A control method for a vehicle to achieve autonomous speed tracking

Abstract

The present invention discloses a control method for a vehicle to achieve autonomous speed tracking, belonging to the technical field of vehicle autonomous control. According to the laws of the vehicle throttle, vehicle speed, and acceleration, the present invention determines the non-linear relationship between the change in vehicle speed and the depth of depression of the throttle pedal. Based on the speed and acceleration two-way preview feedforward control proportional-derivative control method, with the speed error and acceleration error between the preview moment and the current moment as the control variables, it solves the problem of speed curve tracking during autonomous driving. Specifically, it includes: establishing a vehicle throttle control model; preprocessing the vehicle speed target test curve; constructing a throttle pedal control model; determining the control strategy; assisting the vehicle to complete more autonomous driving tasks, and realizing the speed tracking test and durability performance test before the vehicle leaves the factory. The present invention can improve the response speed, reduce the response hysteresis, and improve the control accuracy; completely solve the problem of speed curve tracking during the vehicle starting, accelerating, and decelerating processes.

Description

Technical Field

[0001] The present invention relates to a control method for a vehicle to achieve autonomous speed tracking, belonging to the technical field of vehicle autonomous control. Background Art

[0002] Vehicle performance testing is an important means to detect the quality of vehicle design. Traditional automotive performance tests are completed by manual operation, with poor economy, poor repeatability, and a short non-stop test time cycle. Using an autonomous driving robot to replace human drivers to complete various automotive performance tests can significantly reduce the negative impact of driver operation habits and operation accuracy on test results and improve test efficiency. However, autonomous driving robots are expensive, greatly increasing the test cost.

[0003] A vehicle is a complex non-linear and time-lagged system. Existing speed tracking control methods for autonomous driving robots are divided into direct control methods and hierarchical control methods. The direct speed control method has low speed tracking accuracy, poor anti-interference ability, and is prone to severe jitter during vehicle testing; the hierarchical control method has poor speed tracking effect when encountering situations such as vehicle start, rapid acceleration, and rapid deceleration, and has a large amount of data. How to improve the speed tracking test accuracy of autonomous driving robots and effectively assist vehicles has become an urgent problem to be solved. Summary of the Invention

[0004] The purpose of the present invention is to propose a control method for a vehicle to achieve autonomous speed tracking. According to the laws of vehicle throttle, vehicle speed, and acceleration, the non-linear relationship between vehicle speed change and the depth of throttle pedal depression is determined. Based on the speed and acceleration two-way preview feedforward control proportional-derivative control method, with the speed error and acceleration error between the preview moment and the current moment as control quantities, the problem of speed curve tracking during autonomous driving is solved.

[0005] The purpose of the present invention is achieved through the following technical solutions:

[0006] A control method for a vehicle to achieve autonomous speed tracking according to the present invention includes the following steps:

[0007] Step 1: Establishment of vehicle throttle control model:

[0008] The throttle control quantity model is shown in Equation (1):

[0009]

[0010] where CtrValue is the approximate throttle control quantity, l is the actual throttle pedal stroke, and l max is the maximum effective stroke of the throttle pedal;

[0011] Step 2: Preprocessing of the target curve:

[0012] The signal frequency of the vehicle speed target test curve is f Hz, and the signal changes in a stepwise manner. The interpolation method is used to increase the signal frequency to Nf Hz. The vehicle speed v at a certain moment obtained by the interpolation method is shown in Equation (2):

[0013]

[0014] where v1 and v2 are the initial and final speeds within 1 / f s of the target curve respectively, n is the nth newly added sampling point within 1 / f s, and n = 0, 1..., N - 1;

[0015] Step 3: Construct a throttle pedal control model:

[0016] The control model of the throttle pedal adopts the form of an incremental proportional - derivative controller, as shown in Equation (3):

[0017]

[0018] where speed_error is the speed error, as shown in Equation (4), pre_speed_error is the preview speed error, as shown in Equation (5), is the acceleration at the moment t + t1 corresponding to the preview time t1, a des is the target acceleration, a act is the actual acceleration, K p is the proportionality coefficient, K d is the differential coefficient, w1 and w2 are influence weights, 0 ≤ w1 ≤ 1, 0 ≤ w2 ≤ 1;

[0019] speed_error = v des -v act (4)

[0020] where v des is the target speed, v act is the actual speed at the current moment t;

[0021]

[0022] where, is the speed at the moment t + t1 corresponding to the preview time t1;

[0023] Step 4: Determine the control strategy:

[0024] The vehicle is a complex non - linear hysteresis system. Considering the actual working state of the vehicle, the control strategy for the vehicle to achieve autonomous speed tracking includes the following three aspects:

[0025] 1. For the problem of slow vehicle start response, when starting the vehicle, the preview time is increased to t2 (t2 > t1), and an early start prediction is made according to the speed at time t + t2. Make an early start prediction accordingly;

[0026] 2. For the problem that the sensitivity of the vehicle speed to the change amount of the throttle control amount is different during the low-speed and high-speed movement processes of the vehicle, different proportional coefficients and differential coefficients are set for the high-speed stage and the low-speed stage to determine the throttle control amount CtrValue.

