Rotary transformer software decoding method and system considering measurement bias error

Abstract

The invention discloses a rotary transformer software decoding method and system considering a measurement bias error, relates to the technical field of motor control, and solves the problem that the angular frequency and position of a rotor fluctuate due to bias of an output signal of a rotary transformer in the existing software-based demodulation technology of the rotary transformer. The method comprises the following steps: obtaining a rotor position estimation error signal considering a measurement bias error, multiplying the rotor position estimation error signal with an excitation signal, and obtaining a bias error signal caused by the measurement bias error through a low-pass filter; inputting the bias error signal to a second-order generalized integrator to obtain two orthogonal bias error signals; transforming the two orthogonal bias error signals into a dq-axis coordinate system by utilizing coordinate transformation, and converting the two orthogonal bias error signals into direct current bias error signals; and estimating the direct-current bias error signal by using an integral controller to obtain an estimated measurement bias error signal, and compensating the estimated measurement bias error signal into an output signal of the rotary transformer to finish decoding. The method is applied to the fields of equipment manufacturing and military aerospace.

Description

Technical Field

[0001] The invention relates to the technical field of motor control, and in particular to a software decoding method for a rotary transformer taking measurement bias error into consideration. Background Art

[0002] Permanent magnet synchronous motors are widely used in various fields of AC motor speed control systems due to their simple structure, high reliability, high power density and efficiency. With the continuous development of high-performance industrial control occasions such as equipment manufacturing, military and aerospace, higher and higher requirements are put forward for permanent magnet synchronous motor drive systems. Accurate rotor position and speed are crucial for advanced motor control. There are many position sensors at present. Among these sensors, resolvers are widely used in permanent magnet synchronous motor drivers due to their inherent characteristics such as easy installation, strong anti-interference ability and wide temperature range. The rotor position is usually obtained by the resolver digital conversion process of demodulating the resolver output signal. Although using hardware chips to complete this process provides a simple method, it increases the cost of industrial application. Therefore, algorithm-based software decoding technology is the current research focus. It can be integrated in the processor together with the motor control algorithm to realize the demodulation of rotor position and speed with low-cost hardware. However, there are many non-ideal factors in the resolver digital conversion system, such as excitation distortion, amplitude imbalance, sampling offset error, reference phase shift and imperfect orthogonality. These interferences may reduce the accuracy of the estimated rotor position, resulting in sinusoidal ripples in the estimated rotor position and speed.

[0003] The requirements for resolver software demodulation in high-performance control applications include: simple algorithm, small processor computational burden, easy implementation, and reducing the impact of system non-ideal factors on the estimated rotor speed and position. However, the traditional resolver software demodulation algorithm has the following problems:

[0004] Due to the influence of the bias circuit and sampling circuit, the output signal of the secondary winding of the resolver contains a measurement bias error. The sinusoidal disturbance caused by the measurement bias error is inevitably reflected in the measured rotor angular frequency and position through the PI controller, causing the rotor angular frequency and position to fluctuate at the same frequency. When the measured rotor angular velocity and position are used in the permanent magnet synchronous motor drive system, it will affect the control performance of the motor, making it difficult to achieve high-precision control of the permanent magnet synchronous motor. Summary of the invention

[0005] Aiming at the problem that the output signal of the rotary transformer is biased, which causes the rotor angular frequency and position to fluctuate in the existing rotary transformer demodulation technology based on software, the present invention proposes a rotary transformer software decoding method which takes the measurement bias error into consideration.

[0006] A software decoding method for a rotary transformer taking into account a measurement bias error is described in the present invention, using a permanent magnet synchronous motor to obtain a rotor position signal, and the method comprises:

[0007] Step S1: According to the theoretical derivation process of the resolver software decoding strategy, the rotor position estimation error signal e is obtained taking into account the measurement bias error. θ ;

[0008] Step S2: Estimate the error signal e according to the rotor position θ Multiplying with the excitation signal and passing through a low-pass filter, the bias error signal caused by the measurement bias error is obtained;

[0009] Step S3: inputting the bias error signal into a second-order generalized integrator to generate a 90° phase shift, thereby obtaining two orthogonal bias error signals;

[0010] Step S4: transforming the two orthogonal bias error signals into the dq axis coordinate system by using coordinate transformation, and transforming the AC bias error signal into a DC bias error signal;

[0011] Step S5: using an integral controller to estimate the DC bias error signal, obtaining an estimated measurement bias error signal, and compensating the estimated measurement bias error signal to the resolver output signal to complete decoding.

