Anti-pinch control method for tail door of electric automobile

Abstract

The invention discloses an anti-pinch control method for a tail door of an electric automobile, and belongs to the technical field of electric automobiles. Comprising the steps of collecting and updating driving motor working data; anti-pinch pre-judgment is carried out; obtaining a time interval t1 when the anti-pinch pre-judgment takes effect; performing state estimation on the torque in the time interval t1 through a steady-state Kalman filtering algorithm; calculating a sliding square average value TM of the torque estimation value in the time interval t1; judging whether the motor is stable within the time interval t1 or not according to the torque estimation value; if so, calculating a torque dynamic threshold value Tth in a steady state; and comparing the TM with the Tth, and judging whether the anti-pinch function is started or not. According to the method, the motor torques under different tail gate loads of the electric vehicle are dynamically estimated through the steady-state Kalman filtering algorithm, and then the torque threshold value is dynamically adjusted, so that the anti-pinch control reliability is improved, and anti-pinch misjudgment is avoided.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric vehicles. Specifically, the present invention relates to a method for controlling the anti-pinch function of the tailgate of an electric vehicle. Background Art

[0002] The tailgates of traditional vehicles need to be lifted and closed manually, and cannot be suspended midway, and do not have an anti-pinch function. Electric tailgates can be automatically opened, closed, and stopped at an appropriate height when triggered by a button. Most importantly, electric tailgates have an anti-pinch function, and can stop running when the tailgate encounters an obstacle, avoiding harm to personnel.

[0003] Currently, in the prior art, there are two types of anti-pinch technologies for vehicle tailgates abroad. One is contact anti-pinch: mainly based on sensors installed at the edge or hinge of the tailgate. These sensors monitor whether they come into contact with an object or a person and cause slight extrusion during the movement of the tailgate. The anti-pinch sensor judges this extrusion signal and transmits the extrusion signal to the controller, and the controller makes the tailgate stop or move in the reverse direction. The second type is non-contact anti-pinch; also based on sensors installed around the tailgate, which can detect the space around the tailgate. When an obstacle is detected in the movement path of the tailgate, the system generates an interruption, so that the tailgate triggers anti-pinch to avoid collisions or pinching accidents with objects. In the contact anti-pinch technology, there are three anti-pinch judgment methods. One is mechanical anti-pinch. The second is to use the electric actuator of the electric tailgate, and use the motor in the tailgate actuator as the signal acquisition object, and identify and judge through changes in the torque, current, speed, etc. of the driving motor. The third is to use a pressure sensor. When using the second signal acquisition object, because the armature current value and motor torque of the DC motor are reflected in the operating state, these thresholds are often selected as the judgment basis. Due to the generation of a large amount of noise and coupling information in the current sampling signal, it is easy to cause signal fluctuations and affect anti-pinch misjudgment, and it is impossible to ensure the stability of the anti-pinch force. At the same time, due to the different vehicle use environments, the uncertainty of the load of the electric vehicle tailgate is caused, resulting in the variability of the set threshold. Summary of the Invention

[0004] The present invention aims to overcome the deficiencies of the prior art and proposes a method for controlling the anti-pinch function of the tailgate of an electric vehicle to achieve the following objectives: Dynamically estimate the motor torque under different loads of the electric vehicle tailgate through the steady-state Kalman filter algorithm, and then dynamically adjust the size of the torque threshold, thereby increasing the reliability of the anti-pinch control and avoiding anti-pinch misjudgment.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is: A method for controlling the anti-pinch function of the tailgate of an electric vehicle, the method comprising the following steps:

[0006] Step S1: Collect and update the operating data of the drive motor within the monitoring time period t, including armature current and angular velocity;

[0007] Step S2: Perform anti-pinch pre-judgment. When the anti-pinch pre-judgment does not take effect, return to Step S1; when the anti-pinch pre-judgment takes effect, continue to execute the next step;

[0008] Step S3: Obtain the time interval t1 during which the anti-pinch pre-judgment takes effect;

[0009] Step S4: Take the motor torque calculated from the angular velocity as the state variable for anti-pinch control, and perform state estimation on the torque within the time interval t1 through the steady-state Kalman filtering algorithm to obtain the torque estimated value within the time interval t1;

[0010] Step S5: Calculate the sliding square average value TM of the torque estimated value within the time interval t1;

[0011] Step S6: Determine whether the motor is stable within the time interval t1 according to the torque estimated value; if it is not stable, return to Step S1; if it is stable, calculate the torque dynamic threshold Tth under the steady state;

[0012] Step S7: Compare TM with Tth to determine whether to activate anti-pinch; if anti-pinch is activated, the motor rotates in reverse for reverse protection; otherwise, return to Step S1.

