Self-learning method for steering zero position of steering system, control device, steering system and vehicle

Abstract

The invention relates to a steering zero position self-learning method for a steering system. The steering zero position self-learning method comprises the steps that a stored static compensation angle is obtained; acquiring operation parameters of the vehicle; determining whether the vehicle is in a straight driving state based on the operation parameters; if the vehicle is ascertained to be in a straight driving state on the basis of the operating parameters, entering a self-learning loop mode of a steering zero position, in which the steering zero position is learned in a manner of correcting a current steering angle by means of a current dynamic compensation angle, the current dynamic compensation angle can be dynamically changed according to the time progress and / or the value of the self-learning steering zero position; and comparing the current dynamic compensation angle with the acquired static compensation angle, and selectively updating the stored static compensation angle with the current dynamic compensation angle based on the comparison result. In addition, the invention relates to a control device, a computer readable storage medium, a steering system and a vehicle.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle steering, and more specifically, to a self-learning method for a steering zero position of a steering system and a control device for executing the self-learning method. In addition, the present application also relates to a computer-readable storage medium, a steering system and a vehicle. Background Art

[0002] The vehicle's steering system is an important part of the vehicle's driving system. The function of the vehicle's steering system is to control the vehicle's driving direction according to the driver's intention. As an important assembly of the vehicle, the steering system is closely related to the vehicle's handling stability, comfort and driving safety.

[0003] Currently common steering systems include mechanical steering systems, hydraulic power steering systems, electric power steering systems, electronically controlled hydraulic steering systems, and wire-controlled steering systems.

[0004] However, due to system errors in the vehicle (such as assembly errors during vehicle assembly), calibration deviations (such as calibration deviations of SAS sensors) and / or load changes, the steering zero position may deviate, that is, the electronic steering zero position of the steering system deviates from the mechanical steering zero position of the vehicle, which can easily cause the vehicle to deviate. For this reason, the driver needs to frequently correct the direction, which affects driving comfort and leads to frequent market complaints.

[0005] Therefore, how to further improve the functional safety of the vehicle, especially to reduce the steering zero position deviation of the steering system in an efficient and reliable manner, is a technical problem that needs to be solved urgently by those skilled in the art. Summary of the invention

[0006] Therefore, the purpose of the present application is to provide a self-learning method for a steering zero position of a steering system, a control device for executing the self-learning method, a computer-readable storage medium, a steering system, and a vehicle, which can overcome at least one defect in the prior art. This can further improve the functional safety of the vehicle, in particular, reduce the steering zero position deviation of the steering system in an efficient and reliable manner.

[0007] According to a first aspect of the present application, a self-learning method for a steering zero position of a steering system is provided, the self-learning method comprising: obtaining a stored static compensation angle for correcting the steering zero position, especially returning to the zero position; obtaining an operating parameter of a vehicle; determining whether the vehicle is in a straight-line driving state based on the operating parameter; if the vehicle is in a straight-line driving state based on the operating parameter, entering a self-learning cycle mode of the steering zero position, and in the self-learning cycle mode of the steering zero position, the current dynamic compensation angle D is used to correct the steering zero position. T To correct the current steering angle E TThe way comes from learning to turn to zero position A T , where the current dynamic compensation angle D T Can be turned to zero position A according to the progress of time and / or self-learning T The current dynamic compensation angle is compared with the acquired static compensation angle, and the stored static compensation angle is selectively updated with the current dynamic compensation angle based on the comparison result.

[0008] In some embodiments, obtaining the operating parameters of the vehicle includes: obtaining the yaw angular velocity of the vehicle; obtaining the lateral acceleration of the vehicle; obtaining the vehicle speed; obtaining the wheel speed of the vehicle; and / or obtaining the steering rate of the vehicle.

[0009] In some embodiments, determining whether the vehicle is in a straight-line driving state based on the operating parameters includes: determining whether the vehicle's yaw angular velocity is less than a first threshold value; determining whether the vehicle's lateral acceleration is less than a second threshold value; and / or determining whether the vehicle's speed is greater than a third threshold value; and / or determining whether the vehicle's wheel speed difference is less than a fourth threshold value; and / or determining whether the vehicle's turning rate is less than a fifth threshold value; and / or determining whether the sum of the current steering angle and the current dynamic compensation angle is less than a sixth threshold value. If some or all of the above-mentioned determination results are affirmative, it is determined that the vehicle is in a straight-line driving state.

[0010] In some embodiments, the first threshold is between 0.01° / s and 1° / s or between 0.05° / s and 0.5° / s; preferably, the second threshold is between 0.01 m / s 2 Up to 1m / s 2 or 0.05m / s 2 Up to 0.5m / s 2 preferably, the third threshold is between 3 kph and 60 kph; preferably, the fourth threshold is between 0.1 kph and 3 kph or between 0.5 and 2 kph; preferably, the fifth threshold is between 1 ° / s and 5 ° / s; preferably, the sixth threshold is between 10 ° and 50 ° or between 20 ° and 40 °.

[0011] In some embodiments, the self-learning method includes: obtaining a first steering angle from a steering angle sensor, in particular a steering wheel angle sensor, and correcting a steering zero position for the steering system based on the first steering angle and a stored static compensation angle, in particular determining the steering zero position for the steering system by summing the first steering angle and the stored static compensation angle.