[0012] Furthermore, a preferred method is proposed, wherein step S1 comprises:

[0013]

[0014] Among them, LPF[] is a low-pass filter for the signal in the brackets, U exc The excitation signal generator provides an excitation signal to the primary winding, e is the error signal, K R is the ratio of the resolver, U E is the excitation signal amplitude, θ m is the actual rotor position, To estimate the rotor position signal, e O is the error signal caused by the measurement offset error, ω e is the angular frequency of the excitation signal.

[0015] Furthermore, a preferred method is proposed, wherein the error signal e is calculated based on the actual output signal of the secondary winding and the estimated rotor position signal It is obtained by multiplying the sine and cosine values ​​and then taking the difference.

[0016] Furthermore, a preferred method is proposed, wherein step S2 comprises:

[0017] When the estimated rotor position is consistent with the actual position, Then the position error signal e θ for:

[0018] e θ ≈LPF[e O U E sin(ω e t)]

[0019] The position error signal and the excitation signal U exc Multiply and demodulate again through the filter to get the error signal e caused by the measurement offset error O :

[0020]

[0021] Among them, O sin and O cos Represents the measured offset error of the two outputs of the resolver secondary winding.

[0022] Furthermore, a preferred method is proposed, in which the second-order generalized integrator in step S3 is:

[0023]

[0024] Among them, G α (s) is the output signal e α and the input signal e O The transfer function between β (s) is the output signal e β and the input signal e O The transfer function between α and e β are the two output signals of the second-order generalized integrator, e O is the input signal of the second-order generalized integrator, K S is the control gain of the second-order generalized integrator, ω m is the mechanical angular velocity of the rotor, and s is a frequency domain variable.

[0025] Furthermore, a preferred method is proposed, wherein step S4 comprises:

[0026] The two orthogonal signals obtained by the second-order generalized integrator are transformed from the two-term stationary coordinate system to the two-phase rotating coordinate system by coordinate transformation to obtain the DC signal:

[0027]

[0028] Among them, e d and e q Represents the DC error signal obtained after coordinate transformation.

[0029] Furthermore, a preferred embodiment is proposed, wherein step S5 comprises:

[0030] The DC error signal is regulated by an integral controller, and the output regulated signal is the estimated measurement bias error signal compensation term:

[0031]

[0032] in, and K represents the estimated value of the measured offset error of the two outputs of the resolver secondary winding, si and K ci represents the gain coefficients of the two integral controllers.

[0033] Based on the same inventive concept, the present invention also proposes a resolver software decoding system taking into account the measurement bias error, the system comprising:

[0034] The rotor position estimation error signal acquisition unit is used to obtain the rotor position estimation error signal e considering the measurement bias error according to the theoretical derivation process of the resolver software decoding strategy. θ ;

[0035] A bias error signal acquisition unit is used to estimate the error signal e according to the rotor position θ Multiplying with the excitation signal and passing through a low-pass filter, the bias error signal caused by the measurement bias error is obtained;

[0036] A second-order generalized integrator processing unit, used for inputting the bias error signal into the second-order generalized integrator to generate a 90° phase shift, thereby obtaining two orthogonal bias error signals;

[0037] A transformation unit, used to transform the two orthogonal bias error signals into a dq axis coordinate system by using coordinate transformation, and to transform the AC bias error signal into a DC bias error signal;

[0038] The compensation unit is used to estimate the DC bias error signal by using an integral controller, obtain an estimated measurement bias error signal, and compensate the estimated measurement bias error signal to the resolver output signal to complete decoding.

[0039] Based on the same inventive concept, the present invention also proposes a computer device, including a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes a software decoding method for a rotary transformer taking into account a measurement bias error as described in any one of the above items.

[0040] Based on the same inventive concept, the present invention also proposes a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of a software decoding method for a rotary transformer taking into account a measurement bias error as described in any one of the above items are executed.

[0041] The present invention is beneficial in that:

[0042] The present invention proposes a method for software decoding of a rotary transformer that takes into account the measurement bias error. By taking into account the measurement bias error, the decoding accuracy of the rotor position can be significantly improved, and the error caused by signal bias can be reduced. Furthermore, the method proposed in the present invention has strong adaptability and can be applied to different types of rotary transformers, especially those that are easily affected by bias when working under a high dynamic range. By adopting real-time bias error compensation technology, the output signal can be dynamically adjusted to make the decoding process more stable. By using a low-pass filter and a second-order generalized integrator, noise suppression is ensured during the signal processing process, which helps to improve the anti-interference ability of the overall system. Through the optimization of mathematical models and algorithms, the complexity of the entire decoding process is reduced, which is easy to implement and maintain.

