CN109808512A - Hybrid power fuel cell car simulation control method and system - Google Patents
Hybrid power fuel cell car simulation control method and system Download PDFInfo
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- CN109808512A CN109808512A CN201910015834.2A CN201910015834A CN109808512A CN 109808512 A CN109808512 A CN 109808512A CN 201910015834 A CN201910015834 A CN 201910015834A CN 109808512 A CN109808512 A CN 109808512A
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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
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
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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
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/40—Application of hydrogen technology to transportation, e.g. using fuel cells
Abstract
The invention discloses a kind of hybrid power fuel cell car simulation control method and systems, by building fuel cell and super capacitor model, DC/DC system controller and whole vehicle model, using controller in kind, is combined with this and build hybrid power fuel cell car analogue system.Flow indicator calculates method is recognized using power demand in terms of control method, quickly obtain power demand, the output power of fuel cell and super capacitor is obtained by the fuzzy control to demand power again, then fuel cell is controlled using fuzzy control, to super capacitor using the PI for introducing feedback, to reach the control to fuel cell and super capacitor output power, being finally introducing system output negative-feedback makes system change response to driving information.The present invention controls fuel cell power generation power using fuzzy control strategy, reduces the complexity of fuel cell system control and has certain intelligence；System output is inputted as negative-feedback, so that system control precision is high, stability is good.
Description
Technical field
The present invention relates to hybrid power fuel cell car technical field of system control, fire in particular to a kind of hybrid power
Expect battery car simulation control method and system.
Background technique
With the continuous development of automobile, industrialization has also obtained constantly being promoted, and global every country and area are right
The demand of automobile is increasing, and the popularity and technical level of automobile have become one country modernization of measurement
Horizontal important symbol.Along with the development of automobile industry, increasingly increase of the people to oil demand amount, exhaust gas emission problem is got over
Come more serious, causes serious air pollution, daily life and life and health are caused to seriously endanger, tapped a new source of energy
Vehicle it is imperative.
Pure electric automobile have many advantages, such as cleaning, it is high-efficient, very important position is occupied in new-energy automobile, it
Key technology is energy-storage battery, and energy-storage battery converts electrical energy into kinetic energy to meet the driving performance of automobile, and discharge amount of exhaust gas is
Zero, air pollution is not caused, therefore the pure electric automobile of developing low-cost, continual mileage length will become electric car research
Ultimate aim, but the initial cost of pure electric automobile is high at present, battery charge time is long, an inconvenient to use, charging row
Sail bottleneck of the problems such as mileage is limited, battery is short, infrastructure construction is incomplete as Development of Electric Vehicles.
Fuel cell car can with the above-mentioned pure electric automobile of effective solution there are the problem of.Various countries' automobile industry is also big
Power develops fuel cell car, and European Union is in approval fuel cells in 2009 and Hydrogen Technology project action plan, planned investment 4.7
Hundred million Euros of subsidy fuel cell cars and infrastructure technique research and development.German BMW and Toyota Motor company were in 2013 1
Formal externally declaration endorsed about " joint development fuel cell system ", " joint development sports model ", " grind jointly the moon 24
Study carefully exploitation Lightweight Technology " formal cooperation agreement, Toyota Motor is drafted in release business-purpose fuel cell automobile in 2015.
China early has appreciated that the scarcity of petroleum resources as an energy consumption big country, and developing new-energy automobile is to realize
One of the important decision of the American-European-Japanese equal automobile superpowers of Domestic Automotive Industry technology catch-up.For grinding for fuel cell car technology
Study carefully, developed countries are also closely followed in China in the nineties in last century, and Hydrogen Fuel-cell Vehicles were once causing attention in the industry.
Hybrid power fuel cell car joined one to two other power sources on the basis of fuel cell car,
It assists fuel cell to increase fuel cell service life collectively as power output with this, is Future New Energy Source development of automobile
A big main flow direction, it is necessary for integrating out a kind of control method of hybrid power fuel cell car in this context
's.
Summary of the invention
The purpose of the present invention is to solve deficiencies existing for above-mentioned background technique, and a kind of hybrid power fuel proposed
Battery car simulation control method and system accurately simulate the dynamic mistake that fuel cell and super capacitor change over time
Journey is used fuzzy control to fuel cell, is controlled using the PI for introducing feedback super capacitor, to reach to fuel cell and surpass
The control of grade capacitor output power, being finally introducing system output negative-feedback keeps system fast to driving information variation response, and has
Good stability.
