CN115045581B - Resistance self-learning method for anti-pinch module lifting system - Google Patents

Abstract

The invention discloses an efficient and reliable self-learning method for the rising and falling resistance parameters of electric window glass, which belongs to the technical field of vehicle electronics, includes the condition setting for resistance update, and considers the motion state and direction of the window glass motor. The starting position of the window glass, the coverage of the anti-pinch range, and the resistance update are more reasonable, so that the anti-pinch function of the window can be better realized; the initialization process and the resistance update after the initialization are set, when the resistance fluctuates The resistance is updated only when several conditions are met. The trigger condition and the resistance value updating condition of the present invention are reliable and effective, and can meet the requirements for the anti-pinch function of the electric window when the vehicle is in use.

Description

A resistance self-learning method of anti-pinch module lifting system

technical field

The invention belongs to the technical field of vehicle electronics, and more specifically relates to a resistance self-learning method for an anti-pinch module lifting system.

Background technique

The current household car windows are electric, that is, the rotation of the window motor is controlled by the window button, thereby driving the window glass to rise or fall. Usually electric windows also have one-button up and down and anti-pinch functions. There are many ways to realize the anti-pinch function, but the condition is that the window glass encounters an obstacle during the rising process, causing the motor to stall, thereby causing changes in other related variables.

Considering that during the use of the vehicle, the parameters of the window will change with the influence of rubber aging, structural wear, temperature and humidity, etc., and such changes will cause changes in the resistance of the window glass to rise and fall, so the vehicle leaves the factory. Obviously, the anti-pinch parameters at the time cannot be static, and the relevant anti-pinch parameters need to be updated in real time according to the current situation of the vehicle.

Contents of the invention

In order to solve the problem that during the use of the vehicle, the parameters of the window will change with the influence of rubber aging, structural wear, temperature and humidity, etc., and such changes will cause the resistance of the window glass to rise and fall. For the realization of the anti-pinch function of the electric window, the present invention provides a self-learning method for the resistance of the lifting system of the anti-pinch module, which can update the window lift resistance in real time, and considering the influence of the voltage fluctuation of the window motor, it can An accurate resistance base value is provided for the corresponding anti-pinch method, and the reliability of the anti-pinch function of the electric vehicle window is improved.

In order to achieve the above object, the present invention provides a self-learning method for the resistance of the lifting system of the anti-pinch module, including:

Step 1: Determine whether the voltage fluctuation of the motor exceeds the current range, if so, go to step 2, otherwise go to step 3;

Step 2: Clear the initialization process completion flag;

Step 3: Set several voltage ranges for the voltage of the motor, and assign a first threshold and a second threshold to each voltage range;

Step 4: Judging whether the signal given by the switch is an up signal and whether the initial position of the window is below the anti-pinch range, or whether the signal given by the switch is a down signal and whether the initial position of the window is above the anti-pinch range, if the signal given by the switch is Up signal and the initial position of the window is below the anti-pinch range, or the switch gives a down signal and the initial position of the window is above the anti-pinch range, then go to step 5, otherwise go to step 11;

Step 5: Determine whether the switch within the anti-pinch range has given a stop command or whether the window has encountered an obstacle. If the switch within the anti-pinch range has given a stop command or the vehicle window has encountered an obstacle, go to step 11, otherwise Go to step 6;

Step 6: Determine whether the motor is overheated after walking through the anti-pinch range, if so, go to step 11, otherwise go to step 7;

Step 7: Determine whether the initialization process is complete, if so, go to step 9, otherwise go to step 8;

Step 8: Store the resistance value recorded in this process into the self-learning data, and send the completion flag of the initialization process;

Step 9: compare the resistance value of this process with the value after data processing with the self-learning base value and the first threshold;

Step 10: Determine whether the number of times the result of step 9 is greater than the threshold exceeds the second threshold, if so, go to step 8, otherwise go to step 11;

Step 11: Exit.

In some optional embodiments, step 9 includes:

The difference between the resistance value of this process and the self-learning base value is compared with the self-learning base value, and the absolute value is taken after multiplying by N, and the largest numbers of the obtained result values are stored in an array, and these number The average value of the number, compare the average value with the first threshold.

In some optional embodiments, the thresholds set in steps 9 and 10 are changed according to the fluctuation of the window motor voltage.