[0012] In some embodiments, the self-learning method includes: obtaining a second steering angle from an angle sensor of a motor of a steering system, and obtaining a current steering angle E based on the first steering angle and the second steering angle. TPreferably, in the self-learning cycle mode of steering zero position, the initial value of the current steering angle is set to the first steering angle.

[0013] In some embodiments, in the self-learning cycle mode of steering to zero position, according to the previous value D of the dynamic compensation angle T-1 and the dynamic compensation factor to obtain the current dynamic compensation angle D T Preferably, the dynamic compensation factor can be adjusted to zero position A according to the progress of time and / or self-learning T The value changes dynamically.

[0014] In some embodiments, in the self-learning cycle mode of turning to zero, the turning to zero position A is self-learned by the first formula T , that is, A T =D T +E T .

[0015] In some embodiments, in the self-learning cycle mode of steering to zero position, the current dynamic compensation angle D is determined by the second formula: T , that is, D T =D T-1 +D factor .

[0016] In some embodiments, in the self-learning cycle mode of turning to zero, the dynamic compensation factor D is set by the third formula factor , that is, D factor =Vx*T, where Vx is the compensation speed coefficient and T is the time parameter.

[0017] In some embodiments, in the self-learning cycle mode of the steering zero position, according to the self-learned steering zero position A T To determine the value of the compensation speed coefficient Vx, so that the self-learning steering zero position A T The sign is opposite to that of the compensation speed coefficient Vx.

[0018] In some embodiments, in the self-learning cycle mode of the steering zero position, the self-learned steering zero position A is determined. T The absolute value of which is less than a predetermined threshold value of the time parameter and / or the learned steering zero position A T The compensation speed coefficient Vx is set based on the jitter parameters within a predetermined time period. Preferably, the absolute value of the compensation speed coefficient Vx is between 0.01° / s and 1° / s or between 0.05° / s and 0.5° / s.

[0019] In some embodiments, the self-learning method includes: if it is found based on the operating parameters that the vehicle is not in a straight-line driving state, then exiting the self-learning cycle mode of the steering zero position and entering the holding cycle mode of the steering zero position, in which the current dynamic compensation angle D is used to adjust the steering zero position. T To correct the current steering angle E T Self-learning to zero position A T , where the current dynamic compensation angle D T Equal to the previous value of the dynamic compensation angle D T-1 .

[0020] In other embodiments, the current dynamic compensation angle D may also be specified. T Equal to the previous value of the dynamic compensation angle D T-1 Summation or product with a correction factor.

[0021] In some embodiments, the self-learning method includes: if the absolute value of the difference between the current dynamic compensation angle and the acquired static compensation angle is greater than a first update threshold at least once within a predetermined time period, then activating the updating of the stored static compensation angle with the current dynamic compensation angle, and / or if the absolute value of the difference between the current dynamic compensation angle and the acquired static compensation angle is greater than a second update threshold for multiple times within multiple predetermined time periods, then activating the updating of the stored static compensation angle with the current dynamic compensation angle, wherein the second update threshold is smaller than the first update threshold.

[0022] In some embodiments, the predetermined time period is between 3 minutes and 30 minutes or between 5 minutes and 15 minutes; preferably, the first update threshold is between 5° and 10°, and the second update threshold is between 1° and 5°.

[0023] In some embodiments, it is only allowed to call the stored static compensation angle to compensate the zero position of the steering system during the steering return power assistance of the steering system. Advantageously, since the self-learning method only affects the steering return power assistance and the steering system itself meets the functional safety goals of preventing self-steering and steering lock, adding the self-learning method of the present invention does not affect the steering system meeting the relevant functional safety goals in preventing self-steering and steering lock.

[0024] In some embodiments, the predetermined time period is calculated continuously during the self-learning cycle mode and the holding cycle mode of the turn-to-zero position.

[0025] In some embodiments, the self-learning method includes: obtaining an activation request, preferably automatically generating an activation request based on power-on of the steering system; allowing the stored static compensation angle to be updated with the current dynamic compensation angle up to 5 times, preferably 3 times, during each power-on activation of the steering system.

[0026] According to a second aspect of the present application, a control device is provided, comprising: a processor; and a computer-readable memory coupled to the processor, the computer-readable memory being configured to store a series of computer-executable instructions, wherein the series of computer-executable instructions, when executed by the processor, causes the processor to perform the self-learning method described in some embodiments of the present invention.

[0027] According to a third aspect of the present application, a computer-readable storage medium is provided, the computer-readable storage medium comprising computer-executable instructions stored thereon, and the computer-executable instructions, when executed by a processor, cause the processor to perform the method according to some embodiments of the present invention.

[0028] According to a fourth aspect of the present application, a steering system is provided, the steering system comprising a motor and a control device according to some embodiments of the present invention for controlling the motor.