To achieve the above object, the hybrid power fuel cell car simulation control method designed by the present invention, the side
Method includes the following steps:
1) to the driving information S of inputiIt is recognized, with current driving information SkBe compared, find out speed difference △ v,
Acceleration difference △ a, ramp difference △ l and environmental factor, are calculated demand power P'k+1；As the driving information S of inputiWith
Current driving information SkWhen equal, control terminates；
2) the output accounting that fuel cell and super capacitor are calculated using power distribution fuzzy control method, obtains fuel
The power allocation factor K of battery and super capacitora；
3) according to power demand P'k+1With power allocation factor KaBe calculated fuel cell need export power P 'fu、
The power P that super capacitor needs to export 'soc；The power P for needing to export according to obtained fuel cell 'fuAnd current fuel cell
Output power PfuThe control program that fuzzy control obtains fuel cell mode is done, power needed for exporting fuel cell mode；According to
The power P for needing to export according to super capacitor 'socIt determines the charging and recharging model of super capacitor, introduces current super capacitor output power
PsocNegative-feedback carries out PI control to it, power needed for exporting the charging and recharging model of super capacitor；
4) control program of DC/AC/DC model fuel cell model needs defeated to whole vehicle model output fuel cell
Power P out 'fu, two-way DC/DC model to whole vehicle model output super capacitor need export power P 'soc；
5) by fuel cell need export power P 'fu, super capacitor need export power P 'socSuperposition obtains power
Demand P'k+1, the updated current driving information S of whole vehicle model acquisitionk+1, return step 1).
Preferably, in the step 1) by speed difference △ v, acceleration difference △ a, ramp difference △ l and environment because
Element calculates demand power P'k+1Process are as follows: demand power P'k+1Equal to operation Damping Power, motor drive power, transmission function
The summation of rate loss and electronic instrument power loss, operation Damping Power includes damping in roll power, ramp Damping Power, sky
Gas Damping Power and acceleration Damping Power；Power loss during transmission device and motor drive passes through power factor ηtIt retouches
It states, demand power P'k+1Calculation formula are as follows:
ηtIt is coefficient of rolling resistance, C for the power transfer factor, fDFor air resistance coefficient, A be front face area, δ is vehicle rotary
Mass conversion coefficient, m are complete vehicle quality, and g is acceleration of gravity, v is automobile driving speed, l is ramp angle, a is that traveling adds
Speed.
Preferably, fuel cell and super capacitor are calculated using power distribution fuzzy control method in the step 2)
Export the process of accounting are as follows:
21) to demand power P'k+1, current fuel cell output power PfuAnd current super capacitor output power PsocDo mould
Gelatinization calculates and is converted into demand power fuzzy parameter Kk+1, fuel cell output power fuzzy parameter KfuAnd super capacitor output work
Rate fuzzy parameter；
22) with demand power fuzzy parameter Kk+1, fuel cell output power fuzzy parameter KfuAnd super capacitor output power
Fuzzy parameter KsocAs the input of fuzzy reasoning, fuzzy reasoning is carried out according to fuzzy rule 1；
23) the accounting factor K a of fuel cell and super capacitor output power is obtained to fuzzy deduction result defuzzification.
The power P that the fuel cell that preferably, foundation obtains in the step 3) needs to export 'fuAnd current fuel cell
Output power PfuDo the detailed process that fuzzy control obtains the control program of fuel cell mode are as follows:
The power P for needing to export with calculated fuel cell 'fuAnd current fuel cell output power PfuAs fuzzy
The input of control, according to fuzzy rule 2, defuzzification obtains the control method of fuel cell mode after fuzzy deduce, and passes through
Controller controls fuel cell mode, and fuzzy rule 2 sets as follows:
(1) fuel cell demand power P'fu>PfuWhen, the auxiliary systems parameter value such as Hydrogen Vapor Pressure, air pressure and temperature
It increases；
(2) fuel cell demand power P'fu≈PfuWhen, the auxiliary systems parameter value such as Hydrogen Vapor Pressure, air pressure and temperature
It is constant；
(3) fuel cell demand power P'fu< PfuWhen, the auxiliary systems parameter value such as Hydrogen Vapor Pressure, air pressure and temperature
Reduce.
The power P that preferably, foundation super capacitor needs to export in the step 3) 'socDetermine the charge and discharge of super capacitor
Mode introduces current super capacitor output power PsocThe process for carrying out PI control is exported to super capacitor model as negative-feedback
If are as follows: P'soc>=0, then super capacitor model is discharge mode, and it is boosting that DC/DC controller, which controls two-way DC/DC model, at this time
Mode；Conversely, if P'soc< 0, super capacitor model are discharge mode, and the two-way DC/DC model of DC/DC controller control at this time is
Decompression mode.
The present invention also proposes a kind of hybrid power fuel cell car simulation control subsystem, is characterized in that, described
System includes fuel cell mode, super capacitor model, DC/AC/DC and two-way DC/DC model and whole vehicle model, fuel cell
System controller, DC/DC system controller and entire car controller, power demand recognize computing module, power distribution fuzzy control
Module, fuel cell fuzzy control model and super capacitor PI control module and DC/DC convert control module and for inputs
Driving information SiWith the man-machine interface of display device status information；
The fuel cell mode and super capacitor model are used for the dynamic process that object simulating changes over time, as whole
The power source of vehicle model；The DC/AC/DC and two-way DC/DC model for power P according to demand 'k+1With the function of super capacitor
Rate distribution factor KaFuel cell mode output power and super capacitor model output power are transformed to whole vehicle model institute respectively
The input power size needed；The fuel cell system controller controls fuel for acquiring fuel cell mode operating parameter
Component in battery system；The DC/DC system controller is used to acquire the voltage swing of DC/DC conversion process front and back end, control
Each switching tube opening and turning off in DC/DC transformation model processed；The entire car controller is used to acquire gear, the speed of whole vehicle model
Degree, acceleration and pedal opening signal, control relay, pedal opening and the driving pattern information of whole vehicle model；The power
Demand recognizes computing module and is used for according to driving information SiIt calculates and exports demand power P'k+1；The power distribution fuzzy control
Module is used to obtain the power allocation factor K of fuel cell and super capacitor using power distribution fuzzy control methoda；The combustion
Material battery fuzzy control model and super capacitor PI control module are respectively used to the control program of output fuel cell mode and surpass
Grade capacitor PI control program；DC/DC converts the control program and super capacitor PI that control module is used for fuel cell model
Control program exports demand power P' to DC/AC/DC and two-way DC/DC modelk+1。
Further, the fuel cell controller includes for acquiring pressure, temperature, switching value and the object of voltage and current
Reason amount acquisition unit and for the fuel cell control unit to fuel cell mode export control policy.
