A steering wheel zero offset self-learning method, system, device and computer medium

Abstract

The application discloses a steering wheel zero offset self-learning method, system, device and computer medium, relates to the vehicle driving technical field, and responds to the state that the vehicle is stable and straight, then records the state value of the steering wheel steering angle; the state average value of the steering wheel steering angle is generated according to the state value; the steering angle statistical information is updated based on the state average value, and the steering angle statistical information is used for recording the distribution information of the steering angle average value in the set steering angle interval; the deviation value of the steering wheel steering angle is obtained based on the steering angle statistical information and the steering angle interval; the target zero offset value of the steering wheel is obtained based on the deviation value and the historical zero offset value, so that the vehicle is controlled based on the target zero offset value; wherein the distribution information includes the number or the continuous time length of the steering angle average value in the steering angle interval; the historical zero offset value includes the zero offset value of the steering wheel stored when the vehicle is powered off last time. The accuracy of the steering angle and the steering angle statistical information is guaranteed, the accuracy of the deviation value is improved, and the accurate identification of the steering wheel zero offset is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle driving, and more particularly to a steering wheel zero offset self-learning method, system, device and computer medium. BACKGROUND

[0002] With the increase of vehicle driving time, the vehicle may have a steering wheel zero offset phenomenon, which refers to the fixed offset of the steering wheel in the non-operation state. The steering wheel zero offset not only causes the user to have a driving operation problem, but also may cause the vehicle to deviate from the expected trajectory, affecting the driving safety and stability. Therefore, the steering wheel zero offset needs to be identified to maintain or assist the vehicle driving.

[0003] To sum up, how to accurately identify the steering wheel zero offset is a problem to be solved by the person skilled in the art. SUMMARY

[0004] The purpose of the present application is to provide a steering wheel zero offset self-learning method which can solve the technical problem of how to accurately identify the steering wheel zero offset. The present application also provides a steering wheel zero offset self-learning system, an electronic device and a computer readable storage medium.

[0005] In order to achieve the above purpose, the present application provides the following technical solutions:

[0006] A steering wheel zero offset self-learning method, comprising:

[0007] In response to the vehicle being in a stable and straight driving state, the state value of the steering wheel angle is recorded;

[0008] The state average value of the steering wheel angle is generated according to the state value;

[0009] The steering angle statistical information is updated based on the state average value, and the steering angle statistical information is used to record the distribution information of the steering angle average value in the set steering angle interval;

[0010] The deviation value of the steering wheel angle is obtained based on the steering angle statistical information and the steering angle interval;

[0011] The target zero offset value of the steering wheel is obtained based on the deviation value and the historical zero offset value, and the vehicle is controlled based on the target zero offset value;

[0012] The distribution information includes the number or duration of the steering angle average value in the steering angle interval, and the historical zero offset value includes the zero offset value of the steering wheel stored when the vehicle is last powered off.

[0013] Preferably, in response to the vehicle being in a stable and straight driving state, the state value of the steering wheel angle is recorded, comprising:

[0014] detecting whether the steering wheel meets a first stability condition, the first stability condition comprising whether the steering wheel angle is less than a set angle value for a duration period, a next time point of the duration period being a recording time point of a state value, the set angle value comprising an angle value defining a steering wheel failure;

[0015] in response to the steering wheel meeting the first stability condition, detecting whether the vehicle meets a second stability condition, the second stability condition comprising that the centering retention function is turned on, the vehicle speed is within a set range value, a lane line radius is greater than a first set value, and a steering hand torque is less than a second set value;

[0016] in response to the vehicle meeting the second stability condition, detecting whether the vehicle meets a straight-going condition;

[0017] in response to the vehicle meeting the straight-going condition, recording a state value of a steering wheel rotation angle.

[0018] Preferably, the detecting whether the vehicle meets the straight-going condition comprises:

[0019] acquiring, at a set acquisition interval, a distance between a vehicle center line and a lane center line and an included angle between the vehicle center line and the lane center line;

[0020] generating a variance of the distance based on a latest acquired distance and a preset number of historically acquired distances;

[0021] in response to the variance being less than a third set value, a number of acquired distances being greater than or equal to a first number, and the included angle being less than a fourth set value, determining that the vehicle meets the straight-going condition;

[0022] wherein a sign of the distance is used to represent a position of the vehicle center line relative to the lane center line, and a value of the distance is used to represent a degree of deviation of the vehicle center line from the lane center line.

[0023] Preferably, the rotation angle statistical information comprises hit data of each rotation angle average value hitting each rotation angle interval; and the obtaining a deviation value of the steering wheel rotation angle based on the rotation angle statistical information and the rotation angle interval comprises:

[0024] generating a first sum value based on the hit data;

[0025] determining a weight of each rotation angle interval based on the hit data of the rotation angle interval and the first sum value;

[0026] determining the deviation value of the steering wheel rotation angle according to the weight of each rotation angle interval and a midpoint value of each rotation angle interval.

