CN112906906B - Self-learning method of pedal driving robot - Google Patents
Self-learning method of pedal driving robot Download PDFInfo
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- CN112906906B CN112906906B CN202110261583.3A CN202110261583A CN112906906B CN 112906906 B CN112906906 B CN 112906906B CN 202110261583 A CN202110261583 A CN 202110261583A CN 112906906 B CN112906906 B CN 112906906B
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Abstract
The invention relates to a pedal driving robot self-learning method, which comprises an accelerator pedal self-learning part, wherein the accelerator pedal self-learning part comprises the following steps: determining a zero position of an accelerator pedal; determining an end position of an accelerator pedal; self-learning the accelerator pedal sectional opening degree: a plurality of accelerator pedal opening nodes are arranged between the first accelerator pedal opening and the second accelerator pedal opening; calculating the angles of the servo motors corresponding to the accelerator pedals under different opening degree nodes; calculating the force of an accelerator pedal through a servo motor dynamic characteristic model; and obtaining the vehicle acceleration condition of the accelerator pedal from a lower accelerator pedal opening node to a higher accelerator pedal opening node, and obtaining the relation between the accelerator pedal and the vehicle speed. The invention can shorten the time for adjusting the control parameters under different vehicle conditions and after vehicle model replacement.
Description
Technical Field
The invention relates to an automobile driving robot, in particular to a pedal driving robot self-learning method.
Background
As the automotive industry has developed, human performance requirements for automobiles have become higher and higher, and design improvements by means of extensive testing have been required. The automobile test has strong repeatability, long duration and severe working environment, so the automobile test is more suitable for being operated by a robot. The driving robot is adopted for automobile test, so that the labor intensity of testers can be reduced, the test cost is saved, the test efficiency is improved, the influence of human factors can be eliminated, and the accuracy and the effectiveness of automobile test data are ensured.
The vehicle performance self-learning is a key technology of the automobile driving robot, and dynamic parameters of different types of vehicles, even different vehicles of the same type or unified vehicles are different at different running moments. In order to shorten the control parameter adjustment time under different vehicle conditions and after vehicle model replacement, a pedal-driven robot self-learning method is urgently needed.
Disclosure of Invention
The invention aims to provide a pedal driving robot self-learning method, which can shorten the control parameter adjusting time under different vehicle conditions and after vehicle model replacement.
The technical scheme adopted by the invention for solving the technical problem is as follows: the pedal driving robot self-learning method comprises an accelerator pedal self-learning part, wherein the accelerator pedal self-learning part comprises the following steps:
(a) Determining a zero position of an accelerator pedal;
(b) Determining an end position of an accelerator pedal;
(c) Self-learning the accelerator pedal sectional opening degree: a plurality of accelerator pedal opening nodes are arranged between the first accelerator pedal opening and the second accelerator pedal opening; calculating the angles of the servo motors corresponding to the accelerator pedals under different opening degree nodes; calculating the force of an accelerator pedal through a servo motor dynamic characteristic model; and obtaining the vehicle acceleration condition of the accelerator pedal from a lower accelerator pedal opening node to a higher accelerator pedal opening node, and obtaining the relation between the accelerator pedal and the vehicle speed.
And (b) judging whether the gearbox and the end face of the rocker arm slide or not through the encoder in the step (a), and acquiring the force of the accelerator pedal when the gearbox and the end face of the rocker arm slide, wherein the force of the accelerator pedal at the moment is the maximum force which can be borne by the zero position of the accelerator pedal.
And (b) controlling the servo motor to rotate the zero position of the accelerator pedal to the tail position of the accelerator pedal within a preset time, wherein when the locked-rotor current of the servo motor is stabilized to a fixed value in the process, the current position of the accelerator pedal is the tail position of the accelerator pedal.
The step (c) of obtaining the vehicle acceleration condition of the accelerator pedal from a node with a lower accelerator pedal opening degree to a node with a higher accelerator pedal opening degree, and obtaining the relation between the accelerator pedal and the vehicle speed means that: respectively moving an accelerator pedal from a zero position to different accelerator pedal opening degree nodes and tail positions of the accelerator pedal to obtain a first group of vehicle acceleration conditions; respectively moving the minimum accelerator pedal opening node to other accelerator pedal opening nodes and the final positions of the accelerator pedals to obtain a second group of vehicle acceleration conditions, and so on to obtain a plurality of groups of vehicle acceleration conditions; and filling the obtained groups of vehicle acceleration conditions into the self-learning map.