[0029] According to a fifth aspect of the present application, a vehicle is provided, the vehicle comprising a steering system according to some embodiments of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The present application will be described in more detail below with reference to the accompanying drawings and by means of specific embodiments. The schematic drawings are briefly described as follows:

[0031] Figure 1 A partial schematic diagram of a vehicle according to some embodiments of the present application is shown, which includes a steering system according to some embodiments of the present application;

[0032] Figure 2 A flow chart showing a self-learning method for a steering zero position of a steering system according to some embodiments of the present application is shown;

[0033] Figure 3 An exemplary variation graph of the yaw rate of a vehicle is shown;

[0034] Figure 4 An exemplary variation graph of the lateral acceleration of the vehicle is shown;

[0035] Figure 5 An exemplary variation graph of the vehicle's yaw rate, lateral acceleration, and wheel speed difference is shown;

[0036] Figure 6 An exemplary variation curve diagram of the dynamic compensation angle is shown;

[0037] Figure 7 An exemplary curve of a learned steering zero position after correction of the steering angle by the dynamic compensation angle is shown. DETAILED DESCRIPTION

[0038] The present application will be described below with reference to the accompanying drawings, wherein the accompanying drawings illustrate several embodiments of the present application. However, it should be understood that the present application can be presented in a variety of different ways and is not limited to the embodiments described below; in fact, the embodiments described below are intended to make the disclosure of the present application more complete and fully explain the scope of protection of the present application to those skilled in the art. It should also be understood that the embodiments disclosed herein can be combined in various ways to provide more additional embodiments.

[0039] In the various embodiments described in different ways, the same elements are assigned the same reference numerals or the same element names, wherein the disclosure contained in the entire specification can be transferred to the elements assigned the same reference numerals or the same element names according to the meaning. In addition, in various embodiments, the number, implementation and / or arrangement structure of the elements are not limited to the examples shown, but other numbers, implementations and / or arrangements can be selected according to actual needs.

[0040] As used herein, spatial relational terms such as "upper," "lower," "left," "right," "front," "rear," "higher," "lower," etc. may describe the relationship of one feature to another feature in the accompanying drawings. It should be understood that the spatial relational terms encompass different orientations of the device in use or operation in addition to the orientation shown in the accompanying drawings. For example, features previously described as being "below" other features may now be described as being "above" the other features when the device in the accompanying drawings is turned over. The device may also be otherwise oriented (rotated 90 degrees or in other orientations), and the relative spatial relationships will be interpreted accordingly.

[0041] Herein, the term "A or B" includes "A and B" and "A or B" rather than exclusively including only "A" or only "B", unless specifically stated otherwise.

[0042] In this document, the terms "illustrative" or "exemplary" mean "used as an example, instance or illustration" rather than as a "model" to be exactly copied. Any implementation described as an example herein is not necessarily to be interpreted as preferred or advantageous over other implementations. Moreover, this application is not limited by any expressed or implied theory given in the above technical field, background technology, invention content or detailed description.

[0043] As used herein, the term "substantially" is intended to include any minor variations due to design or manufacturing defects, tolerances of devices or components, environmental influences, and / or other factors.

[0044] In this document, the term "part" may be a part of any proportion, for example, greater than 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90%.

[0045] In addition, the terms "first", "second" and the like may also be used herein for reference purposes only, and thus are not intended to be limiting. For example, the terms "first", "second" and other such numerical terms referring to structures or elements do not imply a sequence or order unless the context clearly indicates otherwise.

[0046] Next, various aspects of the present application are described in detail with reference to the accompanying drawings.

[0047] Reference Figure 1 , Figure 1 A partial schematic diagram of a vehicle 100 according to some embodiments of the present application is shown, in which a steering system 10 according to some embodiments of the present application is integrated. In the current embodiment, a commercial vehicle is used as an example for introduction. It should be understood that in the present application, the vehicle 100 can be any motor vehicle, such as a car, a bus, a truck, a van, or other movable tools.

[0048] like Figure 1 As shown, the vehicle 100 of the present application adopts an electronically controlled hydraulic steering system 10 , which can realize hydraulic power steering with the help of a hydraulic steering assembly 5 on the one hand, and can also realize electric power steering with the help of an electric steering assembly 2 on the other hand.

[0049] The hydraulic steering assembly 5 may include, for example, a hydraulic pot 501 (eg, an oil pot), a hydraulic pipe 502 and a hydraulic pump 503. The hydraulic pot 501 may provide hydraulic assistance to the steering gear input shaft 3 by means of the hydraulic pump 503 and the hydraulic pipe 502.

[0050] The electric steering assembly 2 may include a motor 6 for electric power assistance, a control device 50 for controlling the motor 6, and a power supply (not shown) for feeding the motor 6. The control device 50 may be configured to control the motor 6 according to the acquired steering angle so that the torque provided by the motor 6 can be provided to the steering input shaft 3 via the transmission mechanism 62 for electric power assistance. In some embodiments, the motor 6 for electric power assistance may be a DC motor, such as a brushless DC motor. At this time, the power supply for feeding the motor 6 may be constituted as a battery in the vehicle 100 and a corresponding DC / DC converter. In some embodiments, the motor 6 for electric power assistance may be an AC motor. At this time, the power supply for feeding the motor 6 may be constituted as a battery in the vehicle 100 and a corresponding DC / AC converter.