[0027] Preferably, the obtaining a target zero offset value of the steering wheel based on the deviation value and a historical zero offset value comprises:

[0028] obtaining a deviation weight and a history zero deviation weight based on the first sum value and a first setting factor, wherein the history zero deviation weight is a difference between 1 and the deviation weight;

[0029] obtaining a target zero deviation value of the steering wheel according to the deviation value, the deviation weight, the history zero deviation value and the history zero deviation weight;

[0030] The first setting factor is determined according to a maximum number of average values of the steering angle recorded in a self-learning process.

[0031] Preferably, the steering angle statistical information comprises a duration of the average value of the steering angle in a corresponding steering angle interval; and the deviation value of the steering angle is obtained based on the steering angle statistical information and the steering angle interval, comprising:

[0032] generating a second sum value based on the duration;

[0033] determining a weight of each steering angle interval based on the duration of the steering angle interval and the second sum value;

[0034] determining the deviation value of the steering angle according to the weight of each steering angle interval and a midpoint value of each steering angle interval.

[0035] Preferably, the target zero deviation value of the steering wheel is obtained based on the deviation value and a history zero deviation value, comprising:

[0036] obtaining a deviation weight and a history zero deviation weight based on the first sum value and a first setting factor, wherein the history zero deviation weight is a difference between 1 and the deviation weight;

[0037] obtaining a target zero deviation value of the steering wheel according to the deviation value, the deviation weight, the history zero deviation value and the history zero deviation weight;

[0038] The second setting factor is determined according to a duration value of a self-learning process.

[0039] A steering wheel zero deviation self-learning system, comprising:

[0040] a first recording module configured to record a state value of a steering angle when a vehicle is in a stable and straight driving state;

[0041] a first generating module configured to generate an average value of the steering angle based on the state value;

[0042] a first updating module configured to update steering angle statistical information based on the average value, wherein the steering angle statistical information is used to record distribution information of the average value of the steering angle in a set steering angle interval;

[0043] a second generating module configured to obtain a deviation value of the steering wheel angle based on the steering angle statistical information and the steering angle interval;

[0044] a third generating module configured to obtain a target zero offset value of the steering wheel based on the deviation value and a historical zero offset value, and to control the vehicle based on the target zero offset value;

[0045] wherein the distribution information comprises a number or a duration of the steering angle average value in the steering angle interval; and the historical zero offset value comprises a zero offset value of the steering wheel stored when the vehicle is last powered off.

[0046] An electronic device, comprising:

[0047] a memory configured to store a computer program;

[0048] a processor configured to implement the steps of the steering wheel zero offset self-learning method according to any one of the above embodiments when executing the computer program.

[0049] A computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the steering wheel zero offset self-learning method according to any one of the above embodiments.

[0050] The application provides a steering wheel zero offset self-learning method, in response to the vehicle being in a stable and straight driving state, the steering wheel angle state value is recorded; the steering wheel angle state average value is generated according to the state value; the steering angle statistical information is updated based on the state average value, the steering angle statistical information is used to record the distribution information of the steering angle average value in the set steering angle interval; the steering wheel angle deviation value is obtained based on the steering angle statistical information and the steering angle interval; the target zero offset value of the steering wheel is obtained based on the deviation value and the historical zero offset value, so as to control the vehicle based on the target zero offset value; wherein the distribution information includes the number or the continuous time length of the steering angle average value in the steering angle interval; the historical zero offset value includes the zero offset value of the steering wheel stored when the vehicle is last powered off. The application records the steering wheel angle state value only when the vehicle is in a stable and straight driving state, so that the state value can reflect the steering wheel zero offset information, and the accuracy of the state value is ensured; then the steering wheel angle state average value is generated according to the state value, and the steering angle statistical information is updated based on the state average value, so as to reduce the influence of the steering angle fluctuation on the steering angle statistical information and improve the accuracy of the steering angle statistical information; since the distribution information includes the number or the continuous time length of the steering angle average value in the steering angle interval, the distribution information can reflect the distribution weight of the steering angle when the vehicle is driving straight, so that the steering wheel angle deviation value is obtained based on the steering angle statistical information and the steering angle interval, which is equivalent to obtaining the deviation value according to the distribution weight of the steering angle when the vehicle is driving straight, so that the deviation value can be prevented from being too large or too small, the deviation value can accurately reflect the real steering wheel angle of the vehicle during continuous straight driving, and the accuracy of the deviation value is improved; finally, the deviation value and the historical zero offset value are processed, which is equivalent to referring to the historical zero offset value to transition and adjust the deviation value, so that a more accurate target zero offset value can be obtained, and accurate identification of the steering wheel zero offset is realized. The steering wheel zero offset self-learning system, the electronic equipment and the computer readable storage medium provided by the application also solve the corresponding technical problems. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only embodiments of the application, and for those skilled in the art, other drawings can be obtained without creative labor based on the provided drawings.

[0052] Figure 1 The flow chart of the steering wheel zero offset self-learning method provided by the embodiments of the application;

[0053] Figure 2 The schematic diagram for calculating the steering wheel zero offset according to the continuous time length;

[0054] Figure 3 The structural schematic diagram of the steering wheel zero offset self-learning system provided by the embodiments of the application;

[0055] Figure 4 A structural schematic diagram of an electronic device provided by an embodiment of the present application is shown in FIG. 1.