[0043] The present invention proposes a method for software decoding of a rotary transformer taking into account the measurement bias error. The method demodulates the rotor position error signal to obtain an error signal caused by the measurement bias, and uses a second-order generalized integrator to generate a 90° phase shift on the sinusoidal error signal, thereby obtaining two orthogonal signals. The orthogonal error signal can be transformed into a DC error signal by coordinate transformation. Finally, an integral controller is used to estimate the DC error signal and compensate it to the output signal of the rotary transformer, so as to reduce the influence of the measurement bias error on the rotor angular frequency and position estimation deviation, reduce the first harmonic in the motor rotor position and speed, and improve the motor control performance.

[0044] Compared with the traditional resolver software decoding method, the method of the present invention can effectively compensate for the bias error and suppress the sinusoidal fluctuations in the motor speed and rotor position error signals. For example, when the motor speed is the rated speed of 3000r / min, the motor angular velocity fluctuation is reduced from 8rad / s to 3rad / s, and the rotor position error fluctuation is reduced from 3° to 1°. When the motor speed is 50% of the rated speed of 1500r / min, the motor angular velocity fluctuation is reduced from 6rad / s to 3rad / s, and the rotor position error fluctuation is reduced from 3° to 1°.

[0045] The present invention is applied to industrial control fields such as equipment manufacturing, military industry, aerospace, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1This is a structural block diagram of a software decoding method for a rotary transformer taking into account a measurement bias error according to an eleventh embodiment;

[0047] Figure 2 This is a structural block diagram of the measurement bias error adaptive compensation method described in Implementation Example 11;

[0048] Figure 3 This is a flow chart of the measurement bias error adaptive compensation method described in Embodiment 11;

[0049] Figure 4 is a structural block diagram of the second-order generalized integrator described in Embodiment 11;

[0050] Figure 5 The Bode diagram of the closed-loop transfer function of the second-order generalized integrator according to the eleventh embodiment, wherein Figure (a) is a logarithmic amplitude-frequency characteristic curve of the closed-loop transfer function of the second-order generalized integrator, and Figure (b) is a logarithmic phase-frequency characteristic curve of the closed-loop transfer function of the second-order generalized integrator;

[0051] Figure 6 The experimental results of the rotary transformer software decoding system based on the measurement bias error compensation method described in the eleventh embodiment at a speed of 3000r / min;

[0052] Figure 7 The FFT analysis result of the motor speed waveform at the rated speed of 3000r / min described in the eleventh embodiment, wherein Figure (a) is the FFT analysis result without using the proposed method, and Figure (b) is the FFT analysis result using the proposed method, the horizontal axis represents the frequency, and the vertical axis represents the amplitude;

[0053] Figure 8 The experimental results of the rotary transformer software decoding system based on the measurement bias error compensation method described in the eleventh embodiment at a rotation speed of 1500r / min;

[0054] Fig. 9 This is the FFT analysis result of the motor speed waveform at the rated speed of 1500r / min as described in the eleventh implementation mode, wherein Figure (a) is the FFT analysis result without using the proposed method, and Figure (b) is the FFT analysis result with using the proposed method. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments.

[0056] Implementation method 1: A software decoding method for a rotary transformer taking into account a measurement bias error is described in this implementation method, and the method includes:

[0057] Step S1: According to the theoretical derivation process of the resolver software decoding strategy, the rotor position estimation error signal e is obtained taking into account the measurement bias error. θ ;

[0058] Step S2: Estimate the error signal e according to the rotor position θ Multiplying with the excitation signal and passing through a low-pass filter, the bias error signal caused by the measurement bias error is obtained;

[0059] Step S3: inputting the bias error signal into a second-order generalized integrator to generate a 90° phase shift, thereby obtaining two orthogonal bias error signals;

[0060] Step S4: transforming the two orthogonal bias error signals into the dq axis coordinate system by using coordinate transformation, and transforming the AC bias error signal into a DC bias error signal;

[0061] Step S5: using an integral controller to estimate the DC bias error signal, obtaining an estimated measurement bias error signal, and compensating the estimated measurement bias error signal to the resolver output signal to complete decoding.

[0062] The software decoding method of a rotary transformer taking into account the measurement bias error proposed in this embodiment can significantly improve the decoding accuracy of the rotor position and reduce the error caused by signal bias by taking into account the measurement bias error. Furthermore, this method has strong adaptability and can be applied to different types of rotary transformers, especially those that are easily affected by bias when working under a high dynamic range. The real-time bias error compensation technology is used to dynamically adjust the output signal to make the decoding process more stable. The use of low-pass filters and second-order generalized integrators ensures noise suppression during signal processing, which helps to improve the anti-interference ability of the overall system. Through the optimization of mathematical models and algorithms, the complexity of the entire decoding process is reduced, which is easy to implement and maintain.

[0063] The method proposed in this embodiment has the following specific principles:

[0064] In step S1, the rotor position estimation error signal e is obtained by theoretical derivation. θ , which reflects the gap between the actual state of the rotor position and the expected value, and thus provides a basis for subsequent bias error processing.

[0065] In step S2, the error signal is multiplied by the excitation signal, and a bias error signal caused by the measurement bias error is extracted using a low-pass filter. This process helps to effectively distinguish useful components and noise in the signal.

[0066] In step S3, a second-order generalized integrator is used to generate a 90° phase shift, and two orthogonal bias error signals can be obtained. This is a key step in the decoding process, making the subsequent coordinate transformation more accurate.

[0067] In step S4, the orthogonal bias error signal is transformed into the dq axis coordinate system, which can convert the AC signal into a DC signal, simplifying the error processing process. The dq axis transformation is widely used in electrical engineering and effectively improves the intuitiveness of signal processing.

[0068] In step S5, an integral controller is used to estimate the DC bias error signal, so that a more accurate measurement bias error signal can be obtained. This signal is compensated to the output signal of the resolver to complete the decoding process, making the final output signal more accurate and reliable.

[0069] Implementation method 2: This implementation method further limits the software decoding method of the rotary transformer considering the measurement bias error described in implementation method 1, and the step S1 includes:

[0070]

[0071] Among them, LPF[] is a low-pass filter for the signal in the brackets, U exc The excitation signal generator provides an excitation signal to the primary winding, e is the error signal, K R is the ratio of the resolver, U E is the excitation signal amplitude, θ m is the actual rotor position, To estimate the rotor position signal, e O is the error signal caused by the measurement offset error, ω e is the angular frequency of the excitation signal.

[0072] The specific process of step S1 described in this embodiment is as follows:

[0073] The excitation signal generator provides an excitation signal U to the primary winding. exc , the expression is shown in formula (1):

[0074] U exc =U E sin(ω e t) (1)

[0075] Where: U E is the excitation signal amplitude, ω e is the angular frequency of the excitation signal.

[0076] The output signal of the secondary winding of the rotary transformer can be expressed by formula (2):

[0077]

[0078] Where: U sin and U cos Represents the output signal of the secondary winding, K R is the ratio of the resolver, θ m is the actual position of the rotor.

[0079] However, if the influence of the bias circuit and the sampling circuit is taken into account, the actual secondary winding output signal will contain a measurement bias error, which can be expressed by formula (3):

[0080]

[0081] Where: O sin and O cos They respectively represent the measurement offset errors of the two outputs of the secondary winding of the resolver.

[0082] The actual output signal of the secondary winding is compared with the estimated rotor position signal The error signal e can be obtained by multiplying the sine and cosine values ​​of and taking the difference, as shown in formula (4):

[0083]

[0084] Where: is the measured position of the rotor, e O represents the error signal caused by the measurement offset error, which can be expressed by formula (5):

[0085]

[0086] According to formula (4), the high-frequency excitation signal is superimposed on the error signal e. In order to filter out the high-frequency excitation signal, the error signal e in formula (4) is demodulated and the error signal e is combined with the excitation signal U exc After multiplication and low-pass filtering, the rotor position error signal e can be obtained. θ As shown in formula (6):

[0087]

[0088] Where: LPF[] is defined as low-pass filtering of the signal in the brackets.

[0089] Assumption: The cutoff frequency of the low-pass filter is greater than the rotation frequency of the resolver. That is, the low-pass filter will not cause phase delay to the measured offset error signal.

[0090] If the offset error signal e is ignored O , rotor position error signal e θIt can be approximated by Taylor formula as shown in formula (7):

[0091]

[0092] Finally, the PI controller is used to adjust the error signal in formula (7) so that it converges to 0, as shown in formula (8):

[0093]

[0094] Where: u m is the controller output, K p and K i is the control gain of the PI controller, and s is a frequency domain variable.