[0051] The use of the electronically controlled hydraulic steering system 10 is advantageous, as it can have not only a hydraulic power-assisting function but also an electric power-assisting function, so that the power-assisting characteristics of the steering system 10 can be flexibly and efficiently adjusted to better adapt to the current driving state. Furthermore, when there is no steering operation, the electric steering assembly 2 can stop running, thereby advantageously reducing energy consumption, which is more advantageous for commercial vehicles that usually have a high load. It should be understood that the configuration of the electronically controlled hydraulic steering system 10 can have a variety of variations and is not limited to the illustrated embodiment.

[0052] It should be understood that the present application takes the electronically controlled hydraulic steering system 10 as an example for description. However, the steering system 10 of the present application can also be applied to an electric power steering system, a wire control steering system or other forms of steering systems.

[0053] Next reference Figures 2 to 7 , a self-learning method for a steering zero position of a steering system according to some embodiments of the present application is described in detail. It should be understood that the steps of the method presented below are intended to be illustrative. In some embodiments, the method can be completed with one or more additional undescribed steps, and / or without one or more of the steps discussed. In addition, the order of the steps of the method shown in the figures and described below is not intended to be limiting. In some embodiments, one or more steps may be alternative or preferred to achieve further advantageous technical effects.

[0054] At least part of the method steps of the self-learning method can be executed by the control device of the present application, and the control device may include one or more processors; and one or more computer-readable memories coupled to the one or more processors, and the computer-readable memories are configured to store a series of computer-executable instructions, wherein the series of computer-executable instructions, when executed by the one or more processors, enable the one or more processors to perform at least part of the method steps of the self-learning method of the present application.

[0055] In some embodiments, the control device that performs the self-learning method may be the control device for controlling the motor. Additionally or alternatively, the control device may be a domain controller of the vehicle, such as a vehicle controller, which may communicate with the control device for controlling the motor.

[0056] In the present application, the so-called self-learning method can be understood as an automatically executed program instruction, which allows the dynamic compensation angle that matches the current operation or current driving to be adaptively determined when the vehicle is running or driving, so as to compensate for the deviation between the electronic steering zero position of the steering system and the mechanical steering zero position of the vehicle, so as to learn or obtain the corrected steering zero position of the steering system, especially the return zero position. This can further improve the functional safety of the vehicle, especially reduce the steering zero position deviation of the steering system in an efficient and reliable manner.

[0057] like Figure 2 As shown, according to a favorable embodiment of the present application, the self-learning method can be automatically activated, for example, based on an activation request automatically generated when the vehicle is powered on or the steering system is powered on. Additionally or alternatively, the self-learning method can be activated, for example, based on an activation request from a user, such as a driver. For example, the vehicle 100 may include a human-machine interface (not shown), which is configured to obtain an activation request for self-learning steering zero position. In some embodiments, the human-machine interface can be configured as a touch screen installed in the cockpit, and a specific self-learning mode can be selected on the touch screen. In some embodiments, the human-machine interface can be configured as a switch or knob installed in the cockpit, and a specific self-learning mode can be selected by operating the corresponding switch or knob. It should be understood that the human-machine interface can have a variety of variant possibilities. In some embodiments, the human-machine interface can be configured as a gesture recognition device or a language recognition device. In some embodiments, the human-machine interface can be configured as a portable smart device. By registering the corresponding portable smart device in the vehicle 100 in advance, the portable smart device can be allowed to select a specific self-learning mode.

[0058] Additionally or alternatively, the self-learning method may include: entering an initial state mode based on an acquired activation request, acquiring the vehicle's operating diagnostic parameters in the corresponding initial state mode; and continuing to execute the self-learning method based on the vehicle's operating diagnostic parameters being in a normal state. Otherwise, if the vehicle's operating diagnostic parameters are not in a normal state, indicating that the vehicle has a related fault, the self-learning method may be exited and the fault state mode may be entered. Preferably, the vehicle's operating diagnostic parameters being in a normal state may include: the steering gear is operating normally (e.g., the internal sensor is not failed and there are no other hardware faults, such as overtemperature, etc.), the fieldbus network is operating normally, and the sensor signal is valid (e.g., no external signal is missing or wrong).

[0059] Additionally or alternatively, the self-learning method may include: obtaining a first steering angle from a steering angle sensor, especially a steering wheel angle sensor; obtaining a stored static compensation angle for correcting a steering zero position, especially a return to zero position; based on the first steering angle and the stored static compensation angle, a corrected electronic steering zero position may be obtained. The so-called static compensation angle may be understood as a compensation angle value stored in a predetermined memory, which may be used to correct the steering angle detected by the steering angle sensor, especially during the return to zero assist, so as to minimize or eliminate the degree of deviation between the electronic steering zero position and the mechanical steering zero position. In some embodiments, it may be provided that the electronic steering zero position for the steering system is corrected by summing the first steering angle with the stored static compensation angle. Thus, the relevant control device may perform the return to zero assist based on the steering angle compensated by the static compensation angle or the corrected electronic steering zero position, so as to avoid the electronic steering zero position from deviating from the mechanical steering zero position to a large extent when the vehicle is traveling straight.