Further, the DC/DC system controller includes acquisition unit and DC/DC control unit, and the acquisition is single
The voltage value of member acquisition DC/DC conversion process front and back ends, the DC/DC control unit control DC/DC by PWM module and convert
Switching tube opening and turning off in device model.
Further, the entire car controller includes AD/ switch acquisition unit, drive module and full-vehicle control list
Member, gear, speed, acceleration, pedal opening signal in AD/ switch acquisition unit acquisition whole vehicle model, by vehicle
Control unit makes control strategy, realizes the control to relay, pedal opening and driving mode by drive module.
Further, the fuel cell and super capacitor model are based on industrial personal computer LabVIEW software realization, using four
The dynamic process that rank Runge Kutta algorithm simulation fuel cell and super capacitor change over time；DC/AC/DC and two-way DC/DC
Model and whole vehicle model are realized in FPGA, and modularization parallel computation strategy and euler algorithm is respectively adopted.
A kind of hybrid power fuel cell car simulation control method proposed by the present invention and system, take in LabVIEW
Fuel cell and super capacitor model are built, DC/DC converter and whole vehicle model are built in FPGA, using controller in kind, with
This, which combines, builds hybrid power fuel cell car analogue system.Flow indicator calculates side is recognized using power demand in terms of control method
Method quickly obtains power demand, then the output work of fuel cell and super capacitor is obtained by the fuzzy control to demand power
Then rate is controlled fuel cell using fuzzy control, to super capacitor using the PI for introducing feedback, to reach to fuel cell
And the control of super capacitor output power, being finally introducing system output negative-feedback keeps system fast to driving information variation response, and
With good stability.
The present invention has the advantages that
(1) present invention calculates vehicle demand power using difference identification calculation method, accelerates calculating speed, improves meter
The relative precision of calculation.
(2) present invention controls fuel cell power generation power using fuzzy control strategy, reduces fuel cell system
The complexity controlled of uniting simultaneously has certain intelligence.
(3) present invention inputs system output as negative-feedback, so that system control precision is high, stability is good.
(4) present invention uses fourth order Runge-Kutta algorithm, accurately simulates fuel cell and super capacitor becomes at any time
The dynamic process of change.
Detailed description of the invention
Fig. 1 is the structural block diagram of hybrid power fuel cell car simulation control subsystem of the present invention.
In figure: fuel cell mode 110, super capacitor model 120, DC/AC/DC and two-way DC/DC model 130, vehicle
Model 140, fuel cell system controller 210, physical quantity acquisition unit 211, fuel cell control unit 212, DC/DC system
Controller 220, acquisition unit 221, DC/DC control unit 222, entire car controller 230, AD/ switch acquisition unit 231 drive
Dynamic model block 232, full-vehicle control unit 233, man-machine interface 240, power demand recognize computing module 311, power distribution Fuzzy Control
Molding block 312, fuel cell fuzzy control model 321, super capacitor PI control module 322, DC/DC convert control module 330.
Fig. 2 is the control structure schematic diagram figure of hybrid power fuel cell car Simulation Control of the present invention
Fig. 3 is the flow chart of hybrid power fuel cell car simulation control method of the present invention.
Specific embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is described in further detail.
As shown in Figure 1, hybrid power fuel cell car simulation control subsystem proposed by the present invention, including fuel cell mould
Type 110, super capacitor model 120, DC/AC/DC and two-way DC/DC model 130 and whole vehicle model 140, fuel cell system control
Device 210, DC/DC system controller 220 and entire car controller 230 processed, power demand recognize computing module 311, power distribution mould
Paste control module 312, fuel cell fuzzy control model 321 and super capacitor PI control module 322 and DC/DC transformation control mould
Block 330 and driving information S for inputiWith the man-machine interface 240 of display device status information.