[0095] According to formula (8), the angular velocity and position of the rotor can be measured as shown in formula (9):

[0096]

[0097] Where: m is the rotor angular velocity, is the rotor position.

[0098] In this embodiment, by introducing the excitation signal, the actual position and the estimated position in step S1, and processing the signal with a low-pass filter, the error caused by the measurement bias can be estimated more accurately. This enables the decoder to better cope with the nonlinear effects caused by the bias error. The amplitude and angular frequency of the excitation signal are taken into account in step S1, which means that the decoding method can be dynamically adjusted according to the characteristics of the excitation signal. This feature improves the system's responsiveness to environmental changes and signal fluctuations.

[0099] Furthermore, the process of filtering the signal using a low-pass filter (LPF) in this embodiment can effectively suppress high-frequency noise and reduce interference with error estimation, thereby improving the reliability and accuracy of decoding. Since this method can dynamically adjust the error estimation according to different excitation signals and actual rotor positions, it can maintain good decoding performance in different application scenarios (such as different operating frequencies and load conditions). By combining the excitation signal with the error signal and processing it through a low-pass filter, a more optimized signal processing process is formed. This method not only improves the accuracy of error estimation, but also simplifies the complexity of subsequent steps.

[0100] Implementation method 3: This implementation method is a further limitation of the software decoding method of the rotary transformer considering the measurement bias error described in implementation method 2. The error signal e is calculated based on the actual output signal of the secondary winding and the estimated rotor position signal. It is obtained by multiplying the sine and cosine values ​​and then taking the difference.

[0101] Implementation 4: This implementation is a further limitation of the resolver software decoding method considering the measurement bias error described in Implementation 2, and the step S2 includes:

[0102] When the estimated rotor position is consistent with the actual position, Then the position error signal e θ for:

[0103] e θ ≈LPF[e O U E sin(ω e t)]

[0104] The position error signal and the excitation signal U exc Multiply and demodulate again through the filter to get the error signal e caused by the measurement offset error O :

[0105]

[0106] Among them, O sin and O cos Represents the measured offset error of the two outputs of the resolver secondary winding.

[0107] In this embodiment, the measurement accuracy of the rotary transformer can be significantly improved by estimating the rotor position and compensating for the measurement bias error. Implementation method 2 can effectively eliminate or reduce the error caused by the measurement bias by calculating the position error signal and multiplying it with the excitation signal. This method can quickly respond to dynamically changing input signals by estimating the rotor position in real time and calculating the error signal. Through the processing of the low-pass filter, high-frequency noise can be effectively filtered out, the sensitivity of the rotary transformer to low-frequency signal changes can be maintained, and the dynamic response capability can be improved. During the implementation process, the signal processed by the low-pass filter can reduce the influence of external noise and interference, making the decoding process more stable and reliable. Especially in complex industrial environments, it is particularly important to reduce the influence of external factors on the measurement results. The decoding method can dynamically adjust the compensation strategy of the measurement bias according to the changes in the actual working environment. This adaptability enables the rotary transformer to maintain efficient operation under different working conditions and meet various application requirements.

[0108] Implementation 5: This implementation is a further limitation of the software decoding method for a rotary transformer considering the measurement bias error described in Implementation 1. The second-order generalized integrator in step S3 is:

[0109]

[0110] Among them, G α(s) is the output signal e α and the input signal e O The transfer function between β (s) is the output signal e β and the input signal e O The transfer function between α and e β are the two output signals of the second-order generalized integrator, e O is the input signal of the second-order generalized integrator, K S is the control gain of the second-order generalized integrator, ω m is the mechanical angular velocity of the rotor, and s is a frequency domain variable.

[0111] The second-order generalized integrator in this embodiment can effectively process and eliminate the bias error in the signal, which is crucial in the measurement of the rotary transformer. The output signal can be adjusted and optimized in real time by accurately controlling the control gain, thereby improving the overall measurement accuracy.

[0112] Implementation 6: This implementation is a further limitation of the software decoding method for a rotary transformer considering the measurement bias error described in Implementation 5, and the step S4 includes:

[0113] The two orthogonal signals obtained by the second-order generalized integrator are transformed from the two-term stationary coordinate system to the two-phase rotating coordinate system by coordinate transformation to obtain the DC signal:

[0114]

[0115] Among them, e d and e q Represents the DC error signal obtained after coordinate transformation.

