and y.
When crew module and heat pump air conditioner state belong to third class, judgement is supplied to crew module's by heat pump air conditioning system
Heat exchange amount Qneed.If Qneed> 0, cockpit need heating, and specific cyclic process is identical as the first and second class.Judge heat pump air conditioner system
System needs whether the heat exchange amount △ Q adjusted is equal to 0, if being equal to 0, current heat pump air conditioner state is just met for occupant under this state
Cabin temperature requirement, so there is no need to adjust;As △ Q > 0, since △ Q is larger at this time, electronic expansion valve opening is exceeded and has adjusted model
It encloses, therefore 510 aperture of the first electric expansion valve is directly increased into evaporator outlet degree of superheat Δ TeReach 4.5 DEG C;It adjusts simultaneously
Duty ratio, the duty ratio and compressor rotary speed of interior cooling fan of the outer cooling fan of vehicle, it is cold until △ Q=0, and outside vehicle
But the general power of fan, interior cooling fan and compressor is minimum;As △ Q < 0, since △ Q is larger at this time, electronics is exceeded
Expansion valve opening adjustable range, therefore 510 aperture of the first electric expansion valve is directly decreased to evaporator outlet degree of superheat Δ TeIt reaches
To 5.5 DEG C, while the duty ratio of the outer cooling fan of vehicle, the duty ratio and compressor rotary speed of interior cooling fan are adjusted, until
△ Q=0, and the general power of the outer cooling fan of vehicle, interior cooling fan and compressor is minimum;
If Qneed< 0, crew module need to freeze, and specific cyclic process is identical as the first and second class.Judge heat pump air conditioning system
Whether the heat exchange amount △ Q for needing to adjust is equal to 0, if being equal to 0, current heat pump air conditioner state is just met for crew module under this state
Temperature requirement, so there is no need to adjust;As △ Q > 0, since △ Q is larger at this time, exceed expansion valve opening adjustable range, thus it is straight
It connects and 630 aperture of the second electric expansion valve is increased into evaporator outlet degree of superheat Δ TeReach 4.5 DEG C, while adjusting cooling outside vehicle
The duty ratio and compressor rotary speed of the duty ratio of fan, interior cooling fan, until △ Q=0, and the outer cooling fan of vehicle,
Interior cooling fan and the general power of compressor are minimum;As △ Q < 0, since △ Q is larger at this time, electric expansion valve is exceeded
Aperture regulation range, therefore 630 aperture of the second electric expansion valve is directly decreased to evaporator outlet degree of superheat Δ TeReach 5.5
DEG C, while the duty ratio of the outer cooling fan of vehicle, the duty ratio and compressor rotary speed of interior cooling fan are adjusted, until △ Q=
0, and the general power of the outer cooling fan of vehicle, interior cooling fan and compressor is minimum.
For third class situation, the duty of the duty ratio, interior cooling fan that adjust the outer cooling fan of vehicle when compressor
Revolving speed, so that the general power of the outer cooling fan of vehicle, interior cooling fan and compressor is reached the smallest process as follows.
Optimal energy consumption solution is determined using simulated annealing, since separately adjustable cooling fan rotation speed is unable to satisfy △ Q's
It needs, therefore cooling fan need to be adjusted jointly with compressor, solve the formula of optimal energy consumption are as follows:
Wtotal=A1(Wfan1+Wcompressor,1)+A2(Wfan2+Wcompressor,2)+A3Wcompressor,3;
In formula, (Wfan1+WCompressor, 1) it is that the outer cooling fan of vehicle is adjusted jointly with compressor, when reaching △ Q=0
The power of consumption, (Wfan2+WCompressor, 2) it is that interior cooling fan is adjusted jointly with compressor, disappear when reaching △ Q=0
The power of consumption, Wfan1For the maximum power of cooling fan outside vehicle, Wfan2For the maximum power of interior cooling fan;WCompressor, 3For
The separately adjustable power reached when △ Q=0 is consumed of compressor;Using simulated annealing, A is adjusted1、A2、A3Obtain optimal energy consumption
Solution, to obtain WtotalThe duty ratio of the outer cooling fan of the corresponding vehicle of minimum value, the duty of interior cooling fan when compresses
Machine revolving speed.Simulated annealing detailed process is as shown in Figure 8.
