阅读说明：本技术 一种车辆隔断系统的防夹自适应学习方法及装置 (Anti-pinch self-adaptive learning method and device for vehicle partition system ) 是由 张宁 于 2020-12-16 设计创作，主要内容包括：本发明实施例公开了一种车辆隔断系统的防夹自适应学习方法及装置,该方法包括：依次采集目标距离分段对应的电机的实时电流；判断实时电流、目标距离分段对应的学习电流以及预设防夹阈值是否满足第一预设对应关系；若是,根据实时电流与学习电流,获得第一电流,该第一电流大于学习电流且小于实时电流；将学习电流更新为第一电流,有利于提高防夹自适应学习方法的平稳性,有效避免误学习,保证防夹检测的准确性。(The embodiment of the invention discloses an anti-pinch self-adaptive learning method and device of a vehicle partition system, wherein the method comprises the following steps: sequentially collecting real-time current of a motor corresponding to a target distance segment; judging whether the real-time current, the learning current corresponding to the target distance segments and the preset anti-pinch threshold value meet a first preset corresponding relation or not; if yes, obtaining a first current according to the real-time current and the learning current, wherein the first current is larger than the learning current and smaller than the real-time current; the learning current is updated to be the first current, so that the stability of the anti-pinch self-adaptive learning method is improved, the error learning is effectively avoided, and the accuracy of anti-pinch detection is ensured.)

1. An anti-pinch self-adaptive learning method of a vehicle partition system is characterized by comprising the following steps:

sequentially collecting real-time current of a motor corresponding to a target distance segment;

judging whether the real-time current, the learning current corresponding to the target distance segment and a preset anti-pinch threshold value meet a first preset corresponding relation or not;

if so, obtaining a first current according to the real-time current and the learning current, wherein the first current is larger than the learning current and smaller than the real-time current;

updating the learning current to the first current.

2. The method of claim 1, further comprising:

and if the real-time current, the learning current corresponding to the target distance segments and the preset anti-pinch threshold value do not satisfy the first preset corresponding relation but satisfy the second preset corresponding relation, updating the learning current into the real-time current.

3. The method of claim 2, wherein the determining whether the real-time current, the learning current corresponding to the target distance segment, and a predetermined anti-pinch threshold satisfy a first predetermined relationship comprises:

judging whether the difference value of the real-time current and the learning current is larger than the preset anti-pinch threshold value or not;

if the difference value is larger than the preset anti-pinch threshold value, determining that the real-time current, the learning current corresponding to the target distance subsection and the preset anti-pinch threshold value meet the first preset corresponding relation;

if the difference value is smaller than or equal to the preset anti-pinch threshold value, the real-time current, the learning current corresponding to the target distance subsection and the preset anti-pinch threshold value are determined to be not satisfied, the first preset corresponding relation is satisfied, and the second preset corresponding relation is satisfied.

4. The method according to any one of claims 1-3, wherein obtaining a first current from the real-time current and the learning current comprises:

obtaining the difference value of the real-time current and the learning current, multiplying the difference value by a preset proportion to obtain a product, and taking the product as a change current;

calculating the sum of the learning current and the variation current to obtain a first current.

5. An anti-pinch adaptive learning device of a vehicle partition system, comprising:

the acquisition module is used for sequentially acquiring real-time current of the motor corresponding to the target distance in a segmented manner;

the relation determining module is used for judging whether the real-time current, the learning current corresponding to the target distance subsection and a preset anti-pinch threshold value meet a first preset corresponding relation or not;

an obtaining module, configured to obtain a first current according to the real-time current and the learning current when a determination result of the relationship determining module is yes, where the first current is greater than the learning current and smaller than the real-time current;

an updating module for updating the learning current to the first current.

6. The apparatus of claim 5, wherein:

the updating module is further used for updating the learning current to the real-time current when the relation determining module determines that the real-time current, the learning current corresponding to the target distance segments and the preset anti-pinch threshold do not satisfy the first preset corresponding relation but satisfy the second preset corresponding relation.

7. The apparatus of claim 6, wherein:

the relation determining module is specifically used for judging whether the difference value of the real-time current and the learning current is larger than the preset anti-pinch threshold value or not; if the difference value is larger than the preset anti-pinch threshold value, determining that the real-time current, the learning current corresponding to the target distance segment and the preset anti-pinch threshold value meet the first preset corresponding relation; and if the difference value is smaller than or equal to the preset anti-pinch threshold value, determining the real-time current, the learning current corresponding to the target distance subsection and the preset anti-pinch threshold value are not satisfied, wherein the first preset corresponding relation is satisfied, and the second preset corresponding relation is satisfied.

