CN115826456A - Electric vehicle window current ripple anti-pinch control method based on software filtering - Google Patents
Electric vehicle window current ripple anti-pinch control method based on software filtering Download PDFInfo
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Abstract
The invention discloses a software filtering-based electric vehicle window current ripple anti-pinch control method, which comprises the following steps of: the method comprises the following steps: determining system parameters; step two: parameter adaptive learning; step three: recognizing the position of the car window; step four: compensating the position of the car window; step five: and determining and implementing an anti-pinch scheme according to the position of the car window and the filtered motor current. According to the method, a Hall sensor and related circuits are not required to be installed, a ripple signal is extracted by adopting software filtering, the position of the car window is identified, different car window mechanisms and motors can be flexibly matched, filter parameters can be adjusted in a self-adaptive mode, and low-cost and high-precision car window position signal extraction is realized; furthermore, on the basis of current ripple extraction, the direct current component of the current of the vehicle window motor is calculated, and the direct current component of the current of the motor is used as the input of the anti-pinch control system, so that the probability of mistaken anti-pinch of the vehicle window is effectively reduced.
Description
Technical Field
The invention belongs to the technical field of automobile body area control, relates to a power window current ripple anti-pinch control method, and particularly relates to a power window current ripple anti-pinch control method based on software filtering.
Background
With the recent higher requirements of people on automobile safety, the power window anti-pinch function has become one of the basic functions of automobiles. At present, the anti-pinch control system of the car window mainly has two realization modes, namely a non-contact type and a contact type.
The non-contact type car window anti-pinch control system mainly uses an infrared sensor to realize car window anti-pinch judgment, and has the advantage of being free from the influence of factors such as car window vibration, aerodynamic change and the like. However, it requires integrated sensors and associated circuit modules and wiring, which adds cost and limits the styling of the vehicle door. In addition, under severe weather conditions (heavy rain, heavy fog, dust, etc.), the infrared system is difficult to ensure normal operation and is not suitable for the reliable requirements of automobile rigor.
Contact type car window anti-pinch control system mainly uses Hall elements to realize the position judgment of car window anti-pinch, and is the current mainstream car window anti-pinch control system. This solution is less costly than a non-contact window anti-pinch system, however it also requires the installation of a hall sensor and its associated circuitry to obtain the window position signal, and the added sensors and circuitry also present problems to the reliability of the system.
On the basis of a contact type car window anti-pinch control system, in order to further reduce the cost and simplify the installation of a sensor, the hall-sensor-free car window anti-pinch control system is provided. The current Hall sensor-free car window anti-pinch control system mainly obtains ripple signals through hardware circuit filtering, and then realizes anti-pinch judgment according to the ripple signals of a car window motor. The main defects of the scheme are that the hardware filter circuit is related to specific characteristics and parameters of the motor, the characteristics of the same motor in different stages are different, and the hardware filter method cannot flexibly adjust filter parameters, so that the filter effect is influenced, and the anti-pinch performance is further influenced.
In addition, the current contact type car window anti-pinch control technology mainly uses motor current to judge the size of the clamping force. Because the existence of motor current ripple, current door window prevents that the control technique is pressed from both sides relatively poor to the judgement uniformity of clamp force, if other interference factor of superpose again, prevents pressing from both sides the probability increase of misjudgement.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides the electric vehicle window current ripple anti-pinch control method based on software filtering, the method does not need to install a Hall sensor and a related circuit thereof, adopts software filtering to extract a ripple signal, identifies the position of a vehicle window, can flexibly match different vehicle window mechanisms and motors, can adaptively adjust filter parameters, and realizes low-cost and high-precision vehicle window position signal extraction; furthermore, on the basis of current ripple extraction, the direct current component of the current of the vehicle window motor is calculated, and the direct current component of the current of the motor is used as the input of the anti-pinch control system, so that the probability of mistaken anti-pinch of the vehicle window is effectively reduced.