Wherein, fuel cell mode 110 and super capacitor model 120 are used for the dynamic mistake that object simulating changes over time
Journey, the power source as whole vehicle model；DC/AC/DC and two-way DC/DC model 130 for power P according to demand 'k+1With it is super
The power allocation factor K of capacitoraFuel cell mode output power and super capacitor model output power are transformed to respectively whole
Input power size needed for vehicle model 140；Fuel cell system controller 210 is for acquiring fuel cell mode operation ginseng
Number controls the component in fuel cell system；DC/DC system controller 220 is used to acquire the electricity of DC/DC conversion process front and back end
Size is pressed, each switching tube opening and turning off in control DC/DC transformation model；Entire car controller 230 is for acquiring whole vehicle model
140 gear, speed, acceleration and pedal opening signal controls relay, pedal opening and the driving mould of whole vehicle model 140
Formula information；Power demand recognizes computing module 311 and is used for according to driving information SiIt calculates and exports demand power P'k+1；Power point
It is used to obtain the power distribution of fuel cell and super capacitor using power distribution fuzzy control method with fuzzy control model 312
Factor Ka；Fuel cell fuzzy control model 321 and super capacitor PI control module 322 are respectively used to output fuel cell mode
Control program and super capacitor PI control program；DC/DC converts the control that control module 330 is used for fuel cell model
Scheme and super capacitor PI control program export demand power P' to DC/AC/DC and two-way DC/DC model 130k+1。
Hybrid power fuel cell car semi-hardware type simulation test system includes model part and in-kind portion.Wherein model
Part includes fuel cell mode 110 and super capacitor model 120, DC/AC/DC and two-way DC/DC model 130 and whole vehicle model
140；In-kind portion includes fuel cell system controller 210, DC/DC system controller 220 and entire car controller 230.Fuel
Battery model 110 and super capacitor model 120 are realized in the LabVIEW software in industrial personal computer, are calculated using fourth order Runge-Kutta
Method accurately simulates the dynamic process that fuel cell and super capacitor change over time；DC/AC/DC and two-way DC/DC model
130 and whole vehicle model 140 realized in FPGA, modularization parallel computation strategy and euler algorithm is respectively adopted.
Fuel cell controller 210 includes acquiring list for acquiring the physical quantity of pressure, temperature, switching value and voltage and current
Member 211 and for the fuel cell control unit 212 to 110 export control policy of fuel cell mode.Physical quantity acquisition unit
The voltage value of 211 acquisition DC/DC conversion process front and back ends, can be with the pressure of acquisition system, temperature, switching value and voltage and current
Signal；Fuel cell control unit 212 controls switching tube in DC/DC converter model by PWM module and opening and turning off, can
It is communicated with the control of each valve of complete paired systems and with man-machine interface.DC/DC system controller 220 includes 221 He of acquisition unit
DC/DC control unit 222, acquisition unit 211 acquire voltage, the current signal of DC/DC conversion process front and back ends, control unit
The control that export to DC/DC model can be realized by PWM module simultaneously by communicating with man-machine interface, DC/DC control unit 222 and
Man-machine interface communication being opened and being turned off by switching tube in PWM module control DC/DC converter model simultaneously.
Entire car controller 230 includes AD/ switch acquisition unit 231, drive module 232 and full-vehicle control unit 233,
Gear, speed, acceleration, pedal opening signal in the acquisition whole vehicle model of AD/ switch acquisition unit 231, by full-vehicle control
Unit 233 makes control strategy, and control unit, which handles the signal of acquisition unit and receives control instruction in man-machine unit communication, to be turned
It turns to driving signal and passes to drive module 232, realized by drive module 232 to relay, pedal opening and driving mode
Control, drive whole vehicle model in each component.
The present invention also proposes a kind of hybrid power fuel cell car simulation control method, and this method can be based on above-mentioned system
System is realized, can also be realized based on other control system.
Described method includes following steps:
1) to the driving information S of inputiIt is recognized, with current driving information SkBe compared, find out speed difference △ v,
Acceleration difference △ a, ramp difference △ l and environmental factor, are calculated demand power P'k+1；As the driving information S of inputiWith
Current driving information SkWhen equal, control terminates.
There are some settings: (1) business district to Environment identification；(2) suburb；(3) super expressway has not for different environment
Same torque settings.Demand power is calculated by speed difference △ v, acceleration difference △ a, ramp difference △ l and environmental factor
P'k+1Process are as follows: demand power P'k+1Equal to operation Damping Power, motor drive power, transmission power loss and electronics
The summation of instrument power loss, operation Damping Power include damping in roll power, ramp Damping Power, air damping power and add
Fast Damping Power；Power loss during transmission device and motor drive passes through power factor ηtDescription, demand power
P'k+1Calculation formula are as follows:
ηtIt is coefficient of rolling resistance, C for the power transfer factor, fDFor air resistance coefficient, A be front face area, δ is vehicle rotary
Mass conversion coefficient, m are complete vehicle quality, and g is acceleration of gravity, v is automobile driving speed, l is ramp angle, a is that traveling adds
Speed.
2) the output accounting that fuel cell and super capacitor are calculated using power distribution fuzzy control method, obtains fuel
The power allocation factor K of battery and super capacitora。
The process of the output accounting of fuel cell and super capacitor is calculated using power distribution fuzzy control method are as follows:
21) to demand power P'k+1, current fuel cell output power PfuAnd current super capacitor output power PsocDo mould
Gelatinization calculates and is converted into demand power fuzzy parameter Kk+1, fuel cell output power fuzzy parameter KfuAnd super capacitor output work
Rate fuzzy parameter；Specific steps are as follows:
(1) demand power P'k+1Fuzzy parameter calculates:
The basic domain of demand power is set as [- Pd.max,Pd.max], to demand power P'k+1It is done at discretization by formula (1)
Reason:
Take dispersion n=3；Calculate Kk+1={ -3, -2, -1,0,1,2,3 }, the Linguistic Value domain of corresponding demand power
For [NB, NM, NL, ZO, PL, PM, PB]；
(2) fuel cell output power fuzzy parameter calculates:
The basic domain of fuel cell output power is set as [0, Pfu.max], sliding-model control is done by formula (2) to it:
Take dispersion n=4；Calculate Kfu={ 0,1,2,3,4 }, corresponding fuel cell output power Linguistic Value domain are
[ZO,ML,L,MH,H]；
(3) the basic domain of super capacitor output power is set as [- Psoc.max,Psoc.max], discretization is done referring to formula (1)
Processing, takes dispersion n=2, calculates Ksoc={ -2, -1,0,1,2 }, the Linguistic Value domain of corresponding super capacitor output power
For [NH, NL, ZO, PL, PH]；
22) with demand power fuzzy parameter Kk+1, fuel cell output power fuzzy parameter KfuAnd super capacitor output power
Fuzzy parameter KsocAs the input of fuzzy reasoning, fuzzy reasoning is carried out according to fuzzy rule 1 (being shown in Table 1)；
1 fuzzy rule 1 of table
23) the accounting factor K a of fuel cell and super capacitor output power is obtained to fuzzy deduction result defuzzification.
Defuzzification process is as follows:
For example, obtaining a fuzzy reasoning results set [Kk+1,Kfu,Ksoc]=[PS, ML, PL] be optimal reasoning knot
Fruit is cooked Fuzzy processing to the value.Using maximum membership degree method, fuel cell fuzzy parameter can be by the corresponding K of Linguistic Value MLfu=
1, obtain Pfu1=Pfu.max/ 4, P is similarly calculatedsoc1=Psoc.max/ 3, therefore deduce that output power accounting factor Ka=
Pfu1/Psoc1。
3) according to power demand P'k+1With power allocation factor KaBe calculated fuel cell need export power P 'fu、
The power P that super capacitor needs to export 'soc；The power P for needing to export according to obtained fuel cell 'fuAnd current fuel cell
Output power PfuThe control program that fuzzy control obtains fuel cell mode is done, power needed for exporting fuel cell mode, control
Scheme processed is for hydrogen input, air input, hydrogen gas circulating pump, cooling water circulation, fan and load (output) size of current；According to
The power P exported is needed according to super capacitors'ocIt determines the charging and recharging model of super capacitor, introduces current super capacitor output power
PsocNegative-feedback carries out PI control to it, power needed for exporting the charging and recharging model of super capacitor.
The power P for needing to export according to obtained fuel cell 'fuAnd current fuel cell output power PfuDo Fuzzy Control
It is made the detailed process of the control program of fuel cell mode are as follows: the power P for needing to export with calculated fuel cell 'fu
And current fuel cell output power PfuAs the input of fuzzy control, foundation fuzzy rule 2 ambiguity solution after fuzzy deduce
Change the control method for obtaining fuel cell mode, fuel cell mode is controlled by controller, fuzzy rule 2 is set such as
Under:
(1) fuel cell demand power P'fu>PfuWhen, the auxiliary systems parameter value such as Hydrogen Vapor Pressure, air pressure and temperature
It increases；
(2) fuel cell demand power P'fu≈PfuWhen, the auxiliary systems parameter value such as Hydrogen Vapor Pressure, air pressure and temperature
It is constant；
(3) fuel cell demand power P'fu< PfuWhen, the auxiliary systems parameter value such as Hydrogen Vapor Pressure, air pressure and temperature
Reduce.
The power P for needing to export according to super capacitor 'socIt determines the charge and discharge mode of super capacitor, introduces current super electricity
Hold output power PsocThe process for carrying out PI control is exported to super capacitor model as negative-feedback are as follows: if P'soc>=0, then it is super
Capacitor model is discharge mode, and it is boost mode that DC/DC controller, which controls two-way DC/DC model, at this time；Conversely, if P'soc< 0,
Super capacitor model is discharge mode, and it is decompression mode that DC/DC controller, which controls two-way DC/DC model, at this time.
4) control program of DC/AC/DC model fuel cell model needs defeated to whole vehicle model output fuel cell
Power P out 'fu, two-way DC/DC model to whole vehicle model output super capacitor need export power P 'soc；
5) by fuel cell need export power P 'fu, super capacitor need export power P 'socSuperposition obtains power
Demand P'k+1, fuel cell output power P'fuThrough DC/AC/DC transformation, super capacitor output power P'socBecome through two-way DC/DC
It after changing, is incorporated in (superposition) to 140 input direct-current bus of whole vehicle model, after whole vehicle model 140 is updated according to input power output
Current driving information Sk+1, return step 1.
It will be understood by those of skill in the art that specific embodiment herein is only used and explains the invention patent, and do not have to
In limitation the invention patent.Any modifications, equivalent replacements, and improvements etc. made within the spirit and principle of the invention patent,
It should be included among the scope of protection of the patent of the present invention.
Claims (10)
1. a kind of hybrid power fuel cell car simulation control method, it is characterised in that: described method includes following steps:
1) to the driving information S of inputiIt is recognized, with current driving information SkIt is compared, finds out speed difference △ v, accelerates
Difference △ a, ramp difference △ l and environmental factor are spent, demand power P' is calculatedk+1；As the driving information S of inputiWith it is current
Driving information SkWhen equal, control terminates；
2) the output accounting that fuel cell and super capacitor are calculated using power distribution fuzzy control method, obtains fuel cell
With the power allocation factor K of super capacitora；
3) according to power demand P'k+1With power allocation factor KaBe calculated fuel cell need export power P 'fu, it is super
The power P that capacitor needs to export 'soc；The power P for needing to export according to obtained fuel cell 'fuAnd current fuel cell output
Power PfuThe control program that fuzzy control obtains fuel cell mode is done, power needed for exporting fuel cell mode；According to super
The power P that grade capacitor needs to export 'socIt determines the charging and recharging model of super capacitor, introduces current super capacitor output power Psoc
Negative-feedback carries out PI control to it, power needed for exporting the charging and recharging model of super capacitor.
The power P for needing to export according to obtained fuel cell 'fuAnd current fuel cell output power PfuFuzzy control is done to obtain
The detailed process of the control program of fuel cell mode are as follows:
The power P for needing to export with calculated fuel cell 'fuAnd current fuel cell output power PfuAs fuzzy control
Input, according to fuzzy rule 2, defuzzification obtains the control method of fuel cell mode after fuzzy deduce, and passes through controller
Fuel cell mode is controlled, fuzzy rule 2 sets as follows:
(1) fuel cell demand power P'fu>PfuWhen, the auxiliary systems parameter value such as Hydrogen Vapor Pressure, air pressure and temperature increases；
(2) fuel cell demand power P'fu≈PfuWhen, the auxiliary systems parameter value such as Hydrogen Vapor Pressure, air pressure and temperature is constant；
(3) fuel cell demand power P'fu< PfuWhen, the auxiliary systems parameter value such as Hydrogen Vapor Pressure, air pressure and temperature reduces.
The power P for needing to export according to super capacitor 'socIt determines the charge and discharge mode of super capacitor, it is defeated to introduce current super capacitor
Power P outsocThe process for carrying out PI control is exported to super capacitor model as negative-feedback are as follows: if P'soc>=0, then super capacitor
Model is discharge mode, and it is boost mode that DC/DC controller, which controls two-way DC/DC model, at this time；Conversely, if P'soc< 0, it is super
Capacitor model is discharge mode, and it is decompression mode that DC/DC controller, which controls two-way DC/DC model, at this time.
4) control program of DC/AC/DC model fuel cell model needs to export to whole vehicle model output fuel cell
Power P 'fu, two-way DC/DC model to whole vehicle model output super capacitor need export power P 'soc；
5) by fuel cell need export power P 'fu, super capacitor need export power P 'socSuperposition obtains power demand
P'k+1, the updated current driving information S of whole vehicle model acquisitionk+1, return step 1).
2. hybrid power fuel cell car simulation control method according to claim 1, it is characterised in that: the step
1) demand power P' is calculated by speed difference △ v, acceleration difference △ a, ramp difference △ l and environmental factor ink+1Process
Are as follows: demand power P'k+1Equal to operation Damping Power, motor drive power, transmission power loss and electronic instrument power damage
The summation of consumption, operation Damping Power include damping in roll power, ramp Damping Power, air damping power and accelerate damping function
Rate；Power loss during transmission device and motor drive passes through power factor ηtDescription, demand power P'k+1Calculating
Formula are as follows:
ηtIt is coefficient of rolling resistance, C for the power transfer factor, fDIt is front face area for air resistance coefficient, A, δ is vehicle rotary quality
Conversion coefficient, m are complete vehicle quality, and g is acceleration of gravity, v is automobile driving speed, l is ramp angle, a is traveling acceleration.
3. hybrid power fuel cell car simulation control method according to claim 1, it is characterised in that: the step
2) process of the output accounting of fuel cell and super capacitor is calculated in using power distribution fuzzy control method are as follows:
21) to demand power P'k+1, current fuel cell output power PfuAnd current super capacitor output power PsocIt is blurred
Calculating is converted into demand power fuzzy parameter Kk+1, fuel cell output power fuzzy parameter KfuAnd super capacitor output power mould
Paste parameter；
22) with demand power fuzzy parameter Kk+1, fuel cell output power fuzzy parameter KfuAnd super capacitor output power is fuzzy
Parameter KsocAs the input of fuzzy reasoning, fuzzy reasoning is carried out according to fuzzy rule 1；
23) the accounting factor K a of fuel cell and super capacitor output power is obtained to fuzzy deduction result defuzzification.