[0013] Preferably, Step S2 includes: During the anti-pinch pre-judgment process, set a current change threshold I1 and an angular velocity change threshold N1. When it is detected that the change amount of the increasing current exceeds the threshold I1 and the change amount of the decreasing angular velocity exceeds the threshold N1, it is regarded as the anti-pinch pre-judgment taking effect.

[0014] Preferably, Step S3 includes:

[0015] Select the current value before the signal change as the current reference value Iref, and the angular velocity value before the signal change as the angular velocity reference value Nref;

[0016] Perform current integration based on the current reference value Iref to obtain IS, perform difference calculation based on the angular velocity reference value Nref to obtain NS, and record the time when IS is greater than the current integration threshold I2 and NS is greater than the angular velocity difference threshold N2 as the starting point of the time interval t1, and the corresponding end point is synchronized with the end point of the monitoring time period t.

[0017] Preferably, Step S4 includes:

[0018] The prediction iteration equation of the steady-state Kalman filtering algorithm is:

[0019]

[0020] Among them, α represents the motor angle, ω represents the angular velocity, Δt represents the time interval, and n represents the ordinal number;

[0021] Assume the state variable is S(n) = [a(n) ω(n)], and the state equation can be obtained from the kinematic equation:

[0022]

[0023] Among them,

[0024] The measured value is regarded as the state value plus a measurement noise to obtain the measurement equation:

[0025] x(n) = Cs(n) + v(n) = [1 0][a(n) ω(n)] + v(n)

[0026] x(n) is the posterior estimation matrix of the state variable at the nth time, that is, the torque estimation value; C = [1 0]; v(n) represents the measurement noise.

[0027] Preferably, the step S5 includes: The calculation formula of the sliding square average value TM of the torque estimation value is as follows:

[0028]

[0029] Among them, T - total - time represents the total time of torque measurement, and T(t) represents the torque estimation value at time t.

[0030] Preferably, the step S6 includes:

[0031] Calculate the average value μT and the standard deviation σT of the torque estimation value within the time interval t1;

[0032] Confirm the confidence level x of the torque estimation value;

[0033] Calculate the confidence interval [a, b]: Upper limit of the interval: a = μT - x * σT;

[0034] Lower limit of the interval: b = μT + x * σT;

[0035] If the torque estimation values within the time interval t1 all fall within the confidence interval [a, b], it is considered that the motor is stable, otherwise return to the step S1.

[0036] Preferably, in the step S6, the calculation formula of the torque dynamic threshold Tth under steady state is:

[0037] Tth = μT + 3 * σT;

[0038] Among them, μT and σT respectively represent the average value and the standard deviation of the torque estimation value within the time interval t1.

[0039] Preferably, the step S7 includes: if TM is greater than Tth, it is determined that anti-pinch is enabled, at this time the motor reverses and retracts for protection; if TM is less than or equal to Tth, return to the step S1.

[0040] Preferably, the driving motor of the electric vehicle tailgate adopts a permanent magnet DC brushed motor.

[0041] The technical effects of the present invention are as follows: The present invention uses the steady-state Kalman filter algorithm to estimate the motor torque, which can dynamically change with the different loads of the electric vehicle tailgate, and then dynamically adjust the size of the torque threshold, thereby increasing the reliability of anti-pinch control, avoiding false anti-pinch judgments, improving the user experience, and at the same time improving the overall use efficiency. The present invention also sets anti-pinch pre-judgment to provide a basis for subsequent judgments to improve the reliability of subsequent anti-pinch judgment results. The formal anti-pinch judgment of this embodiment judges the time when anti-pinch takes effect by integrating the current, and at the same time combines the change of angular velocity for double judgment, avoiding false anti-pinch judgments caused by a large amount of noise, coupled information and signal fluctuations in the current sampling signal under a single condition, and at the same time ensuring the stability of the anti-pinch force, improving the user experience and at the same time improving the overall use efficiency. Description of the Drawings

