CN115796056B - Torsion angle estimation method of automotive axial flow cooling fan blade considering Reynolds number change - Google Patents
Torsion angle estimation method of automotive axial flow cooling fan blade considering Reynolds number change Download PDFInfo
- Publication number
- CN115796056B CN115796056B CN202310054892.2A CN202310054892A CN115796056B CN 115796056 B CN115796056 B CN 115796056B CN 202310054892 A CN202310054892 A CN 202310054892A CN 115796056 B CN115796056 B CN 115796056B
- Authority
- CN
- China
- Prior art keywords
- blade
- reynolds number
- individual
- segment
- generation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- 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
Landscapes
- Structures Of Non-Positive Displacement Pumps (AREA)
Abstract
The invention discloses a torsion angle estimation method of a vehicle axial flow heat radiation fan blade considering Reynolds number change, which considers the Reynolds number of the blade along with the change of the spanwise length and the average inlet speed and comprises the following steps: 1, setting parameters such as output power of a motor shaft, rated rotating speed of a fan, chord length of a blade, blade profile, hub and fan blade radius and the like; 2, establishing a target function based on a phyllotactic theory; 3, establishing a parameter domain according to a lift curve and a polar diagram corresponding to the blade profile; 4, optimizing by using a genetic algorithm by taking the inlet flow rate as the fitness, and considering the change of Reynolds number in the iterative process; and 5, finally, calculating the change rule of the blade torsion angle which enables the flow speed of the blade inlet to be the maximum along the spanwise direction of the blade. The method considers the Reynolds number distribution of the blades, optimizes the inlet flow velocity as the fitness of the genetic algorithm, and thus can obtain the change rule of the torsional angle of the blades along the spanwise direction of the blades, which can improve the flow of the axial flow cooling fan for the vehicle.
Description
Technical Field
The invention belongs to the field of design of cooling fans, and particularly relates to a method for estimating a fan blade installation angle of an axial flow cooling fan.
Background
Axial-flow type heat dissipation fans are widely used in various products such as automobiles and computers, especially fuel cell vehicles, due to the characteristics of relatively low power consumption and compact structure. The flow rate per unit time, i.e. the mass flow rate or the volume flow rate, is a main parameter for measuring the heat dissipation performance of the fan. When the fan is sized, its flow rate is mainly affected by the average inlet airflow velocity, i.e. the larger the average inlet airflow velocity, the larger the volumetric flow rate of the fan. Blade twist angle is one of the main contributors to average inlet airflow velocity, and determining blade twist angle places higher demands on engineer experience, increasing the length of the experimental cycle. For the axial flow cooling fan for the vehicle, the requirement on the rotating speed is high, and the Reynolds numbers of the blades in the radial direction have certain difference. The fan inlet airflow velocity is also relatively high and is a factor that cannot be ignored in calculating the reynolds number.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides a method for estimating the torsion angle of the blade of the axial-flow cooling fan for the vehicle by considering Reynolds number change, so that the torsion angle of the blade can be optimized under the condition of considering Reynolds number distribution, the change rule of the torsion angle of the blade of the flow of the axial-flow cooling fan for the vehicle along the spanwise direction of the blade is obtained, and the arrangement scheme of the torsion angle of the blade aiming at improving the flow of the axial-flow fan for the vehicle is accurately obtained.
The invention adopts the following technical scheme for solving the technical problems:
the invention discloses a torsion angle estimation method of an automotive axial flow heat dissipation fan blade considering Reynolds number change, which is characterized by comprising the following steps of:
step 1: obtaining the output power of the motor shaft of the fanP w Rated speed of fanΩChord length of blade topc t Root chord lengthc 0 Radius of the blade and hubr 0 And radius of fan blader t Number of bladesN b ；
Step 2:according to the length of blade, the blade is divided intoNSegment and calculated using equation (1)NReynolds number of segment bladeR 0 ~R N ：
In the formula (1), the acid-base catalyst,R 0 the root Reynolds number;R i is as followsiReynolds numbers of the segment blades;R N the Reynolds number of the top of the blade,ρis the air density;r i ，c i are respectively the firstiThe radius of the section blade and the chord length of the blade;μis an aerodynamic viscosity and has:
in the formulae (2) and (3),Nrepresenting the total number of the blade sections;