When crew module and heat pump air conditioner state belong to four classes, judgement is supplied to crew module's by heat pump air conditioning system
Heat exchange amount Qneed。
If Qneed> 0, cockpit need heating, and specific cyclic process is identical as the first, second and third class.Judge heat pump air conditioner
System needs whether the heat exchange amount △ Q that adjusts is equal to 0, if being equal to 0, current heat pump air conditioner state is just met for multiplying under this state
Member cabin temperature requirement, so there is no need to adjust;As △ Q > 0, since △ Q is very big at this time, directly the first electric expansion valve 510 is opened
Degree increases to evaporator outlet degree of superheat Δ TeReach 4.5 DEG C and the outer cooling fan motor duty ratio of control vehicle and car are cooling
Fan motor duty ratio increases to maximum, adjusts compressor rotary speed later and makes △ Q=0;As △ Q < 0, due to △ Q at this time
Greatly, 510 aperture of the first electric expansion valve is directly decreased to evaporator outlet degree of superheat Δ TeReach outside 5.5 DEG C and control vehicle
Cooling fan motor duty ratio and interior cooling fan motor duty ratio minimize, and adjust compressor rotary speed later and make
△ Q=0.
If Qneed< 0, crew module need to freeze, and specific cyclic process is identical as the first, second and third class.Judge heat pump air conditioner
System needs whether the heat exchange amount △ Q that adjusts is equal to 0, if being equal to 0, current heat pump air conditioner state is just met for multiplying under this state
Member cabin temperature requirement, so there is no need to adjust.As △ Q > 0, since △ Q is very big at this time, directly by the aperture of the second expansion valve 630
Increase to evaporator outlet degree of superheat Δ TeReach 4.5 DEG C and the outer cooling fan motor duty ratio of control vehicle and control are interior cold
But fan motor duty ratio increases to maximum, adjusts compressor rotary speed later and makes △ Q=0.As △ Q < 0, due to △ at this time
Q is very big, and the aperture of the second expansion valve 630 is directly decreased to evaporator outlet degree of superheat Δ TeReach outside 5.5 DEG C and control vehicle
Cooling fan motor duty ratio and the interior cooling fan motor duty ratio of control minimize, and adjust compressor rotary speed later
So that △ Q=0.
As shown in figure 9, controlling using radial base neural net battery flat state, remain battery flat temperature
Within the scope of 25 ± 5 DEG C.7th temperature sensor 720 measures temperature before battery cooling line exchanges heat;8th temperature sensor 730
Temperature after battery cooling line exchanges heat is measured, battery cooling line heat exchange front and back temperature value T is obtainedb1、Tb2.As illustrated, pass through
Experiment obtains 150 groups of experimental datas as sample data, including automobile driving speed V, running car acceleration a, air-conditioning system
General power Wtotal, battery flat temperature Tb, battery cooling line exchange heat before temperature value Tb1, battery cooling line heat exchange after temperature value
Tb2And 750 aperture of battery flat electric expansion valve.Randomly select cluster centre, the first six (running car speed in input sample data
Spend V, running car acceleration a, air-conditioning system general power Wtotal, battery flat temperature Tb, battery cooling line exchange heat before temperature value
Tb1, battery cooling line heat exchange after temperature value Tb2) as input, hidden layer node number is 6, last (battery flat electricity
Sub- 750 aperture of expansion valve) it is used as desired output, cluster numbers are 3, calculate the Euclidean distance of sample and cluster centre, sample
Which cluster minimum is just classified as which class in notebook data, updates cluster centre, and gradually adjustment is so that 30 aperture of battery flat valve exported
With corresponding desired output in error 1 × 10-7It is interior, when cluster centre no longer adjusts, convergence.After selected cluster centre, use
Gaussian function calculates standard deviation.Using LMS algorithm, learn weight, so far radial base neural net training is completed.Controller can
To receive the automobile driving speed V, running car acceleration a, air-conditioning system general power W of real-time monitoringtotal, battery flat temperature
Tb, battery cooling line exchange heat before temperature value Tb1, battery cooling line heat exchange after temperature value Tb2;By radial base neural net
Defeated battery flat electric expansion valve 750 after habit, to realize the adjusting to battery flat temperature.