8. The apparatus according to any one of claims 5-7, wherein:

the obtaining module is specifically configured to obtain a difference between the real-time current and the learning current, multiply the difference by a preset ratio to obtain a product, and use the product as a change current; and calculating the sum of the learning current and the change current to obtain a first current.

9. An electronic device, comprising:

a memory storing executable program code;

a processor coupled with the memory;

the processor calls the executable program code stored in the memory for performing the method of any of claims 1 to 4.

10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, the computer program causing a computer to execute the method according to any one of claims 1 to 4.

Technical Field

The invention relates to the field of control of intelligent electronic equipment, in particular to an anti-pinch self-adaptive learning method and device of a vehicle partition system.

Background

With the development of automobile technology, more and more motor driving devices are used on automobiles, which can be beneficial to improving the comfort of the automobiles, but simultaneously, new requirements on the safety performance of the motor driving devices are required to be continuously provided. For example, for partition systems such as windows and skylights, regulations require that the windows or skylights have openings in the 4-200mm position areas as anti-pinch areas, that is, anti-pinch rebound operations are performed in the anti-pinch areas, thereby avoiding human body injuries caused by pinching events.

In order to realize anti-pinch control, states of a car window or a skylight and the like need to be detected, and in order to accurately judge the states, a plurality of learning currents and distance segments need to be learned in advance so as to distinguish normal running of the car window or the skylight, clamping occurs or the car window or the skylight reaches the top, wherein the learning currents and the distances are anti-pinch parameters needing to be learned. During in-service use, for example the door window can influence the operation of door window because ambient temperature, humidity, the circumstances such as ageing of the friction strip that brings because of using cause door window mechanical structure to change for what learn in advance prevents that the clamp parameter is no longer suitable, consequently, requires to prevent that the clamp algorithm possesses the self-adaptation function, can in time self-adaptation study updates and prevent the clamp parameter, improves the accuracy of preventing the clamp detection. But the door window structure can take place structural change by accident under some accidental scenes but this kind of change can disappear rapidly again, and accidental scenes such as the door window is by the hand push of user or press, fall mud piece/snow/ice-cube etc. on the door window, if carry out the self-adaptation study update of preventing pressing from both sides the parameter this moment, can be the mistake study of an excessive reaction, reduce the accuracy of preventing pressing from both sides the detection.

Disclosure of Invention

The embodiment of the invention discloses an anti-pinch self-adaptive learning method and device of a vehicle partition system, which are used for providing a gradually updated anti-pinch self-adaptive learning method, effectively avoiding error learning and ensuring the accuracy of anti-pinch detection.

The embodiment of the invention discloses a self-adaptive anti-pinch learning method for a vehicle partition system in a first aspect, which comprises the following steps:

sequentially collecting real-time current of a motor corresponding to a target distance segment;

judging whether the real-time current, the learning current corresponding to the target distance segment and a preset anti-pinch threshold value meet a first preset corresponding relation or not;

if so, obtaining a first current according to the real-time current and the learning current, wherein the first current is larger than the learning current and smaller than the real-time current;

updating the learning current to the first current.

As an optional implementation manner, in the first aspect of this embodiment of the present invention, the method further includes:

and if the real-time current, the learning current corresponding to the target distance segments and the preset anti-pinch threshold value do not satisfy the first preset corresponding relation but satisfy the second preset corresponding relation, updating the learning current into the real-time current.

In the above embodiment, when the second preset correspondence relationship is satisfied, the change between the real-time current and the learning current is not large, and the real-time current may be directly substituted for the learning current to be used for the next adaptive learning.

As an optional implementation manner, in the first aspect of the embodiment of the present invention, the determining whether the real-time current, the learning current corresponding to the target distance segment, and a preset anti-pinch threshold satisfy a first preset corresponding relationship includes:

judging whether the difference value of the real-time current and the learning current is larger than the preset anti-pinch threshold value or not;

if the difference value is larger than the preset anti-pinch threshold value, determining that the real-time current, the learning current corresponding to the target distance subsection and the preset anti-pinch threshold value meet the first preset corresponding relation;

if the difference value is smaller than or equal to the preset anti-pinch threshold value, the real-time current, the learning current corresponding to the target distance subsection and the preset anti-pinch threshold value are determined to be not satisfied, the first preset corresponding relation is satisfied, and the second preset corresponding relation is satisfied.