The purpose of the invention is realized by the following technical scheme:
a power window current ripple anti-pinch control method based on software filtering comprises the following steps:
the method comprises the following steps: determination of system parameters
The system parameters comprise the number N of ripples generated by one rotation of the motor, the motor parameters and the sampling frequency omega s The travel of the car window;
the motor parameters comprise motor resistance R and motor back electromotive force coefficient k e And a motor inductance L;
the system parameters are used for vehicle window position identification and position compensation in the third step and the fourth step;
step two: parameter adaptive learning
Step two, filtering and processing current signals of the vehicle window motor
Decomposing the current signal into a low-frequency signal and a high-frequency signal by using a filter, wherein the low-frequency signal is a stable current signal, and the high-frequency signal is a ripple current signal;
step two, self-learning of resistance of vehicle window motor
The vehicle window motor is locked, and the updated motor resistance R can be obtained according to ohm's law;
step two and step three, ripple amplitude self-learning of vehicle window motor
According to the ripple current signal obtained in the first step, counting the accumulated rising value N of the ripple current signal in the complete stroke up And the cumulative drop value N down Then, an average ripple amplitude i is obtained according to the number of ripples a Comprises the following steps:
i a ＝(N up +N down )/(2*N r )；
wherein, N r The number of current ripples which should be generated by the window motor for one complete stroke;
self-adaptive learning parameters are used for vehicle window position identification and position compensation in the third step and the fourth step, and parameter self-learning operation is required when the system is in initial operation and the operation precision does not meet the requirement due to environmental change;
step three: vehicle window position detection
In the ascending process of the car window, a ripple current signal is obtained in a segmented software filtering mode, namely, software filtering is carried out once at every X current sampling points, the ascending value and the descending value of the ripple current signal are extracted from the current signal, accumulated and counted, and when the accumulated ascending value and the accumulated descending value are higher than n X i a Adding one to the counted number of ripples, wherein n is a coefficient, and is more than 0 and less than 1, and the number of ripples is counted by regulating and controlling the amplitude of ripples;
the car window movement distance and the number of ripples are in a direct proportional relation, the approximate car window movement distance can be obtained according to the method, and the more accurate car window movement distance can be obtained according to the compensation mechanism in the fourth step;
step four: vehicle window position compensation
Step four, when the window motor stably runs, estimating the motor rotating speed omega according to the measured voltage and current values and the motor resistance and the back electromotive force coefficient determined in the step one, wherein the calculation formula is as follows:
ω＝(U-Ri)/k e ；
step two, according to the motor rotating speed omega, the theoretical ripple duration can be estimated:
T e ＝2π/(ω*N)；
wherein, T e Representing the theoretical ripple duration when the two ripple counts are too short apart, less than a x T e Meanwhile, considering that the current fluctuation counts the false ripple waves, and the ripple wave count is reduced by one; when the two ripple counts are too long apart, greater than b x T e When the ripple count is reached, it is determined that one of the two ripples is not countedAdding one, wherein a and b are both coefficients, a is more than 0 and less than 1, and b is more than 1 and less than 2;
the compensation mechanism introduces ripple compensation based on time on the basis of the third step, so that more accurate ripple number can be obtained compared with the third step, more accurate window running distance can be further obtained, and the position of the window can be determined according to the initial position and the movement distance of the window;
step five: anti-pinch scheme is determined and implemented according to window position and filtered motor current
At the ascending in-process of door window, confirm the door window position according to the ripple number, and then judge whether the door window is in and prevent pressing from both sides the region, judge whether the centre gripping takes place for the door window according to the motor current after the filtering, when the door window rises to preventing pressing from both sides the region and taking place the centre gripping, start and prevent pressing from both sides the scheme and make the door window descend to the bottom.
Compared with the prior art, the invention has the following advantages:
the hall sensor-free car window anti-pinch control system saves a hall sensor and related circuits thereof, and reduces the hardware cost; by adopting a software filtering method, the filtering parameters of the system can be flexibly adjusted, different vehicle window mechanisms and motors can be flexibly matched, the parameters of the filter can be adaptively adjusted, and the universality of the system is enhanced; whether clamping occurs or not is judged by using the filtered motor current, so that clamping prevention judgment is more stable, and the probability of mistakenly preventing clamping of the car window is effectively reduced.