Wherein, the affiliated cluster centre of sample data is calculated:
i(Xk)=argmin | | Xk-ti(n)||
XkFor training sample, tiIt (n) is cluster centre.
Update cluster centre:
η is Learning Step, only updates a cluster centre every time, other are not updated.
Standard deviation formula:
N=4, dmaxFor the maximum distance between selected cluster centre.
Although the embodiments of the present invention have been disclosed as above, but its is not only in the description and the implementation listed
With it can be fully applied to various fields suitable for the present invention, for those skilled in the art, can be easily
Realize other modification, therefore without departing from the general concept defined in the claims and the equivalent scope, the present invention is simultaneously unlimited
In specific details and legend shown and described herein.
Claims (10)
1. a kind of control method of automobile heat pump air conditioner, which comprises the steps of:
Step 1: by evaporator outlet temperature Teo, evaporator exit pressure Peo, evaporator temperature Tei, evaporator pressure
Power Pei, evaporator inlet refrigerant flow q and vaporizer side air themperature TairThe first BP neural network is inputted after normalization,
Obtain evaporator outlet degree of superheat Δ Te, evaporator heat exchange amount QeAnd evaporator air side heat exchange amount Qair;
Meanwhile by condensator outlet temperature Tco, condensator outlet pressure Pco, condenser inlet temperature Tci, condenser inlet pressure
Pci, condenser inlet refrigerant flow qcAnd the air themperature T of condenserair,cThe second BP neural network is inputted after normalization,
Obtain condensator outlet degree of supercooling Δ Tc, condenser heat exchange amount QcAnd condenser air side heat exchange amount Qair,c;
Step 2: calculating the heat exchange amount Δ Q that heat pump air conditioner needs to adjust;
Δ Q=| Qneed|-|Qair| or Δ Q=| Qneed|-|Qair,c|;
Wherein, QneedThe heat exchange amount of crew module is provided to for heat pump air conditioning system;
Step 3: being provided to the heat exchange amount Q of crew module to heat pump air conditioning systemneed, evaporator air side heat exchange amount QairAnd
It is cooling outside by the aperture to electric expansion valve, vehicle after the heat exchange amount △ Q that heat pump air conditioning system needs to adjust carries out clustering
The revolving speed of the duty when compressor of the duty ratio of fan, interior cooling fan is adjusted, and makes △ Q=0, and heat pump air conditioner
The general power of system is minimum.
2. the control method of automobile heat pump air conditioner according to claim 1, which is characterized in that in said step 1, the
The hiding node layer of one BP neural network is 8, and the hidden layer number of nodes of the second BP neural network is 7.
3. the control method of automobile heat pump air conditioner according to claim 2, which is characterized in that in the step 2, heat
Pump air conditioner system is provided to the heat exchange amount Q of crew moduleneedAre as follows:
Qneed=Qtotal-Qheat;
Wherein, QtotalFor total heat exchange amount inside vehicle occupant compartment, QheatFor the total heat duties for entering vehicle occupant compartment.
4. the control method of automobile heat pump air conditioner according to claim 3, which is characterized in that total inside vehicle occupant compartment
Heat exchange amount QtotalAre as follows:
Qtotal=cp,air·ρair·V·(Tsetting-Tinside);
Wherein, TsettingFor driver's set temperature;cp,airFor air specific heat capacity;ρairFor atmospheric density;V is crew module
Volume.
5. the control method of automobile heat pump air conditioner according to claim 3 or 4, which is characterized in that described to multiply into automobile
The total heat duties Q in member storehouseheatAre as follows:
Qheat=Qg+Qroof+Qside+Qbottom+Qperson+Qluggage+Qengine+Qskylight+Qwind;
Wherein, QgFor glass thermic load;QroofFor roof thermic load;QsideFor side wall thermic load;QbottomFor vehicle bottom thermic load;
QpersonFor occupant's thermic load;QluggageFor luggage compartment thermic load;QengmeFor piggyback pod thermic load;QskylightFor skylight heat
Load;QwindFor fresh air and thermic load of leaking out.