As an optional implementation manner, in the first aspect of the embodiment of the present invention, the obtaining a first current according to the real-time current and the learning current includes:

obtaining the difference value of the real-time current and the learning current, multiplying the difference value by a preset proportion to obtain a product, and taking the product as a change current;

calculating the sum of the learning current and the variation current to obtain a first current.

Through above-mentioned embodiment, carry out different study electric current updates through judging real-time electric current, study electric current and predetermine and prevent the relation of pressing from both sides between the threshold value three, can help improving the stationarity of the self-adaptation study of preventing pressing from both sides the parameter, avoid preventing the mistake study of pressing from both sides the parameter, improve the rate of accuracy of preventing pressing from both sides the detection.

As an optional implementation manner, in the first aspect of the embodiment of the present invention, the learning current is obtained by learning at initialization or obtained by last adaptive learning.

The second aspect of the embodiment of the invention discloses an anti-pinch self-adaptive learning device of a vehicle partition system, which comprises:

the acquisition module is used for sequentially acquiring real-time current of the motor corresponding to the target distance in a segmented manner;

the relation determining module is used for judging whether the real-time current, the learning current corresponding to the target distance subsection and a preset anti-pinch threshold value meet a first preset corresponding relation or not;

an obtaining module, configured to obtain a first current according to the real-time current and the learning current when a determination result of the relationship determining module is yes, where the first current is greater than the learning current and smaller than the real-time current;

an updating module for updating the learning current to the first current.

As an optional implementation manner, in the second aspect of the embodiment of the present invention, the updating module is further configured to update the learning current to the real-time current when the relationship determining module determines that the real-time current, the learning current corresponding to the target distance segment, and the preset anti-pinch threshold do not satisfy the first preset corresponding relationship but satisfy a second preset corresponding relationship.

As an optional implementation manner, in the second aspect of the embodiment of the present invention, the relationship determining module is specifically configured to determine whether a difference between the real-time current and the learning current is greater than the preset anti-pinch threshold; if the difference value is larger than the preset anti-pinch threshold value, determining that the real-time current, the learning current corresponding to the target distance segment and the preset anti-pinch threshold value meet the first preset corresponding relation; and if the difference value is smaller than or equal to the preset anti-pinch threshold value, determining the real-time current, the learning current corresponding to the target distance subsection and the preset anti-pinch threshold value are not satisfied, wherein the first preset corresponding relation is satisfied, and the second preset corresponding relation is satisfied.

As an optional implementation manner, in a second aspect of the embodiment of the present invention, the obtaining module is specifically configured to obtain a product obtained by multiplying a difference value between the real-time current and the learning current by a preset ratio, and use the product as the change current; and calculating the sum of the learning current and the change current to obtain a first current.

As an optional implementation manner, in the second aspect of the embodiment of the present invention, the learning current is obtained by learning at initialization or obtained by last adaptive learning.

A third aspect of an embodiment of the present invention discloses an electronic device, which may include:

a memory storing executable program code;

a processor coupled with the memory;

the processor calls the executable program code stored in the memory to execute the anti-pinch self-adaptive learning method of the vehicle partition system disclosed by the first aspect of the embodiment of the invention.

In a fourth aspect of the embodiments of the present invention, a computer-readable storage medium is disclosed, which stores a computer program, where the computer program enables a computer to execute the anti-pinch adaptive learning method for a vehicle partition system disclosed in the first aspect of the embodiments of the present invention.

A fifth aspect of embodiments of the present invention discloses a computer program product, which, when run on a computer, causes the computer to perform some or all of the steps of any one of the methods of the first aspect.