[0056] Figure 5 Another structural schematic diagram of an electronic device provided by an embodiment of the present application is shown in FIG. 2. DETAILED DESCRIPTION

[0057] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0058] Please refer to Figure 1 , Figure 1 A flowchart of a steering wheel zero offset self-learning method provided by an embodiment of the present application is shown in FIG. 3.

[0059] The steering wheel zero offset self-learning method provided by an embodiment of the present application can include the following steps.

[0060] Step S101: In response to the vehicle being in a stable and straight driving state, record the state value of the steering wheel angle.

[0061] In actual application, considering that the steering wheel zero offset is the deflection angle of the steering wheel when the vehicle is driving straight, the vehicle can be first detected to determine whether it is in a stable and straight driving state. If yes, the state value of the steering wheel angle is recorded, that is, the latest value of the steering wheel angle is recorded, so as to analyze the state value to learn the steering wheel zero offset value subsequently. Correspondingly, if the vehicle is not in a stable and straight driving state, the steering wheel angle state value can be recorded after the vehicle re-enters the stable and straight driving state, so as to avoid collecting the steering wheel angle in the non-stable and straight driving state to affect the subsequent steering wheel zero offset self-learning.

[0062] It should be noted that the vehicle is in a stable and straight driving state, which means that the vehicle is stable and straight driving. The detection method of the stable and straight driving of the vehicle can be flexibly determined according to the application scene. For example, in response to the vehicle being in a stable and straight driving state, the process of recording the current steering angle of the steering wheel can be detected to determine whether the steering wheel meets the first stability condition. The first stability condition includes whether the steering wheel angle is less than a set angle value within a continuous time period. The next time of the continuous time period is the recording time of the state value. The set angle value includes an angle value that defines the failure of the steering wheel. When the steering wheel angle exceeds the set angle value, the vehicle needs to be repaired and corrected. The value can be flexibly determined according to the application scene. For example, the continuous time period can be 1.2s, and the set angle value can be 3 degrees, 3.1 degrees, etc. In response to the steering wheel meeting the first stability condition, it is detected whether the vehicle meets the second stability condition. The second stability condition includes starting the centering function, the vehicle speed being within a set range value, the lane line radius being greater than a first set value, and the steering wheel torque being less than a second set value. The centering function can be started and maintained by the ADAS (Advanced Driving Assistance System) of the vehicle, etc. The set range value, the first set value and the second set value can be flexibly determined according to actual needs. For example, the set range value can be 30-100kph, the first set value can be 10000m, and the second set value can be 0.5Nm, etc. In response to the vehicle meeting the second stability condition, it is detected whether the vehicle meets the straight driving condition. In response to the vehicle meeting the straight driving condition, the state value of the steering wheel angle is recorded.

[0063] In a specific application scenario, in the process of detecting whether the vehicle meets the straight driving condition, because the vehicle needs to be on a straight driving road when driving straight, the lane center line of the straight driving road is in a straight line form, so the vehicle center line can be referred to for detecting whether the vehicle meets the straight driving condition. That is, the distance between the vehicle center line and the lane center line can be collected at a set collection interval, such as once every 0.5s, etc. The positive and negative of the distance represent the position of the vehicle center line relative to the lane center line, and the numerical value of the distance represents the degree of deviation of the vehicle center line from the lane center line. For example, the vehicle center line is on the left side of the lane center line, which is negative, and the vehicle center line is on the right side of the lane center line, which is positive. In addition, the unit of the distance can be meters, etc. The angle psi between the vehicle center line and the lane center line is collected. The unit of the angle can be radians, etc. Based on the latest collected distance and a preset number of historically collected distances, the variance of the distance is generated. For example, the variance of the first number of newly collected distances is generated. Assuming that the first number is 5, the newly collected distance value is y0, and the distance values collected at the previous 4 times are y1, y2, y3, and y4, then the variance is In response to the variance being less than a third set value, the number of collected distances y0counter being greater than or equal to a first number, and the included angle being less than a fourth set value, it is determined that the vehicle meets the straight-going condition. The third set value, the second number, and the fourth set value can be flexibly determined according to actual needs. For example, the third set value can be 0.0006, the second number can be 5, and the fourth set value can be 0.02, etc.

[0064] It should be noted that the specific content of the first stable condition, the second stable condition, and the straight-going condition can be flexibly adjusted according to the application scenario, and when any of the first stable condition, the second stable condition, and the straight-going condition is not established, it is determined that the vehicle is not in a stable and straight-going state, etc. It should be noted that a corresponding flag bit can be set for each condition to reflect whether the vehicle meets the corresponding condition. Taking the first stable condition as an example, when the steering wheel angle is less than a set angle value and the duration is greater than 1.2s, SWAIsFit can be set to true, otherwise SWAIsFit can be set to fail, etc. to clearly and effectively represent whether the corresponding condition is established. In addition, when the number of collected distance values is less than the first number, the variance cannot be generated for corresponding detection. At this time, the distance value can be collected at the detection time or the collection time to supplement the number of distance values, so that the vehicle state detection can be performed after the number of distance values is greater than or equal to the first number.