6. the control method of automobile heat pump air conditioner according to claim 5, which is characterized in that in the step 3, lead to
It crosses clustering four class situations is divided into heat pump air conditioning system and be adjusted, comprising:
The first kind increases electronic expansion valve opening as Δ Q > 0, until Δ Q=0;As Δ Q < 0, by electric expansion valve
Aperture reduces, until Δ Q=0;
Second class increases electronic expansion valve opening as △ Q > 0, as evaporator outlet degree of superheat Δ TeReach 4.5 DEG C, stops
The aperture for only increasing electric expansion valve adjusts the duty ratio of the outer cooling fan of vehicle and the duty ratio of interior cooling fan, until △ Q
=0, and the outer cooling fan of vehicle and interior cooling fan are optimal duty ratio;
As Δ Q < 0, electronic expansion valve opening is reduced, as evaporator outlet degree of superheat Δ TeReach 5.5 DEG C, stops reducing electricity
The aperture of sub- expansion valve adjusts the duty ratio of the outer cooling fan of vehicle and the duty ratio of interior cooling fan, until △ Q=0, and
The outer cooling fan of vehicle and interior cooling fan are optimal duty ratio;
The aperture of electric expansion valve is increased to evaporator outlet degree of superheat Δ T as Δ Q > 0 by third classeReach 4.5 DEG C;Together
When adjust the duty when compressor rotary speed of the duty ratio of the outer cooling fan of vehicle, interior cooling fan, until Δ Q=0, and vehicle
The general power of outer cooling fan, interior cooling fan and compressor is minimum;
As Δ Q < 0, the aperture of electric expansion valve is decreased to evaporator outlet degree of superheat Δ TeReach 5.5 DEG C;It adjusts simultaneously
The duty when compressor rotary speed of the duty ratio of the outer cooling fan of vehicle, interior cooling fan, it is cooling until Δ Q=0, and outside vehicle
The general power of fan, interior cooling fan and compressor is minimum;
The aperture of electric expansion valve is increased to evaporator outlet degree of superheat Δ T as Δ Q > 0 by the 4th classeReach 4.5 DEG C simultaneously
And the duty ratio of the duty of the outer cooling fan of vehicle when interior cooling fan is adjusted to maximum, while adjusting compressor rotary speed, directly
To Δ Q=0;
As △ Q < 0, expansion valve is decreased to evaporator outlet degree of superheat Δ TeReach 5.5 DEG C and adjusts the outer cooling fan of vehicle
Duty when interior cooling fan duty ratio to minimum, while compressor rotary speed is adjusted, until △ Q=0.
7. the control method of automobile heat pump air conditioner according to claim 6, which is characterized in that in second class, really
Determine the outer cooling fan of vehicle and interior cooling fan be optimal the objective function of duty ratio are as follows:
Wfan=U (k1·x2+k2·y2)
In formula, U is crest voltage, and x is the duty ratio of the outer cooling fan of vehicle, and y is the duty ratio of interior cooling fan, k1Outside for vehicle
The inverse of the resistance of cooling fan, k2For the inverse of the resistance of interior cooling fan;
Work as WfanValue minimum when, corresponding x value is the optimal duty ratio of the outer cooling fan of vehicle, and corresponding y value is the outer cooling wind of vehicle
The optimal duty ratio of fan.
8. the control method of automobile heat pump air conditioner according to claim 6, which is characterized in that in the third class, vehicle
The general power of outer cooling fan, interior cooling fan and compressor are as follows:
Wtotal=A1(Wfan1+Wcompressor,1)+A2(Wfan2+Wcompressor,2)+A3Wcompressor,3;
In formula, (Wfan1+WCompressor, 1) it is that the outer cooling fan of vehicle is adjusted jointly with compressor, it is consumed when reaching Δ Q=0
Power, (Wfan2+WCompressor, 2) it is that interior cooling fan is adjusted jointly with compressor, the function consumed when reaching △ Q=0
Rate, Wfan1For the maximum power of cooling fan outside vehicle, Wfan2For the maximum power of interior cooling fan;WCompressor, 3For compressor
The separately adjustable power reached when △ Q=0 is consumed;
Adjust A1、A2And A3Make WtotalReach minimum value, obtains WtotalThe outer cooling fan of the corresponding vehicle of minimum value duty ratio,
The duty of interior cooling fan when compressor rotary speed.