Drawings
FIG. 1 is a block flow diagram of a method for controlling anti-pinch of current ripples of a power window based on software filtering according to the present invention;
FIG. 2 is a high frequency motor current spectrum;
FIG. 3 is a graph of window motor current during a lift stroke;
FIG. 4 is a graph of ripple current of wavelet filtering;
fig. 5 is a dc current diagram of wavelet filtering.
Detailed Description
The technical solution of the present invention is further described below with reference to the accompanying drawings, but not limited thereto, and any modification or equivalent replacement of the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention shall be covered by the protection scope of the present invention.
The invention provides a software filtering-based electric vehicle window current ripple anti-pinch control method, which comprises the following steps of:
the method comprises the following steps: determination of system parameters
The step is needed before system development, and the determination of system parameters specifically comprises the following steps:
1) The number of ripples generated by one rotation of the motor
The number of ripples generated by one rotation of the motor can be directly obtained by motor parameters, and can also be determined by an experimental method. By adopting an experimental method, a sensor at the position of the motor, such as a Hall sensor, an encoder and the like, is needed to record the rotating speed of the motor, then the ripple current of the motor is subjected to spectrum analysis, and two groups of frequencies are compared, so that the number of ripples generated by one rotation of the motor can be obtained, wherein the specific relationship is as follows:
N＝ω 1 /ω；
wherein, N is the ripple number, omega, generated by one rotation of the motor 1 And omega is the motor ripple current frequency and the motor rotating speed.
2) Internal parameters of the motor
A window motor can be generally described as:
wherein U represents motor voltage, R represents motor resistance, i represents motor current, L represents motor inductance, and k represents motor current e Representing the motor back emf coefficient. When the motor is running steadily or stalling, the rate of change of current may be approximately 0, and the above equation may be expressed as:
U＝Ri+k e ω；
during locked rotor, the motor speed is zero, and the motor resistance R can be obtained through the calculation of the motor voltage and current:
R＝U/i；
again according to a steady operation periodThe motor resistance obtained by calculating the voltage and the current and the motor rotating speed measured by the sensor can obtain the motor inverse electromotive factor k e The specific calculation formula is as follows:
k e ＝(U-Ri)/ω；
other parameters are determined, and the motor inductance value can be calculated:
L＝∫U-Ri-k e ωdt/i。
3) Sampling frequency
According to the Shannon's sampling law, the sampling frequency is greater than twice the signal frequency, so that the sampling frequency omega is s Comprises the following steps:
ω s ＞2ω 1 。
4) Vehicle window stroke
The window motor carries out a complete stroke, for example, the window is lifted from a lower locked rotor position to an upper locked rotor position, and the number of motor rotation turns N in the complete stroke is recorded through a Hall sensor or an encoder m . When then carrying out once complete stroke, the electric current ripple number that window motor should produce is:
N r ＝N m *N；
wherein, N r The number of current ripples which are required to be generated by the window motor for one complete stroke.
Step two: parameter adaptive learning
When the system runs for the first time or the system running environment changes greatly, the step needs to be carried out, and the parameter self-adaptive learning comprises the following steps:
step two, filtering and processing current signals of the vehicle window motor
And decomposing the current signal into a low-frequency signal and a high-frequency signal by using a filter, wherein the low-frequency signal is a stable current signal, the high-frequency signal is a ripple current signal, and the ripple current signal is used for self-learning of the ripple amplitude of the window motor.