[0116] In this embodiment, by using coordinate transformation, the AC bias error signal is converted into a DC bias error signal, which can effectively eliminate the error caused by signal changes. After conversion to the dq axis coordinate system, the system can better identify and compensate for the bias error, thereby improving the accuracy of the measurement. In the dq axis coordinate system, the signal usually appears in the form of DC, which makes the subsequent signal processing and decoding algorithms simpler. It is much easier to process DC signals than AC signals because DC signals have no frequency changes, which can reduce the computational complexity. This method converts the orthogonal signal into a DC signal, so that the error compensation algorithm can be applied more effectively.

[0117] Embodiment 7: This embodiment further limits the method for software decoding of a rotary transformer taking into account a measurement bias error described in Embodiment 6, and the step S5 includes:

[0118] The DC error signal is regulated by an integral controller, and the output regulated signal is the estimated measurement bias error signal compensation term:

[0119]

[0120] in, and They represent the estimated values ​​of the measured offset errors of the two outputs of the resolver secondary winding, K si and K ci Represent the gain coefficients of the two integral controllers respectively.

[0121] In this embodiment, by using an integral controller to estimate the DC bias error, the decoding error caused by the measurement bias can be effectively reduced, thereby improving the accuracy of the output signal. This compensation mechanism can correct the deviation caused by factors such as system characteristics, environmental changes or device aging in real time, making the decoding result more reliable. The integral controller can adjust the continuous bias error, and its output signal can respond quickly to the error change. Compared with other compensation methods, the integral controller shows better stability and dynamic response capability when dealing with slow changes or steady-state errors. Integrating the compensation logic of the bias error directly in the software decoding process can simplify hardware design and implementation and reduce costs.

[0122] Embodiment 8: A resolver software decoding system considering measurement bias error described in this embodiment, the system includes:

[0123] The rotor position estimation error signal acquisition unit is used to obtain the rotor position estimation error signal e considering the measurement bias error according to the theoretical derivation process of the resolver software decoding strategy. θ ;

[0124] A bias error signal acquisition unit is used to estimate the error signal e according to the rotor position θ Multiplying with the excitation signal and passing through a low-pass filter, the bias error signal caused by the measurement bias error is obtained;

[0125] A second-order generalized integrator processing unit, used for inputting the bias error signal into the second-order generalized integrator to generate a 90° phase shift, thereby obtaining two orthogonal bias error signals;

[0126] A transformation unit, used to transform the two orthogonal bias error signals into a dq axis coordinate system by using coordinate transformation, and to transform the AC bias error signal into a DC bias error signal;

[0127] The compensation unit is used to estimate the DC bias error signal by using an integral controller, obtain an estimated measurement bias error signal, and compensate the estimated measurement bias error signal to the resolver output signal to complete decoding.

[0128] Embodiment 9. A computer device described in this embodiment includes a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes a software decoding method for a rotary transformer taking into account a measurement bias error as described in any one of embodiments 1 to 7.

[0129] Embodiment 10. A computer-readable storage medium described in this embodiment, on which a computer program is stored, and when the computer program is executed by a processor, the steps of a software decoding method for a rotary transformer taking into account a measurement bias error as described in any one of embodiments 1 to 7 are executed.

[0130] Implementation Method XI: Combination Figures 1 to 7 This embodiment provides a specific example of a method for software decoding a rotary transformer taking into account a measurement bias error described in the first embodiment, and is also used to explain the second to seventh embodiments, specifically:

[0131] The present implementation method describes a resolver software decoding strategy that takes into account measurement bias error. The method comprises the following steps:

[0132] Step 1: According to Figure 1 The resolver software decoding system block diagram shown in Figure 1 obtains the rotor position estimation error signal e considering the measurement bias error. θ .

[0133] Step 2: Use the rotor position estimation error signal e obtained in step 1 taking into account the measurement bias error θ , multiply it with the excitation signal and pass it through a low-pass filter to obtain the offset error signal e caused by the measurement offset error O .