and 3, step 3: using equation (4) to calculateiPower of sectional bladeP i ；
In the formula (4), the reaction mixture is,Vin order to obtain the flow rate at the inlet of the fan,C Li andC Di are respectively the firstiThe airfoil lift coefficient and drag coefficient of the segment blades,rrepresenting the distance from any section of the blade to the blade root;
and 4, step 4: calculating the output power of the motor shaft by using the formula (4)P w ：
And 5: construction of the flow Rate for Inlet, liter, using equation (5)Equation of force coefficient and resistance coefficientf：
f(V,C L1 ,C D1 ,C L2 ,C D2 ,…,C LN ,C DN )-P w =0 (6)
And 6: forming parameter domains with different Reynolds numbers according to the lift characteristic curve and the polar diagram of the blade profile;
by DeltaRIs a gap betweenR 0 ~2R N The range has a Reynolds number dispersion of [ [ alpha ] ]R 1 ,R 2 ,…,R q ,…,R Q ](ii) a Obtaining on the lift mapqReynolds number of segment bladeR q Corresponding lift curve and Reynolds numberR q On the corresponding lift curve, in deltaαFor interval, obtainJLift coefficient at angle of attackC q Lj |j= 1, 2,…,J}，C q Lj Denotes the firstjAngle of attackα j Lift coefficient under;
then find out the first one according to the polar diagramjAngle of attackα j Coefficient of drag atC q Dj Thereby constituting a Reynolds numberR q Corresponding parameter setb q =[(α 1 ,C q L1 ,C q D1 ), (α 2 ,C q L2 ,C q D2 ),…, (α j ,C q Lj ,C q Dj ),…,(α J ,C q LJ ,C q DJ )](ii) a Wherein the content of the first and second substances,α 1 ,α 2 , …, α J 1 st, 2 nd to 2 nd in the representation parameter setJAn angle of attack; further obtainQParameter domain composed of parameter groups corresponding to discrete Reynolds numbersB=[b 1 ,b 2 ,…,b q ,…,b Q ] T ；
And 7: define an inclusionMPopulation set of individualA=[a 1 ,a 2 ,…,a m ,…,a M ] T Wherein, in the step (A),a m denotes the firstmAn individual, anda m =[(C m L1 ,C m D1 ), (C m L2 ,C m D2 ),…, (C m Li ,C m Di ),…,(C m LN ,C m DN )]；(C m Li ,C m Di ) Respectively representmIndividual(s) ofa m To middleiReynolds number of segment bladeR i Lift and drag coefficients in corresponding parameter domains;
defining the iteration number of the current population askAnd is initializedk=1, total number of iterationsK；
The Reynolds numberR 0 ~R N As a firstkReynolds number of 1 iteration, noteR 1 k(-1) ,R 2 k(-1) ,…,R i k(-1) ,…,R N k( -1) Wherein, in the process,R i k(-1) is shown ask1 st iterationiReynolds number of the segment blade;
according to the firstkReynolds number of generation-1R 1 k(-1) ,R 2 k(-1) ,…,R i k(-1) ,…,R N k(-1) From the parameter domainBIn selectionMIndividual and constitute the firstk-1 generation populationA k(-1) Wherein, the firstk-1 generation populationA k(-1) To middlemThe individual is recorded asa m k(-1) ；
And 8: will be firstk-1 generation populationA k(-1) Substitution equationfThe average inlet flow rate for each individual was calculated and recorded asV k(-1) =[V 1 k(-1) ,V 2 k(-1) ,…,V m k(-1) ,…,V M k(-1) ]And from the firstk1 cycle average inlet flow Rate setV k(-1) To select the maximum inlet flow rateV max k-1() Then, the second calculation is performed by using the formula (7)kReynolds number of i-th blade in sub-iterationR i k() ；
And step 9: according to the firstkReynolds number of sub-iterationR 1 k() ,R 2 k() ,…,R i k() ,…,R N k() From the parameter domainBIs selected tomThe individual isa m k() Thereby obtaining the firstkGeneration groupA k() ；
Step 10: if doesR i k() -R i k(-1) |>ΔRThen will bek+1 assignmentkThen, returning to the step 8 for sequential execution, otherwise, executing the step 11;
step 11, will bekGeneration groupA k() Substitution equationfCalculating the inlet flow rate of each individualV k() Taking the inlet velocity as the fitness of the individual, whereinmThe inlet flow rate of each individual is the fitnessV m k() . To the firstkGeneration groupA k() Performing crossover and mutation to obtain the updatedkGeneration group
(ii) a And selecting the maximum inlet flow rate, i.e. the maximum fitnessV max k() The corresponding individual is taken as the firstkGeneration of optimal individualsa best k() ；
Step 12: if doesV max k() -V max k-1() |>εAnd isk<KThen will bek+1 assignmentkThen, returning to step 9 for sequential execution, otherwise, stopping iteration and outputting the first outputkMaximum inlet flow rate of the sub-iterationV max k() And corresponding theretoR 1 k() ,R 2 k() ,…,R i k() ,…,R N k() First, akGeneration optimizationa best k() Corresponding as the optimum inlet flow rateV * max Optimum Reynolds numberR 1 * ,R 2 * ,…,R i * ,…,R N * Optimal individuala * best Wherein, in the step (A),R i * is shown asiThe final reynolds number of the segment blade,εindicating the set error;
step 13: according to the optimum Reynolds numberR i * And optimal individualsa * best Lift/drag coefficient of (1), from the parameter domainBTo obtainiAngle of attack corresponding to the section airfoilα i And calculating the second step according to the velocity geometryiThe torsion angles corresponding to the blade profiles are as follows:
θ i =α i +arctan(V * max /(Ωr i ))；
step 14: obtaining a regular relation formula of the installation angle along with the change of the spanwise length of the blade by utilizing linear interpolation shown in the formula (8):
in the formula (8), the reaction mixture is,r i-1 is as followsi-Radius of 1 segment of blade;θ i-1 is as followsi-The twist angle corresponding to the 1-segment blade profile,θ(r,i) Is shown asiThe twist angle of the segment blade at any cross section,i=1,2,…,N。
the method for estimating the torsional angle of the blade of the axial-flow heat-dissipation fan for the vehicle, which takes the Reynolds number change into consideration, is also characterized in that the crossing and the variation in the step 11 comprise the following steps:
step 11.1: will be firstkGeneration groupA k() All individuals in the system are arranged according to the descending mode of the average inlet flow velocity to obtain the ordered firstkThe generation group is marked asA' k() ；
Step 11.2: will be firstkGeneration groupA' k() Middle frontM(ii) a retention of 3 individuals, wherein,Mfor the total number of individuals in the population, will remainM/3~2MPerforming cross operation on 3 individuals to obtainM/3~2M(iii) 3 individuals after crossing;
step 11.3: will be firstkGeneration groupA' k() In 2M/3~MSubjecting individual to mutation to obtain 2M/3~M(ii) an individual after mutation;
step 11.3.1:will be firstkGeneration groupA' k() In 2M/3~MBefore replacing individualM(ii)/3 individuals;
step 11.3.2: random generationN2 pieces 1 toNIs a positive integer of (2)p 1 ,p 2 ,…,p l ,…,p N/2 ]Wherein, in the step (A),p l is shown aslA random number;
step 11.3.3: according to the firstp l Reynolds number of sectionR k() pl In the parameter domainBIn which a pair of lift and drag coefficients (C L ,C D ) And replace the current secondkGeneration groupA' k() To middlem' Individual corresponding to the secondp l Segment parameter (C m k'() L pl() ,C m k'() D pl() ) Wherein, in the step (A),m' is 2M/3~MA positive integer therebetween, thereby completingNUpdating the parameters of the positions corresponding to 2 random numbers;
step 11.4: from the firstkGeneration groupA' k() Middle frontM(3 individuals, the firstkGeneration groupA' k() Middle frontM/3 individuals andkgeneration groupA' k() Middle frontMThe/3 individuals form the updatedkGeneration group
。
Compared with the prior art, the invention has the beneficial effects that:
1. according to the method, the lift characteristic curve and the polar diagram of the blade profile are converted into parameter domains with different Reynolds numbers, the problem is converted into the problem of finding the optimal parameter combination, and therefore the pneumatic data of the blade profile can be directly used for optimization calculation without fitting, and the calculation efficiency is improved.
2. The Reynolds number is updated in the iterative process in consideration of the change of the Reynolds number along with the spanwise direction of the blade and the change of the average inlet flow velocity, so that parameter combinations which are more in line with actual conditions can be selected, and a more accurate torsion angle estimation rule is provided for the fan blade.
3. The invention aims at the maximum average inlet flow velocity, is favorable for improving the important performance index of high flow of the fan, and provides an initial torsion angle scheme favorable for improving the flow for the fan blade, thereby improving the heat radiation performance of the fan.
4. The invention can calculate the change rule of the torsional angle of the blade only by using some basic parameters such as the output power of the motor shaft, the rated rotating speed of the fan, the chord length of the blade, the blade profile, the radius of the hub, the radius of the blade, the number of the blades and the like, reduces the dependence on the experience of engineering technicians and the times and the period of experiments, and improves the efficiency of the research and development work of the fan blade.
Drawings
FIG. 1 is a schematic view of an axial-flow heat dissipation fan blade according to the present invention;
FIG. 2 is a schematic representation of the blade velocity geometry of the present invention;
FIG. 3a is a schematic representation of a profile lift characteristic and polar plot of the present invention;
FIG. 3b is a schematic illustration of a profile lift characteristic and polar line plot of the present invention;
FIG. 4 is a schematic illustration of the iterative error of the genetic algorithm of the present invention;
FIG. 5 is a schematic illustration of the output of the present invention;
fig. 6 is a flow chart of the method of the present invention.
Detailed Description
The following examples of the present invention will be described in detail, and the present invention is implemented on the premise of the technical solution of the present invention, but the scope of the present invention is not limited to the following examples.