[0042] Figure 1 It is a flowchart of a method for controlling anti-pinch of an electric vehicle tailgate provided by an embodiment of the present invention. Detailed Embodiment

[0043] The following is a further detailed description of the specific embodiments of the present invention by describing the embodiments with reference to the drawings, aiming to help those skilled in the art have a more complete, accurate and in-depth understanding of the inventive concept and technical solution of the present invention, and contribute to its implementation. It should be noted that the terms "first", "second", etc. used in this application are only for the convenience of describing the technical solution to distinguish different components, and do not limit this application. To make the technical solution of the present invention clearer, the present invention is explained by the following embodiments.

[0044] This embodiment provides a method for controlling anti-pinch of an electric vehicle tailgate, as Figure 1 shown, the method includes the following steps:

[0045] Step S1, collect and update the working data of the driving motor within the monitoring time period t, including armature current and angular velocity; the monitoring time period t represents the preset acquisition duration;

[0046] Step S2, perform anti-pinch pre-judgment. When the anti-pinch pre-judgment does not take effect, return to the step S1; when the anti-pinch pre-judgment takes effect, continue to execute the next step;

[0047] Step S3: Obtain the time interval t1 when the anti-pinch prediction takes effect;

[0048] Step S4: Take the motor torque calculated by angular velocity as the state variable for anti-pinch control, and perform state estimation on the torque within the time interval t1 through the steady-state Kalman filtering algorithm to obtain the torque estimation value within the time interval t1;

[0049] Step S6: Calculate the sliding square average value TM of the torque estimation value within the time interval t1;

[0050] Step S9: Judge whether the motor is stable within the time interval t1 according to the torque estimation value; if it is not stable, return to Step S1; if it is stable, calculate the torque dynamic threshold Tth under the steady state;

[0051] Step S7: Compare TM with Tth to determine whether to activate anti-pinch; if it is activated, the motor rotates in reverse for reverse protection; otherwise, return to Step S1.

[0052] Specifically, the tailgate drive motor of the electric vehicle in this embodiment uses a permanent magnet DC brush motor, and the PWM pulse width modulation technology can be used to realize the speed regulation of the DC motor, with sensitive control, which is convenient for the anti-pinch control of the tailgate drive motor of the electric vehicle.

[0053] In Step S1 of this embodiment, the armature current is obtained by collecting the phase current of the drive motor through current sampling tools such as a current sampling circuit and an ammeter. The angular velocity of the motor is obtained through the Hall signal collected by the Hall sensor, and the motor torque can be calculated through the angular velocity. During the execution of the method in this embodiment, data is collected and the original data is updated every time Step S1 is executed. Specifically, data collection can be automatically performed at fixed intervals. During the repeated execution of Step S1, the collected data can be directly called and updated in chronological order to ensure the continuity of data collection and improve the reliability of the data.

[0054] Step S2 of this embodiment includes setting a current change threshold I1 and an angular velocity change threshold N1 during the anti-pinch prediction. When it is detected that the change amount of the current increase exceeds the threshold I1 and the change amount of the angular velocity decrease exceeds the threshold N1, it is regarded as the anti-pinch prediction taking effect. Specifically, the setting of the threshold can be flexibly selected according to the actual situation and does not limit this application. The anti-pinch prediction is used to initially judge whether the anti-pinch function of the motor is activated, providing a basis for subsequent judgments to improve the reliability of subsequent anti-pinch judgment results.

[0055] Step S3 of this embodiment: Obtain the time interval t1 when the anti-pinch prediction takes effect, specifically including:

[0056] Select the current value before the signal change as the current reference value Iref, and the angular velocity value before the signal change as the angular velocity reference value Nref;

[0057] Based on the current reference value Iref, perform current integration to obtain IS. Based on the angular velocity reference value Nref, perform difference calculation to obtain NS. Record the time when IS is greater than the current integration threshold I2 and NS is greater than the angular velocity difference threshold N2 as the starting point of the time interval t1, and the corresponding end point is synchronized with the end point of the monitoring time period t. In this embodiment, the time when anti-pinch takes effect is judged by current integration, and at the same time, the change of angular velocity is combined for double judgment, avoiding the influence of signal fluctuations caused by a large amount of noise and coupling information in the current sampling signal under a single condition, which is prone to anti-pinch misjudgment, while ensuring the stability of the anti-pinch force, improving the overall use efficiency while enhancing the user experience.