A sixth aspect of the present embodiment discloses an application publishing platform, where the application publishing platform is configured to publish a computer program product, where the computer program product is configured to, when running on a computer, cause the computer to perform part or all of the steps of any one of the methods in the first aspect.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

in the embodiment of the invention, by sequentially collecting the real-time current corresponding to the target distance segment, and by judging whether the real-time current, the learning current corresponding to the target distance segment and the preset anti-pinch threshold satisfy the first preset corresponding relation, if the first preset corresponding relation is satisfied, the first current which is larger than the learning current and smaller than the real-time current is obtained according to the real-time current and the learning current, and then the learning current is updated to be the first current; therefore, through the implementation of the embodiment of the invention, as the first current is smaller than the practice current and larger than the study current, the anti-pinch self-adaptive learning method which is gradually updated is adopted, the error learning can be effectively avoided, and the accuracy of anti-pinch detection is ensured.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.

FIG. 1 is a schematic flow chart illustrating a method for anti-pinch adaptive learning for a vehicle partition system according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart illustrating a method for anti-pinch adaptive learning for a vehicle partition system according to a second embodiment of the present invention;

FIG. 3 is a graph comparing current curves obtained by the prior self-learning disclosed by the embodiment of the invention and the self-learning provided by the invention;

FIG. 4 is a schematic structural diagram of an anti-pinch adaptive learning device of a vehicle partition system according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of an electronic device according to still another embodiment of the disclosure.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that the terms "first", "second", "third", and "fourth" and the like in the description and the claims of the present invention are used for distinguishing different objects, and are not used for describing a specific order. The terms "comprises," "comprising," and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

The invention is suitable for the isolating systems of windows, skylights and the like in automobiles, taking a window as an example, a motor for controlling the movement of the window is arranged at the lower part of the window glass, a sampling resistor for acquiring the current of the motor is arranged on an input circuit of the motor and is used as a current sensor, the current sensor sends the voltage values at two ends of the sampling resistor to a window anti-pinch controller through a current collector, and the window anti-pinch controller calculates the current of the motor according to ohm's law. The output end of the motor is provided with a Hall sensor, the Hall sensor is used for acquiring a square wave pulse signal of a car window distance, the square wave pulse signal is counted by a Hall counter and then sent to a car window anti-pinch controller, and an anti-pinch self-adaptive learning device, an anti-pinch control device, an interruption module, a storage module and the like are arranged in the car window anti-pinch controller.

In the normal ascending process of the car window, the change of the motor current is very small, the change value is fluctuated near zero almost, and the motor current can be obviously increased only when the car window meets an obstacle or reaches the top of the car window. In the embodiment of the invention, the motor current is detected when clamping occurs by carrying out multiple clamping experiments on vehicles of the same model, and the anti-pinch current threshold is set according to the detected motor current, wherein the anti-pinch current threshold can be the average value of the motor current obtained by the multiple experiments. Based on the anti-pinch current threshold value that sets for, at the door window operation in-process, if the actual electric current of the motor that detects is greater than this anti-pinch current threshold value, then think that the centre gripping takes place, carry out corresponding anti-pinch bounce-back operation to reduce the injury.

Besides the clamping state of the vehicle window, the vehicle window normally runs, the vehicle window glass reaches the top and other states, before the vehicle is put into use, the vehicle window needs to be initialized, and self-adaptive learning is performed to obtain anti-pinch parameters during initialization of the vehicle window so as to accurately judge the state of the vehicle window according to the anti-pinch parameters. The initialized process of door window includes a reasonable self-adaptation learning process, prevents that clamp self-adaptation learning device from self-learning to two parameters of preventing of motor current and distance segmentation, can include:

in the process that the window glass ascends to the top from the bottom, the interval time (set to be 10ms) is used for sending a timing interruption request signal to the current collector and the Hall counter, the current collector responds to the interruption request and collects a motor sampling voltage value at a timing through the current sensor, the sampling voltage value is sent to the window anti-pinch controller through the current sensor, the window anti-pinch controller divides the voltage values at the two ends of the sampling resistor by the resistance value of the sampling resistor to convert the sampling resistor into motor current, and meanwhile, the motor current obtained by calculation in the reasonable learning process at different moments is recorded. The Hall counter responds to the interrupt request to count the number of the square wave pulse signals collected in the Hall sensor at regular time, sends the number to the car window anti-clamping controller, calculates the distance of the car window according to a preset formula, can also be regarded as the height of the car window, and obtains the distance segmentation and the corresponding learning current after storage.

Based on the introduction, the embodiment of the invention discloses an anti-pinch self-adaptive learning method and device of a vehicle partition system, which can effectively reduce the error learning generated in the anti-pinch self-adaptive learning of a vehicle so as to improve the accuracy of anti-pinch detection.