[0065] Step S102: generating a state average value of the steering wheel rotation angle according to the state value.

[0066] Step S103: updating the rotation angle statistical information based on the state average value. The rotation angle statistical information is used to record the distribution information of the rotation angle average value in a set rotation angle interval. The distribution information includes the number or the duration of the rotation angle average value in the rotation angle interval.

[0067] In actual application, the state value can only represent the steering wheel angle value at the current moment. Although the steering wheel angle changes within a certain range when the vehicle is driving straight, the steering wheel angle will still fluctuate. In order to smooth the fluctuation of the steering wheel angle, a state average value of the steering wheel angle can be generated according to the state value, for example, the state average value of the steering wheel angle can be obtained by averaging the second number of newly recorded steering angles, and so on. Assuming that the third number is 4, the average value of the current steering angle can be calculated by averaging the latest four steering angles. It is not difficult to understand that when the steering angle recording counter swaCounter is not enough for the second number at the beginning of the operation of the scheme, the corresponding steering angle average value cannot be generated. However, as time goes on, the number of recorded steering angles will increase, and the corresponding steering angle average value can be generated at each steering angle recording moment. In other words, the application can generate multiple steering angle average values. On this basis, as the number of obtained steering angle average values increases, the distribution information of the steering angle average values becomes more and more obvious. In this process, a steering angle interval can be set, the steering angle interval is obtained by dividing the maximum value interval of the steering wheel zero offset, the steering angle statistical information is updated based on the state average value, and the steering angle statistical information is used to record the distribution information of the steering angle average values in the set steering angle interval. The distribution information can include the number or the duration of the steering angle average values in the steering angle interval, and so on. That is, the steering angle statistical information is used to record the distribution information of the historical average values and the state average values in the set steering angle interval value. For example, if the state average value is located in the steering angle interval value 2, the distribution information of the new state average value in the steering angle interval value 2 can be obtained.

[0068] In a specific application scenario, before updating the steering angle statistical information based on the state average value, the steering angle interval can be determined first, for example, the maximum value interval of the steering wheel zero offset can be determined. The maximum value interval is equally divided to obtain a target number of steering angle intervals. Assuming that the maximum value interval is [-3°, 3°] and the target number is 10, the steering angle interval values can be state=1, representing the steering angle interval value [-3°, -2.4°), state=2, representing the steering angle interval value [-2.4°, -1.8°), state=3, representing the steering angle interval value [-1.8°, -1.2°), state=4, representing the steering angle interval value [-1.2°, -0.6°), state=5, representing the steering angle interval value [-0.6°, 0°), state=6, representing the steering angle interval value [0°, 0.6°), state=7, representing the steering angle interval value [0.6°, 1.2°), state=8, representing the steering angle interval value [1.2°, 1.8°), state=9, representing the steering angle interval value [1.8°, 2.4°), and state=10, representing the steering angle interval value [2.4°, 3°].

[0069] Step S104: Obtain the deviation value of the steering wheel angle based on the steering angle statistical information and the steering angle interval.

[0070] Step S105: obtaining a target zero offset value of the steering wheel based on the deviation value and a historical zero offset value, and controlling the vehicle based on the target zero offset value; the historical zero offset value includes a zero offset value of the steering wheel stored when the vehicle is powered off last time.

[0071] In actual application, after determining the distribution information of the average steering angle in the steering angle interval, there is a difference between the average steering angles hit by each steering angle interval, which can reflect the influence weight of the steering angle interval on the steering angle of the steering wheel, that is, the distribution information can reflect the influence weight of the steering angle interval on the steering angle of the steering wheel, so that the deviation value of the steering angle of the steering wheel can be obtained based on the steering angle statistical information and the steering angle interval, such as the deviation value of the steering angle of the steering wheel can be obtained by weighted average of the steering angle interval based on the steering angle statistical information, so as to comprehensively consider the distribution information of the average steering angle in the steering angle interval. In addition, considering that the vehicle may be affected by the outside world during the process of steering wheel zero offset self-learning, the vehicle may be parked or terminated in this round of self-learning, so that the determined deviation value is not the most accurate steering wheel zero offset. In order to obtain more accurate steering wheel zero offset, the obtained steering wheel zero offset can be stored when the vehicle is powered off, and then the historical zero offset value stored when the vehicle is powered off last time is read, and the target zero offset value of the steering wheel is obtained based on the deviation value and the historical zero offset value, such as the deviation value and the historical zero offset value can be weighted and averaged to refer to the historical zero offset value to transition and adjust the deviation value, so as to obtain the target zero offset value closer to the real steering wheel zero offset.

[0072] It should be noted that as the self-learning time increases, the obtained steering wheel zero offset is more and more consistent with the real steering wheel zero offset, so that the length of single steering wheel zero offset self-learning or the number of iterations can be limited, such as the length of single steering wheel zero offset self-learning is fixed to be the set length, and the learned steering wheel zero offset is considered as the real steering wheel zero offset only after the set length is reached. In this process, considering that the scheme needs to refer to the historical zero offset value for self-learning, the self-learning of this time is equivalent to continuing the self-learning based on the last self-learning, so that the historical zero offset value is increased from 0 to an unchanged value, and it is considered that one self-learning is completed. In other words, the length of time when the historical zero offset value is increased from 0 to an unchanged value can be regarded as the length of single steering wheel zero offset self-learning.