[0058] In step S4 of this embodiment, based on the steady-state Kalman filter algorithm, perform state estimation on the motor torque within the time interval t1, so that the obtained torque accuracy and reliability are higher.

[0059] Specifically, the prediction iteration equation of the steady-state Kalman filter algorithm is:

[0060]

[0061] Among them, α represents the motor angle, ω represents the angular velocity, Δt represents the time interval, and n represents the ordinal number;

[0062] Assume that the state quantity is S(n) = [a(n) ω(n)]. From the kinematic equation, the state equation can be obtained:

[0063]

[0064] Among them,

[0065] The measured value is regarded as the state value plus a measurement noise to obtain the measurement equation:

[0066] x(n) = Cs(n) + v(n) = [1 0][a(n) ω(n)] + v(n)

[0067] x(n) is the posterior estimation matrix of the nth state variable, that is, the torque estimation value; C = [1 0]; v(n) represents the measurement noise during signal acquisition. In this way, according to the real-time collected data, the torque estimation value measured by the steady-state Kalman filter algorithm can dynamically estimate the torque with the change of the electric tailgate load.

[0068] After obtaining the torque estimation value, in step S5 of this embodiment, the sliding square average value TM of the torque estimation value within the time interval t1 can be calculated. The specific calculation formula is as follows:

[0069]

[0070] Where T - total - time represents the total time of torque measurement, and T(t) represents the torque estimation value at time t.

[0071] When the motor is stable, the anti - pinch force generated is stable. When the motor is unstable, misjudgment of the anti - pinch function is likely to occur. Therefore, in step S6 of this embodiment, the stability judgment of the motor is added, that is, the estimated torque data within the time interval t1 is respectively compared with the confidence interval of the estimated torque. Specifically:

[0072] Calculate the average value μT and standard deviation σT of the torque estimation value within the time interval t1;

[0073] Confirm the confidence level x of the torque estimation value; in this embodiment, the confidence level is set to 95%, and the corresponding x is equal to 1.96;

[0074] Calculate the confidence interval [a, b]: upper limit of the interval: a = μT - x * σT;

[0075] lower limit of the interval: b = μT + x * σT;

[0076] If the torque estimation values within the time interval t1 all fall within the confidence interval [a, b], the motor is considered stable; otherwise, return to the above - mentioned step S1.

[0077] After the motor is stable, the torque dynamic threshold Tth under steady state can be obtained. The specific calculation formula is:

[0078] Tth = μT + 3 * σT;

[0079] Where μT and σT respectively represent the average value and standard deviation of the torque estimation value within the time interval t1. Since the torque estimation value is dynamically estimated according to the change of the electric tailgate load, the torque dynamic threshold Tth set by the torque estimation value also changes with the change of the electric tailgate load, avoiding the uncertainty of the load of the electric vehicle tailgate caused by different vehicle use environments in the prior art, thus avoiding the variability of the set threshold, and finally avoiding misjudgment of anti - pinch caused by inappropriate threshold setting.

[0080] Finally, step S7 of this embodiment includes: if TM is greater than Tth, it indicates that there is an obstruction during the opening and closing process of the electric vehicle tailgate, and it is determined to activate anti - pinch. At this time, the motor rotates in reverse for retraction protection; if TM is less than or equal to Tth, return to the above - mentioned step S1.

[0081] The present invention has been described exemplarily in conjunction with the accompanying drawings. Obviously, the specific implementation of the present invention is not limited by the above methods. As long as various non-substantive improvements are made by adopting the method concept and technical solution of the present invention; or without improvement, the above concept and technical solution of the present invention are directly applied to other occasions, all fall within the protection scope of the present invention.

Claims

1. An anti-pinch control method for the tailgate of an electric vehicle, characterized in that: The method includes the following steps: Step S1: Collect and update the operating data of the drive motor within the monitoring time period t, including armature current and angular velocity; Step S2: Perform anti-pinch pre-judgment. When the anti-pinch pre-judgment does not take effect, return to Step S1; when the anti-pinch pre-judgment takes effect, continue to execute the next step; Step S3: Obtain the time interval t1 during which the anti-pinch pre-judgment takes effect; Step S4: Take the motor torque calculated from the angular velocity as the state variable for anti-pinch control, and perform state estimation on the torque within the time interval t1 through the steady-state Kalman filter algorithm to obtain the torque estimation value within the time interval t1; Step S5: Calculate the sliding square average value TM of the torque estimation value within the time interval t1; Step S6: Determine whether the motor is stable within the time interval t1 based on the torque estimation value; if it is not stable, return to Step S1; if it is stable, calculate the torque dynamic threshold Tth under steady state; Step S7: Compare TM with Tth to determine whether to activate anti-pinch; if anti-pinch is activated, the motor rotates in reverse for retraction protection; otherwise, return to Step S1.

2. The anti-pinch control method for the tailgate of an electric vehicle according to claim 1, characterized in that: Step S2 includes: During the anti-pinch pre-judgment process, set a current change threshold I1 and an angular velocity change threshold N1. When it is detected that the change amount of the increased current exceeds the threshold I1 and the change amount of the decreased angular velocity exceeds the threshold N1, it is regarded as the anti-pinch pre-judgment taking effect.

3. A method for controlling the anti-pinch function of an electric vehicle's tailgate according to claim 2, characterized in that: Step S3 includes: Select the current value before the signal change as the current reference value Iref, and the angular velocity value before the signal change as the angular velocity reference value Nref; Perform current integration based on the current reference value Iref to obtain IS, perform difference calculation based on the angular velocity reference value Nref to obtain NS, and record the time when IS is greater than the current integration threshold I2 and NS is greater than the angular velocity difference threshold N2 as the starting point of the time interval t1, and the corresponding end point is synchronized with the end point of the monitoring time period t.

4. The anti-pinch control method for the tailgate of an electric vehicle according to claim 3, characterized in that: Step S4 includes: The prediction iteration equation of the steady-state Kalman filter algorithm is: where α represents the motor angle, ω represents the angular velocity, Δt represents the time interval, and n represents the ordinal number; Assume the state quantity is S(n) = [a(n) ω(n)], and the state equation can be obtained from the kinematic equation: Among them, The measured value is regarded as the state value plus a measurement noise to obtain the measurement equation: x(n) = Cs(n) + v(n) = [1 0][a(n) ω(n)] + v(n) x(n) is the posterior estimation matrix of the nth state variable, that is, the torque estimation value; C = [1 0]; v(n) represents the measurement noise.

5. A method for controlling the anti-pinch function of an electric vehicle tailgate according to claim 4, characterized in that: Step S5 includes: The calculation formula for the sliding square average value TM of the torque estimation value is as follows: where T - total - time represents the total time of torque measurement, and T(t) represents the torque estimation value at time t.

6. A method for controlling anti-pinch of an electric vehicle tailgate according to claim 5, characterized in that: Step S6 includes: Calculate the average value μT and the standard deviation σT of the torque estimation value within the time interval t1; Confirm the confidence level x of the torque estimation value; Calculate the confidence interval [a, b]: Upper limit of the interval: a = μT - x * σT; Lower limit of the interval: b = μT + x * σT; If the torque estimation values within the time interval t1 all fall within the confidence interval [a, b], the motor is considered stable; otherwise, return to the step S1.

7. A method for controlling anti-pinch of an electric vehicle tailgate according to claim 6, characterized in that: In the step S6, the calculation formula for the torque dynamic threshold Tth under steady state is: Tth = μT + 3 * σT; where μT and σT respectively represent the average value and the standard deviation of the torque estimation values within the time interval t1.

8. A method for controlling anti-pinch of an electric vehicle tailgate according to claim 7, characterized in that: The step S7 includes: if TM is greater than Tth, it is determined to activate anti-pinch, at this time the motor reverses for retraction protection; if TM is less than or equal to Tth, return to the step S1.

9. A method for controlling anti-pinch of an electric vehicle tailgate according to any one of claims 1-8, characterized in that: The electric vehicle tailgate drive motor adopts a permanent magnet DC brushed motor.

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