Step two, self-learning of resistance of vehicle window motor
Receiving motor temperature and motor ageing's influence, window motor's resistance value may deviate from the norm value, need carry out the self-adaptation to update motor resistance value this moment, and concrete method is: make window motor locked rotor, can obtain the motor resistance R who updates according to ohm's law:
R＝U/i；
step two and step three, ripple amplitude self-learning of vehicle window motor
According to the ripple current signal obtained in the step two, the accumulated ascending value N of the ripple current signal in the complete travel is counted up And the cumulative drop value N down And then the average ripple amplitude i can be obtained according to the number of ripples a Comprises the following steps:
i a ＝(N up +N down )/(2*N r )；
obtain the average ripple amplitude i a Is used for ripple determination in step three.
Step three: vehicle window position recognition
In the process of ascending of the car window, the limited storage space of the single chip microcomputer, the requirement of car window position real-time performance and the limitation of computing capacity are considered, a ripple current signal is obtained in a segmented software filtering mode, namely, software filtering is carried out once at every X current sampling points, the ripple current signal is extracted from the current signal, and X is selected according to the software filtering requirement and the system real-time performance requirement. And then, accumulating the rising value and the falling value of the statistical ripple current signal, and when the accumulated rising value and the accumulated falling value are both higher than n x i a And adding one to the statistical number of the ripples (n is a coefficient, n is more than 0 and less than 1, and is used for regulating and controlling the amplitude of the ripples to count the number of the ripples and is determined by experiments). The number of the ripples is positively correlated with the rotation angle of the motor, and the position of the motor can be determined according to the initial position and the rotation direction of the motor.
Step four: vehicle window position compensation
Due to the existence of interference, the ripple number is not accurately counted purely according to the ripple amplitude, so that a time-based compensation mechanism can be introduced to enable the ripple number to be counted more accurately. When the window motor runs stably, the motor speed can be estimated according to the measured voltage and current values and the motor resistance and the back electromotive force coefficient estimated in the step one, and the calculation formula is as follows:
ω＝(U-Ri)/k e ；
obtaining the motor speed, namely estimating and obtaining the theoretical ripple duration:
T e ＝2π/(ω*N)；
wherein, T e Represents the duration of the ripple in theory, when the two ripple counts are too short apart by less than a x T e Meanwhile, the false ripple is counted due to the current fluctuation, and the ripple count is reduced by one; when the two ripple counts are too long apart, greater than b T e In this case, one of the two ripples is not counted, and the ripple count is incremented by one. Wherein a and b are coefficients, a is more than 0 and less than 1, and b is more than 1 and less than 2.
Step five: anti-pinch scheme is determined and implemented according to window position and filtered motor current
At the ascending in-process of door window, the ripple number that window motor produced is directly proportional with door window movement distance, so can confirm the door window position according to the ripple number, and then judge whether the door window is in and prevent pressing from both sides the region, the door window is prevented pressing from both sides the region and is generally in 200mm to the within range apart from 4mm at the top apart from the bottom. Because can lead to its electric current to rise fast when the clamping takes place for window motor, so can judge whether the window takes place the clamping according to the motor current after the filtering. When the door window rises to the anti-pinch region and takes place the centre gripping, start the anti-pinch scheme and make the door window descend to the bottom.
Examples
This embodiment carries out data verification based on the door of actually taking hall sensor, and control chip selects STM32F103, and motor drive chip selects DRV8305, converts current signal into voltage signal through sampling resistance and reads out by MCU's AD module again. The number of hall signals generated by one complete stroke of the test motor is shown in table 1.
After high-pass filtering, the motor current spectrum is shown in FIG. 2, which has a frequency of about 800Hz. The motor speed is about 81.27r/s according to hall sensor. Since even number of ripple signals are generated by one rotation of the motor, it can be known from the experimental method that 10 ripple signals are generated by one rotation of the motor, and thus the ripple signal generated by one complete stroke is about 2415 according to table 1.