[0073] In actual application, the steering angle statistical information can include hit data of each steering angle average value hitting each steering angle interval, that is, can include the number value of the steering angle average value falling in each steering angle interval, and the distribution information is the number value. Correspondingly, in the process of obtaining the deviation value of the steering wheel steering angle based on the steering angle statistical information and the steering angle interval, the first sum value can be generated based on the hit data, that is, the first sum value of the number value; based on the hit data of the steering angle interval and the first sum value, the weight of each steering angle interval is determined, that is, for each steering angle interval, the number value of the steering angle interval is divided by the first sum value to obtain the weight of the steering angle interval; the midpoint value of each steering angle interval is determined; according to the weight of each steering angle interval and the midpoint value of each steering angle interval, the deviation value of the steering wheel steering angle is determined, that is, according to the weight value of the steering angle interval, the weighted average of all midpoint values is obtained to obtain the current deviation value of the steering wheel steering angle. Then, in the process of obtaining the target zero offset value of the steering wheel based on the deviation value and the historical zero offset value, the deviation weight and the historical zero offset weight can be obtained based on the first sum value and the first set factor, wherein the historical zero offset weight is the difference between 1 and the deviation weight, that is, the first sum value is divided by the first set factor to obtain the deviation weight, and the deviation weight is subtracted from 1 to obtain the historical zero offset weight; according to the deviation value, the deviation weight, the historical zero offset value and the historical zero offset weight, the target zero offset value of the steering wheel is obtained, that is, according to the deviation weight and the historical zero offset weight, the weighted average of the deviation value and the historical zero offset value is obtained to obtain the zero offset value of the steering wheel; wherein the first set factor is determined according to the maximum number value of the steering angle average value recorded in a round of self-learning process, such as the first set factor can be directly the maximum number value, etc.

[0074] For the convenience of understanding, taking the aforementioned 10 target number of steering angle intervals as an example, assuming that the steering angle average value is swaMean, the historical zero offset value is swaOffsetRecord, the target zero offset value is swaOffset, and the deviation value is swaOffsetNew, then the process of calculating the current steering wheel zero offset according to the number value is as follows: count swaMean in different steering angle intervals respectively, count the number value of swaMean in each steering angle interval, and record it as Statescalar1~Statescalar10, calculate the first sum value of the number value scalarSum=Statescalar1+Statescalar2+…+Statescalar10; calculate the weight of each steering angle interval stateWeight1=Statescalar1 / scalarSum, stateWeight2=Statescalar2 / scalarSum…stateWeight10=Statescalar10 / scalarSum; calculate the deviation weight swaOffsetNewFactor=scalarSum / 5000 (5000 is an adjustable value), and the value range of swaOffsetNewFactor is 0~1; calculate the deviation value of the steering angle swa swaOffsetNew=stateWeight1*(-2.7)+stateWeight2*(-2.1)+stateWeight3*(-1.5)+ stateWeight4*(-0.9)+stateWeight5*(-0.3)+stateWeight6*0.3+stateWeight7*0.9+stateWeight8*1.5+stateWeight9*2.1+stateWeight10*2.7; calculate the target zero offset value swaOffset=swaOffsetRecord*(1-swaOffsetNewFactor)+swaOffsetNew*swaOffsetNewFactor.

[0075] In actual application, the turn angle statistical information can include a duration of a turn angle average value in a corresponding turn angle interval, and the distribution information is the duration, which can be determined according to a duration before and after a turn angle value used to generate the turn angle average value, or the number of turn angle average values multiplied by a fixed duration, etc. The fixed duration can be 0.02s, 0.03s, etc. Correspondingly, in the process of obtaining the deviation value of the steering wheel turn angle based on the turn angle statistical information and the turn angle interval, the second sum value can be generated based on the duration, i.e., the second sum value of the duration is generated. The weight of each turn angle interval is determined based on the duration of the turn angle interval and the second sum value, i.e., for each turn angle interval, the duration of the turn angle interval is divided by the second sum value to obtain the weight of the turn angle interval. The midpoint value of each turn angle interval is determined. The deviation value of the steering wheel turn angle is determined according to the weight of each turn angle interval and the midpoint value of each turn angle interval, i.e., the midpoint values are weighted and averaged according to the weight of the turn angle interval to obtain the deviation value of the steering wheel turn angle. In the process of obtaining the target zero offset value of the steering wheel based on the deviation value and the historical zero offset value, the deviation weight and the historical zero offset weight can be obtained based on the second sum value and the second setting factor, wherein the historical zero offset weight is the difference between 1 and the deviation weight, i.e., the second sum value is divided by the second setting factor to obtain the deviation weight, and 1 is subtracted from the deviation weight to obtain the historical zero offset weight. The target zero offset value of the steering wheel is obtained according to the deviation value, the deviation weight, the historical zero offset value and the historical zero offset weight, i.e., the deviation value and the historical zero offset value are weighted and averaged according to the deviation weight and the historical zero offset weight to obtain the target zero offset value of the steering wheel. The second setting factor is determined according to the duration value of one round of self-learning process, such as the second setting factor being the duration value, etc.

[0076] For ease of understanding, still taking the aforementioned target number of 10 corner intervals as an example, assuming that the average value of the steering wheel angle is swaMean, the historical zero offset value is swaOffsetRecord, the target zero offset value is swaOffset, and the deviation value is swaOffsetNew, then the process of calculating the current steering wheel zero offset according to the duration is as follows: swaMean is counted in different corner intervals, the duration of swaMean in each corner interval is counted, and is recorded as StateTimer1~StateTimer10; the second sum of the duration is calculated, TimerSum=StateTimer1+StateTimer2+…+StateTimer10; the weight of each corner interval is calculated, stateWeight1=StateTimer1 / TimerSum, stateWeight2=StateTimer2 / TimerSum…stateWeight10=StateTimer10 / TimerSum; swaOffsetNewFactor=TimerSum / 100 (100 is an adjustable value), and the value range of swaOffsetNewFactor is 0~1; the deviation value of the steering wheel angle swa is calculated, swaOffsetNew=stateWeight1*(-2.7)+stateWeight2*(-2.1)+stateWeight3*(-1.5)+stateWeight4*(-0.9)+stateWeight5*(-0.3)+stateWeight6*0.3+stateWeight7*0.9+stateWeight8*1.5+stateWeight9*2.1+stateWeight10*2.7; the target zero offset value swaOffset is calculated, swaOffset=swaOffsetRecord*(1-swaOffsetNewFactor)+swaOffsetNew*swaOffsetNewFactor. The whole data flow process is shown in Figure 2

[0077] It should be noted that after the deviation value and the historical zero offset value are weighted and averaged to obtain the target zero offset value of the steering wheel, the vehicle is powered off in response, and then the target zero offset value can be stored. At this time, the newly stored target zero offset value becomes the new historical zero offset value, so that the historical zero offset value can be updated.

[0078] ​The application provides a steering wheel zero offset self-learning method, in response to the vehicle being in a stable and straight driving state, the state value of the steering wheel angle is recorded, the state average value of the steering wheel angle is generated according to the state value, the steering angle statistical information is updated based on the state average value, the steering angle statistical information is used to record the distribution information of the steering angle average value in the set steering angle interval, the deviation value of the steering wheel angle is obtained based on the steering angle statistical information and the steering angle interval, and the target zero offset value of the steering wheel is obtained based on the deviation value and the historical zero offset value, so as to control the vehicle based on the target zero offset value, wherein the distribution information includes the number or the continuous time length of the steering angle average value in the steering angle interval, and the historical zero offset value includes the zero offset value of the steering wheel stored when the vehicle is last powered off. The application records the state value of the steering wheel angle only when the vehicle is in a stable and straight driving state, so that the state value can reflect the steering wheel zero offset information and the accuracy of the state value is ensured, then the state average value of the steering wheel angle is generated according to the state value, the steering angle statistical information is updated based on the state average value, so as to reduce the influence of the steering angle fluctuation on the steering angle statistical information and improve the accuracy of the steering angle statistical information, since the distribution information includes the number or the continuous time length of the steering angle average value in the steering angle interval, the distribution information can reflect the distribution weight of the steering angle when the vehicle is driving straight, therefore, when the deviation value of the steering wheel angle is obtained based on the steering angle statistical information and the steering angle interval, the deviation value is obtained according to the distribution weight of the steering angle when the vehicle is driving straight, so that the deviation value can be prevented from being too large or too small, the deviation value can accurately reflect the real steering wheel angle of the vehicle when continuously driving straight, and the accuracy of the deviation value is improved, finally, the deviation value and the historical zero offset value are processed, which is equivalent to that the deviation value is transitioned and adjusted by referring to the historical zero offset value, so that a more accurate target zero offset value can be obtained, and accurate identification of the steering wheel zero offset is realized.

[0079] Please refer to Figure 3 , Figure 3 The application provides a steering wheel zero offset self-learning system.

[0080] The application provides a steering wheel zero offset self-learning system, which can include:

[0081] The first recording module 101 is used to record the state value of the steering wheel angle in response to the vehicle being in a stable and straight driving state.

[0082] The first generation module 102 is used to generate the state average value of the steering wheel angle according to the state value.

[0083] The first update module 103 is used to update the steering angle statistical information based on the state average value, and the steering angle statistical information is used to record the distribution information of the steering angle average value in the set steering angle interval.

[0084] The second generation module 104 is used to obtain the deviation value of the steering wheel angle based on the steering angle statistical information and the steering angle interval.

[0085] The third generation module 105 is configured to obtain a target zero offset value of the steering wheel based on the deviation value and the historical zero offset value, and control the vehicle based on the target zero offset value.

[0086] The distribution information includes the number or the duration of the average steering angle in the steering angle interval, and the historical zero offset value includes the zero offset value of the steering wheel stored when the vehicle is last powered off.