In this embodiment, as shown in fig. 6, a method for estimating a torsional angle of a blade of an axial-flow heat-dissipating fan for a vehicle, which considers a change in a reynolds number, includes the following steps:
step 1: obtaining the output power of the motor shaft of the fanP w Rated speed of fanΩChord length of blade topc t Root chord lengthc 0 Blade profile, hub radiusr 0 And radius of fan blader t Number of bladesN b ；
Initial design parameters of a given cooling fan are shown in table 1, and a fan blade schematic diagram is shown in fig. 1;
table 1 initial design parameters of cooling fan
Step 2: dividing the blades into groups according to their lengthsNSegment and calculated using equation (1)NReynolds number of segment bladeR 0 ~R N ：
In the formula (1), the reaction mixture is,R 0 the root Reynolds number;R i is as followsiReynolds number of the segment blade;ρis the air density;R N is the Reynolds number of the leaf top;r i ，c i are respectively the firstiThe radius of the segment blade and the blade chord length;μis an aerodynamic viscosity and has:
in the formulas (2) and (3), N represents the total number of blade stages;
in this example, N =10, and the initial reynolds number range obtained by substituting data is 1.193 × 10 5 ~3.272 ×10 5 ；
First, theiSegment radius ofr i =0.048+0.0105iChord length ofc i =0.086-0.0012i；
First, theiSegment Reynolds number ofR i =2.89X10 7 ×(0.048+0.0105i)(0.086-0.0012i)；
And step 3: using equation (4) to calculateiPower of sectional bladesP i ；
In the formula (4), the reaction mixture is,Vin order to obtain the flow rate at the inlet of the fan,C Li andC Di are respectively the firstiThe airfoil lift coefficient and drag coefficient of the segment blade,rrepresenting the distance from any section of the blade to the blade root;
the formula (4) is obtained according to the stress of the blade, the stress schematic diagram of the blade is shown in figure 2, and the stress schematic diagram can be calculated by numerical analysis software in an auxiliary mode after being substituted into data.
And 4, step 4: calculating the output power of the motor shaft using equation (4)P w ：
And 5: equations for inlet flow velocity, lift coefficient and drag coefficient were constructed using equation (5)f：
f(V,C L1 ,C D1 ,C L2 ,C D2 ,…,C LN ,C DN )-P w =0 (6)
The substitution of the data can be assisted by numerical analysis software.
Step 6: forming parameter domains with different Reynolds numbers according to the lift characteristic curve and the polar diagram of the blade profile;
by DeltaRIs a gap betweenR 0 ~2R N The range has a Reynolds number dispersion of [ [ alpha ] ]R 1 ,R 2 ,…,R q ,…,R Q ](ii) a On the lift characteristic diagramGet firstqReynolds number of segment bladeR q Corresponding lift curve and Reynolds numberR q On the corresponding lift curve, in deltaαFor interval, obtainJLift coefficient at angle of attackC q Lj |j=1,2,…,J}，C q Lj Is shown asjAngle of attackα j Lift coefficient under;
then find out the first one according to the polar diagramjAngle of attackα j Coefficient of resistance ofC q Dj Thereby constituting a Reynolds numberR q Corresponding parameter setb q =[(α 1 ,C q L1 ,C q D1 ), (α 2 ,C q L2 ,C q D2 ),…, (α j ,C q Lj ,C q Dj ),…,(α J ,C q LJ ,C q DJ )](ii) a Wherein the content of the first and second substances,α 1 ,α 2 , …,α J representing the 1 st, 2 nd to J th angles of attack in the parameter set; further obtainQParameter domain composed of parameter sets corresponding to discrete Reynolds numbersB=[b 1 ,b 2 ,…,b q ,…,b Q ] T ；
In this example, ΔR=1×10 4 ,Δα=0.1˚,Q=40,J=200, the resulting parameter domain is a parametric combination of 40 × 200 data, with lift plots and pole plots as shown in fig. 3a and 3 b.
And 7: define an inclusionMPopulation set of individualA=[a 1 ,a 2 ,…,a m ,…,a M ] T Wherein, in the step (A),a m is shown asmAn individual, anda m =[(C m L1 ,C m D1 ), (C m L2 ,C m D2 ),…, (C m Li ,C m Di ),…,(C m LN ,C m DN )]；(C m Li ,C m Di ) Respectively representmIndividual onea m To middleiReynolds number of segment bladeR i Lift and drag coefficients in corresponding parameter domains;
defining the iteration number of the current population askAnd is initializedk=1, total number of iterationsK；
The Reynolds numberR 0 ~R N As a firstkReynolds number of 1 iteration, noteR 1 k(-1) ,R 2 k(-1) ,…,R i k(-1) ,…,R N k( -1) Wherein, in the step (A),R i k(-1) denotes the firstk1 st iterationiReynolds number of the segment blade;
according to the firstkReynolds number of generation-1R 1 k(-1) ,R 2 k(-1) ,…,R i k(-1) ,…,R N k(-1) From the parameter domainBIn selectionMIndividual and constitute the firstk-1 generation populationA k(-1) Wherein, a firstk-1 generation populationA k(-1) To middlemThe individual is recorded asa m k(-1) ；
In this embodiment, letM=20,K=300. Convergence error is set asε=0.2。
And 8: will be firstk-1 generation populationA k(-1) Substitution equationfThe average inlet flow rate for each individual was calculated and recorded asV k(-1) =[V 1 k(-1) ,V 2 k(-1) ,…,V m k(-1) ,…,V M k(-1) ]And from the firstk1 cycle average inlet flow Rate setV k(-1) To select the maximum inlet flow rateV max k-1() Then, the second calculation is made by equation (7)kReynolds number of i-th segment blade in sub-iterationR i k() ；
And step 9: according to the firstkReynolds number of sub-iterationR 1 k() ,R 2 k() ,…,R i k() ,…,R N k() From the parameter domainBIs selected frommThe individual isa m k() Thereby obtaining the firstkGeneration groupA k() ；
Step 10: if doesR i k() -R i k(-1) |>ΔRThen will bek+1 assignmentkThen, returning to the step 8 for sequential execution, otherwise, executing the step 11;
step 11, will bekGeneration groupA k() Substitution equationfCalculating the inlet flow rate of each individualV k() Taking the inlet velocity as the fitness of the individual, whereinmThe inlet flow rate of each individual is the fitnessV m k() . To the firstkGeneration groupA k() To make an intersectionAnd mutation to get the updatedkGeneration group
(ii) a And selecting the maximum inlet flow rate, i.e. the maximum fitnessV max k() The corresponding individual is taken as the firstkGeneration of optimal individualsa best k() ；
Step 11.1: will be firstkGeneration groupA k() All individuals in the system are arranged according to the descending mode of the average inlet flow velocity to obtain the ordered firstkThe generation group is marked asA' k() ；
Step 11.2: will be firstkGeneration groupA' k() Middle frontMA/3 individual reserve will remainM/3~2MPerforming cross operation on 3 individuals to obtainM/3~2M(iii) 3 individuals after crossing;
the first third of the most suitable data is retained to prevent the excellent individuals from being eliminated.