TABLE 1 complete run number of Hall signals
A graph of the current of the window motor measured in a stroke (taking the rise as an example) in the parameter adaptive process is shown in fig. 3, and the current is filtered by adopting a proper wavelet filter coefficient, wherein the specific way of the wavelet filter is as follows: and performing low-frequency decomposition on the motor current signal by using a proper wavelet basis and a proper wavelet decomposition layer number, and reconstructing the motor current signal. When the wavelet basis and the wavelet decomposition layer are proper, the reconstructed signal can be considered as a motor current signal without ripple signals, and the difference value of the original signal and the reconstructed signal is the ripple signals, so that the filtering effect is achieved. The basic formula of wavelet calculation is as follows:
V i ＝Lo_D*↓V i-1 ；
W i ＝Hi_D*↓V i-1 ；
V i-1 ＝Lo_R*↑V i ；
W i-1 ＝Hi_R*↑V i ；
wherein, V i Low frequency coefficient, W, representing wavelet ith layer decomposition i High-frequency coefficients representing wavelet i-th layer decomposition, lo _ D, hi _ D, lo _ R i And Hi _ R respectively represents a low-frequency decomposition coefficient, a high-frequency decomposition coefficient, a low-frequency reconstruction coefficient and a high-frequency reconstruction coefficient corresponding to a certain wavelet base.
In this embodiment, db2 wavelet basis and 4 wavelet decomposition layers are selected to obtain a ripple current diagram and a dc current diagram of wavelet filtering, which are shown in fig. 4 and 5, respectively, and according to the descriptions in the first step and the second step, the motor resistance R and the average ripple amplitude i can be obtained respectively a 0.73 and 1.0978, respectively.
The wavelet filtering method is adopted to carry out segmented filtering on the current, because of the particularity of the wavelet filtering, the number of filtering data needs to be selected to be a power number of 2, and the index of the filtering data is not less than the number of decomposition layers. For better real-time performance, the number of filter points is chosen to be 16. In order to achieve the same effect of the segmented wavelet filtering and the direct wavelet filtering, a plurality of values of the wavelet decomposition of the upper group of data need to be recorded according to the number of coefficients of the wavelet filter, and the data is extended according to the recorded values of the wavelet decomposition of the upper group of data when the wavelet decomposition is carried out each time, so that the wavelet transformation is carried out. In this embodiment, since the selected db2 wavelet-based filter has 4 coefficients, two values of the wavelet decomposition of the previous group need to be placed before the wavelet decomposition data of this time as continuation when performing wavelet decomposition each time, so as to ensure the consistency of the segmented wavelet filtering and the direct wavelet filtering.
According to experiments, the ripple amplitude coefficient n is determined to be 0.5 and the ripple time coefficients a, b are determined to be 0.68 and 1.48, respectively, in the present embodiment. And counting and compensating the number of the ripples according to the fourth step and the fifth step to obtain a more accurate car window position. And finally, judging whether the car window is required to be started to prevent clamping or not better according to the filtered current value. According to the test, the position error of the full-stroke motor is about 0.6%.
Compare fig. 3 and fig. 5, because there is ripple signal in the motor current signal of not filtering in fig. 3, for preventing the mistake and preventing the clamp, need to judge the centre gripping and judge that the electric current setting is slightly big, get 7A in this embodiment. And ripple signals have been filtered out to the motor current signals in fig. 5, the clamping judgment current can be set to be small, in this embodiment, 6A is taken, and then the filtered current signals are used for judging the anti-pinch effect, which is 7 milliseconds earlier than the non-filtered current signals. Because the oscillation of the current is reduced after filtering, the times of mistaken anti-pinch of the motor are obviously reduced when the same clamping judgment current is selected.
