Motor angle calculation method

Abstract

To provide a method for calculating a motor angle that also performs a failover function which enables an alternative driving even when a fault occurs in any one or more sensors, and enables a smooth switching to accurate angle information even in a fault situation.SOLUTION: A method for calculating a motor angle includes steps of: deriving a model-based sensored current vector via a sensored voltage model; deriving a model-based sensorless current vector via a sensorless voltage model; deriving a sensor weight and a sensorless weight using a cross product of an actual current vector and the model-based sensored current vector and a cross product of the actual current vector and the model-based sensorless current vector; and calculating a final motor angle by applying the sensor weight and the sensorless weight to a sensor angle and a sensorless angle, respectively.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an angle sensor fusion technique for a high-power motor for Urban Air Mobility (UAM), and more particularly to a motor angle calculation method that performs a failover function that enables alternative driving even if any sensor fails, and enables smooth switching to accurate angle information even in a fault situation. [Background technology]

[0002] In the conventional method of calculating the motor angle, three or more angle sensors are required, and the priority is determined by voting, and the motor is driven at one angle. However, in this case, if an abnormality occurs in the angle sensor with the highest priority, a hard transition is made to the sensor with the next highest priority, which has raised the issue of unstable failover. Specifically, the absolute value of the angle error of three sensors a, b, and c is calculated, and the angle information with the smallest error is given the highest priority. When the angle errors of the angle information a, b, and c are averaged, the method operates with sensor b, which has the smallest error, but this has raised the issue of unstable failover.

[0003] Another method is to fuse angles obtained by a sensorless technique using low-cost sensors and back electromotive force, in which case the weights are adjusted using a Kalman filter to output new angle information. However, this method also has the disadvantage that the selection of the average value is vague and based on statistical data, so it takes a long time to store the data in order to output the average value.

[0004] The matters described above as the background art are merely intended to enhance understanding of the background of the present invention, and should not be construed as admitting that they constitute prior art already known to those having ordinary skill in the art. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Korean Patent No. 10-1470025 Summary of the Invention [Problem to be solved by the invention]

[0006] The present invention has been made to solve these problems, and its purpose is to provide a motor angle calculation method that is an angle sensor fusion technique for UAM (Urban Air Mobility) high-power motors, and that also performs a failover function that allows alternative driving if any sensor fails, and enables smooth switching to accurate angle information even in a fault situation. [Means for solving the problem]

[0007] To achieve the above object, the motor angle calculation method according to the present invention includes the steps of: deriving a model-based sensored current vector via a sensored voltage model; deriving a model-based sensorless current vector via a sensorless voltage model; deriving sensor weights and sensorless weights using the cross product of the actual current vector and the model-based sensored current vector, and the cross product of the actual current vector and the model-based sensorless current vector; and calculating a final motor angle by applying the sensor weights and sensorless weights to the sensor angle and sensorless angle, respectively.

[0008] The sensored voltage model can take the motor's fixed shaft voltage command vector, the sensor angle, and the sensor angular velocity as inputs, and can output a model-based sensored current vector.

[0009] The sensorless voltage model can take the motor's fixed shaft voltage command vector, the sensorless estimated angle, and the sensorless estimated angular velocity as inputs, and can output a model-based sensorless current vector.

[0010] The sensored voltage model and the sensorless voltage model can be constructed using ordinary differential equations and integrators.

[0011] In the step of deriving the sensor weights and the sensorless weights, a sensored error can be obtained by squaring the cross product of the actual current vector and the model-based sensored current vector, and a sensorless error can be obtained by squaring the cross product of the actual current vector and the model-based sensorless current vector.

[0012] In the step of deriving the sensor weights and the sensorless weights, the sensored errors and the sensorless errors may be normalized to derive the sensor weights and the sensorless weights, respectively.

[0013] In the step of calculating the final motor angle, the sensor angle is multiplied by the sensor weight, and the sensorless angle is multiplied by the sensorless weight and added together to calculate the final motor angle. Effect of the Invention

[0014] The motor angle calculation method of the present invention is an angle sensor fusion technique for UAM (Urban Air Mobility) high-power motors, and also provides a failover function that enables alternative operation if any sensor fails, making it possible to smoothly switch to accurate angle information even in a fault situation. [Brief description of the drawings]

[0015] [Figure 1] FIG. 2 is a block diagram showing a motor angle calculation method according to an embodiment of the present invention. [Diagram 2]FIG. 11 is a diagram showing a sensored voltage model of a motor angle calculation method according to an embodiment of the present invention. [Diagram 3] FIG. 11 is a diagram showing a sensorless voltage model of a motor angle calculation method according to an embodiment of the present invention. [Figure 4] FIG. 13 is a current vector-based cross product block diagram of a motor angle calculation method according to an embodiment of the present invention. [Diagram 5] FIG. 2 is an angle fusion block diagram of a motor angle calculation method according to an embodiment of the present invention. [Figure 6] FIG. 13 is a diagram illustrating an estimator that outputs fused angle speed information in the motor angle calculation method according to an embodiment of the present invention. [Figure 7] This is the simulation result when a fault occurs in the output of the sensor (resolver) at the exact moment that it reaches 1 second. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] FIG. 1 is a block diagram showing a motor angle calculation method according to one embodiment of the present invention, FIG. 2 is a diagram showing a sensored voltage model of a motor angle calculation method according to one embodiment of the present invention, FIG. 3 is a diagram showing a sensorless voltage model of a motor angle calculation method according to one embodiment of the present invention, FIG. 4 is a current vector based cross product block diagram of a motor angle calculation method according to one embodiment of the present invention, FIG. 5 is an angle fusion block diagram of a motor angle calculation method according to one embodiment of the present invention, and FIG. 6 is a diagram showing an estimator that outputs speed information of the fused angle of the motor angle calculation method according to one embodiment of the present invention.