In some optional implementations, Step 4, Step 5 and Step 6 are the preconditions for performing the self-learning initialization process and updating the resistance value.

Generally speaking, compared with the prior art, the above technical solutions conceived by the present invention can achieve the following beneficial effects:

Because the working condition of the vehicle changes at any time, the voltage of the window motor fluctuates, which will affect the external characteristics of the motor, thereby affecting the output of the resistance value of the motor. The present invention considers this situation and sets the corresponding Update initialization process. The update of the self-learning resistance value in the present invention can be targeted to update the lifting resistance for those situations such as aging of glass rubber, wear and tear of structural parts, etc. that have a continuous impact on the rise and fall of the window glass, so as to guarantee At the same time, the real-time performance of the lifting resistance of the window glass avoids the situation that the self-learning data is wrong due to some occasional special circumstances. The invention is applicable to various algorithms for realizing the anti-pinch function based on the driving force of the motor, including algorithms such as ripple anti-pinch and Hall anti-pinch.

Description of drawings

Fig. 1 is a schematic diagram of realization of a resistance self-learning method of an anti-pinch module lifting system provided by an embodiment of the present invention;

Fig. 2 is a schematic flow chart of a resistance self-learning method of an anti-pinch module lifting system provided by an embodiment of the present invention;

Among them, 1-door; 2-door frame; 3-door glass; ①-initialization process; ②-resistance update process.

Detailed ways

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

In the examples of the present invention, "first", "second", etc. are used to distinguish different objects, rather than to describe a specific sequence or sequence.

Basic principle of the present invention is as follows:

A Hall sensor is installed in the window motor, and the Hall sensor will send a Hall pulse signal in real time as the motor runs. The number of Hall pulses is positively related to the operation of the motor, and the motor will generate a certain number of pulses per revolution. . At the same time, the pulse width value of the pulse is positively related to the force on the motor. Therefore, the window position information can be obtained by the pulse number, and the window resistance information can be obtained by the pulse width value.

As shown in Fig. 1 and Fig. 2, the anti-pinch module lifting system resistance self-learning method of the present invention, the entry condition considers the voltage fluctuation of the window motor, and several voltage ranges are set for the voltage of the motor, and each voltage range corresponds to Different thresholds; use level 1 resistance update conditions: compare the current resistance with the self-learning base value after data processing with the set threshold, and only enter the next level of resistance update judgment if it is greater than the threshold. For the processing method, see The following step 9: use the second-level resistance update condition: when the first-level condition is met, start accumulating times, and when the accumulated times reach the set threshold, update the self-learning resistance base value. Specifically, it can be achieved through the following steps:

Step 1: Determine whether the voltage fluctuation of the motor exceeds the current range, if so, go to step 2, otherwise go to step 3;

In step 1, the current range is determined according to the external characteristics of the motor, and the external characteristics of the motors in different voltage ranges have certain differences, which will lead to differences in the normal pulse width value.

Step 2: Clear the initialization process completion flag;

Step 3: Set several voltage ranges for the voltage of the motor, and assign a first threshold and a second threshold to each voltage range;

Among them, the first threshold and the second threshold are different in size, which is realized through modeling during the development of the car door, through model simulation and subsequent physical testing of the car door, and by analyzing the test results of various working conditions and scenarios, considering the sensitivity and Stability to set these two thresholds.

Step 4: Judging whether the signal given by the switch is an up signal and whether the initial position of the window is below the anti-pinch range, or whether the signal given by the switch is a down signal and whether the initial position of the window is above the anti-pinch range, if the signal given by the switch is Up signal and the initial position of the window is below the anti-pinch range, or the switch gives a down signal and the initial position of the window is above the anti-pinch range, then go to step 5, otherwise go to step 11;

Step 5: Determine whether the switch within the anti-pinch range has given a stop command or whether the window has encountered an obstacle. If the switch within the anti-pinch range has given a stop command or the vehicle window has encountered an obstacle, go to step 11, otherwise Go to step 6;

Step 6: Determine whether the motor is overheated after walking through the anti-pinch range, if it is overheated, go to step 11, otherwise go to step 7;

Among them, steps 1, 3, 4, 5, and 6 are S1, S3, S4, S5, and S6 in the schematic diagram of Figure 1, namely 'conditions'.

Step 7: Determine whether the initialization process is complete, if so, go to step 9, otherwise go to step 8;

Step 8: Store the resistance value recorded in this process into the self-learning data, and send the completion flag of the initialization process;

Wherein, step 8 is S8, and the above steps are ① in FIG. 1 , which is the initialization process.

Step 9: Make the difference between the resistance value of this process and the self-learning base value of each corresponding position, then compare it with the self-learning base value, multiply by 100 and take the absolute value, and use a The array is stored, and the average value of these 10 numbers is calculated, and the average value is compared with the first threshold;

Wherein, the self-learning base value represents the self-learning value stored in the last update.

Among them, during the operation of the window motor, every time a pulse is generated, the array is updated once, and the average value is calculated at the same time. Only the change of the cumulative resistance will trigger the algorithm, so the data processing within the anti-pinch range is a dynamic process. The movement of the car window is constantly judging and accumulating the resistance update conditions, so it can avoid some accidental resistance changes that make the self-learning resistance data wrong, and ensure the reliability of the algorithm.

Step 10: Determine whether the number of times the result of step 9 is greater than the threshold exceeds the second threshold, if so, go to step 8, otherwise go to step 11;

Wherein, description: steps 9, 10 are S9, S10, as shown in ② in Fig. 1, steps 9, 10, 8 complete the resistance updating process under the premise of satisfying the conditions.

Step 11: Exit the algorithm.

Wherein, the threshold value set in step 9 and step 10 changes according to the fluctuation of the window motor voltage, so as to ensure the accuracy of updating the resistance base value.

Among them, step 4, step 5 and step 6 are the prerequisites for the self-learning initialization process and resistance value update, and the setting of conditions can ensure that the obtained resistance value is correct and reasonable, thereby ensuring the stability of the algorithm.

It should be pointed out that according to the needs of implementation, each step/component described in this application can be split into more steps/components, and two or more steps/components or part of the operations of steps/components can also be combined into a new Step/component, to realize the object of the present invention.

It is easy for those skilled in the art to understand that the above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention, All should be included within the protection scope of the present invention.

Claims (3)

1. The utility model provides a resistance self-learning method of anti-pinch module lifting system, which is characterized in that:

step 1: judging whether the voltage fluctuation of the motor exceeds the current range, if so, entering a step 2, and otherwise, entering a step 3;

step 2: clearing the initialization process completion flag;

and 3, step 3: setting a plurality of voltage ranges for the voltage of the motor, and endowing a first threshold value and a second threshold value for each voltage range;

and 4, step 4: judging whether the switch gives a rising signal and the initial position of the car window is below an anti-pinch range or not, or judging whether the switch gives a falling signal and the initial position of the car window is above the anti-pinch range or not, if the switch gives the rising signal and the initial position of the car window is below the anti-pinch range or the switch gives the falling signal and the initial position of the car window is above the anti-pinch range, entering the step 5, and if the switch gives the falling signal and the initial position of the car window is above the anti-pinch range, entering the step 11;

and 5: judging whether the switch in the anti-pinch range gives a stop command or the vehicle window meets an obstacle, if so, giving the stop command or the vehicle window meets the obstacle _， Step 11 is entered, if not, step 6 is entered;

step 6: judging whether the motor is overheated after the anti-pinch range is finished, if so, entering a step 11, and if not, entering a step 7;

and 7: judging whether the initialization process is finished, if so, entering a step 9, and if not, entering a step 8;

and 8: storing the resistance value recorded in the process into self-learning data, and sending an initialization process completion mark;

and step 9: comparing the resistance value of the process with the self-learning base value after data processing with a first threshold value;

step 10: judging whether the number of times that the resistance value and the self-learning base value in the step 9 are subjected to data processing and then are larger than the first threshold exceeds a second threshold, if so, entering a step 8, and if not, entering a step 11;

step 11: withdrawing;

wherein, step 9 includes:

and (3) making a ratio of the resistance value of the process to the self-learning base value after the resistance value of the process is differed with the self-learning base value, multiplying N to obtain an absolute value, storing the maximum number of the obtained result values by an array, calculating the average value of the number of the maximum number of the obtained result values, and comparing the average value with a first threshold value.

2. A method according to claim 1, wherein the threshold values set in steps 9 and 10 are varied in response to fluctuations in the window motor voltage.

3. The method of claim 2, wherein steps 4, 5 and 6 are premised on a self-learning initialization procedure and a resistance value update.

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