Step 11.3: will be firstkGeneration groupA' k() In 2M/3~MSubjecting individual to mutation to obtain 2M/3~M(ii) an individual after mutation;
step 11.3.1: will be firstkGeneration groupA' k() In 2M/3~MBefore the individual is replacedM(ii)/3 individuals;
the step is to eliminate the batch with the worst fitness and carry out the next mutation operation on the individuals with the larger fitness to make the mutation direction go to the good direction as much as possible.
Step 11.3.2: random generationN2 pieces 1 toNIs a positive integer of (2)p 1 ,p 2 ,…,p l ,…,p N/2 ]Wherein, in the step (A),p l is shown aslA random number;
step 11.3.3: according to the firstp l Reynolds number of sectionR k() pl In the parameter domainBIn which a pair of lift and drag coefficients (C L ,C D ) And replace the current secondkGeneration groupA' k() To middlem' Individual corresponding to the secondp l Segment parameter (C m k'() L pl() ,C m k'() D pl() )，m' is 2M/3~MA positive integer in between, thereby completingN2, updating parameters of corresponding positions of the random numbers;
step 11.4: from the firstkGeneration groupA' k() Middle frontM(3 individuals, the firstkGeneration groupA' k() Middle frontMA/3 individuals andkgeneration groupA' k() Middle frontMThe/3 individuals form the updatedkGeneration group
。
Step 12: if doesV max k() -V max k-1() |>εAnd isk<KThen will bek+1 assignmentkThen, returning to step 9 to execute in sequence, otherwise, stopping iteration and outputting the first outputkMaximum inlet flow rate of the sub-iterationV max k() And corresponding theretoR 1 k() ,R 2 k() ,…,R i k() ,…,R N k() The first stepkGeneration optimizationa best k() Corresponding as the optimum inlet flow rateV * max Optimum Reynolds numberR 1 * ,R 2 * ,…,R i * ,…,R N * Optimal individualsa * best Wherein, in the step (A),R i * is shown asiThe final reynolds number of the segment blade,εindicating the set error;
and when the convergence error is smaller than the specified error or the iteration times reach the maximum iteration times, determining that the population optimization has reached the limit, and preventing the population optimization from being limited into a dead loop. The individual with the maximum fitness at this time is the individual with the maximum inlet airflow speed. The convergence error during the iteration of the genetic algorithm is shown in fig. 4.
Step 13: according to the optimum Reynolds numberR i * And optimal individualsa * best Lift/drag coefficient of (1), from the parameter domainBTo obtainiAngle of attack corresponding to the section airfoilα i And calculating the second step according to the velocity geometryiThe torsion angles corresponding to the blade profiles are as follows:
θ i =α i +arctan(V * max /(Ωr i ))；
the relationship of twist angle to angle of attack is derived from the blade's velocity vector trigonometry, as shown in FIG. 2. The results of the calculations for this example are shown in Table 2.
TABLE 2 Final results of the parameter calculations for each segment
Step 14: obtaining a regular relation expression of the installation angle along with the change of the spanwise length of the blade by utilizing linear interpolation shown in an expression (8):
in the formula (8), the reaction mixture is,r i-1 is as followsi-Radius of 1 segment of blade;θ i-1 is as followsi-The twist angle corresponding to the 1-segment blade profile,θ(r,i) Is shown asiThe twist angle of the segment blade at any cross section,i=1,2,…,N。
by substituting the data in step 13, a piecewise function of the change rule can be obtained, and the effect is shown in fig. 5.