[0017] The motor angle calculation method according to the present invention includes the steps of: deriving a model-based sensored current vector via a sensored voltage model; deriving a model-based sensorless current vector via a sensorless voltage model; deriving sensor weights and sensorless weights using the cross product of the actual current vector and the model-based sensored current vector and the cross product of the actual current vector and the model-based sensorless current vector; and calculating a final motor angle by applying the sensor weights and the sensorless weights to the sensor angle and the sensorless angle, respectively.

[0018] Specifically, Fig. 1 is a block diagram of a motor angle calculation method according to an embodiment of the present invention. Referring to Fig. 1, a fixed shaft voltage command vector 100 of a motor is commonly applied to a permanent magnet type actual motor 200, a sensored voltage model 202 created in a processor, and a sensorless voltage model 203. A sensor angle 104 and a sensor angular velocity 106 sensed from a sensor are used as inputs to the sensored voltage model 202, and a sensorless angle 105 and a sensorless angular velocity 107 estimated from a sensorless control are used as inputs to the sensorless voltage model 203.

[0019] The three-phase currents sensed by the actual motor 200, i abc obtains the actual current vector 101 of the fixed axis through a coordinate converter 201 to the fixed axis. A model-based sensored current vector 102 and a sensorless current vector 103 are estimated from a sensored voltage model 202 and a sensorless voltage model 203. When the sensor angle 104 or the sensorless angle 105 coincides with the angle of the actual motor rotor, the cross product of the current vectors is 0. Using this fact, a current vector-based cross product block 204 calculates the cross product of the actual current vector 101 and the sensored current vector 102, and calculates the cross product of the actual current vector 101 and the sensorless current vector 103 in a similar manner.

[0020] The calculated cross product values ​​are input in the form of squares to the weight-based sensor fusion block 205 and, after normalization, are used to calculate the sensor weights ρ sen , and the sensorless weight ρ, which decreases as the sensorless error increases. st and outputs fusion angle information 108 based on the generated fusion angle information.

[0021] First, the meanings of important variables used in the following description are as follows:

[0022] JPEG0007640045000001.jpg76144

[0023] Specifically, the present invention first performs a step of deriving a model-based sensored current vector via a sensored voltage model, and a step of deriving a model-based sensorless current vector via a sensorless voltage model. The sensored voltage model and the sensorless voltage model can be configured with ordinary differential equations and integrators. The sensored voltage model can receive a fixed shaft voltage command vector of the motor, a sensor angle, and a sensor angular velocity as inputs, and can output a model-based sensored current vector, while the sensorless voltage model can receive a fixed shaft voltage command vector of the motor, a sensorless estimated angle, and a sensorless estimated angular velocity as inputs, and can output a model-based sensorless current vector.

[0024] 2 and 3 are diagrams showing a sensored voltage model and a sensorless voltage model of a motor angle calculation method according to an embodiment of the present invention. Referring to Fig. 2, a sensored motor fixed shaft voltage model 202 receives a fixed shaft voltage command vector 100, a sensor angle 104, and a sensor angular velocity 106 as inputs, and outputs a model-based sensored current vector 102.

[0025] The sensored motor fixed shaft voltage model 202 is composed of an ordinary differential equation 400 of the fixed shaft voltage model and an integrator 401. The ordinary differential equation 400 of the fixed shaft voltage model is s, d-axis inductance L d , q-axis inductance L q , the total inductance L Σ , the inductance difference L Δ and the back electromotive force constant ψ m is essential, as shown in the formula below.

[0026]

number

[0027] 3, the sensorless motor fixed shaft voltage model 203 receives the fixed shaft voltage command vector 100, the sensorless angle 105, and the sensorless angular velocity 107 as inputs, and outputs a model-based sensorless current vector 103. The sensorless motor fixed shaft voltage model 203 is internally configured with an ordinary differential equation 400 of the fixed shaft voltage model and an integrator 401, similar to the sensored motor fixed shaft voltage model.

[0028] FIG. 4 is a block diagram of a current vector-based cross product of a motor angle calculation method according to an embodiment of the present invention, FIG. 5 is a block diagram of an angle fusion of a motor angle calculation method according to an embodiment of the present invention, and FIG. 6 is a diagram showing an estimator that outputs speed information of a fused angle of a motor angle calculation method according to an embodiment of the present invention.