Claims (10)
1. A power window current ripple anti-pinch control method based on software filtering is characterized by comprising the following steps:
the method comprises the following steps: determination of system parameters
The system parameters comprise the number N of ripples generated by one rotation of the motor, the motor parameters and the sampling frequency omega s Vehicle window travel;
the motor parameters comprise motor resistance R and motor back electromotive force coefficient k e And a motor inductance L;
step two: parameter adaptive learning
Step two, filtering and processing current signals of the vehicle window motor
Decomposing the current signal into a low-frequency signal and a high-frequency signal by using a filter, wherein the low-frequency signal is a stable current signal, and the high-frequency signal is a ripple current signal;
step two, self-learning of vehicle window motor resistance
The vehicle window motor is locked, and the updated motor resistance R can be obtained according to ohm's law;
step two and step three, ripple amplitude self-learning of vehicle window motor
According to the ripple current signal obtained in the step two, the accumulated ascending value N of the ripple current signal in the complete travel is counted up And the cumulative drop value N down And then obtaining the average ripple amplitude i according to the number of ripples a ；
Step three: vehicle window position recognition
Step three, in the process of lifting the car window, obtaining a ripple current signal in a segmented software filtering mode, namely performing software filtering once every X current sampling points, and extracting the ripple current signal from the current signal;
step three, accumulating and counting the rising value and the falling value of the ripple current signal, and when the accumulated rising value and the accumulated falling value are higher than n x i a Adding one to the counted number of ripples, wherein n is a coefficient, and is more than 0 and less than 1, and the number of ripples is counted by regulating and controlling the amplitude of ripples;
step four: vehicle window position compensation
Step four, when the window motor runs stably, estimating the rotating speed of the motor according to the measured voltage and current values and the motor resistance and the back electromotive force coefficient determined in the step one;
step four, according to the rotating speed of the motor, the theoretical ripple duration T can be estimated e When the two ripple counts are too short, less than a T e Meanwhile, the false ripple is counted due to the current fluctuation, and the ripple count is reduced by one; when the two ripple counts are too long apart, greater than b T e When the measured ripple is measured, one of the two ripples is not counted,adding one to ripple count, wherein a and b are coefficients, a is more than 0 and less than 1, and b is more than 1 and less than 2;
step five: anti-pinch scheme is determined and implemented according to window position and filtered motor current
In the process of ascending the car window, judging whether the car window is in an anti-pinch area according to the position determined by the ripple waves, and judging whether the car window is pinched according to the filtered motor current; when the door window rises to the anti-pinch region and takes place the centre gripping, start the anti-pinch scheme and make the door window descend.
2. The software filtering-based power window current ripple anti-pinch control method according to claim 1, wherein the number N of ripples generated by one rotation of the motor is directly obtained from motor parameters or obtained by the following formula:
N＝ω 1 /ω；
wherein, ω is 1 Is the motor ripple current frequency.
3. The software filtering-based power window current ripple anti-pinch control method according to claim 1, wherein the motor back electromotive force coefficient k is e The calculation formula of (2) is as follows:
k e ＝(U-Ri)/ω。
4. the electric vehicle window current ripple anti-pinch control method based on software filtering of claim 1, wherein a calculation formula of the motor inductance L is as follows:
L＝∫U-Ri-k e ωdt/i。
5. the power window current ripple anti-pinch control method based on software filtering according to claim 1, wherein the sampling frequency ω is a sampling frequency s ＞2ω 1 ，ω 1 Is the motor ripple current frequency.
6. The software filtering-based power window current ripple anti-pinch control method according to claim 1, wherein the ripple amplitude i is a The calculation formula of (2) is as follows:
i a ＝(N up +N down )/(2*N r )；
wherein N is r The number of current ripples which are required to be generated by the window motor for one complete stroke.
7. The software filtering-based power window current ripple anti-pinch control method according to claim 6, wherein the number N of current ripples r The calculation formula of (2) is as follows:
N r ＝N m *N；
wherein, N m The number of turns of the motor is.
8. The power window current ripple anti-pinch control method based on software filtering of claim 1, 2 or 3, wherein the calculation formula of the motor rotation speed ω is as follows:
ω＝(U-Ri)/k e 。
9. the software filtering-based power window current ripple anti-pinch control method according to claim 1, wherein the theoretical ripple duration T is e The calculation formula of (a) is as follows:
T e ＝2π/(ω*N)。
10. the software filtering-based power window current ripple anti-pinch control method according to claim 1, wherein the window anti-pinch region is within a range from 200mm from the bottom to 4mm from the top.
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