Claims (3)
1. A torsion angle estimation method for vehicle axial flow cooling fan blades considering Reynolds number change is characterized by comprising the following steps:
step 1: obtaining the output power of the motor shaft of the fanP w Rated speed of fanΩChord length of blade topc t Root chord lengthc 0 Radius of the blade and hubr 0 And radius of fan blader t Number of bladesN b ；
Step 2: according to the length of blade, the blade is divided intoNSegment and calculated using equation (1)NReynolds number of segment bladeR 0 ~R N ：
In the formula (1), the reaction mixture is,R 0 the root Reynolds number;R i is as followsiReynolds number of the segment blade;R N is the Reynolds number of the blade top,ρis the air density;r i ，c i are respectively the firstiThe radius of the segment blade and the blade chord length;μis an aerodynamic viscosity and has:
in the formulae (2) and (3),Nrepresenting the total number of the blade sections;
and step 3: using equation (4) to calculateiPower of sectional bladeP i ；
In the formula (4), the reaction mixture is,Vin order to obtain the flow rate at the inlet of the fan,C Li andC Di are respectively the firstiThe airfoil lift coefficient and drag coefficient of the segment blades,rrepresenting the distance from any section of the blade to the blade root;
and 4, step 4: calculating the output power of the motor shaft using equation (4)P w ：
And 5: equations for inlet flow velocity, lift coefficient and drag coefficient were constructed using equation (5)f：
f(V, C L1 , C D1 , C L2 , C D2 ,…, C LN , C DN )- P w =0 (6)
And 6: forming parameter domains with different Reynolds numbers according to the lift characteristic curve and the polar diagram of the blade profile;
by DeltaRIs at interval ofR 0 ~2R N The range has a Reynolds number dispersion of [ [ alpha ] ]R 1 , R 2 ,…, R q ,…, R Q ](ii) a Obtaining on the lift mapqReynolds number of segment bladeR q Corresponding lift curve and Reynolds numberR q On the corresponding lift curve, in deltaαFor interval, obtainJLift coefficient at each angle of attackC q Lj | j= 1, 2,…, J}，C q Lj Is shown asjAngle of attackα j Lift coefficient under;
then find the first one according to the polar diagramjAngle of attackα j Coefficient of resistance ofC q Dj Thereby constituting a Reynolds numberR q Corresponding parameter setb q =[(α 1 , C q L1 , C q D1 ), (α 2 , C q L2 , C q D2 ),…, (α j , C q Lj , C q Dj ), …,( α J , C q LJ , C q DJ )]Wherein, in the process,α 1 , α 2 , …, α J representing the 1 st, 2 nd to J th angles of attack in the parameter set; further obtainQParameter domain composed of parameter sets corresponding to discrete Reynolds numbersB=[b 1 ,b 2 ,…,b q , …,b Q ] T ；
And 7: define an inclusionMPopulation set of individualA=[a 1 ,a 2 ,…,a m ,…,a M ] T Wherein, in the step (A),a m is shown asmAn individual, anda m =[(C m L1 , C m D1 ), (C m L2 ,C m D2 ),…, (C m Li , C m Di ),…,(C m LN , C m DN )]；(C m Li , C m Di ) Respectively represent the firstmIndividual onea m To middleiReynolds number of segment bladeR i Lift and drag coefficients in corresponding parameter domains;
defining the iteration number of the current population askAnd is initializedk=1, total number of iterationsK；
The Reynolds numberR 0 ~R N As a firstkReynolds number of 1 iteration, noteR 1 k(-1) , R 2 k(-1) ,…, R i k(-1) ,…, R N k(-1) Wherein, in the process,R i k(-1) is shown ask1 st iterationiReynolds number of the segment blade;
according to the firstkReynolds number of generation-1R 1 k(-1) , R 2 k(-1) ,…, R i k(-1) ,…, R N k(-1) From the parameter domainBIn selectionMIndividual and constitute the firstk-1 generation populationA k(-1) Wherein, a firstk-1 generation populationA k(-1) To middlemThe individual is recorded asa m k(-1) ；
And 8: will be firstk-1 generation populationA k(-1) Substitution equationfThe average inlet flow rate for each individual was calculated and recorded asV k(-1) =[V 1 k(-1) ,V 2 k(-1) ,…,V m k(-1) ,…,V M k(-1) ]And from the firstk1 cycle average inlet flow Rate setV k(-1) To select the maximum inlet flow rateV max k-(1) Then, the second calculation is made by equation (7)kReynolds number of i-th segment blade in sub-iterationR i k() ；
And step 9: according to the firstkSub-iterationReynolds number ofR 1 k() , R 2 k() , …, R i k() , …, R N k() From the parametric domainBIs selected tomThe individual isa m k() Thereby obtaining the firstkGeneration groupA k() ；
Step 10: if doesR i k() - R i k(-1) |>ΔRThen will bek+1 assignmentkThen, returning to the step 8 for sequential execution, otherwise, executing the step 11;
step 11, will bekGeneration groupA k() Substitution equationfCalculating the inlet flow rate of each individualV k() Taking the inlet velocity as the fitness of the individual, whereinmThe inlet flow rate of each individual is the fitnessV m k() To the secondkGeneration groupA k() Performing crossover and mutation to obtain the updatedkGeneration group
(ii) a And selecting the maximum inlet flow rate, i.e. the maximum fitnessV max k() The corresponding individual is taken as the firstkGeneration of optimal individualsa best k() ；