[0134] For the rotor position estimation error signal e considering the measurement bias error θ , which is of the form:

[0135]

[0136] When the estimated rotor position is consistent with the actual position, it can be assumed that Then we can get the error signal e θ In the following form:

[0137] e θ ≈LPF[e O U E sin(ω e t)]

[0138] By multiplying it with the excitation signal and demodulating it again through the filter, the error signal e generated by the measurement offset error can be obtained. O :

[0139]

[0140] Step 3: Convert the error signal e O The input to the second-order generalized integrator produces a 90° phase shift, and two orthogonal bias error signals e can be obtained. α 、e β Input signal O To two output signals e α and e β The transfer functions are:

[0141]

[0142] Combine the following Figure 4 Explain and analyze the second-order generalized integrator:

[0143] The second-order generalized integrator can track and phase-shift the AC signal of a specific frequency, and can be used to separate and filter the voltage signal. Figure 3 As shown, the input signal e O To two output signals e α and e β The transfer functions are:

[0144]

[0145] Where: K S is the control gain of the second-order generalized integrator.

[0146] According to formula (21), at frequency ω m At , the amplitude and phase angle of the closed-loop frequency characteristics of the second-order generalized integrator are:

[0147]

[0148] According to formula (22), when the frequency of the input signal is the same as the set frequency, the output signal e of the second-order generalized integrator is α The output signal will be the same as the input signal, β Compared to the input signal, the amplitude remains unchanged, but there is a 90° phase delay. Therefore, when the input signal is a frequency of ω m The sinusoidal signal sin(ω m t), the output signal of the second-order generalized integrator is:

[0149]

[0150] Step 4: Measure the sinusoidal fluctuation caused by the bias error. It is still difficult to directly estimate the bias error after passing through the second-order generalized integrator. Since its output is a pair of orthogonal signals with a phase difference of 90°, it can be considered that the pair of signals is located in a two-phase stationary coordinate system. Based on this, the pair of orthogonal signals can be transformed into a two-phase rotating coordinate system using coordinate transformation to obtain a pair of DC error signals, which are specifically implemented as follows:

[0151]

[0152] According to step 3, the DC error signal e d and e q for:

[0153]

[0154] Step 5: According to the DC error signal e in step 4 d 、e q It can be seen that the measurement bias error will cause a DC deviation on the dq axis of the two-phase rotating coordinate system. The deviation on the d axis is caused by the output U sin The deviation on the q-axis is caused by the offset error on the channel. cos The offset error on the channel is caused by this. Based on this, dq The DC deviation on the axis is equivalent to the measurement bias error on the two output channels of the resolver. Based on this, the DC error signal is adjusted using an integral controller to obtain the estimated measurement bias error compensation term as follows:

[0155]

[0156] Where: and They represent the estimated values ​​of the measurement offset errors of the two outputs of the resolver, K si and K ci Represent the gain coefficients of the two integral controllers respectively.

[0157] Finally, the estimated measurement deviation value is compensated to the output signal of the secondary winding of the resolver, which is:

[0158]

[0159] Where: They are respectively the compensated resolver secondary winding output signals.

[0160] By compensating for the measurement bias error, the rotor estimated position error e can be effectively reduced. θ The sinusoidal disturbance in the rotor can be reduced, thereby reducing the fluctuations in the estimated rotor position and speed signals and improving the control performance of the motor.

[0161] Experimental results:

[0162] according to Figure 6 When the motor speed is 3000r / min, the proposed method can reduce the angular velocity pulsation from 8rad / s to 3rad / s, and the rotor position error pulsation from 3° to 1°. Figure 7 , the amplitude of the first harmonic of the motor speed is reduced from 2.2% to 0.35%. Figure 8 When the motor speed is 50% of the rated speed 1500r / min, the proposed method can reduce the angular velocity pulsation from 6rad / s to 3rad / s, and the rotor position error pulsation from 3° to 1°. Fig. 9 , the amplitude of the first harmonic of the motor speed is reduced from 1.31% to 0.35%. The experimental results show that the proposed scheme can effectively compensate for the bias error and suppress the sinusoidal fluctuations in the motor speed and rotor position error signals, thereby enhancing the driving performance of the motor system.

[0163] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0164] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram and the combination of processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the process in the flowchart. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0165] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0166] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit its protection scope. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that after reading the present invention, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the invention, but these changes, modifications or equivalent substitutions are all within the protection scope of the pending claims of the invention.