Referring to fig. 1, fig. 1 is a schematic flow chart illustrating an anti-pinch adaptive learning method for a vehicle partition system according to an embodiment of the present invention; as shown in fig. 1, the anti-pinch adaptive learning method of the vehicle partition system may include:

101. and sequentially collecting real-time current corresponding to the target distance segments.

It will be appreciated that the anti-pinch parameters described above are self-learned and stored during initialization of the window, and further updated during subsequent window operation if adaptive learning conditions (e.g., temperature and voltage conditions) are met.

The distance segment is the distance from the glass of the vehicle window to the top of the vehicle window. Wherein, the rotating speed of the motor is obtained by a Hall sensor, the working principle of the Hall sensor is that when the rotor of the motor rotates for one circle, the Hall sensor can output a square wave pulse signal, the Hall counter is used for calculating the number of the square wave pulse signals output by the Hall sensor, the vehicle window anti-clamping controller determines the rotating speed of the motor according to the square wave pulse signals calculated by the Hall counter, for example, the number of the square wave pulse signals output by the Hall sensor is 500 within 1 second, the corresponding rotating speed of the motor is 500r/s, the target distance segmentation is determined according to the preset corresponding relation between the number of the square wave pulse signals and the distance segmentation, meanwhile, the current sensor sends the voltage values at two ends of the sampling resistor to the vehicle window anti-clamping controller through a current collector, and the vehicle window anti-clamping controller calculates the real-time current of the motor according to, thereby obtaining the real-time current corresponding to the target distance segment.

102. Judging whether the real-time current, the learning current corresponding to the target distance segments and the preset anti-pinch threshold value meet a first preset corresponding relation or not; if the determination result is yes, go to the execution step 103 and 104, otherwise, go to the execution step 105.

In the embodiment of the invention, the learning current can be the motor current obtained by self-learning for the first time during initialization or the motor current obtained by self-adaptive learning for the last time.

Wherein, prevent pressing from both sides the current threshold value and be the motor current that the door window took place the centre gripping when the structure is normal (when not changing), can carry out a lot of centre gripping experiments to a certain model car to the electric current of motor when obtaining a plurality of centre grippings and taking the average value of above-mentioned a plurality of electric currents as presetting of this model car prevents pressing from both sides the threshold value, perhaps takes the minimum electric current among a plurality of electric currents that detect as presetting of this model car to prevent pressing from both sides the threshold value and predetermine and prevent pressing from both sides the threshold value. The preset anti-pinch threshold value in the embodiment of the invention is the difference value between the actual current of the motor and the anti-pinch current threshold value when the clamping is detected, a plurality of difference values can be detected in an experiment, and the average value of the difference values is taken as the preset anti-pinch threshold value.

103. And obtaining a first current according to the real-time current and the learning current, wherein the first current is greater than the learning current and less than the real-time current.

In order to prevent over-learning, in the embodiment of the invention, the learning current is not directly modified into the real-time current, but a first current which is larger than the learning current and smaller than the real-time current is obtained, the learning current is updated and stored as the first current, so that the phenomenon that the learning current changes too much, namely over-learning can be avoided, updating can be alleviated, and the accuracy of anti-pinch detection can be improved.

104. The learning current is updated to the first current.

The learning current is updated to the first current, that is, the first current is stored instead of the learning current as the learning current for the next adaptive learning.

105. And determining that the real-time current, the learning current corresponding to the target distance segment and the preset anti-pinch threshold value meet a second preset corresponding relation, and updating the learning current into the real-time current.

When the second preset corresponding relation is met, the change between the real-time current and the learning current is not large, and the real-time current can be directly used for replacing the learning current to serve as the learning current for next self-adaptive learning.

By implementing the embodiment, the real-time current corresponding to the target distance segment is sequentially collected, whether the real-time current, the learning current corresponding to the target distance segment and the preset anti-pinch threshold meet the first preset corresponding relation or not is judged, if the first preset corresponding relation is met, the first current which is larger than the learning current and smaller than the real-time current is obtained according to the real-time current and the learning current, and then the learning current is updated to be the first current; therefore, through the implementation of the embodiment of the invention, as the first current is smaller than the practice current and larger than the study current, the anti-pinch self-adaptive learning method which is gradually updated is adopted, the error learning can be effectively avoided, and the accuracy of anti-pinch detection is ensured.