The pedal driving robot self-learning method further comprises a brake pedal self-learning part, and the brake pedal self-learning part comprises the following steps:
(A) Determining a zero position of the brake pedal;
(B) Self-learning the sectional opening of the brake pedal: accelerating the vehicle to a first preset speed, decelerating the speed of the vehicle to a second preset speed through running resistance after the vehicle is stabilized, and controlling a brake pedal to brake with preset brake force to obtain the vehicle braking deceleration condition.
And (B) limiting the zero position of the brake pedal through a limiter in the step (A).
And (B) accelerating the vehicle to a first preset speed, decelerating the vehicle to a second preset speed through running resistance after the vehicle is stabilized, controlling a brake pedal to brake with preset brake force, and obtaining a plurality of groups of vehicle brake deceleration conditions by adjusting the first preset speed, the second preset speed and the preset brake force when the vehicle brake deceleration conditions are obtained, and filling the plurality of groups of vehicle brake deceleration conditions into a self-learning map.
Advantageous effects
Due to the adoption of the technical scheme, compared with the prior art, the invention has the following advantages and positive effects: the relation between the accelerator pedal and the vehicle speed is obtained by determining the zero position and the final position of the accelerator pedal and performing subsection opening self-learning on the accelerator pedal, and the relation between the brake pedal and the vehicle speed is obtained by determining the zero position of the brake pedal and performing subsection opening self-learning on the brake pedal, so that the time for adjusting control parameters under different vehicle conditions and after vehicle type replacement is shortened.
Detailed Description
The invention will be further illustrated with reference to the following specific examples. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Further, it should be understood that various changes or modifications of the present invention may be made by those skilled in the art after reading the teaching of the present invention, and such equivalents may fall within the scope of the present invention as defined in the appended claims.
The embodiment of the invention relates to a pedal driving robot self-learning method which comprises an accelerator pedal self-learning part and a brake pedal self-learning part.
The accelerator pedal self-learning part comprises the following steps:
determining the zero position (0 position) of the accelerator pedal: the rocker arm is positioned at about 15 degrees in the negative direction, and an adjustable initial rotation angle limiter is arranged for limiting the initial position (0-position limiting position); the electromagnetic clutch is electrified, so that the gearbox is combined with the end face power (by the static friction force of two combined surfaces) of the rocker arm, and the problem of relative sliding is solved between two end faces (through mechanical design, the friction material between the two end faces can be designed to ensure that the accelerator pedal force does not have relative sliding under the condition that the force is less than or equal to 250N or the torque is less than or equal to 20Nm, and once the relative sliding is generated, the encoder identifies and calculates the rotating angle to generate deviation); the hardware mounting assembly is compact and gapless, and has no acceleration effect on the vehicle. Therefore, whether the gearbox and the end face of the rocker arm slide or not can be judged through the encoder when the zero position of the accelerator pedal is determined, and the accelerator pedal force is obtained when the gearbox and the end face of the rocker arm slide, wherein the accelerator pedal force at the moment is the maximum force which can be borne by the zero position of the accelerator pedal.
Determining the final position of the accelerator pedal (accelerator pedal opening 100%): in the step, the servo motor is controlled to rotate the zero position of the accelerator pedal to the final position of the accelerator pedal within preset time, and when the locked-rotor current of the servo motor is stabilized to a fixed value in the process, the current position of the accelerator pedal is the final position of the accelerator pedal.
Specifically, the above function can be realized by application software, first setting 100% position, and setting learning time to 5s, and the program of the application software can automatically drive the servo motor to rotate from 0 position to 100% maximum throttle opening position within 5 s. The position of the accelerator pedal reaching the maximum opening of 100% at the moment can be identified/distinguished by means of force control (for example, a maximum force of 100N is applied until the servomotor stalling current is greater than a certain value, and the maximum opening of 100% at the moment is considered). The other is to set the 100% position first, and at this moment, the 100% maximum accelerator opening can be guided by manually stepping on the accelerator pedal from 0 position to bottom, and certainly, in the manual stepping process, the force is slowly applied and the servo motor, the reducer, the electromagnetic clutch, the rocker arm and other execution mechanisms are required to perform good and easy following actions, so that the servo motor accurately calculates the rotating angle from 0 position to 100% maximum opening position.
Self-learning the accelerator pedal sectional opening degree: a plurality of accelerator pedal opening nodes are arranged between the first accelerator pedal opening and the second accelerator pedal opening; calculating the angles of the servo motors corresponding to the accelerator pedals under different opening nodes; calculating the force of an accelerator pedal through a servo motor dynamic characteristic model; and obtaining the vehicle acceleration condition of the accelerator pedal from a lower accelerator pedal opening node to a higher accelerator pedal opening node, and obtaining the relation between the accelerator pedal and the vehicle speed.
Specifically, the accelerator pedal opening degree is divided into 5-6 nodes (the increment gradient is 10-20%) in the middle of 10% -90% or 20% -80%. Considering the parameter transformation relationship: the radius of the rocker arm is 80mm, the accelerator pedal also rotates around a fixed point, the rotating radius of the accelerator pedal can be known through the accelerator pedal product parameters of each vehicle, and the angle of the servo motor corresponding to each node of the accelerator pedal in 0-100% can be accurately calculated through the calculation relation (the hardware assembly clearance is not considered, the slipping of the electromagnetic clutch is not considered, and the rotating angle is converted into the rotating angle of the servo motor through the speed reducer); under the condition that the vehicle is not started, the force of 0-100% of different opening degrees of the accelerator pedal is self-learned (in the embodiment, under the condition that an accelerator pedal force sensor is not arranged, the force of 0-100% of different opening degrees of the accelerator pedal is calculated through a servo motor dynamic characteristic model, and the corresponding torque can be calculated on the basis of the calculated force 2 + bV + c (resistance F is a quadratic function relationship of the vehicle speed V, where a is a quadratic coefficient, b is a first order coefficient, and c is a constant term), which is a relationship between the resistance received by the vehicle when traveling on a straight road and the vehicle speed; when the vehicle is running in acceleration, the acceleration is a (only the acceleration motion is considered now, a is more than or equal to 0m/s 2 ），F=aV 2 + bV + c + ma; when the vehicle is in the running condition of acceleration and climbing, the climbing gradient is alpha (only the upward climbing running condition is considered at present), and the force for overcoming the climbing is F 1 = m g sin (α), i.e. total force F = aV 2 +bV+c+ma+ m*g*sin（α）。
Acquiring the acceleration condition of a vehicle under the condition that an accelerator pedal is from a 0 position to different accelerator opening degrees (0-10%, 0-20%,0-30%.. 0-100%), wherein the response time of the accelerator pedal from the 0 position to a certain set accelerator opening degree is determined by the automatic driving robot; then obtaining the acceleration conditions of the vehicle from 10% of accelerator opening to different accelerator opening (10-20%, 10-30%,10-40%.. 10-100%); and then obtaining the acceleration condition of the group of vehicles from 20% of the accelerator opening degree to different accelerator opening degrees (20-30%, 20-40% and 20-50%. 20-100%), and so on, and then obtaining the acceleration condition of the group of vehicles from 60% of the accelerator opening degree to different accelerator opening degrees (60-70% and 60-70%. 20-100%). A series of 2-dimensional and 3-dimensional self-learning map maps can be obtained through a vehicle speed signal fed back by a rotating hub, and a series of values obtained through self-learning are filled in the map to be used for a series of acceleration tests of the vehicle (so that the initial opening, the final opening, the delta accelerator opening, the response time of an accelerator pedal robot, the initial vehicle speed of the vehicle, the final vehicle speed of the vehicle, the delta vehicle speed of the vehicle, the acceleration time of the vehicle, the acceleration of the vehicle at each moment, the resistance value calculated by the vehicle speed and the vehicle acceleration, even the climbing slope and the like can be calculated), and therefore the self-learning of the accelerator pedal is completed.
The brake pedal self-learning part comprises the following steps:
determining the zero position of the brake pedal: the rocker arm is positioned at about 15 degrees of negative direction, and an adjustable initial rotation angle limiter is used for limiting the initial position (0-position limiting position); through adjusting screw, the hardware installation assembly is compact and gapless, and does not have the braking effect to vehicle itself. As can be seen, in the present embodiment, the zero position of the brake pedal is determined by limiting the zero position of the brake pedal by the limiter.
Self-learning the sectional opening of the brake pedal: accelerating the vehicle to a first preset speed, decelerating the speed of the vehicle to a second preset speed through running resistance after the vehicle is stabilized, and controlling a brake pedal to brake with preset brake force to obtain the braking and decelerating condition of the vehicle.
Specifically, the vehicle is firstly accelerated to 20/30/40/50/60/70/80/90/100/110/120/140km/h through an accelerator pedal, the accelerator pedal is quickly released when the vehicle is stable at the vehicle speed, and the vehicle is normally decelerated and operated under the action of running resistance(deceleration thereof is-a = -F/m = - (aV) 2 + bV + c)/m), when the vehicle speed (the vehicle speed is input by a hub vehicle speed analog signal) is respectively reduced to 10/20/30/40/50/60/70/80/90/100/110/120km/h, the brake pedal is controlled to rapidly brake, the brake force is respectively 50N/100N/200N/300N/400N/500N (the response time is t, namely the time used by the brake pedal robot for braking force is 0 to 50N/100N/200N/300N/400N/500N, and the t is determined by the brake robot body and the controller system), and a group of vehicle brake deceleration conditions are obtained. A series of 2-dimensional and 3-dimensional self-learning map maps can be obtained through a vehicle speed signal fed back by a rotating hub, and a series of values obtained through self-learning are filled in the map to be used for a series of deceleration braking tests of the vehicle (so that the braking force of a brake pedal, the response time of an accelerator pedal robot, the initial vehicle speed of the vehicle, the final vehicle speed of the vehicle, the delta vehicle speed of the vehicle, the deceleration time of the vehicle, the deceleration of the vehicle at each moment, the resistance value calculated by the vehicle speed and the vehicle deceleration even a downward gradient and the like can be calculated), and therefore the self-learning of the brake pedal is completed.
Claims (6)
1. The pedal driving robot self-learning method is characterized by comprising an accelerator pedal self-learning part, wherein the accelerator pedal self-learning part comprises the following steps:
(a) Determining a zero position of an accelerator pedal;
(b) Determining an end position of an accelerator pedal;
(c) Self-learning the subsection opening degree of the accelerator pedal: a plurality of accelerator pedal opening nodes are arranged between the first accelerator pedal opening and the second accelerator pedal opening; calculating the angles of the servo motors corresponding to the accelerator pedals under different opening degree nodes; calculating the force of an accelerator pedal through a servo motor dynamic characteristic model; obtaining the vehicle acceleration condition of an accelerator pedal from a lower accelerator pedal opening node to a higher accelerator pedal opening node, and obtaining the relation between the accelerator pedal and the vehicle speed; the method comprises the following steps of obtaining the vehicle acceleration condition of an accelerator pedal from a lower accelerator pedal opening node to a higher accelerator pedal opening node, and obtaining the relation between the accelerator pedal and the vehicle speed, wherein the relation between the accelerator pedal and the vehicle speed is as follows: respectively moving an accelerator pedal from a zero position to different accelerator pedal opening degree nodes and tail positions of the accelerator pedal to obtain a first group of vehicle acceleration conditions; respectively moving the minimum accelerator pedal opening node to other accelerator pedal opening nodes and the final positions of the accelerator pedals to obtain a second group of vehicle acceleration conditions, and so on to obtain a plurality of groups of vehicle acceleration conditions; and filling the obtained groups of vehicle acceleration conditions into the self-learning map.
2. The self-learning method of the pedal-driven robot as claimed in claim 1, wherein in the step (a), whether the gearbox and the end surface of the rocker arm slide or not is judged through the encoder, and when the gearbox and the end surface of the rocker arm slide, the accelerator pedal force is obtained, and the accelerator pedal force is the maximum force which can be borne by the zero position of the accelerator pedal.
3. The pedal-driven robot self-learning method according to claim 1, wherein the servo motor is controlled in the step (b) to rotationally move the zero position of the accelerator pedal to the final position of the accelerator pedal within a preset time, and when the locked-rotor current of the servo motor is stabilized to a fixed value during this process, the current position of the accelerator pedal is the final position of the accelerator pedal.
4. The pedal-driven robot self-learning method according to claim 1, further comprising a brake pedal self-learning section, the brake pedal self-learning section comprising the steps of:
(A) Determining a zero position of the brake pedal;
(B) Self-learning the sectional opening of the brake pedal: accelerating the vehicle to a first preset speed, decelerating the speed of the vehicle to a second preset speed through running resistance after the vehicle is stabilized, and controlling a brake pedal to brake with preset brake force to obtain the braking and decelerating condition of the vehicle.
5. The pedal-driven robot self-learning method according to claim 4, wherein the zero position of the brake pedal is limited in step (A) by a limiter.
6. The pedal-driven robot self-learning method according to claim 4, wherein in the step (B), the vehicle is accelerated to a first preset speed, the speed of the vehicle is decelerated to a second preset speed through the running resistance after the vehicle is stabilized, the brake pedal is controlled to brake with a preset braking force, and when the braking deceleration condition of the vehicle is obtained, a plurality of groups of braking deceleration conditions of the vehicle are obtained by adjusting the first preset speed, the second preset speed and the preset braking force, and the plurality of groups of braking deceleration conditions of the vehicle are filled in the self-learning map.
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| CN109489991B (en) * | 2018-12-07 | 2020-05-19 | 安徽江淮汽车集团股份有限公司 | Method and system for calculating opening degree of accelerator pedal in electric vehicle performance test |
| CN109556885B (en) * | 2018-12-07 | 2020-05-05 | 安徽江淮汽车集团股份有限公司 | Automatic driving control method and system for electric vehicle performance test |
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