[0060] However, due to system errors, calibration deviations and / or load changes of the vehicle, the deviation between the electronic steering zero position and the mechanical steering zero position may change to varying degrees over time, so the use of a fixed static compensation angle cannot always maintain the best compensation effect. To this end, the present application teaches an adaptive learning method that is performed along with the operation or driving of the vehicle, which allows the dynamic compensation angle that matches the current operation or current driving to be adaptively determined. Replacing the static compensation angle with the dynamic compensation angle that matches the current operation or current driving can further reduce the deviation between the electronic steering zero position and the mechanical steering zero position, which is particularly beneficial for driving experience and driving safety, because the pull feeling on the steering wheel will be further weakened or even disappear when the vehicle is driving straight, and after the pull feeling is weakened or disappears, the vehicle will remain stable and will no longer pull the hand or run off the track.

[0061] like Figure 2 As shown, the self-learning method may include: obtaining a stored static compensation angle for correcting the steering zero position, especially returning to the zero position; obtaining an operating parameter of the vehicle; determining whether the vehicle is in a straight-line driving state based on the operating parameter; if the vehicle is in a straight-line driving state based on the operating parameter, entering a self-learning cycle mode of the steering zero position, and in the self-learning cycle mode of the steering zero position, the current dynamic compensation angle D is used to correct the steering zero position. T To correct the current steering angle E T The way comes from learning (electronic) to turn zero position A T Advantageously, the current dynamic compensation angle D T Can be turned to zero position A according to the progress of time and / or self-learning T The value of the dynamic compensation angle DT Ability to gradually correct the steering angle, thus allowing self-learning of the steering zero position A T Gradually decrease and stabilize within a smaller angle range, for example, approaching zero-degree oscillation (for example, within ±2° or ±1°). In addition, the self-learning method may include: comparing the current dynamic compensation angle with the acquired static compensation angle and selectively updating the stored static compensation angle with the current dynamic compensation angle based on the comparison result. Advantageously, the present application can efficiently infer that the vehicle should currently be in a mechanical steering zero position state by ascertaining that the vehicle is in a straight-line driving state. Thus, the current steering angle can be corrected in real time during vehicle driving by selecting a suitable dynamic compensation angle to obtain a self-learned electronic steering zero position, so that the self-learned electronic steering zero position can be further approached to the mechanical steering zero position state.

[0062] In some embodiments, obtaining the operating parameters of the vehicle may include obtaining the yaw rate of the vehicle. Additionally or alternatively, obtaining the operating parameters of the vehicle may include obtaining the lateral acceleration of the vehicle. Additionally or alternatively, obtaining the operating parameters of the vehicle may include obtaining the speed of the vehicle. Additionally or alternatively, obtaining the operating parameters of the vehicle may include obtaining the wheel speed of the vehicle. Additionally or alternatively, obtaining the operating parameters of the vehicle may include obtaining the steering rate of the vehicle.

[0063] In some embodiments, determining whether the vehicle is in a straight-line driving state based on the operating parameters may include: determining whether the yaw rate of the vehicle is less than a first threshold, preferably the first threshold is between 0.01° / s and 1° / s or between 0.05° / s and 0.5° / s. Figure 3 As shown, an exemplary variation curve diagram of the yaw rate of the vehicle is shown, wherein the middle narrow fluctuation section framed can represent straight-line driving. That is, when the yaw rate of the vehicle remains less than the first threshold value over a predetermined period of time, straight-line driving can be inferred.

[0064] Additionally or alternatively, determining whether the vehicle is in a straight-line driving state based on the operating parameters may include: determining whether the lateral acceleration of the vehicle is less than a second threshold value, preferably the second threshold value is 0.01 m / s 2 Up to 1m / s 2 or 0.05m / s 2 Up to 0.5m / s 2 Between. Figure 4 As shown, an exemplary variation curve diagram of the lateral acceleration of the vehicle is shown, wherein the middle narrow fluctuation section framed can represent straight-line driving. That is, when the lateral acceleration of the vehicle remains less than the second threshold value over a predetermined period of time, straight-line driving can be inferred.

[0065] Additionally or alternatively, determining whether the vehicle is in a straight-line driving state based on the operating parameters may include determining whether the vehicle speed is greater than a third threshold value, preferably, the third threshold value is between 3 kph and 60 kph. The effectiveness of the self-learning method can be advantageously improved by limiting the vehicle speed, for example, activating the self-learning process in a parking state can be excluded.

[0066] Additionally or alternatively, determining whether the vehicle is in a straight-line driving state based on the operating parameters may include: determining whether the wheel speed difference of the vehicle is less than a fourth threshold value, preferably, the fourth threshold value is between 0.1 kph and 3 kph or between 0.5 and 2 kph. Figure 5 , an exemplary curve diagram of the yaw rate, lateral acceleration and wheel speed difference of the vehicle is shown. Advantageously, by additionally taking into account the wheel speed difference, the effectiveness of the self-learning method can be further improved, for example, activation of the self-learning process when turning can be reliably excluded. The wheel speed difference can exceed a certain value when turning.