[0029] In the present invention, a step of deriving sensor weights and sensorless weights is performed using the cross product of the previously derived actual current vector and the model-based sensored current vector, and the cross product of the actual current vector and the model-based sensorless current vector.

[0030] Specifically, in the step of deriving the sensor weights and the sensorless weights, the sensored error may be calculated by squaring the cross product of the actual current vector and the model-based sensored current vector, and the sensorless error may be calculated by squaring the cross product of the actual current vector and the model-based sensorless current vector. In the step of deriving the sensor weights and the sensorless weights, the sensor weights and the sensorless weights may be derived by normalizing the sensored error and the sensorless error, respectively.

[0031] The present invention performs a step of calculating a final motor angle by applying the sensor weight and the sensorless weight to the sensor angle and the sensorless angle, respectively. Specifically, in the step of calculating the final motor angle, the sensor angle is multiplied by the sensor weight, and the sensorless angle is multiplied by the sensorless weight and added together to calculate the final motor angle.

[0032] 4, the current vector-based cross product block 204 obtains the cross product 402 of the fixed axis actual current vector 101 and the model-based sensored current vector 102 to obtain an error component, which is then squared 403 to calculate the error 301 between the actual current and the sensored current vector, and in a similar manner, the cross product 402 of the fixed axis actual current vector 101 and the model-based sensorless current vector 103 is obtained, which is then squared 403 to obtain the error 302 between the actual current and the sensorless current vector. The error 301 between the actual current and the sensored current vector and the error 302 between the actual current and the sensorless current vector are expressed by the following equations.

[0033]

number

[0034] 5, the weight-based sensor fusion block 205 is composed of a normalization block 404 that calculates weights using the error 301 between the actual current and the sensored current vector and the error 302 between the actual current and the sensorless current vector, and an angle fusion block 405 that fuses the sensor angle 104 and the sensorless angle 105 using the calculated weights. sen and the sensorless weight ρ st , and the final calculated fusion angle 108 is:

[0035]

number

[0036] The simulation result in FIG. 7 shows the case where a fault occurs in the output of the sensor (resolver) at the moment when it becomes 1 second. It shows the case where one of the sin and cos output coils is short-circuited. First, the weights to be assigned to the sensor angle and the sensorless angle are calculated by the sensor fusion method of the present invention. Before the fault, the angle difference between both sensors is negligible, so a weight of 0.5 is assigned to each. After the fault, a weighting transient state of about 0.12 seconds is passed, and after the transient state, a weight of 0 (zero) is assigned to the faulty sensor angle and a weight of 1 is assigned to the sensorless angle. As a result, it can be seen that the vector control of the motor is continuously performed with the fused angle information, and robust angle information is provided even in a fault situation.

[0037] In general, stable speed sensing is important for the speed control characteristics of motors. However, there is a problem that errors occur in the speed information after a fault occurs in the angle information of the sensor. In contrast, errors do not occur significantly in the speed information extracted by the angle fusion method of the present invention.

[0038] The motor angle calculation method of the present invention relates to an angle sensor fusion technique for a high-power motor for Urban Air Mobility (UAM), and also provides a failover function that enables alternative operation if any sensor fails, enabling smooth switching to accurate angle information even in a fault situation.

[0039] While the present invention has been illustrated and described with reference to specific embodiments, it will be apparent to those having ordinary skill in the art that various modifications and changes can be made therein without departing from the spirit and scope of the invention as set forth in the following claims.

Claims

1. deriving a model-based sensored current vector via a sensored voltage model; deriving a model-based sensorless current vector via a sensorless voltage model; deriving sensor weights and sensorless weights using a cross product of the actual current vector and the model-based sensored current vector and a cross product of the actual current vector and the model-based sensorless current vector; and applying the sensor weights and the sensorless weights to the sensor angle and the sensorless angle, respectively, to calculate a final motor angle.

2. 2. The motor angle calculation method according to claim 1, wherein the sensored voltage model receives a fixed shaft voltage command vector of the motor, a sensor angle, and a sensor angular velocity as inputs, and outputs a model-based sensored current vector.

3. 2. The motor angle calculation method according to claim 1, wherein the sensorless voltage model receives a fixed shaft voltage command vector of the motor, a sensorless estimated angle, and a sensorless estimated angular velocity as inputs, and outputs a model-based sensorless current vector.

4. 2. The motor angle calculation method according to claim 1, wherein the sensored voltage model and the sensorless voltage model are configured with an ordinary differential equation and an integrator.

5. 2. The motor angle calculation method of claim 1, wherein in the step of deriving the sensor weights and the sensorless weights, a sensored error is calculated by squaring a cross product of the actual current vector and a model-based sensored current vector, and a sensorless error is calculated by squaring a cross product of the actual current vector and a model-based sensorless current vector.

6. 6. The motor angle calculation method according to claim 5, wherein in the step of deriving the sensor weights and the sensorless weights, the sensored error and the sensorless error are normalized to derive the sensor weights and the sensorless weights, respectively.

7. 2. The motor angle calculation method according to claim 1, wherein in the step of calculating the final motor angle, the final motor angle is calculated by multiplying the sensor angle by a sensor weight and multiplying the sensorless angle by the sensorless weight and adding the results.

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