A switch reluctance motor initial position detection method based on polynomial curve fitting

Abstract

The application discloses a kind of based on polynomial curve fitting switch reluctance motor initial position detection method.The method needs to obtain the inductance-rotor position characteristic of switch reluctance motor by offline measurement and constructs data table, obtains each inductance parameter of motor by pulse voltage injection method, establishes objective function by least square method using the inductance value obtained by measurement and the inductance data table constructed, further by polynomial curve fitting objective function, initial rotor position information can be quickly obtained using root formula, compared with existing switch reluctance motor initial position detection method, the present application uses simple fitting and formula calculation instead of complex iterative calculation and additional data measurement, while reducing the requirements of processor and memory, ensure the accuracy of measurement, conducive to promoting the practical application of switch reluctance motor in industry.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of motor control, and relates to a switching reluctance motor initial position detection method based on polynomial curve fitting. BACKGROUND

[0002] The switching reluctance motor has simple structure, wide speed regulation range, high temperature resistance and the like, and thus becomes a powerful competitor in the industrial field. A real-time rotor position signal is a necessary condition for the operation of the switching reluctance motor. Traditionally, the rotor position information is measured by using a position sensor. However, the accuracy of most traditional position sensors is seriously affected in a harsh environment such as high temperature, humidity, oil dirt and the like, so that the reliability of the system is reduced. In addition, since the position sensor increases an additional mechanical component, the complexity of the system is also increased. Therefore, developing a reliable position sensorless control technology is a research hotspot in the field of switching reluctance motor control.

[0003] The initial position detection of the rotor in the static state is a difficulty in the position sensorless control technology of the switching reluctance motor. The traditional initial position detection method relies on complex iterative calculation or measurement of complex parameters such as motor flux to determine the initial position of the motor. These methods not only have slow detection speed and large calculation amount, but also increase the control cost of the motor and reduce the robustness of the whole system, which brings challenges to the industrial application of the switching reluctance motor. SUMMARY

[0004] The application provides a switching reluctance motor initial position detection method based on polynomial curve fitting. The inductance parameters of the motor are obtained by using the pulse voltage injection method. The rotor position is determined according to the size of the phase inductance. The target function is established by using the measured inductance value and the existing data table, and the polynomial curve form of the target function is given. The initial rotor position information can be quickly obtained by using the root formula.

[0005] The technical scheme of the application is as follows:

[0006] The switching reluctance motor initial position detection method based on polynomial curve fitting has the following steps:

[0007] Step 1: measuring the inductance characteristics of the switching reluctance motor and constructing a data table L(θ); wherein θ is the rotor position, and L is the measured phase inductance value.

[0008] Step 2: injecting pulse voltage into each winding of the motor in the static state of the motor, and calculating the inductance values of the motor by using the given phase inductance calculation formula

[0009]

[0010] U bus , VT , V D , L cal , i ph , R, ω, θ, di ph / dt ON , di ph / dt OFF are bus voltage, power switch voltage drop and diode voltage drop, phase inductance, phase current, motor resistance, motor speed, rotor position, current slope at switch opening and closing time obtained by real-time calculation;

[0011] Step 3: According to the size relationship of the phase inductance calculated in step 2, the rotor position is determined in the electrical angle interval [a, b]; define L A , L B , L C respectively represent the A, B, C three-phase real-time inductance of the three-phase switched reluctance motor measured in step 2, when L A ≤L B ≤L C , the electrical angle interval is [0°, 60°); when L B ≤L A ≤L C , the electrical angle interval is [60°, 120); when L B ≤L C ≤L A , the electrical angle interval is [120°, 180°); when L C ≤L B ≤L A , the electrical angle interval is [180°, 240); when L C ≤L A ≤L B , the electrical angle interval is [240°, 300°; when L A ≤L C ≤L B , the electrical angle interval is [300°, 360);

[0012] Step 4: Construct a linear regression model using the measured inductance value in step 1 data table and the phase inductance obtained by real-time calculation in step 2

[0013] L cal = α + βL(θ) + ε

[0014] Where α and β are linear regression coefficients, and ε is the estimation error;

[0015] Step 5: Solve

[0016]

[0017] Residual square of linear regression model is taken as objective function

[0018]

[0019] wherein is linear regression coefficient obtained by least square method;

[0020] Step 6: polynomial form of objective function obtained in step 5 is given

[0021]

[0022] wherein k=3 is order of fitting polynomial, c is coefficient of fitting polynomial, N ph is number of phases of switched reluctance motor;

[0023] Step 7: in position interval [a, b] determined in step 3, θ1=a, θ4=b are taken respectively and brought into objective function obtained in step 5 to obtain RSS(θ1), RSS(θ2), RSS(θ3), RSS(θ4);

[0024] Step 8: polynomial coefficients of polynomial form of objective function obtained in step 6 are calculated

[0025] c=(Φ T Φ) -1 Φ T y

[0026] c=[c k c k-1 c1 c0] T

[0027] y=[RSS(θ1)RSS(θ2)...RSS(θ M )] T

[0028]

[0029] and further obtain

[0030] RSS(θ)=c k θ k +c k-1 θ k-1 +...+c1θ+c0

[0031] wherein M=4, k=3;

[0032] Step 9: root formula is used to quickly solve RSS(θ)=0 obtained by fitting in step 8, and solution in interval [a, b] is initial rotor position estimated.

[0033] Advantages

[0034] The application provides a switch reluctance motor initial position detection method based on polynomial curve fitting. The method obtains motor inductance parameters through pulse voltage injection, establishes a target function by using the measured inductance values, further fits the target function by using a polynomial curve, and quickly obtains initial rotor position information by using a root formula. Compared with the existing switch reluctance motor initial position detection method, the application uses simple polynomial fitting and formula calculation to replace the complex iterative calculation and additional data measurement of the existing switch reluctance motor initial position detection method, greatly speeds up the switch reluctance motor initial position detection, reduces the requirements for the processor and the memory, ensures the measurement accuracy, and is beneficial to promoting the practical application of the switch reluctance motor in the industry. BRIEF DESCRIPTION OF DRAWINGS

[0035] The above and / or additional aspects and advantages of the application will become apparent and be readily understood from the following description, taken in connection with the following drawings, in which:

[0036] Figure 1 ; pulse voltage injection method for calculating inductance;

[0037] Figure 2 ; error diagram of the rotor position obtained by the application and the actual rotor position in a cycle;

[0038] Figure 3 ; curve diagram of the target function in the form of a polynomial when the rotor position is 35°. DETAILED DESCRIPTION

[0039] The embodiments of the application are described in detail below, which are exemplary and are intended to explain the application, and cannot be understood as a limitation of the application.

[0040] The motor used in the example is a 1kW three-phase 12 / 8-pole switch reluctance motor.

[0041] Step 1: Measure the inductance characteristics of the switch reluctance motor and construct a data table L(θ); wherein θ is the rotor position, and L is the measured phase inductance value;

[0042] Step 2: When the two switches of the same phase foot are opened, the phase voltage equation can be represented as shown in Fig. (1)

[0043]

[0044] When the two switches of the same phase foot are opened, the phase voltage equation can be represented as

[0045]

[0046] Then we get the phase inductance calculation formula

[0047]

[0048] Among them U bus 、V T 、V D , L cal 、i ph , R, ω, θ, di ph / dt| ON 、di ph / dt| OFF They are bus voltage, power switch voltage drop and diode voltage drop, phase inductance calculated in real time, phase current, motor resistance, motor speed, rotor position, and current slope at switch opening and closing times;

[0049] Step 3: Based on the magnitude relationship of the phase inductances calculated in step 2, determine the electrical angle interval [a, b] where the rotor position is located; define L A , L B , L C They represent the real-time inductances of the three-phase A, B, and C of the three-phase switched reluctance motor measured in step 2. A ≤L B ≤L C When the electrical angle range is [0°, 60°); when L B ≤L A ≤L C When L B ≤L C ≤L A When L C ≤L B ≤L A When L C ≤L A ≤L B When the electrical angle range is [240°, 300°; when L A ≤L C ≤L B When , the electrical angle range is [300°,360);

[0050] Step 4: Use the inductance values ​​measured in the datasheet in step 1 and the phase inductance calculated in real time in step 2 to build a linear regression model

[0051] L cal =α+βL(θ)+ε

[0052] Where α and β are linear regression coefficients, and ε is the estimation error;

[0053] Step 5: Solve with least square method And the residual sum of squares of linear regression model RSS(θ) as the objective function, the specific formula is as follows

[0054]

[0055] Its gradient in the direction of α, β is zero

[0056]

[0057] Further get

[0058]

[0059] Wherein is the linear regression coefficient obtained by calculation;

[0060] Step 6: Give the target function of the fitting polynomial form

[0061]

[0062] Wherein k=3 is the order of fitting polynomial, c is the coefficient of fitting polynomial, N ph The number of phases of switched reluctance motor;

[0063] Step 7: In the inductance interval [a, b] determined in step 3, take θ1=a, θ4=b and respectively bring them into the objective function obtained in step 5 to get RSS(θ1), RSS(θ2), RSS(θ3), RSS(θ4);

[0064] Step 8: Calculate the polynomial coefficients of the polynomial form of the objective function obtained in step 6

[0065] c=(Φ T Φ) -1 Φ T y

[0066] c=[c k c k-1 c1 c0] T

[0067] y=[RSS(θ1) RSS(θ2)...RSS(θ M )] T

[0068]

[0069] Further get

[0070] RSS(θ)=c k θk c k-1 θ k-1 +...+c1θ+c0

[0071] where M=4, k=3;

[0072] Step 9: the root-finding formula is used The solution of the equation RSS(θ)=0 in the interval [a, b] is the estimated initial rotor position.

[0073] The applicant uses the method of the application to detect the initial rotor position of the motor every 12° (electrical angle) in a cycle, and the rotor position estimation error obtained is as shown in Figure 2 The initial rotor position estimation error is within 2.1° (electrical angle), which shows that the application greatly improves the detection speed while maintaining high accuracy.

[0074] Although the embodiments of the application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the application, and those of ordinary skill in the art can make changes, modifications, replacements and variations to the above embodiments without departing from the principles and spirit of the application within the scope of the application.

Claims

1. A method for detecting initial position of a switched reluctance motor based on polynomial curve fitting, characterized in that: Comprising the following steps: Step 1: Measure the inductance characteristics of the switched reluctance motor and construct a data table L(θ); Where θ is the rotor position, L is the measured phase inductance value; Step 2: Inject pulse voltage into each winding of the motor in the stationary state of the motor, and calculate the inductance value of each winding of the motor through the given phase inductance calculation formula where U bus , V T , V D , L cal , i ph , di ph / dt ON , di ph / dt OFF are bus voltage, power switch voltage drop and diode voltage drop, phase inductance obtained by real-time calculation, phase current, current slope at switch on and off time, respectively; Step 3: According to the size relationship of each phase inductance calculated in step 2, the electrical angle interval [a, b] where the rotor position is located is determined; define L A 、 B 、 C respectively represent the real-time inductance of A, B, C three phases of the switched reluctance motor measured in step 2, when L A ≤L B ≤L C , the electrical angle interval is [0°, 60°); when L B ≤L A ≤L C , the electrical angle interval is [60°, 120°); when L B ≤L C ≤L A , the electrical angle interval is [120°, 180°); when L C ≤L B ≤L A , the electrical angle interval is [180°, 240°); when L C ≤L A ≤L B , the electrical angle interval is [240°, 300°); when L A ≤L C ≤L B , the electrical angle interval is [300°, 360°). Step 4: Construct a linear regression model using the measured inductance value in the data table of step 1 and the phase inductance obtained by real-time calculation in step 2 L cal = a + bL(0) + e Where α, β are linear regression coefficients, and ε is the estimation error; Step 5: Solve for least squares Take the residual square of the linear regression model as the objective function wherein is a linear regression coefficient obtained by least square method; Step 6: Give the fitting polynomial form of the objective function obtained in step 5 where k=3 is the order of the fitting polynomial, c is the coefficients of the fitting polynomial, N ph is the number of phases of the switched reluctance motor; Step 7: In the inductance interval [a, b] determined in step 3, take θ1=a, θ4=b and respectively bring them into the objective function obtained in step 5 to obtain RSS(θ1), RSS(θ2), RSS(θ3), RSS(θ4); Step 8: Calculate the polynomial coefficients of the objective function in the polynomial form obtained in step 6 c = (Φ T Φ) -1 Φ T y y = [RSS(θ1) RSS(θ2)... RSS(θ M )] T Further get RSS(0) = c k 0 k + c k-1 0 k-1 +... + c1θ + c0 Where M=4, k=3; Step 9; Using the root formula Solve the equation RSS(0) = 0 quickly in the interval [a, b] to get the estimated initial rotor position.

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