Step 12: if does V max k() - V max k-1() |>εAnd isk<KThen will bek+1 assignmentkThen, returning to step 9 for sequential execution, otherwise, stopping iteration and outputting the first outputkMaximum inlet flow rate of the sub-iterationV max k() And corresponding theretoR 1 k() , R 2 k() ,…, R i k() , …, R N k() The first stepkGeneration optimizationa best k() Corresponding as the optimum inlet flow rateV * max Optimum Reynolds numberR 1 * , R 2 * , …, R i * , …, R N * Optimal individuala * best Wherein, in the process,R i * denotes the firstiThe final reynolds number of the segment blade,εindicating the set error;
step 13: according to the optimum Reynolds numberR i * And optimal individualsa * best The lift/drag coefficient of (1), the second one is obtained from the parameter domain BiAngle of attack corresponding to the profile of the sectionα i And calculating the second from the geometric relationship of the velocitiesiThe torsion angles corresponding to the segment blade profiles are as follows:
θ i =α i +arctan(V * max /(Ωr i ))；
step 14: obtaining a regular relation formula of the installation angle along with the change of the spanwise length of the blade by utilizing linear interpolation shown in the formula (8):
in the formula (8), the reaction mixture is,r i-1 is a firsti-Radius of 1 segment of blade;θ i-1 is a firsti-The twist angle corresponding to the 1-segment blade profile,θ(r, i) Is shown asiThe twist angle of the segment blade at any cross section,i=1,2, …,N。
2. the method for estimating the torsion angle of the blade of the axial-flow heat-dissipation fan for the vehicle considering the reynolds number variation as claimed in claim 1, wherein the crossing and the variation in step 11 include:
step 11.1: will be firstkGeneration groupA k() All individuals in the system are arranged according to the descending mode of the average inlet flow velocity to obtain the ordered firstkThe generation group is marked asA' k() ；
Step 11.2: will be firstkGeneration groupA' k() Middle frontM(ii) individual retention of 3, whereinMFor the total number of individuals in the population, will remainM/3~2MPerforming cross operation on 3 individuals to obtainM/3~2M(iii) 3 individuals after crossing;
step 11.3: will be firstkGeneration groupA' k() In 2M/3~MSubjecting individual to mutation to obtain 2M/3~M(ii) an individual after mutation;
step 11.4: from the firstkGeneration groupA' k() Middle frontMPer 3 individuals, the firstkGeneration groupA' k() Middle frontMA/3 individuals andkgeneration groupA' k() Middle frontMThe 3 individuals form the updated thekGeneration group
。
3. The method for estimating the torsion angle of the blade of the axial flow heat dissipation fan for the vehicle, considering the reynolds number change, according to claim 2, wherein the step 11.3 includes:
step 11.3.1: will be firstkGeneration groupA' k() In (1)M/3~MBefore replacing individualM(ii)/3 individuals;
step 11.3.2: random generationN2 pieces 1 toNIs a positive integer of (2)p 1 , p 2 ,…, p l ,…, p N/2 ]Wherein, in the step (A),p l is shown aslA random number;
step 11.3.3: according to the firstp l Reynolds number of segmentR k() pl In the parameter domainBIn which a pair of lift and drag coefficients (C L ,C D ) And replace the current secondkGeneration groupA' k() To middlem' Individual corresponding to the secondp l Segment parameter (C m k'() L pl() , C m k'() D pl() )， m' is 2M/3~MA positive integer in between, thereby completingNAnd/2 updating the parameters of the positions corresponding to the random numbers.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310054892.2A CN115796056B (en) | 2023-02-03 | 2023-02-03 | Torsion angle estimation method of automotive axial flow cooling fan blade considering Reynolds number change |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310054892.2A CN115796056B (en) | 2023-02-03 | 2023-02-03 | Torsion angle estimation method of automotive axial flow cooling fan blade considering Reynolds number change |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115796056A CN115796056A (en) | 2023-03-14 |
| CN115796056B true CN115796056B (en) | 2023-04-18 |
Family
ID=85429696
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310054892.2A Active CN115796056B (en) | 2023-02-03 | 2023-02-03 | Torsion angle estimation method of automotive axial flow cooling fan blade considering Reynolds number change |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115796056B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106919749A (en) * | 2017-02-24 | 2017-07-04 | 湖北工业大学 | A kind of low noise vane design of wind turbines method and low noise pneumatic equipment bladess |
| CN109340042A (en) * | 2018-11-19 | 2019-02-15 | 内蒙古工业大学 | Turbine blade and its design method and solar chimney electricity generation system |
| CN111859651A (en) * | 2020-07-10 | 2020-10-30 | 浙江运达风电股份有限公司 | Method for optimizing power generation performance of wind turbine generator set under low air density |
| WO2021045931A2 (en) * | 2019-08-26 | 2021-03-11 | Massachusetts Institute Of Technology | Propeller design systems and methods |