[0087] The steering wheel zero offset self-learning system provided by the embodiments of the present application can include the following components:

[0088] The first detection unit is configured to detect whether the steering wheel meets a first stable condition, and the first stable condition includes whether the steering wheel angle is less than a set angle value within a continuous time period, the next time of the continuous time period is the recording time of the state value, and the set angle value includes an angle value that defines a steering wheel failure.

[0089] The second detection unit is configured to detect whether the vehicle meets a second stable condition in response to the steering wheel meeting the first stable condition, and the second stable condition includes that the centering and holding function is turned on, the vehicle speed is within a set range value, the lane line radius is greater than a first set value, and the steering wheel hand torque is less than a second set value.

[0090] The third detection unit is configured to detect whether the vehicle meets a straight driving condition in response to the vehicle meeting the second stable condition.

[0091] The first recording unit is configured to record the state value of the steering wheel angle in response to the vehicle meeting the straight driving condition.

[0092] The steering wheel zero offset self-learning system provided by the embodiments of the present application can include the following components:

[0093] The steering wheel zero offset self-learning system provided by the embodiments of the present application can include the following components:

[0094] The first processing unit is configured to generate a first sum value based on the hit data amount.

[0095] The second processing unit is configured to determine a weight of each corner interval based on the hit data of the corner interval and the first sum value.

[0096] The first generating unit is configured to determine a deviation value of the steering wheel corner based on the weight of each corner interval and a midpoint value of each corner interval.

[0097] The third generating module can comprise:

[0098] The third processing unit is configured to obtain a deviation weight and a historical zero offset weight based on the first sum value and a first setting factor, wherein the historical zero offset weight is a difference between 1 and the deviation weight.

[0099] The second generating unit is configured to obtain a target zero offset value of the steering wheel based on the deviation value, the deviation weight, a historical zero offset value and the historical zero offset weight.

[0100] The first setting factor is determined according to a maximum number of average values of the steering wheel corner recorded in one self-learning process.

[0101] The third generating module can comprise:

[0102] The fourth processing unit is configured to generate a second sum value based on the duration.

[0103] The fifth processing unit is configured to determine the weight of each corner interval based on the duration of the corner interval and the second sum value.

[0104] The third generating unit is configured to determine the deviation value of the steering wheel corner based on the weight of each corner interval and a midpoint value of each corner interval.

[0105] The third generating module can comprise:

[0106] The sixth processing unit is configured to obtain the deviation weight and the historical zero offset weight based on the second sum value and a second setting factor, wherein the historical zero offset weight is a difference between 1 and the deviation weight.

[0107] The fourth generating unit is configured to obtain the target zero offset value of the steering wheel based on the deviation value, the deviation weight, a historical zero offset value and the historical zero offset weight.

[0108] The second setting factor is determined according to a duration value of one self-learning process.

[0109] The present application also provides an electronic device and a computer readable storage medium, both of which have the corresponding effects of the steering wheel zero offset self-learning method provided by the embodiments of the present application. Please refer toFigure 4 , Figure 4 A structural schematic diagram of an electronic device is provided in an embodiment of the present application.

[0110] An electronic device is provided in an embodiment of the present application, which comprises a memory 201 and a processor 202. The memory 201 stores a computer program. The processor 202 implements the steps of the steering wheel zero offset self-learning method provided in any of the above embodiments when executing the computer program.

[0111] Referring to Figure 5 Another electronic device is provided in an embodiment of the present application, which further comprises: an input port 203 connected to the processor 202, configured to transmit an input command from the outside to the processor 202; a display unit 204 connected to the processor 202, configured to display a processing result of the processor 202 to the outside; and a communication module 205 connected to the processor 202, configured to realize communication between the electronic device and the outside. The display unit 204 can be a display panel, a laser scanning display, or the like. The communication module 205 can adopt a communication mode including but not limited to a Mobile High-Definition Link (MHL) technology, a Universal Serial Bus (USB) technology, a High-Definition Multimedia Interface (HDMI) technology, a wireless connection technology such as a WIreless Fidelity (WiFi) technology, a Bluetooth communication technology, a low-power Bluetooth communication technology, and an IEEE 802.11s-based communication technology.

[0112] A computer readable storage medium is provided in an embodiment of the present application, which stores a computer program. The computer program is executed by a processor to implement the steps of the steering wheel zero offset self-learning method provided in any of the above embodiments.

[0113] The computer readable storage medium involved in the present application includes a Random Access Memory (RAM), a memory, a Read-Only Memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable magnetic disk, a Compact Disc Read-Only Memory (CD-ROM), or any other form of storage medium known in the technical field.

[0114] The description of the related parts in the steering wheel zero offset self-learning system, the electronic device and the computer readable storage medium provided by the embodiments of the present application can refer to the detailed description of the corresponding parts in the steering wheel zero offset self-learning method provided by the embodiments of the present application, which will not be repeated here. In addition, the parts of the above technical solutions provided by the embodiments of the present application that are consistent with the implementation principles of the corresponding technical solutions in the prior art are not described in detail, so as not to be too repetitive.

[0115] It should also be noted that, in this document, the terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0116] The above description of the disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A self-learning method for zero steering wheel bias, characterized in that, include: If the vehicle is in a stable and straight-moving state, the state value of the steering wheel angle is recorded; Generate the average state value of the steering wheel angle based on the state value; The corner statistics are updated based on the average state value, and the corner statistics are used to record the distribution information of the average corner value in the set corner interval; Based on the steering angle statistics and the steering angle range, the deviation value of the steering wheel angle is obtained; Based on the deviation value and the historical zero deviation value, the target zero deviation value of the steering wheel is obtained, and the vehicle is controlled based on the target zero deviation value. The distribution information includes the number or duration of the average turning angle within the turning angle interval; the historical zero bias value includes the zero bias value of the steering wheel stored when the vehicle was last powered off.

2. The method according to claim 1, characterized in that, In response to the vehicle being in a stable and straight-moving state, the state value of the steering wheel angle is recorded, including: The system detects whether the steering wheel meets a first stability condition, which includes whether the steering wheel angle is always less than a set angle value during a duration period. The next moment of the duration period is the recording moment of the state value, and the set angle value includes an angle value that defines a steering wheel malfunction. In response to the steering wheel meeting the first stability condition, it is then detected whether the vehicle meets the second stability condition. The second stability condition includes activating the centering hold function, the vehicle speed being within a set range, the lane line radius being greater than the first set value, and the steering wheel torque being less than the second set value. In response to the vehicle meeting the second stability condition, it is then determined whether the vehicle meets the straight-ahead condition; In response to the vehicle meeting the straight-ahead condition, the state value of the steering wheel angle is recorded.

3. The method according to claim 2, characterized in that, The determination of whether the vehicle meets the straight-ahead condition includes: According to the set data collection interval, the distance between the vehicle centerline and the lane centerline, as well as the angle between the vehicle centerline and the lane centerline, are collected. The variance of the distance is generated based on the latest collected distance and a preset number of historically collected distances; If the variance is less than a third preset value, the number of distances collected is greater than or equal to a first number, and the included angle is less than a fourth preset value, then the vehicle is determined to meet the straight-going condition. The sign of the distance is used to characterize the position of the vehicle's centerline relative to the lane's centerline, and the numerical value of the distance is used to characterize the degree to which the vehicle's centerline deviates from the lane's centerline.

4. The method according to claim 1, characterized in that, The steering angle statistics include the hit data of the average value of each steering angle hitting each steering angle interval; the step of obtaining the deviation value of the steering wheel angle based on the steering angle statistics and the steering angle interval includes: The first sum is generated based on the amount of data hit; Based on the hit data of the corner intervals and the first sum, the weight of each corner interval is determined; The deviation value of the steering wheel angle is determined based on the weight of each turning angle interval and the midpoint value of each turning angle interval.

5. The method according to claim 4, characterized in that, The process of obtaining the target zero-bias value of the steering wheel based on the deviation value and the historical zero-bias value includes: Based on the first sum and the first set factor, the deviation weight and the historical zero-bias weight are obtained, wherein the historical zero-bias weight is the difference between 1 and the deviation weight; The target zero bias value of the steering wheel is obtained based on the deviation value, the deviation weight, the historical zero bias value, and the historical zero bias weight. The first setting factor is determined based on the maximum number of average turning angles recorded during a round of self-learning.

6. The method according to claim 1, characterized in that, The corner statistics include the duration of the average corner value within the corresponding corner interval; The step of obtaining the steering wheel angle deviation value based on the steering angle statistics and the steering angle range includes: A second sum is generated based on the duration; The weight of each corner interval is determined based on the duration of the corner interval and the second sum. The deviation value of the steering wheel angle is determined based on the weight of each turning angle interval and the midpoint value of each turning angle interval.

7. The method according to claim 6, characterized in that, The process of obtaining the target zero-bias value of the steering wheel based on the deviation value and the historical zero-bias value includes: Based on the second sum and the second set factor, the deviation weight and the historical zero-bias weight are obtained, where the historical zero-bias weight is the difference between 1 and the deviation weight. The target zero bias value of the steering wheel is obtained based on the deviation value, the deviation weight, the historical zero bias value, and the historical zero bias weight. The second setting factor is determined based on the duration of a round of self-learning process.

8. A steering wheel zero-bias self-learning system, characterized in that, include: The first recording module is used to record the state value of the steering wheel angle when the vehicle is in a stable and straight-moving state. The first generation module is used to generate the average state value of the steering wheel angle based on the state value; The first update module is used to update the corner statistics based on the average state value, wherein the corner statistics are used to record the distribution information of the average corner value in a set corner interval; The second generation module is used to obtain the deviation value of the steering wheel angle based on the steering angle statistics and the steering angle range; The third generation module is used to obtain the target zero bias value of the steering wheel based on the deviation value and the historical zero bias value, so as to control the vehicle based on the target zero bias value. The distribution information includes the number or duration of the average turning angle within the turning angle interval; the historical zero bias value includes the zero bias value of the steering wheel stored when the vehicle was last powered off.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the steering wheel zero-bias self-learning method as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the steering wheel zero-bias self-learning method as described in any one of claims 1 to 7.

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