Referring to fig. 2, fig. 2 is a schematic flow chart illustrating an anti-pinch adaptive learning method of a vehicle partition system according to a second embodiment of the present invention; as shown in fig. 2, the anti-pinch adaptive learning method of the vehicle partition system may include:

201. and sequentially collecting real-time current corresponding to the target distance segments.

Wherein, the distance segment refers to the distance from the glass of the car window to the top of the car window, and the real-time current is represented as I_new[k]。

202. And judging whether the difference value of the real-time current and the learning current is greater than a preset anti-pinch threshold value or not. If yes, go to execute step 203-; if not, go to step 206.

In the embodiment of the invention, if the collected real-time current is I_new[k]Learning current is I_old[k]Calculating the difference value of the two as I_new[k]-I_old[k]If (I)_new[k]-I_old[k])>Ithr_minStep 203 is performed 205 if (I)_new[k]-I_old[k])≤Ithr_minStep 206 is performed.

Wherein, the above Ithr_minIs a predetermined anti-pinch threshold value, and Ithr_minGreater than 0, in (I)_new[k]-I_old[k])>Ithr_minNow, it means that the motor current has a large variation, and in order to avoid the one-time learning from being too large, the ratio is determined by step 203 and 205For example, the adaptive learning method is improved by learning and updating.

203. Determining that the real-time current, the learning current corresponding to the target distance segment and the preset anti-pinch threshold value meet a first preset corresponding relation, obtaining a difference value of the real-time current and the learning current, multiplying the difference value by a preset proportion to obtain a product, and taking the product as a change current.

It is understood that, in the embodiment of the present invention, the first predetermined corresponding relationship is (I)_new[k]-I_old[k])>Ithr_minAfter the first preset corresponding relation is satisfied, the variable current is calculated to be n (I)_new[k]-I_old[k]) Wherein n is a preset proportion and is a numerical value greater than 0. Preferably, n may take the value 1/3.

204. The sum of the learning current and the variation current is calculated to obtain a first current.

I[k]＝I_old[k]+n(I_new[k]-I_old[k]) Wherein, I [ k ]]For the first current, the change in motor current is updated proportionally, via step 204.

205. The learning current is updated to the first current.

Wherein, after the calculation in step 204, I is updated_old[k]＝I[k]Updated I_old[k]And replacing the original stored current as the learning current corresponding to the target distance segment, and using the learning current as the learning current of the next self-adaptive learning.

206. And determining the real-time current, the learning current corresponding to the target distance segment and the preset anti-pinch threshold value, wherein the preset anti-pinch threshold value does not meet the first preset corresponding relation but meets the second preset corresponding relation, and updating the learning current into the real-time current.

It is understood that, in the embodiment of the present invention, the second predetermined corresponding relationship is I_new[k]-I_old[k])≤Ithr_minIf the second preset corresponding relation is satisfied, the I is updated_old[k]＝I_new[k]Updated I_old[k]And replacing the original stored current as the learning current corresponding to the target distance segment, and using the learning current as the learning current of the next self-adaptive learning.

It should be noted that in the present inventionIn an embodiment, after the detected current satisfies the first predetermined corresponding relationship or the second predetermined corresponding relationship, there are generally I consecutive currents satisfying the relationship, i.e. I_new[k]-I_new[k+i]If the number of the learning currents is i, the learning currents are updated sequentially, and i is a positive integer greater than or equal to 2.

It can be further understood that, in the embodiment of the present invention, when the first preset corresponding relationship or the second preset corresponding relationship is satisfied, it is indicated that the real-time current rises, the vehicle window may encounter an obstacle and the motor is locked, so as to avoid the current rise caused by accidental scenes such as pressing by the user from causing incorrect learning, by determining the corresponding relationship between the three, if the first preset corresponding relationship is satisfied, the real-time current rises more, the real-time current is updated according to a certain proportion instead of being directly updated to the real-time current, and if the second preset corresponding relationship is satisfied, the real-time current rises less, so that the learned current can be more the real-time current.

If the structure of the car window is really changed, the car window is continuously updated through multiple times of self-adaptive learning, and the car window is updated only according to the proportion in each self-adaptive learning update, so that the relatively gentle gradual update is realized, the car window gradually approaches to the actual current, and the stability of anti-pinch self-adaptive learning is improved. Particularly, when the structure of the car window is changed instantly due to accidental situations such as pressing of the car window, the current is changed instantly, through the adaptive learning method provided by the embodiment of the invention, although adaptive learning updating is carried out even under the accidental situations, the single updating amplitude is small, current drop is possibly detected during the following adaptive learning, the current can be updated to the current after the current drop, the current change rate in the whole adaptive learning process is small, and the stability of the adaptive learning algorithm is embodied.

Referring to fig. 3, fig. 3 is a comparison diagram of current curves obtained by the prior self-learning disclosed in the embodiment of the present invention and the self-learning provided by the present invention, in fig. 3, an X axis represents a distance of a window, a Y axis represents a motor current, a lower solid line represents a current curve obtained by approximating a current to an actual current through the prior one-time adaptive learning, an upper dotted line represents a current curve obtained by gradually approximating a current to an actual current through the prior one-time adaptive learning provided by the present invention for a plurality of times, wherein I [ k ] -I [ k + I ] motor currents in the dotted line gradually approximate to an actual current through multiple updates in an arrow direction. It can be seen from the comparison between the solid line and the dotted line shown in fig. 3 that the motor current in the dotted line is updated by multiple times of adaptive learning, gradually approaches to the actual current, does not cause excessive reaction, can effectively improve the existing anti-pinch algorithm, improves the stability of the anti-pinch algorithm and improves the accuracy of anti-pinch detection, and the motor current is directly updated to the actual current only by one time of adaptive learning in the solid line, so that the span is large, and the stability of the anti-pinch algorithm is poor. Wherein i is a positive integer of 2 or more.

It is thus clear that, implement above-mentioned embodiment, carry out different study electric current updates through judging the relation between real-time electric current, study electric current and the preset anti-pinch threshold value three, can help improving the stationarity of the self-adaptation study of preventing pressing from both sides the parameter, avoid preventing the mistake study of pressing from both sides the parameter, improve the rate of accuracy of preventing pressing from both sides and detecting.

Referring to fig. 4, fig. 4 is a schematic structural diagram of an anti-pinch adaptive learning device of a vehicle partition system according to an embodiment of the present invention; as shown in fig. 4, the anti-pinch adaptive learning device of the vehicle partition system may include:

the acquisition module 410 is used for sequentially acquiring real-time current corresponding to the target distance segments;

a relation determining module 420, configured to determine whether the real-time current, the learning current corresponding to the target distance segment, and a preset anti-pinch threshold satisfy a first preset corresponding relation;

an obtaining module 430, configured to obtain a first current according to the real-time current and the learning current when the determination result of the relationship determining module 420 is yes, where the first current is greater than the learning current and smaller than the real-time current;

the updating module 440 is configured to update the learning current to a first current.

Optionally, the learning current is obtained by first adaptive learning or obtained by last adaptive learning update.

As an optional implementation manner, the updating module 440 is further configured to update the learning current to the real-time current when the relationship determining module 420 determines that the real-time current, the learning current corresponding to the target distance segment, and the preset anti-pinch threshold do not satisfy the first preset relationship but satisfy the second preset relationship.

By implementing the device, the real-time current corresponding to the target distance subsection is collected in sequence, whether the real-time current, the learning current corresponding to the target distance subsection and the preset anti-pinch threshold value meet a first preset corresponding relation or not is judged, if the first preset corresponding relation is met, a first current which is larger than the learning current and smaller than the real-time current is obtained according to the real-time current and the learning current, and then the learning current is updated to be the first current; therefore, through the implementation of the embodiment of the invention, as the first current is smaller than the practice current and larger than the study current, the anti-pinch self-adaptive learning method which is gradually updated is adopted, the error learning can be effectively avoided, and the accuracy of anti-pinch detection is ensured.

As an optional implementation manner, the relationship determining module 420 is specifically configured to determine whether a difference between the real-time current and the learning current is greater than a preset anti-pinch threshold; if the difference value is larger than the preset anti-pinch threshold value, determining that the real-time current, the learning current corresponding to the target distance subsection and the preset anti-pinch threshold value meet a first preset corresponding relation; and if the difference value is less than or equal to the preset anti-pinch threshold value, determining that the real-time current, the learning current corresponding to the target distance subsection and the preset anti-pinch threshold value do not meet the first preset corresponding relation but meet the second preset corresponding relation.