| CN114169088A (en) * | 2021-11-12 | 2022-03-11 | 华能华家岭风力发电有限公司 | Fan blade optimization design method and system based on Wilson model and genetic algorithm |
| CN114676529A (en) * | 2022-04-11 | 2022-06-28 | 哈尔滨工程大学 | Material distribution optimization method of blade model |
| CN115344963A (en) * | 2022-08-08 | 2022-11-15 | 合肥工业大学 | Efficient pump blade design method capable of meeting requirements of multiple working conditions |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10718311B2 (en) * | 2015-04-29 | 2020-07-21 | Universiti Brunei Darussalam | Low Reynolds number airfoil for a wind turbine blade and method thereof |
-
2023
- 2023-02-03 CN CN202310054892.2A patent/CN115796056B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106919749A (en) * | 2017-02-24 | 2017-07-04 | 湖北工业大学 | A kind of low noise vane design of wind turbines method and low noise pneumatic equipment bladess |
| CN109340042A (en) * | 2018-11-19 | 2019-02-15 | 内蒙古工业大学 | Turbine blade and its design method and solar chimney electricity generation system |
| WO2021045931A2 (en) * | 2019-08-26 | 2021-03-11 | Massachusetts Institute Of Technology | Propeller design systems and methods |
| CN111859651A (en) * | 2020-07-10 | 2020-10-30 | 浙江运达风电股份有限公司 | Method for optimizing power generation performance of wind turbine generator set under low air density |
| CN114169088A (en) * | 2021-11-12 | 2022-03-11 | 华能华家岭风力发电有限公司 | Fan blade optimization design method and system based on Wilson model and genetic algorithm |
| CN114676529A (en) * | 2022-04-11 | 2022-06-28 | 哈尔滨工程大学 | Material distribution optimization method of blade model |
| CN115344963A (en) * | 2022-08-08 | 2022-11-15 | 合肥工业大学 | Efficient pump blade design method capable of meeting requirements of multiple working conditions |
Non-Patent Citations (2)
| Title |
|---|
| Jianwei Ren et al..Frequency Lock-in Phenomenon of Vortex Induced Vibration of a Roating Blade considering Bending-Torsion Coupling Effect.《J.Turbomach》.2022,第第145卷卷(第第2期期),第Turbo-22-1052页. * |
| 王树杰 ; 王宽宽 ; 袁鹏 ; 于晓丽 ; 王旭超 ; .潮流能水平轴水轮机叶片扭角与弦长分布研究.中国海洋大学学报(自然科学版).2018,第48卷(第10期),第 页. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115796056A (en) | 2023-03-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109460566B (en) | Aerodynamic robust optimization design method for thick airfoil section on inner side of wind turbine blade | |
| CN111859746B (en) | Method for predicting variable working condition performance of turbomachinery based on flow field reconstruction | |
| CN112685855A (en) | Axial flow compressor blade type attack angle and drop relief angle calculation method | |
| CN112685968B (en) | Axial flow compressor pneumatic design method based on space load customization thought | |
| CN112270139B (en) | Pneumatic optimization design method for centrifugal compressor of fuel cell based on mother type library | |
| CN112031998A (en) | Wind turbine generator independent variable pitch control optimization method and system based on laser radar | |
| CN114444331A (en) | Stage characteristic matching method of multistage axial flow compressor | |
| CN106677979A (en) | Coupling optimization method for blade aerodynamic configuration and main engine operation characteristics of wind turbine | |
| CN109409019A (en) | A kind of pre-bending optimization method of pneumatic equipment bladess aerodynamic configuration | |
| CN111209638B (en) | Low wind speed wind turbine blade pneumatic design method based on operation attack angle deviation correction | |
| CN113297705A (en) | Method for predicting characteristics of gas compressor according to design indexes | |
| CN115796056B (en) | Torsion angle estimation method of automotive axial flow cooling fan blade considering Reynolds number change | |
| Bashiri et al. | Design optimization of a centrifugal pump using particle swarm optimization algorithm | |
| Wu et al. | Optimization design of axial fan blade | |
| CN117592388A (en) | CFD-based wind farm multi-machine wake simulation method | |
| CN113742861B (en) | Blade model optimization design method suitable for wind tunnel test of wind driven generator | |
| CN116822417A (en) | Wind turbine blade surface wind pressure analysis method | |
| CN116595874A (en) | Impeller mechanical performance prediction model parameter optimization method and device and storage medium | |
| Pang et al. | Intelligence algorithm for optimization design of the low wind speed airfoil for wind turbine | |
| CN113591419B (en) | Radial turbine machinery one-dimensional design evaluation and optimization method | |
| CN113294297B (en) | Variable weight adjusting method for wind turbine generator nonlinear model prediction torque control | |
| CN115392094A (en) | Turbine disc structure optimization method based on thermal coupling | |
| CN111079367A (en) | Axial flow pump spoke optimization design method suitable for different water inlet taper pipes | |
| CN113982994B (en) | Novel capacity-increasing transformation method for movable blade adjustable axial flow fan of power station | |
| CN115186401B (en) | Method for determining key angle parameters of subsonic cascade modeling of axial flow compressor |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |