CN110210086B - Motor electromagnetic design method based on probability analysis - Google Patents
Motor electromagnetic design method based on probability analysis Download PDFInfo
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Abstract
The invention provides a motor electromagnetic design method based on probability analysis. The invention provides a motor electromagnetic design calculation method considering material performance, processing technology, external load and other random variable fluctuation during motor electromagnetic design calculation, and relates to a motor electromagnetic design calculation method based on probability analysis. The method can be used for correctly, scientifically and objectively designing the electromagnetic scheme meeting the technical conditions and the probability requirements, the standard deviation requirement corresponding to the electromagnetic scheme can provide a basis for process design, guidance suggestions are provided for a production process, and the potential design failure rate is greatly reduced.
Description
Technical Field
The invention relates to the technical field of motors, in particular to an electromagnetic design method of a high-efficiency three-phase asynchronous motor.
Background
The electromagnetic design of the three-phase asynchronous motor is the first step of motor manufacture and is also the most critical step, and whether the motor operation performance index is qualified or not is determined. Electromagnetic design calculation of three-phase asynchronous motors goes from performing electromagnetic calculation manually (adjusting design solutions according to experience of designers), to writing computer programs and implementing automatic calculation and solution optimization for electromagnetic design processes by various methods.
The computer program is mainly based on a small and medium-sized three-phase asynchronous motor electromagnetic calculation program published in 1971 of the institute of electrical and electronics science, and the computer program is compiled according to an equivalent circuit. In 2003, a procedure for magnetic circuit correction was introduced according to the need to develop a Y3 series motor "with cold instead of hot". Later, design calculation of a rotor custom slot type is added to an electromagnetic calculation program, and a specific calculation method is shown in patent CN201110440346.X 'induction motor slot type design calculation based on slot type element combination'. And then, in the calculation of finite element simulation software such as Ansoft Maxwell and the like, in any design calculation method, the deterministic calculation is carried out on the basis of the input variable serving as the determined quantity, and the fluctuation of the material performance, the processing technology and the external load of the motor is not considered in the electromagnetic design calculation.
In patent CN 107666220A, "a robustness optimization method for an ultra-efficient ac permanent magnet synchronous motor", an optimization calculation method for a permanent magnet synchronous motor when a fixed sigma level n =3 is disclosed. The method does not take into account the fact that different production flows, sigma levels are different. Meanwhile, when the sigma level n =3 is not provided, the probability requirement corresponding to the optimal scheme is not provided, and a probability analysis model is not provided.
With the popularization of high-efficiency motors, the high-efficiency motor in China is designed to reach the IE4 level energy efficiency level at present. Due to the limitation of new materials, there is difficulty in designing super IE4 high efficiency motors with energy efficiency above one level. Also, with market demands, it is desirable to design motors with small size and high output power, which increases the difficulty of design and manufacture.
When designing an electromagnetic scheme of a limit efficiency motor or a small-volume capacity-increasing motor, input parameters are average values, and some input parameters in actual production and manufacturing are random variables and obey a certain distribution form. When the production process fluctuates, the design of the electromagnetic scheme is often failed. In view of the characteristics of the ultimate efficiency motor or the small-volume capacity-increased motor, the standard deviation requirement is more severe. Therefore, when the material performance, the processing technology and the external load of the motor fluctuate, the probability of design failure of the qualified scheme calculated by taking the input variable as the mean value tends to increase.
In view of practical requirements, people are concerned about the random characteristics of input parameters of electromagnetic design calculation programs of the motor and the standard deviation requirements corresponding to electromagnetic schemes meeting probability requirements. Therefore, how to correctly, scientifically and objectively design an electromagnetic scheme meeting technical conditions and probability requirements and how to provide a standard deviation requirement corresponding to the electromagnetic scheme is a practical problem in front of people.
Disclosure of Invention
The purpose of the invention is: the motor electromagnetic design method considering the external stress fluctuation of the motor material performance, the processing technology, the external load and the like is provided.
In order to achieve the above object, the technical solution of the present invention is to provide a motor electromagnetic design method based on probability analysis, which is characterized by comprising the following steps:
ith random variable x i Has a standard deviation of i Then there is a standard deviation vector σ = [ σ ] 1 ，σ 2 ，...，σ i ，...，σ n ] T
Ith random variable x i Has a mean value of mu i Then there is the mean vector μ = [ μ ] 1 ，μ 2 ，...，μ i ，...，μ n ] T ；
Step 4, establishing a function F k (X) to represent whether the performance index of the motor and the user specific requirement index meet the minimum requirement, wherein k =1, …, m and m are the number of the performance indexes to be subjected to probability analysis, and F k (X) ≥ 0 indicates that the kth individual performance index requirement is satisfied, F k (X) < 0 indicates that the kth individual performance index requirement cannot be met;
step 5, establishing a probability analysis model:
R k ＝P(F k (x)≥0)，R k the probability that the kth individual performance index requirement is met is obtained;
step 6, determining an algorithm used by probability analysis;
the algorithm is to select whether to perform fitting approximate model or not according to the calculation time of each running of the programmed electromagnetic design computer program. The computer program directly invoked by the invention has short calculation time (about 100 ms) and does not need to be fitted with an approximate model. The selected algorithm is the standard Monte Carlo Monte. When the electromagnetic design calculation is carried out by adopting the finite element, because the calculation time cost is higher, experimental design is preferably carried out and then an approximate model is fitted;
step 7, determining the random sampling calculation times N of each probability analysis;
step 8, calculating the probability that each performance index requirement is met according to the algorithm determined in the step 6 and the random sampling calculation times N determined in the step 7 to obtain a probability vector R, R = [ R = [ R ] ] 1 ，R 2 ，...，R k ，...，R m ] T ；
Step 9, calculating a convergence criterion:
|R k -R ko |≤ξ k in the formula, R ko Is a preset probability, namely a minimum probability set value, ξ, that the kth individual performance index value meets the requirement k Convergence accuracy when the probability value of the kth individual performance index is required to be satisfied;
step 10, starting iterative computation, judging whether a convergence criterion is satisfied, if the convergence criterion is not satisfied, adjusting X = [ X ] according to the computation result of the step 8 1 ，x 2 ，...，x i ，...，x n ] T Then, transferring to the step 2 to calculate the steps from the step 2 to the step 9 again according to the newly adjusted parameters, and if yes, executing the step 11;
step 11, calculating a guaranteed value of the motor performance:
calculating the guaranteed value of the motor performance parameter according to the lowest assessment index value iteratively calculated in the steps 2 to 10 and the electric performance tolerance requirement in the technical condition of the motor, and if the calculated guaranteed value is smaller than the guaranteed value in the technical condition or the technical protocol, transferring to the step 1 to redetermine X = [ X ] according to the newly adjusted optimization scheme 1 ，x 2 ，...，x i ，...，x n ] T Then, the calculation from the step 2 to the step 10 is carried out, and if the calculation is true, the step 12 is carried out;
step 12, outputting a calculation result:
and outputting the mean value mu of the electromagnetic structure parameters of the motor, the guaranteed value of the performance index of the motor and the standard deviation requirement of the random variable selected by the scheme.
Preferably, in step 1, a random variable vector X = [ Di1, D2, K ] calculated by electromagnetic design of three-phase asynchronous motor Fe ，R1，P Cu1 ，P Cu2 ，P Fe ，P fw ，P s ，P 2 ，Lt，kt，kc，sk]In the formula, di1 is the inner diameter of the stator, D2 is the outer diameter of the rotor, K Fe Is iron core lamination coefficient, R1 is DC steady-state resistance, P Cu1 For stator copper loss, P Cu2 For the rotor copper loss, P Fe Is core loss, P fw Is abraded by wind, P s Is stray loss, P 2 The method comprises the following steps of (1) operating load under actual working conditions, lt being the length of an iron core, kt being the iron loss coefficient of a tooth part, kc being the iron loss coefficient of a yoke part and the chute angle of a sk rotor.
Preferably, in step 4, the function F of the three-phase asynchronous motor k (X) is:
in the formula, cos' is the lowest assessment requirement of the initial power factor,
as a function of power factor with respect to X; eta' is the minimum assessment requirement of the initial efficiency, and eta (X) is a function of the efficiency on X; ist' is the maximum assessment requirement of the initial starting current multiple, and Ist (X) is a function of the starting current multiple on X; tst' is the lowest assessment requirement of the initial starting torque multiple, and Tst (X) is a function of the starting torque multiple with respect to X; tm' is the lowest assessment requirement of the initial maximum torque multiple, and Tm (X) is a function of the maximum torque multiple relative to X; k is the minimum power factor to efficiency product required by the user protocol.
Preferably, in step 5, the probability analysis model during electromagnetic design calculation of the three-phase asynchronous motor is as follows:
preferably, in step 10, X = [ X ] is adjusted 1 ，x 2 ，...，x i ，...，x n ] T Refers to adjusting one or more random variables according to the following step principle and priority:
1) Adjusting standard deviation sigma, starting iteration from a lower sigma level, and performing iterative calculation until all performance index requirements are met k Are all greater than a set probability Rko.
2) Adjusting the process coefficient mean value mu, starting iteration from the process level coefficient mean value which is easy to realize, and gradually increasing the process level coefficient as much as possible according to the mean value sensitivity and practical experience of the previous step, thereby achieving the purpose of reducing the sigma level corresponding to convergence or increasing the probability value that the performance index meets the requirement at the same sigma level;
3) And adjusting the lowest assessment index parameter, starting from the performance index which firstly meets the probability requirement, gradually reducing the assessment value from the assessment value with higher requirement, starting iteration, and performing iterative calculation until the performance index probability analysis model meets the probability requirement.
According to the above method, a person skilled in the art can program an electromagnetic design computer program comprising the following: 1) The main input parameters are electromagnetic structure parameters, material numbers, process coefficients, estimated per unit values of all losses and the like; 2) Mainly outputting intermediate parameters as calculation data of a circuit, a magnetic circuit and the like; 3) The main output results are performance parameters of the motor and the like; 4) The program can calculate different electromagnetic schemes by changing the input parameters according to the electromagnetic scheme adjustment measures. 5) All variables with random properties must be defined as double precision data types.
The invention provides a motor electromagnetic design calculation method considering material performance, processing technology, external load and other random variable fluctuation during motor electromagnetic design calculation, and relates to a motor electromagnetic design calculation method based on probability analysis. The method can be used for correctly, scientifically and objectively designing the electromagnetic scheme meeting the technical conditions and the probability requirements, the standard deviation requirement corresponding to the electromagnetic scheme can provide a basis for process design, guidance suggestions are provided for a production process, and the potential design failure rate is greatly reduced.
Adopt the produced beneficial effect of above-mentioned technical scheme to lie in: a probability analysis model R of a three-phase asynchronous motor electromagnetic scheme is established k ＝P(F k (x) Not less than 0); the method for calculating the electromagnetic design of the motor when the external stress such as the material performance, the processing technology, the external load and the like of the motor randomly fluctuates is provided; the method can correctly, scientifically and objectively design the product which meets the technical conditions and probability requirementsThe electromagnetic scheme of (1); the standard deviation requirement corresponding to the electromagnetic scheme can provide reference basis for process design, guidance suggestion for production process, and measured data of production and processing can be used as input data of electromagnetic calculation. According to a data flow diagram (see figure 2), the random variables selected by electromagnetic calculation can realize the loop iterative calculation of 'electromagnetic design-process design-production processing' along with the data flow diagram, realize the continuous correction of the standard deviation of the random variables selected by calculation, design an electromagnetic design scheme which is more in line with the production and manufacturing quality level of enterprises, and greatly reduce the potential design failure rate.
Drawings
FIG. 1 is a block diagram of an electromagnetic design calculation process of the present invention;
FIG. 2 is a flow diagram of the random variable data flow of the present invention;
FIG. 3 is a result of the analysis calculation according to the calculation of (1) in step 11) in the embodiment;
FIG. 4 is a graph of the mean sensitivity at analysis "3 σ" by calculation steps 1-6.
Detailed Description
The invention is further elucidated below with reference to the accompanying drawing. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Further, it should be understood that various changes or modifications of the present invention may be made by those skilled in the art after reading the teaching of the present invention, and such equivalents may fall within the scope of the present invention as defined in the appended claims.
As shown in FIG. 1, a method for calculating electromagnetic design of motor based on probability analysis. The method considers the motor material performance, the processing technology, the external load and other external stress fluctuation, can design an electromagnetic scheme meeting the technical conditions and the probability requirements, can provide a basis for the process design by using the standard deviation requirement corresponding to the electromagnetic scheme, provides guidance suggestions for the production process, and greatly reduces the potential design failure rate. The design method comprises the following steps:
1) And programming an electromagnetic design computer program.
A computer program for writing electromagnetic design calculations should contain the following contents and functions: the main input parameters are electromagnetic structure parameters, material numbers, process coefficients, estimated per unit values of loss and the like; mainly outputting intermediate parameters as calculation data of a circuit, a magnetic circuit and the like; the main output results are performance parameters of the motor and the like; all variables with random properties must be defined as double-precision data types; the input parameters can be changed according to the electromagnetic scheme adjustment measures, and different electromagnetic schemes can be obtained through calculation of the program. A more feasible solution is selected as the further accounting solution.
2) Determining a random variable vector X = [ X ] 1 ，x 2 ，...，x n ] T 。
According to the requirements of motor patterns, technical conditions, practical experience of the manufacturing process and the like, determining that the variable which is sensitive to influence performance indexes in the input variables of the motor electromagnetic design scheme is a random variable x i And obtaining a random variable vector:
X＝[x 1 ，x 2 ，...，x n ] T
x i i = 1.. N, which is some input parameter of the computer program.
The variables which influence the performance index more sensitively are selected as random variables, namely the selected random variables slightly fluctuate and the performance index fluctuates greatly. Obviously, the power factor of the motor is greatly influenced by the stator and rotor core air gap delta = Di1-D2 and the core lamination coefficient; losses of electric machines
P Total loss ＝P Cu1 +P Cu2 +P fw +P Fe +P s The influence on the efficiency is large; the load size matched with the actual working condition of the motor is sensitive to the influence of efficiency and power factor.
According to the debugging experience of an electromagnetic scheme, the inner diameter Di1 of the stator, the outer diameter D2 of the rotor and the iron core lamination coefficient K can be taken as main random variables Fe DC steady state resistance R1, stator copper loss P Cu1 Rotor copper loss P Cu2 Core loss P Fe Wind and wind abrasion P fw Stray loss P s And the actual workerLive operating load P 2 One or more of the core length Lt, the tooth portion iron loss coefficient kt, the yoke portion iron loss coefficient kc, the rotor skewed slot angle sk, and the like. The direct current steady-state resistor R1 can indirectly serve as a random input variable by using the length d of the straight part of the winding extending out of the iron core.
3) Determining random variables x i The type of distribution and its distribution parameters.
The random characteristics of all main influence factors are fully considered, and the distribution type and the distribution parameters are determined by combining the existing measurement data and utilizing distribution fitting and parameter inspection. When actual measurement data is not obtained, the embodiment of the invention assumes each random variable x i Obeying a normal distribution.
4) Setting the lowest performance parameter index of motor (about the value after eating tolerance) and setting the selected input random variable x i Standard deviation of (a):
σ＝[σ 1 ，σ 2 ，...，σ n ] T
σ i i = 1.. N, is the standard deviation of the ith random variable.
Initially setting the selected input random variable x i Mean value:
μ＝[μ 1 ，μ 2 ，...，μ n ] T
μ i i = 1.. N, which is the mean of the ith random variable.
Without statistical data, the initial value of the standard deviation can be iteratively calculated starting from a lower sigma level, up to no more than a six sigma level. If the statistical data exists, the mean value and the standard deviation of actual measurement are used, and the production flow does not need to be changed when the production flow is not changed.
5) Establishing a function F k (X)。
Establishing a function F k (X) to characterize whether the motor performance indicator and the user specific requirement indicator meet minimum requirements, where k = 1. m is a performance index to be subjected to probability analysisNumber of labels, F k (X) ≥ 0 indicates that the kth individual performance index requirement is satisfied, F k (X) < 0 indicates that the kth performance index requirement cannot be satisfied.
And (3) selecting performance parameters with small design margin, important customer attention and special requirements and guaranteed specific working conditions to establish a functional function according to the deterministic design calculation result in the step 1). Setting the probability R that the function meets the requirement ko 。
In this embodiment 1, it is mainly considered whether the power factor, the efficiency, and the product value of the power factor and the efficiency required by the user meet the minimum assessment requirement. Therefore, the following formula (1) is adopted as the function F k (X) characterizing whether these design requirements are met. When F is present k (X) ≥ 0 the design requirement is considered to be met, F k (X) < 0 the design requirement was not satisfied.
The function is established as follows:
in the formula, cos' is the lowest assessment requirement of the initial power factor; eta' is the minimum assessment requirement of the initial efficiency; k is the minimum power factor to efficiency product requirement suggested by the user protocol.
6) Establishing a probability analysis model R k ＝P(F k (X)≥0)。
The probability that the motor performance index and the user-specified requirement index are met is
R k ＝P(F k (X)≥0)
R k I.e. the probability that the kth performance index requirement is met, should be greater than or equal to the probability R designed by the engineer or requested by the customer ko 。
According to the probability design principle of general electromechanical products, the invention divides the probability grade of the motor performance index and the user specific requirement index into 7 grades, so that R is ko The values of (a) can be selected from table 1 according to actual needs.
TABLE 1 probability level that motor performance index and user specific requirement index are met
The probability analysis model is established as follows:
the corresponding probability requirement is taken from table 1:
in the formula, R1o is the lowest probability that the power factor meets the design requirement; r2o is the lowest probability that the efficiency meets the design requirement; and R3o is the lowest probability that the product value of the power factor and the efficiency meets the design requirement.
7) An algorithm is selected.
And selecting whether to perform fitting approximation model or not according to the running calculation time of the programmed electromagnetic design computer program each time. The computer program directly invoked by the invention has short calculation time (about 100 ms) and does not need to be fitted with an approximate model. The algorithm chosen was the standard Monte Carlo. When the electromagnetic design calculation is carried out by adopting the finite element, because the calculation time cost is higher, the experimental design is preferably carried out and then the approximate model is fitted.
8) And determining the random sampling calculation times N of each probability analysis. Each probability analysis was performed with N sampled electromagnetic calculations.
9) Calculating the probability:
R＝[R1，R2，...，Rm] T
10 Computing a convergence criterion:
|R k -R ko |≤ξ k
ξ k namely the convergence accuracy when the kth individual performance index requires that its probability value be satisfied. According to the iteration convergence precision requirement, the parameter xi can be adjusted k Size.
11 Start iterative computation. Decision convergence criterion | R k -R ko |≤ξ k Whether or not this is true.
And if the convergence criterion is not satisfied, adjusting the input parameters according to the calculation result of the step 9). And (5) transferring to the step 2) to calculate 2) to 10) again according to the newly adjusted parameters.
Adjusting the input parameters is adjusting one or more input parameters according to the following step principle and priority:
(1) the standard deviation σ is adjusted. Starting iteration from a lower sigma level, and carrying out iterative calculation until the probability R of all the performance index requirements is met k Are all greater than a set probability R ko 。
(2) And adjusting the process coefficient mean value mu. The iteration starts with the mean of the process level coefficients, which is easier to implement. And gradually increasing the process level coefficient as much as possible according to the average value sensitivity and practical experience of the previous step, thereby achieving the purpose of reducing the sigma level corresponding to the convergence, or increasing the probability value that the performance index meets the requirement at the same sigma level.
(3) And adjusting the minimum assessment index parameters. Starting from the performance index which meets the probability requirement firstly, iteration is started by gradually reducing the assessment value from the assessment value with higher requirement. And iterating until the performance index probability analysis model meets the probability requirement.
If yes, the following steps are executed.
12 Computing a guaranteed value of motor performance.
And calculating the guaranteed value of the motor performance parameter according to the lowest assessment index value iteratively calculated in the steps 2) to 11) and the electric performance tolerance requirement in the motor technical condition. If the calculated guaranteed value is smaller than the guaranteed value in the technical condition or the technical protocol, the step 1) is shifted to calculate 1) to 12) again according to the newly adjusted optimization scheme. If yes, the following steps are executed.
13 Output the calculation result.
And outputting the mean value mu of the electromagnetic structure parameters of the motor, the guaranteed value of the performance index of the motor and the standard deviation requirement of the random variable selected by the scheme.
Example 1:
the above-mentioned electromagnetic design calculation method is readily apparent to those skilled in the art, and an example is described below to illustrate the calculation process of the method. The method is applied to the design process of a non-standard high-efficiency three-phase asynchronous motor, the mass production cost is considered, and the punching sheet material is 50W470.
Motor power: 4kW, pole count: 4.
1) Performing deterministic scheme calculation by using a written electromagnetic design computer program, and calculating a performance parameter calculation value of the obtained scheme: efficiency η =91.81%; power factor
The technical protocol requires an efficiency guarantee value of 91.5%; power factor guaranteed value of
User agreement suggested power factor and efficiency product minimum: 0.726.
2) Determining a random variable vector X = [ K ] Fe ，Di1，D2，Ps，P 2 ] T
3) Random vector X = [ K ] Fe ，Di1，D2，Ps，P 2 ] T 。
K Fe ∈[0.96，0.98]；
P 2 ∈[3.8，4.2]；
P s ∈[0.01333，0.01667]。
Assume each random variable x i The distribution forms all follow normal distribution. P s A per unit value representing the stray loss.
4) Initial minimum efficiency eta min =90.628%, the lowest value cos of the initial power factor min =0.7867. Minimum product of power factor and efficiency required by user protocol: 0.726. initially set input random variable x i The production quality level of (1 a). Initially setting selected input random variable x i Mean value of
μ＝[μK Fe ，μDi1，μD2，μP s ，μP 2 ] T ＝[0.96，115.0215，114.2175，0.015，4] T 。
5) Function F k (X)：
6) And (3) probability analysis model:
the corresponding probability requirement is taken from table 1:
7) The algorithm is as follows: standard monte carlo method.
8) Determining the random sampling times: 10 ten thousand times.
9) Calculating the corresponding probability values at different production quality levels: see table 2 for probability calculation values.
10 ) convergence judgment.
11 Output the result:
(1) minimum value of efficiency eta min =91.3%; lowest value of power factor cos min ＝0.788。
(2) Guaranteed value of efficiency
Guaranteed value of power factor
In order to ensure that the product testing performance does not have tolerance, the recommended efficiency guarantee value is 91.5 percent, and the recommended power factor guarantee value is 0.80 percent. The efficiency and the power factor guarantee value meet the technical protocol requirements.
(3) Minimum value K of product of power factor and efficiency required by user protocol min ＝0.726。
(4) The recommended minimum production quality level requirement is "2.9 σ".
(5) Inputting a mean value of a random variable vector: μ = [ μ K Fe ，μDi1，μD2，μP s ，μP 2 ] T
＝[0.97，115.0215，114.2175，0.015，4] T 。
The corresponding standard deviation requirement:
12 A calculation and analysis report is shown in table 2.
TABLE 2 calculation and analysis report sheet
Claims (5)
1. A motor electromagnetic design method based on probability analysis is characterized by comprising the following steps:
step 1, determining a random variable vector X = [ X ] calculated by electromagnetic design of a motor 1 ，x 2 ，...，x i ，...，x n ] T In the formula, x i Expressing the ith random variable, wherein the random variable is a variable which is relatively sensitive to influence performance indexes in the input variables of the motor electromagnetic design scheme according to the motor pattern, technical conditions and practical experience requirements of the manufacturing process;
step 2, determining the distribution type and the distribution parameters of each random variable in the random variable vector X;
step 3, setting the lowest indexes of the performance parameters of the motor in advance, setting the standard deviation and the mean value of each selected random variable in advance:
ith random variable x i Has a standard deviation of i Then there is a standard deviation vector σ = [ σ ] 1 ，σ 2 ，...，σ i ，...，σ n ] T
Ith random variable x i Has a mean value of mu i Then there is a mean vector μ = [ μ ] 1 ，μ 2 ，...，μ i ，...，μ n ] T ；
Step 4, establishing a function F k (X) to represent whether the motor performance index and the user specific requirement index meet the minimum requirement, wherein k =1, …, m, m is the number of performance indexes to be subjected to probability analysis, and F k (X) ≥ 0 indicates that the kth individual performance index requirement is satisfied, F k (X) < 0 indicates that the kth individual performance index requirement cannot be met;
step 5, establishing a probability analysis model:
R k ＝P(F k (x)≥0)，R k the probability that the kth individual performance index requirement is met is obtained;
step 6, determining an algorithm used by probability analysis;
step 7, determining the random sampling calculation times N of each probability analysis;
step 8, calculating the probability that each performance index requirement is met according to the algorithm determined in the step 6 and the random sampling calculation times N determined in the step 7 to obtainTo the probability vector R, R = [) 1 ，R 2 ，...，R k ，...，R m ] T ；
Step 9, calculating a convergence criterion:
|R k -R ko |≤ξ k in the formula, R ko Is a preset probability, namely a minimum probability set value, xi, that the k individual performance index value meets the requirement k The convergence accuracy when the k individual performance index requires that the probability value thereof is satisfied;
step 10, starting iterative computation, determining whether a convergence criterion is satisfied, if the convergence criterion is not satisfied, adjusting X = [ X ] according to the computation result of the step 8 1 ，x 2 ，...，x i ，...，x n ] T Then, transferring to the step 2 to calculate the steps from the step 2 to the step 9 again according to the newly adjusted parameters, and if yes, executing the step 11;
step 11, calculating a guaranteed value of the motor performance:
calculating the guaranteed value of the motor performance parameter according to the lowest assessment index value iteratively calculated in the steps 2 to 10 and the electric performance tolerance requirement in the technical condition of the motor, and if the calculated guaranteed value is smaller than the guaranteed value in the technical condition or the technical protocol, transferring to the step 1 to redetermine X = [ X ] according to the newly adjusted optimization scheme 1 ，x 2 ，...，x i ，...，x n ] T Then, the calculation from the step 2 to the step 10 is carried out, if yes, the step 12 is carried out;
step 12, outputting a calculation result:
and outputting the mean value mu of the electromagnetic structure parameters of the motor, the guaranteed value of the performance index of the motor and the standard deviation requirement of the random variable selected by the scheme.
2. The method for designing the electromagnetism of the motor based on the probability analysis as claimed in claim 1, wherein in the step 1, the random variable vector X = [ Di1, D2, K ] calculated by the electromagnetism design of the three-phase asynchronous motor Fe ，R1，P Cu1 ，P Cu2 ，P Fe ，P fw ，P s ，P 2 ，Lt，kt，kc，sk]In the form ofIn the formula, di1 is the inner diameter of the stator, D2 is the outer diameter of the rotor, and K Fe Is iron core lamination coefficient, R1 is DC steady-state resistance, P Cu1 For stator copper loss, P Cu2 For the rotor copper loss, P Fe Is core loss, P fw Is abraded by wind, P s Is stray loss, P 2 The method comprises the following steps of (1) operating load under actual working conditions, lt being the length of an iron core, kt being the iron loss coefficient of a tooth part, kc being the iron loss coefficient of a yoke part and the chute angle of a sk rotor.
3. The method for designing an electromagnetic motor based on probability analysis as claimed in claim 2, wherein in step 4, the function F of the three-phase asynchronous motor is k (X) is:
in the formula, cos' is the lowest assessment requirement of the initial power factor,
as a function of power factor with respect to X; eta' is the minimum assessment requirement of the initial efficiency, and eta (X) is a function of the efficiency on X; ist' is the maximum assessment requirement of the initial starting current multiple, and Ist (X) is a function of the starting current multiple on X; tst' is the lowest assessment requirement of the initial starting torque multiple, and Tst (X) is a function of the starting torque multiple with respect to X; tm' is the lowest assessment requirement of the initial maximum torque multiple, and Tm (X) is a function of the maximum torque multiple relative to X; k is the minimum power factor to efficiency product required by the user protocol.
4. The method for designing the motor electromagnetism based on the probability analysis as claimed in claim 3, wherein in the step 5, the probability analysis model in the electromagnetic design calculation of the three-phase asynchronous motor is as follows:
5. the method for designing an electromagnetic motor based on probability analysis as claimed in claim 1, wherein in step 10, X = [ X ] is adjusted 1 ,x 2 ,…,x i ,…,x n ] T Refers to adjusting one or more random variables according to the following step principle and priority:
1) Adjusting standard deviation sigma, starting iteration from a lower sigma level, and performing iterative calculation until all performance index requirements are met k Are all greater than a set probability Rko;
2) Adjusting the process coefficient mean value mu, starting iteration from the process level coefficient mean value which is easy to realize, and gradually increasing the process level coefficient as much as possible according to the mean value sensitivity and practical experience of the previous step, thereby achieving the purpose of reducing the sigma level corresponding to convergence or increasing the probability value that the performance index meets the requirement at the same sigma level;
3) And adjusting the lowest assessment index parameter, starting from the performance index which firstly meets the probability requirement, gradually reducing the assessment value from the assessment value with higher requirement, starting iteration, and performing iterative calculation until the performance index probability analysis model meets the probability requirement.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101783643A (en) * | 2009-01-20 | 2010-07-21 | 包头长安永磁电机研发有限公司 | Permanent magnetic brushless constant voltage generator and voltage stabilizing method thereof |
| CN104767344A (en) * | 2015-04-14 | 2015-07-08 | 上海电机***节能工程技术研究中心有限公司 | Method for eliminating vibration of PWM powered brushless direct current motor through frequency calculation |
| CN105281467A (en) * | 2015-09-25 | 2016-01-27 | 南昌康富科技股份有限公司 | Generator capable of long-term grid-connected operation |
| CN105701297A (en) * | 2016-01-14 | 2016-06-22 | 西安电子科技大学 | Multi-point adaptive proxy model based electromechanical coupling design method of reflector antenna |
| CN107633144A (en) * | 2017-09-25 | 2018-01-26 | 湖南大学 | Large-scale permanent-magnetic wind driven generator Parameters design based on electromagnetism Thermal-mechanical Coupling field |
| WO2018032052A1 (en) * | 2016-08-16 | 2018-02-22 | Macquarie University | Optimisation of designs of electromagnetic devices |
| CN108900132A (en) * | 2018-06-29 | 2018-11-27 | 南京理工大学 | Switch reluctance motor control method based on genetic algorithm and torque partition function |
| CN109600006A (en) * | 2018-11-30 | 2019-04-09 | 浙江大学 | A kind of method for solving for surface-mounted permanent magnet machine electromagnetic design |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB0314550D0 (en) * | 2003-06-21 | 2003-07-30 | Weatherford Lamb | Electric submersible pumps |
-
2019
- 2019-05-20 CN CN201910418520.7A patent/CN110210086B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101783643A (en) * | 2009-01-20 | 2010-07-21 | 包头长安永磁电机研发有限公司 | Permanent magnetic brushless constant voltage generator and voltage stabilizing method thereof |
| CN104767344A (en) * | 2015-04-14 | 2015-07-08 | 上海电机***节能工程技术研究中心有限公司 | Method for eliminating vibration of PWM powered brushless direct current motor through frequency calculation |
| CN105281467A (en) * | 2015-09-25 | 2016-01-27 | 南昌康富科技股份有限公司 | Generator capable of long-term grid-connected operation |
| CN105701297A (en) * | 2016-01-14 | 2016-06-22 | 西安电子科技大学 | Multi-point adaptive proxy model based electromechanical coupling design method of reflector antenna |
| WO2018032052A1 (en) * | 2016-08-16 | 2018-02-22 | Macquarie University | Optimisation of designs of electromagnetic devices |
| CN107633144A (en) * | 2017-09-25 | 2018-01-26 | 湖南大学 | Large-scale permanent-magnetic wind driven generator Parameters design based on electromagnetism Thermal-mechanical Coupling field |
| CN108900132A (en) * | 2018-06-29 | 2018-11-27 | 南京理工大学 | Switch reluctance motor control method based on genetic algorithm and torque partition function |
| CN109600006A (en) * | 2018-11-30 | 2019-04-09 | 浙江大学 | A kind of method for solving for surface-mounted permanent magnet machine electromagnetic design |
Non-Patent Citations (3)
| Title |
|---|
| Induction motor electromagnetic design optimization: Hooke Jeeves method versus genetic algorithms;Lucian Tutelea 等;《2010 12th International Conference on Optimization of Electrical and Electronic Equipment》;20100715;第485-492页 * |
| 基于ANSYS的永磁同步电机场路结合电磁设计方法;王建辉 等;《电机与控制应用》;20190510;第46卷(第5期);第17-24页 * |
| 电动汽车永磁同步驱动电机电磁热设计研究;张斌;《中国博士学位论文全文数据库工程科技Ⅱ辑》;20160715(第7期);C035-25 * |
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