9. the control method of automobile heat pump air conditioner according to claim 1 or 6, which is characterized in that the electric expansion valve
Including the first electric expansion valve and the second electric expansion valve;
When crew module needs heating, the first electric expansion valve is adjusted;
When crew module needs to freeze, the second electric expansion valve is adjusted.
10. the control method of automobile heat pump air conditioner according to claim 1, which is characterized in that further include: by running car
Speed V, running car acceleration a, air-conditioning system general power Wtotal, battery flat temperature Tb, battery cooling line exchange heat before temperature
Value Tb1And temperature value T after the heat exchange of battery cooling lineb2Radial base neural net is inputted, opening for battery flat electric expansion valve is obtained
Degree.
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Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2902472B2 (en) * | 1990-10-08 | 1999-06-07 | 株式会社豊田中央研究所 | Air conditioning control device |
JPH11268513A (en) * | 1998-01-19 | 1999-10-05 | Zexel:Kk | Air conditioner for vehicle and control method thereof |
CN101603751A (en) * | 2009-07-15 | 2009-12-16 | 北京科技大学 | A kind of frequency conversion energy-saving control method of refrigeration system |
CN103743174A (en) * | 2013-12-26 | 2014-04-23 | 柳州职业技术学院 | Vehicle air conditioner control system method based on neural network |
CN107747832A (en) * | 2017-11-30 | 2018-03-02 | 吉林大学 | A kind of electric automobile heat-pump air-conditioning system and its control method |
CN107757299A (en) * | 2017-11-20 | 2018-03-06 | 吉林大学 | A kind of air conditioning for automobiles and its control method using three layers of bushing type Intermediate Heat Exchanger |
CN107826027A (en) * | 2017-09-21 | 2018-03-23 | 山东大学 | Refrigerator car temprature control method and system based on big data analysis |
-
2018
- 2018-08-22 CN CN201810957945.0A patent/CN109050200B/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2902472B2 (en) * | 1990-10-08 | 1999-06-07 | 株式会社豊田中央研究所 | Air conditioning control device |
JPH11268513A (en) * | 1998-01-19 | 1999-10-05 | Zexel:Kk | Air conditioner for vehicle and control method thereof |
CN101603751A (en) * | 2009-07-15 | 2009-12-16 | 北京科技大学 | A kind of frequency conversion energy-saving control method of refrigeration system |
CN103743174A (en) * | 2013-12-26 | 2014-04-23 | 柳州职业技术学院 | Vehicle air conditioner control system method based on neural network |
CN107826027A (en) * | 2017-09-21 | 2018-03-23 | 山东大学 | Refrigerator car temprature control method and system based on big data analysis |
CN107757299A (en) * | 2017-11-20 | 2018-03-06 | 吉林大学 | A kind of air conditioning for automobiles and its control method using three layers of bushing type Intermediate Heat Exchanger |
CN107747832A (en) * | 2017-11-30 | 2018-03-02 | 吉林大学 | A kind of electric automobile heat-pump air-conditioning system and its control method |
Non-Patent Citations (1)
Title |
---|
赵永标: "基于人工神经网络的制冷空调***的仿真研究", 《中国优秀博硕士学位论文全文数据库(硕士)信息科技辑》 * |
Cited By (24)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113423596A (en) * | 2019-02-11 | 2021-09-21 | 株式会社电装 | Refrigeration cycle device |
CN113423596B (en) * | 2019-02-11 | 2024-01-05 | 株式会社电装 | Refrigeration cycle device |
CN113597506B (en) * | 2019-03-25 | 2023-10-24 | 丰田自动车株式会社 | Thermal control device and thermal control method |
CN113597506A (en) * | 2019-03-25 | 2021-11-02 | 丰田自动车株式会社 | Thermal control device and thermal control method |
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