As an optional implementation manner, the obtaining module 430 is specifically configured to obtain a difference value between the real-time current and the learning current, and then multiply the difference value by a preset ratio to obtain a product, and use the product as the change current; and calculating the sum of the learning current and the variation current to obtain a first current.

In the embodiment of the present invention, the first predetermined correspondence is (I)_new[k]-I_old[k])>Ithr_minAfter the first preset corresponding relation is satisfied, the variable current is calculated to be n (I)_new[k]-I_old[k]) Wherein n is a preset proportion and is a numerical value greater than 0. Preferably, n may take the value 1/3. In satisfying (I)_new[k]-I_old[k])>Ithr_min，I[k]＝I_old[k]+n(I_new[k]-I_old[k]) Wherein, I [ k ]]Is a first current. The second predetermined corresponding relationship is I_new[k]-I_old[k])≤Ithr_minIf the second preset corresponding relation is satisfied, the I is updated_old[k]＝I_new[k]Updated I_old[k]And replacing the original stored current as the learning current corresponding to the target distance segment, and using the learning current as the learning current of the next self-adaptive learning.

Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to another embodiment of the disclosure; the electronic device shown in fig. 5 may include: at least one processor 510, such as a CPU, a communication bus 530 is used to enable communication connections between these components. Memory 520 may be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The memory 520 may optionally be at least one memory device located remotely from the processor 510. Wherein a set of program codes is stored in the memory 510, and the processor 510 calls the program codes stored in the memory 520 for performing the following operations:

sequentially collecting real-time current corresponding to target distance segments; judging whether the real-time current, the learning current corresponding to the target distance segment and the preset anti-pinch threshold value meet a first preset corresponding relation or not; if yes, obtaining a first current according to the real-time current and the learning current, wherein the first current is larger than the learning current and smaller than the real-time current; the learning current is updated to the first current.

As an alternative embodiment, the processor 510 is further configured to perform the following steps:

and if the real-time current, the learning current corresponding to the target distance segment and the preset anti-pinch threshold do not meet the first preset corresponding relation but meet the second preset corresponding relation, updating the learning current into the real-time current.

As an alternative embodiment, the processor 510 is further configured to perform the following steps:

judging whether the difference value of the real-time current and the learning current is larger than a preset anti-pinch threshold value or not; if the difference value is larger than the preset anti-pinch threshold value, determining that the real-time current, the learning current corresponding to the target distance subsection and the preset anti-pinch threshold value meet a first preset corresponding relation; and if the difference value is less than or equal to the preset anti-pinch threshold value, determining that the real-time current, the learning current corresponding to the target distance subsection and the preset anti-pinch threshold value do not meet the first preset corresponding relation but meet the second preset corresponding relation.

As an alternative embodiment, the processor 510 is further configured to perform the following steps:

obtaining the difference value of the real-time current and the learning current, multiplying the difference value by a preset proportion to obtain a product, and taking the product as a change current;

the sum of the learning current and the variation current is calculated to obtain a first current.

The embodiment of the invention also discloses a computer readable storage medium which stores a computer program, wherein the computer program enables a computer to execute the anti-pinch self-adaptive learning method of the vehicle partition system disclosed in the figures 1 to 2.

An embodiment of the present invention further discloses a computer program product, which, when running on a computer, causes the computer to execute part or all of the steps of any one of the methods disclosed in fig. 1 to 2.

An embodiment of the present invention further discloses an application publishing platform, where the application publishing platform is configured to publish a computer program product, where when the computer program product runs on a computer, the computer is enabled to execute part or all of the steps of any one of the methods disclosed in fig. 1 to fig. 2.

It will be understood by those skilled in the art that all or part of the steps in the methods of the embodiments described above may be implemented by hardware instructions of a program, and the program may be stored in a computer-readable storage medium, where the storage medium includes Read-Only Memory (ROM), Random Access Memory (RAM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), One-time Programmable Read-Only Memory (OTPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Compact Disc Read-Only Memory (CD-ROM), or other Memory, such as a magnetic disk, or a combination thereof, A tape memory, or any other medium readable by a computer that can be used to carry or store data.

The anti-pinch self-adaptive learning method and device of the vehicle partition system disclosed by the embodiment of the invention are described in detail, a specific embodiment is applied to explain the principle and the implementation mode of the invention, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.