[0067] Additionally or alternatively, ascertaining whether the vehicle is in a straight-line driving state based on the operating parameters may include: ascertaining whether the steering rate of the vehicle is less than a fifth threshold value, preferably, the fifth threshold value is between 1° / s and 5° / s. Additionally or alternatively, ascertaining whether the vehicle is in a straight-line driving state based on the operating parameters may include: ascertaining whether the sum of the current steering angle and the current dynamic compensation angle is less than a sixth threshold value, preferably, the sixth threshold value is between 10° and 50° or between 20° and 40°. It may be provided that: if some or all of the above-mentioned ascertainment results are positive, it is ascertained that the vehicle is in a straight-line driving state. Through one or more of the above-mentioned judgment conditions, it is possible to efficiently and reliably ascertain whether the vehicle is in a straight-line driving state, thereby avoiding an undesirable self-learning process caused by an erroneous judgment.

[0068] It should be understood that the allowable parameters for ascertaining that the vehicle is in a straight-line driving state may be various and are not limited to the parameters listed in the specific embodiment. In other embodiments, obtaining the operating parameters of the vehicle may include obtaining the heading angle of the vehicle, which may be obtained, for example, by integrating the yaw rate, that is, a change in the yaw rate will result in a change in the heading angle. Additionally or alternatively, obtaining the operating parameters of the vehicle may include obtaining the driving trajectory of the vehicle, and based on the driving trajectory of the vehicle, it may be ascertained whether the vehicle is in a straight-line driving state. For example, the driving trajectory of the vehicle may be determined based on image data and / or navigation data. Additionally or alternatively, obtaining the operating parameters of the vehicle may include obtaining the acceleration of the vehicle, and monitoring the acceleration change of the vehicle through an acceleration sensor may be used to observe whether the vehicle is performing an acceleration or deceleration action. In a straight-line state, the acceleration of the vehicle should be relatively stable. Additionally or alternatively, obtaining the operating parameters of the vehicle may include obtaining data from a distance sensor, and the distance sensor on the vehicle may be used to monitor the distance change between the vehicle and the obstacle in front. When the vehicle is in a straight-line state, the distance change of the obstacle in front should be relatively stable.

[0069] In the self-learning cycle mode of steering zero position, the present application proposes to dynamically and cyclically correct the steering angle by dynamic compensation angle. In each self-learning cycle, it can be preferably stipulated that: according to the previous value D of the dynamic compensation angle T-1 and the dynamic compensation factor D factor To obtain the current dynamic compensation angle D T , wherein the initial value of the dynamic compensation angle can be set to the stored static compensation angle. Dynamic compensation factor D factor Can be turned to zero position A according to the progress of time and / or self-learning T The value of the dynamic compensation angle D T Ability to gradually correct the steering angle, thus allowing self-learning of the steering zero position A T Gradually decrease and stabilize within a smaller angle range, such as approaching zero-degree oscillation (for example, within ±2° or ±1°). Figure 6 As shown in FIG. 1 , an exemplary variation curve diagram of the dynamic compensation angle is shown, wherein the dynamic compensation angle can be narrowed to ±2° after 10 minutes of straight-line driving compensation. Figure 7 , an exemplary variation curve diagram of the self-learned steering zero position after the steering angle is corrected by the dynamic compensation angle is shown, wherein the self-learned electronic steering zero position after the steering angle is corrected by the dynamic compensation angle can oscillate close to zero degrees when the vehicle is traveling straight.

[0070] Furthermore, in each self-learning cycle, it is advantageously possible to prescribe the current dynamic compensation angle D T To correct the current steering angle ET Self-learning (electronic) to zero position A T In some embodiments, it may be provided that the first formula is used to self-learn the zero position A T , that is, A T =D T +E T That is to say, the current dynamic compensation angle D T With the current steering angle E T The summation comes from learning the current turning to zero position A T It should be understood that the first formula may also be modified, for example, the current dynamic compensation angle D T and / or the current steering angle E T Assignment correction factor.

[0071] In order to further obtain a more accurate current steering angle E T , and then obtain a more accurate dynamic compensation angle, the self-learning method may include: obtaining a second steering angle from an angle sensor of a motor of a steering system, and obtaining a current steering angle E based on the first steering angle and the second steering angle T Preferably, in the self-learning cycle mode of steering zero position, the initial value of the current steering angle can be set to the first steering angle.

[0072] Advantageously, in each self-learning cycle, the current dynamic compensation angle D can be determined by the second formula: T , that is, D T =D T-1 +D factor That is to say, the previous value D of the dynamic compensation angle can be T-1 and the dynamic compensation factor D factor The summation comes from learning the current dynamic compensation angle D T It should be understood that the second formula can also be modified, for example, the dynamic compensation angle value D T-1 and / or dynamic compensation factor D factor In other embodiments, it is also possible to consider the dynamic compensation angle value D T-1 and the dynamic compensation factor D factor The quadrature is obtained by learning the current dynamic compensation angle D T .

[0073] Advantageously, the dynamic compensation factor D can be set in each self-learning cycle by the third formula: factor , that is, D factor=Vx*T, where Vx is the compensation speed coefficient and T is a time parameter, for example, the duration of the dynamic compensation function. This allows for robust compensation over time and avoids frequent overcompensation. Preferably, according to the self-learned steering zero position A T To determine the value of the compensation speed coefficient Vx, so that the self-learning steering zero position A T The sign of the compensation speed factor Vx is opposite. Advantageously, it can be provided that the self-learned steering zero position A is determined. T The absolute value of which is less than a predetermined threshold value of the time parameter and / or the learned steering zero position A T The compensation speed coefficient Vx is set according to the jitter parameter in a predetermined time period. Preferably, the absolute value of the compensation speed coefficient Vx is between 0.01° / s and 1° / s or between 0.05° / s and 0.5° / s. In other words, the ideal compensation speed coefficient can be set according to the balance between the desired compensation accuracy and the compensation speed. It should be understood that the third formula can also be modified, for example, the dynamic compensation factor D factor In other embodiments, the current steering zero position A can also be considered by self-learning. T The dynamic compensation factor D is determined by summing or multiplying it with the correction factor factor In other embodiments, the current steering zero position A based on self-learning can be considered T The dynamic compensation factor D is determined by using a lookup table factor。

[0074] In some embodiments, the self-learning method may include: if it is determined based on the operating parameters that the vehicle is not in a straight-line driving state, then exiting the self-learning cycle mode of the steering zero position and entering the holding cycle mode of the steering zero position, in which the current dynamic compensation angle D is used to adjust the steering zero position. T To correct the current steering angle E T Self-learning to zero position A T , where the current dynamic compensation angle D T Equal to the previous value of the dynamic compensation angle D T-1 That is, in the hold cycle mode of the steering zero position, the dynamic compensation angle is in the hold phase without being dynamically updated with the help of the dynamic compensation factor. In other embodiments, the current dynamic compensation angle D may also be specified. T Equal to the previous value of the dynamic compensation angle D T-1 Summation or product with a correction factor.

[0075] Advantageously, in each self-learning cycle, it can be provided that: the current dynamic compensation angle is compared with the acquired static compensation angle, and based on the comparison result, the stored static compensation angle is selectively updated with the current dynamic compensation angle. Preferably, in each retention cycle mode, it can be additionally provided that: the current dynamic compensation angle is compared with the acquired static compensation angle, and based on the comparison result, the stored static compensation angle is selectively updated with the current dynamic compensation angle. The so-called selective activation of the update means that the updating of the stored static compensation angle with the current dynamic compensation angle is subject to conditions.

[0076] In some embodiments, if the absolute value of the difference between the current dynamic compensation angle and the acquired static compensation angle is greater than the first update threshold at least once within a predetermined time period, preferably, the first update threshold is between 5° and 10°, then the current dynamic compensation angle is activated to update the stored static compensation angle. Additionally or alternatively, if the absolute value of the difference between the current dynamic compensation angle and the acquired static compensation angle is greater than the second update threshold for multiple times within multiple predetermined time periods, preferably, the second update threshold is between 1° and 5°, then the current dynamic compensation angle is activated to update the stored static compensation angle, wherein the second update threshold is less than the first update threshold, thereby maintaining the reliability of the update and effectively avoiding the adverse effects caused by arbitrary updates. Preferably, the predetermined time period may be between 3 minutes and 30 minutes or between 5 minutes and 15 minutes. Preferably, the predetermined time period is continuously calculated during the self-learning cycle mode and the holding cycle mode of the steering zero position.

[0077] Although some specific embodiments of the present application have been described in detail by way of example, it will be appreciated by those skilled in the art that the above examples are intended only for illustration and not for limiting the scope of the present application. The various embodiments disclosed herein may be combined in any manner without departing from the spirit and scope of the present application. It will also be appreciated by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the present application. The scope of the present application is defined by the appended claims.

Claims

1. A self-learning method for steering zero position of a steering system, characterized in that: The self-learning method comprises: Acquiring a stored static compensation angle for correcting a steering zero position, especially returning to a zero position; Obtaining vehicle operating parameters; determining whether the vehicle is in a straight-line driving state based on the operating parameters; If it is determined based on the operating parameters that the vehicle is in a straight-line driving state, the vehicle enters a self-learning cycle mode of the steering zero position, in which the current dynamic compensation angle D T To correct the current steering angle E T The way comes from learning to turn to zero position A T , where the current dynamic compensation angle D T Can be turned to zero position A according to the progress of time and / or self-learning T The value of changes dynamically; The current dynamic compensation angle is compared with the acquired static compensation angle, and the stored static compensation angle is selectively updated with the current dynamic compensation angle based on the comparison result.

2. The self-learning method according to claim 1, characterized in that: Obtaining the vehicle's operating parameters includes: Obtaining the vehicle's yaw rate; and / or Obtaining the lateral acceleration of the vehicle; and / or Obtain the vehicle's speed; and / or Obtaining the vehicle's wheel speed; and / or Get the vehicle's steering rate, Wherein, determining whether the vehicle is in a straight-line driving state based on the operating parameters includes: determining whether the yaw rate of the vehicle is less than a first threshold; Determine whether the lateral acceleration of the vehicle is less than a second threshold; and / or Determine whether the speed of the vehicle is greater than a third threshold; and / or Find out whether the wheel speed difference of the vehicle is less than a fourth threshold; and / or Determining whether the turning rate of the vehicle is less than a fifth threshold; and / or Check whether the sum of the current steering angle and the current dynamic compensation angle is less than a sixth threshold, If some or all of the above-mentioned findings are positive, it is determined that the vehicle is in a straight-line driving state. Preferably, the first threshold is between 0.01° / s and 1° / s or between 0.05° / s and 0.5° / s; preferably, the second threshold is between 0.01 m / s 2 Up to 1m / s 2 or 0.05m / s 2 Up to 0.5m / s 2 preferably, the third threshold is between 3 kph and 60 kph; preferably, the fourth threshold is between 0.1 kph and 3 kph or between 0.5 and 2 kph; preferably, the fifth threshold is between 1 ° / s and 5 ° / s; preferably, the sixth threshold is between 10 ° and 50 ° or between 20 ° and 40 °.

3. The self-learning method according to claim 1, characterized in that: The self-learning method comprises: Acquire a first steering angle from a steering angle sensor, in particular a steering wheel angle sensor, The steering zero position for the steering system is corrected based on the first steering angle and the stored static compensation angle, in particular the steering zero position for the steering system is determined by summing the first steering angle and the stored static compensation angle.

4. The self-learning method according to claim 3, characterized in that: The self-learning method comprises: Obtaining a second steering angle from an angle sensor of a motor of a steering system, The current steering angle E is calculated based on the first steering angle and the second steering angle T Preferably, in the self-learning cycle mode of steering zero position, the initial value of the current steering angle is set to the first steering angle.

5. The self-learning method according to any one of claims 1 to 4, characterized in that: In the self-learning cycle mode of steering zero position, according to the dynamic compensation angle previous value D T-1 and the dynamic compensation factor to obtain the current dynamic compensation angle D T Preferably, the dynamic compensation factor can be adjusted to zero position A according to the progress of time and / or self-learning T The value changes dynamically.

6. The self-learning method according to any one of claims 1 to 5, characterized in that: In the self-learning cycle mode towards zero position, Learn to turn to zero position A by the first formula T , that is, A T =D T +E T , The current dynamic compensation angle D is determined by the second formula T , that is, D T =D T-1 +D factor , The dynamic compensation factor D is set by the third formula factor , that is, D factor =Vx*T, where Vx is the compensation speed coefficient and T is the time parameter, Preferably, according to the self-learned steering zero position A T To determine the value of the compensation speed coefficient Vx, so that the self-learning steering zero position A T The positive and negative of the compensation speed coefficient Vx are opposite. Preferably, the self-learned steering zero position A is determined T The absolute value of which is less than a predetermined threshold value of the time parameter and / or the learned steering zero position A T The compensation speed coefficient Vx is set based on the jitter parameters within a predetermined time period. Preferably, the absolute value of the compensation speed coefficient Vx is between 0.01° / s and 1° / s or between 0.05° / s and 0.5° / s.

7. The self-learning method according to any one of claims 1 to 6, characterized in that: The self-learning method comprises: If it is found based on the operating parameters that the vehicle is not in a straight-line driving state, the self-learning cycle mode of the steering zero position is exited and the holding cycle mode of the steering zero position is entered. In the holding cycle mode of the steering zero position, the current dynamic compensation angle D is used to adjust the steering zero position. T To correct the current steering angle E T Self-learning to zero position A T , where the current dynamic compensation angle D T Equal to the previous value of the dynamic compensation angle D T-1 .

8. The self-learning method according to any one of claims 1 to 7, characterized in that: The self-learning method comprises: If the absolute value of the difference between the current dynamic compensation angle and the acquired static compensation angle is greater than the first update threshold at least once within a predetermined time period, activating the updating of the stored static compensation angle with the current dynamic compensation angle, and / or If the absolute value of the difference between the current dynamic compensation angle and the acquired static compensation angle is greater than the second update threshold for multiple times within multiple predetermined time periods, activating the updating of the stored static compensation angle with the current dynamic compensation angle, wherein the second update threshold is less than the first update threshold, Preferably, the predetermined time period is between 3 minutes and 30 minutes or between 5 minutes and 15 minutes; preferably, the first update threshold is between 5° and 10°, and the second update threshold is between 1° and 5°, Preferably, the stored static compensation angle is only allowed to be called during the steering return power assistance of the steering system to compensate for the return zero position of the steering system. Preferably, the predetermined time period is calculated continuously during the self-learning cycle mode and the holding cycle mode of the turn-to-zero position.

9. The self-learning method according to any one of claims 1 to 8, characterized in that: The self-learning method comprises: obtaining an activation request, preferably automatically generating the activation request based on powering up of the steering system; During each activation of the steering system by powering on, it is possible to update the stored static compensation angle with the current dynamic compensation angle up to 5 times, preferably 3 times.

10. A control device comprising: processor; and a computer readable memory coupled to the processor, the computer readable memory being configured to store a series of computer executable instructions, When the series of computer executable instructions are executed by a processor, the processor is caused to perform the self-learning method according to any one of claims 1 to 9.

11. A computer-readable storage medium comprising computer-executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 9.

12. Steering system, characterized in that, The steering system comprises an electric motor and a control device according to claim 10 for controlling the electric motor.

13. A vehicle, characterized in that The vehicle includes a steering system according to claim 12.

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