Claims

1. A software decoding method for a rotary transformer taking into account a measurement bias error, characterized in that: The method comprises: Step S1: According to the theoretical derivation process of the resolver software decoding strategy, the rotor position estimation error signal e is obtained taking into account the measurement bias error. θ ; Step S2: Estimate the error signal e according to the rotor position θ Multiplying with the excitation signal and passing through a low-pass filter, the bias error signal caused by the measurement bias error is obtained; Step S3: inputting the bias error signal into a second-order generalized integrator to generate a 90° phase shift, thereby obtaining two orthogonal bias error signals; Step S4: transforming the two orthogonal bias error signals into the dq axis coordinate system by using coordinate transformation, and transforming the AC bias error signal into a DC bias error signal; Step S5: using an integral controller to estimate the DC bias error signal, obtaining an estimated measurement bias error signal, and compensating the estimated measurement bias error signal to the resolver output signal to complete decoding.

2. The method for software decoding a rotary transformer taking into account a measurement bias error according to claim 1, characterized in that: The step S1 comprises: Among them, LPF[] is a low-pass filter for the signal in the brackets, U exc The excitation signal generator provides an excitation signal to the primary winding, e is the error signal, K R is the ratio of the resolver, U E is the excitation signal amplitude, θ m is the actual rotor position, To estimate the rotor position signal, e O is the error signal caused by the measurement offset error, ω e is the angular frequency of the excitation signal.

3. The method for software decoding a rotary transformer taking into account a measurement bias error according to claim 2, characterized in that: The error signal e is calculated based on the actual output signal of the secondary winding and the estimated rotor position signal It is obtained by multiplying the sine and cosine values ​​and then taking the difference.

4. The method for software decoding a rotary transformer taking into account a measurement bias error according to claim 2, characterized in that: The step S2 comprises: When the estimated rotor position is consistent with the actual position, Then the position error signal e θ for: it θ ≈LPF[e O U E that(ω e (t)] The position error signal and the excitation signal U exc Multiply and demodulate again through the filter to get the error signal e caused by the measurement offset error O : Among them, O sin and O cos Represents the measured offset error of the two outputs of the resolver secondary winding.

5. The method for software decoding a rotary transformer taking into account a measurement bias error according to claim 1, characterized in that: The second-order generalized integrator in step S3 is: Among them, G α (s) is the output signal e α and the input signal e O The transfer function between β (s) is the output signal e β and the input signal e O The transfer function between α and e β are the two output signals of the second-order generalized integrator, e O is the input signal of the second-order generalized integrator, K S is the control gain of the second-order generalized integrator, ω m is the mechanical angular velocity of the rotor, and s is a frequency domain variable.

6. The method for software decoding a rotary transformer taking into account a measurement bias error according to claim 5, characterized in that: The step S4 comprises: The two orthogonal signals obtained by the second-order generalized integrator are transformed from the two-term stationary coordinate system to the two-phase rotating coordinate system by coordinate transformation to obtain the DC signal: Among them, e d and e q Represents the DC error signal obtained after coordinate transformation.

7. The method for software decoding a rotary transformer taking into account a measurement bias error according to claim 6, characterized in that: The step S5 comprises: The DC error signal is regulated by an integral controller, and the output regulated signal is the estimated measurement bias error signal compensation term: in, and K represents the estimated value of the measured offset error of the two outputs of the resolver secondary winding, si and K ci represents the gain coefficients of the two integral controllers.

8. A software decoding system for a rotary transformer taking into account measurement bias error, characterized in that: The system comprises: The rotor position estimation error signal acquisition unit is used to obtain the rotor position estimation error signal e considering the measurement bias error according to the theoretical derivation process of the resolver software decoding strategy. θ ; A bias error signal acquisition unit is used to estimate the error signal e according to the rotor position θ Multiplying with the excitation signal and passing through a low-pass filter, the bias error signal caused by the measurement bias error is obtained; A second-order generalized integrator processing unit, used for inputting the bias error signal into the second-order generalized integrator to generate a 90° phase shift, thereby obtaining two orthogonal bias error signals; A transformation unit, used to transform the two orthogonal bias error signals into a dq axis coordinate system by using coordinate transformation, and to transform the AC bias error signal into a DC bias error signal; The compensation unit is used to estimate the DC bias error signal by using an integral controller, obtain an estimated measurement bias error signal, and compensate the estimated measurement bias error signal to the resolver output signal to complete decoding.

9. A computer device, characterized in that: The invention comprises a memory and a processor, wherein a computer program is stored in the memory, and when the processor runs the computer program stored in the memory, the processor executes a software decoding method for a rotary transformer taking into account a measurement bias error according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for software decoding of a rotary transformer taking into account a measurement bias error as claimed in any one of claims 1 to 7 are executed.

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