4. hybrid power fuel cell car simulation control method according to claim 1 and system, it is characterised in that: institute
State need to export according to obtained fuel cell in step 3) power P 'fuAnd current fuel cell output power PfuIt does fuzzy
Control obtains the detailed process of the control program of fuel cell mode are as follows:
The power P for needing to export with calculated fuel cell 'fuAnd current fuel cell output power PfuAs fuzzy control
Input, according to fuzzy rule 2, defuzzification obtains the control method of fuel cell mode after fuzzy deduce, and passes through controller
Fuel cell mode is controlled, fuzzy rule 2 sets as follows:
(1) fuel cell demand power P'fu>PfuWhen, the auxiliary systems parameter value such as Hydrogen Vapor Pressure, air pressure and temperature increases；
(2) fuel cell demand power P'fu≈PfuWhen, the auxiliary systems parameter value such as Hydrogen Vapor Pressure, air pressure and temperature is constant；
(3) fuel cell demand power P'fu< PfuWhen, the auxiliary systems parameter value such as Hydrogen Vapor Pressure, air pressure and temperature reduces.
5. hybrid power fuel cell car analogue system according to claim 1, it is characterised in that: in the step 3)
The power P for needing to export according to super capacitor 'socIt determines the charge and discharge mode of super capacitor, introduces current super capacitor output work
Rate PsocThe process for carrying out PI control is exported to super capacitor model as negative-feedback are as follows: if P'soc>=0, then super capacitor model
For discharge mode, it is boost mode that DC/DC controller, which controls two-way DC/DC model, at this time；Conversely, if P'soc< 0, super capacitor
Model is discharge mode, and it is decompression mode that DC/DC controller, which controls two-way DC/DC model, at this time.
6. a kind of hybrid power fuel cell car simulation control subsystem, it is characterised in that: the system comprises fuel cell moulds
Type (110), super capacitor model (120), DC/AC/DC and two-way DC/DC model (130) and whole vehicle model (140), fuel electricity
Cell system controller (210), DC/DC system controller (220) and entire car controller (230), power demand recognize computing module
(311), power distribution fuzzy control model (312), fuel cell fuzzy control model (321) and super capacitor PI control module
(322) and DC/DC converts control module (330) and the driving information S for inputiWith the man-machine boundary of display device status information
Face (240)；
The fuel cell mode (110) and super capacitor model (120) are used for the dynamic process that object simulating changes over time,
Power source as whole vehicle model；The DC/AC/DC and two-way DC/DC model (130) for power P according to demand 'k+1With it is super
The power allocation factor K of grade capacitoraFuel cell mode output power and super capacitor model output power are transformed to respectively
Input power size needed for whole vehicle model (140)；The fuel cell system controller (210) is for acquiring fuel cell mould
Type operating parameter controls the component in fuel cell system；The DC/DC system controller (220) is for acquiring DC/DC transformation
The voltage swing of process front and back end controls each switching tube in DC/DC transformation model and opening and turn off；The entire car controller
(230) it for acquiring gear, speed, acceleration and the pedal opening signal of whole vehicle model (140), controls whole vehicle model (140)
Relay, pedal opening and driving pattern information；Power demand identification computing module (311) is used for according to driving information
SiIt calculates and exports demand power P'k+1；The power distribution fuzzy control model (312) is used to use power distribution Fuzzy Control
Method processed obtains the power allocation factor K of fuel cell and super capacitora；The fuel cell fuzzy control model (321) and
Super capacitor PI control module (322) is respectively used to the control program and super capacitor PI controlling party of output fuel cell mode
Case；DC/DC convert control module (330) for fuel cell model control program and super capacitor PI control program to
DC/AC/DC and two-way DC/DC model (130) export demand power P'k+1。
7. hybrid power fuel cell car simulation control subsystem according to claim 6, it is characterised in that: the fuel
Battery controller (210) include physical quantity acquisition unit (211) for acquiring pressure, temperature, switching value and voltage and current and
For the fuel cell control unit (212) to fuel cell mode (110) export control policy.
8. hybrid power fuel cell car simulation control subsystem according to claim 6, it is characterised in that: the DC/
DC system controller (220) includes acquisition unit (221) and DC/DC control unit (222), acquisition unit (211) acquisition
The voltage value of DC/DC conversion process front and back ends, the DC/DC control unit (222) control DC/DC converter by PWM module
Switching tube opening and turning off in model.
9. hybrid power fuel cell car simulation control subsystem according to claim 6, it is characterised in that: the vehicle
Controller (230) includes AD/ switch acquisition unit (231), drive module (232) and full-vehicle control unit (233), described
Gear, speed, acceleration, pedal opening signal in AD/ switch acquisition unit (231) acquisition whole vehicle model, by vehicle control
Unit (233) processed makes control strategy, realizes the control to relay, pedal opening and driving mode by drive module (232)
System.
10. hybrid power fuel cell car simulation control subsystem according to claim 6, it is characterised in that: the combustion
Expect that battery and super capacitor model are based on industrial personal computer LabVIEW software realization, using fourth order Runge-Kutta algorithm simulation fuel electricity
The dynamic process that pond and super capacitor change over time；DC/AC/DC and two-way DC/DC model and whole vehicle model are real in FPGA
It is existing, modularization parallel computation strategy and euler algorithm is respectively adopted.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110979030A (en) * | 2019-11-18 | 2020-04-10 | 杭州电子科技大学 | Composite fuzzy control electric automobile composite power supply system control method |
| CN111497678A (en) * | 2020-03-13 | 2020-08-07 | 北汽福田汽车股份有限公司 | Power generation control method and device for fuel cell engine, processor and vehicle |
| CN112379288A (en) * | 2020-10-26 | 2021-02-19 | 上海艾福亿维测试设备有限公司 | Fuel cell in-loop test system and test method thereof |
| CN112644344A (en) * | 2020-12-29 | 2021-04-13 | 武汉格罗夫氢能汽车有限公司 | BP neural network-based power distribution optimization system and optimization method |
| CN113177267A (en) * | 2021-05-26 | 2021-07-27 | 浙江大学 | Full-process multidisciplinary modeling method based on improved fuzzy PID |
| CN113246805A (en) * | 2021-07-02 | 2021-08-13 | 吉林大学 | Fuel cell power management control method considering temperature of automobile cab |
| CN114475281A (en) * | 2022-04-14 | 2022-05-13 | 苏州氢澜科技有限公司 | Fuel cell-super capacitor hybrid power system for unmanned vehicle |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1544265A (en) * | 2003-11-27 | 2004-11-10 | 武汉理工大学 | Energy flow controller of fuel cell electromobile |
| US20140067183A1 (en) * | 2012-08-31 | 2014-03-06 | Johnson Controls Technology Company | Optimized Fuzzy Logic Controller For Energy Management In Micro and Mild Hybrid Electric Vehicles |
| US20150148973A1 (en) * | 2013-11-26 | 2015-05-28 | Nec Laboratories America, Inc. | Fuzzy logic based integrated power coordination system for hybrid energy storage system |
| CN204526865U (en) * | 2015-04-15 | 2015-08-05 | 重庆工商职业学院 | Based on the dual energy source electric car energy management system of fuzzy control |
| CN106564398A (en) * | 2016-11-08 | 2017-04-19 | 西安交通大学 | Vehicle-mounted composite power supply system of electric vehicle and control method |
| CN107140168A (en) * | 2017-04-26 | 2017-09-08 | 武汉理工大学 | A kind of hybrid power ship EMS and control method based on WAVELET FUZZY logic |
-
2019
- 2019-01-08 CN CN201910015834.2A patent/CN109808512B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1544265A (en) * | 2003-11-27 | 2004-11-10 | 武汉理工大学 | Energy flow controller of fuel cell electromobile |
| US20140067183A1 (en) * | 2012-08-31 | 2014-03-06 | Johnson Controls Technology Company | Optimized Fuzzy Logic Controller For Energy Management In Micro and Mild Hybrid Electric Vehicles |
| US20150148973A1 (en) * | 2013-11-26 | 2015-05-28 | Nec Laboratories America, Inc. | Fuzzy logic based integrated power coordination system for hybrid energy storage system |
| CN204526865U (en) * | 2015-04-15 | 2015-08-05 | 重庆工商职业学院 | Based on the dual energy source electric car energy management system of fuzzy control |
| CN106564398A (en) * | 2016-11-08 | 2017-04-19 | 西安交通大学 | Vehicle-mounted composite power supply system of electric vehicle and control method |
| CN107140168A (en) * | 2017-04-26 | 2017-09-08 | 武汉理工大学 | A kind of hybrid power ship EMS and control method based on WAVELET FUZZY logic |
Non-Patent Citations (1)
| Title |
|---|
| 伍贤春: "混合供电系统能量管理研究", 《中国优秀硕士学位论文全文数据库工程科技II辑》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110979030A (en) * | 2019-11-18 | 2020-04-10 | 杭州电子科技大学 | Composite fuzzy control electric automobile composite power supply system control method |
| CN111497678A (en) * | 2020-03-13 | 2020-08-07 | 北汽福田汽车股份有限公司 | Power generation control method and device for fuel cell engine, processor and vehicle |
| CN112379288A (en) * | 2020-10-26 | 2021-02-19 | 上海艾福亿维测试设备有限公司 | Fuel cell in-loop test system and test method thereof |
| CN112644344A (en) * | 2020-12-29 | 2021-04-13 | 武汉格罗夫氢能汽车有限公司 | BP neural network-based power distribution optimization system and optimization method |
| CN113177267A (en) * | 2021-05-26 | 2021-07-27 | 浙江大学 | Full-process multidisciplinary modeling method based on improved fuzzy PID |
| CN113246805A (en) * | 2021-07-02 | 2021-08-13 | 吉林大学 | Fuel cell power management control method considering temperature of automobile cab |
| CN114475281A (en) * | 2022-04-14 | 2022-05-13 | 苏州氢澜科技有限公司 | Fuel cell-super capacitor hybrid power system for unmanned vehicle |
| CN114475281B (en) * | 2022-04-14 | 2022-07-26 | 苏州氢澜科技有限公司 | Fuel cell-super capacitor hybrid power system for unmanned vehicle |
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