[0027] 3. For the problem that the vehicle cannot be quickly stabilized when decelerating to 0, judge whether the throttle control amount CtrValue is 0 according to the speed at the future time t + t2. If CtrValue = 0;

[0028] Further, it also includes step 5: Based on the vehicle throttle control model constructed in step 1, the throttle pedal control model constructed in step 3, and the control strategy determined in step 4, extend it to the actual working conditions, and combine it with a specific autonomous driving robot platform. Without modifying the vehicle internal control unit, assist the vehicle to complete more autonomous driving tasks, and realize the speed tracking test and durability performance test before the vehicle leaves the factory.

[0029] Beneficial effects:

[0030] 1. A control method for a vehicle to achieve autonomous speed tracking according to the present invention takes measures in advance for the future vehicle speed change, especially makes predictions for the vehicle starting, rapid acceleration, and rapid deceleration situations. By setting an appropriate preview time, the response speed is improved, the response lag is reduced, and the control accuracy is improved.

[0031] 2. A control method for a vehicle to achieve autonomous speed tracking according to the present invention completely solves the speed curve tracking problem caused by the vehicle system non-linearity and hysteresis during the vehicle starting, accelerating, and decelerating processes through different control strategies. Description of the drawings

[0032] Figure 1 It is a schematic diagram of the autonomous driving robot control platform in the embodiment;

[0033] Figure 2 It is a flowchart of a control method for a vehicle to achieve autonomous speed tracking according to the present invention;

[0034] Figure 3 It is a throttle control amount - vehicle speed change curve graph in the embodiment;

[0035] Figure 4 It is a target speed curve preprocessing result graph in the embodiment;

[0036] ​Figure 5 It is the vehicle speed tracking result graph in the embodiment. Specific implementation manners

[0037] To better illustrate the purpose and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and examples.

[0038] Embodiment 1:

[0039] As Figure 1 shown, the automatic driving robot control platform of the embodiment includes: a measurement and control computer, an accelerator and a brake pedal execution structure, a force sensor, an encoder, a digital-to-analog acquisition card, and a driver; the accelerator and the brake pedal execution structure include: a high-precision servo electric cylinder and a connecting member.

[0040] The data collected by the measurement and control computer includes: collecting the vehicle speed information through the digital-to-analog acquisition card, collecting the position information of the high-precision servo electric cylinder through the encoder, and collecting the pedal force information through the force sensor.

[0041] The test vehicle adopts a single-pedal mode. Stepping on the accelerator realizes acceleration, and releasing the accelerator quickly decelerates through the electric power recovery system.

[0042] As Figure 2 shown, in the above automatic driving robot control platform of the embodiment, the method of the present invention is applied to realize the autonomous tracking control of speed, including the following steps:

[0043] Step 1: Establishment of the vehicle accelerator control model:

[0044] In the embodiment, the electric cylinder is used to simulate a person stepping on the accelerator pedal. When the force F = 5N, the effective displacement of the vehicle accelerator pedal changes. At this time, the extended position of the electric cylinder is x0 = 15.00mm. When F = 20N, the vehicle accelerator pedal reaches the maximum effective stroke. At this time, the extended position of the electric cylinder is x1 = 55.00mm. Then the effective stroke l max = 40.00mm, and the accelerator control amount model is as shown in Equation (1):

[0045]

[0046] Among them, CtrValue is the approximate accelerator control amount, l is the actual accelerator pedal stroke, which is equivalent to the relative displacement change of the electric cylinder;

[0047] When the relative displacement change of the electric cylinder is l = 20.00mm, according to the vehicle accelerator control model, the accelerator control amount CtrValue is 50%; when the known accelerator control amount is 50%, the relative displacement change l of the electric cylinder = 20.00mm;

[0048] In the embodiment, the electric cylinder slowly extends to step on the accelerator pedal at a speed of v = 0.01 mm / s, so that the vehicle has enough time to reach a stable speed. The throttle control amount - vehicle speed change curve is as Figure 3 shown;

[0049] Step 2: Target curve preprocessing:

[0050] In the embodiment, the target curve is the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) working condition curve. The sampling frequency of the curve speed signal is f = 1 Hz. It is desired to expand the data sampling frequency f = 1 Hz to the sampling frequency f1 = 10 Hz. The number of points to be inserted per unit time is 9. The vehicle speed v at a certain moment obtained by the interpolation method is as shown in Equation (2):

[0051]

[0052] where v1 and v2 are the initial and final speeds within 1 / f s of the target curve, respectively, and n is the nth new sampling point within 1 / f s, n = 0, 1,..., 9;

[0053] The target speed tracking curve obtained by interpolating and expanding the entire WLTC working condition curve is as Figure 4 shown, which changes the original unit time step signal into a step signal with a higher sampling frequency, facilitating the tracking of the target speed curve;

[0054] Step 3: Construct the accelerator pedal control model:

[0055] The control model of the accelerator pedal adopts the form of an incremental proportional - derivative controller, as shown in Equation (3):

[0056]

[0057] where speed_error is the speed error, as shown in Equation (4), pre_speed_error is the preview speed error, as shown in Equation (5), is the acceleration at the moment t + t1 corresponding to the preview time t1, a des is the target acceleration, a act is the actual acceleration, K p is the proportional coefficient, K d is the differential coefficient, w1 and w2 are influence weights, 0 ≤ w1 ≤ 1, 0 ≤ w2 ≤ 1;

[0058] speed_error = v des -v act (4)

[0059] where v des is the target speed, v actis the actual speed at the current time t;

[0060]

[0061] in, is the speed at time t+t1 corresponding to preview time t1;

[0062] Step 4: Determine the control strategy:

[0063] In the embodiment, Figure 3 As shown in the figure, when the vehicle speed v>40Km / h, the influence of the vehicle throttle control change on the vehicle speed increases significantly, and the relationship is not linear.

[0064] When v>40Km / h, the controller setting is as shown in formula (6):

[0065]

[0066] When v≤40Km / h, the controller setting is as shown in formula (7):

[0067]

[0068] Among them, w1=0.5, w2=0.5, the influence of each part on the control quantity is the same, and the speed tracking preview time is selected as t1=1.5s, t2=4.5s;

[0069] Furthermore, it also includes step 5: speed tracking test before the vehicle leaves the factory:

[0070] In the embodiment, the autonomous driving robot is installed in a BAIC Polar Fox series electric vehicle test platform using a single pedal mode. The power recovery braking device can enable the vehicle to achieve rapid deceleration when the accelerator is released. The pre-processed WLTC operating condition curve is added to the measurement and control computer. Based on the vehicle throttle control model constructed in step 1, the accelerator pedal control model constructed in step 3, and the control strategy determined in step 4, the autonomous driving robot controls the telescopic displacement of the accelerator pedal actuator to control the accelerator pedal. The vehicle speed tracking effect is as follows: Figure 5 As shown;

[0071] like Figure 5As shown, when the vehicle is maneuvered to track the target speed, the target curve and the actual speed curve are very close. Although the error is relatively large when the vehicle decelerates, the vehicle speed tracking error is always less than 2 Km / h, meeting the national vehicle speed test error standard. By means of pre-preview in advance, it simulates the driver's behavior habit of making pre-judgments, effectively solves the problem of slow vehicle response during startup and deceleration, verifies the actual application effect of the control method of the present invention, does not need to modify the vehicle internal control unit, assists the vehicle to complete more autonomous driving tasks, and realizes the speed tracking test and durability performance test before the vehicle leaves the factory.

[0072] The above specific description further details the purpose, technical solution and beneficial effects of the invention. It should be understood that the above is only a specific embodiment of the present invention and is not used to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A control method for a vehicle to achieve autonomous speed tracking, characterized in that: According to the laws of the vehicle throttle with respect to vehicle speed and acceleration, determine the non-linear relationship between the vehicle speed change and the depth of the throttle pedal depression. Based on the speed and acceleration two-way preview feedforward control proportional-derivative control method, using the speed error and acceleration error between the preview moment and the current moment as the control variables, solve the speed curve tracking problem during autonomous driving. The specific steps are as follows: Step 1: Establish the vehicle throttle control model: The throttle control variable model is shown in Equation (1): Among them, CtrValue is the approximate throttle control amount, l is the actual throttle pedal travel, and l max is the maximum effective travel of the throttle pedal; Step 2: Preprocess the target curve: The signal frequency of the vehicle speed target test curve is f Hz, and the signal changes in a stepwise manner. The interpolation method is used to increase the signal frequency to Nf Hz. The vehicle speed v at a certain moment obtained by the interpolation method is shown in Equation (2): where v1 and v2 are the initial and final speeds within 1 / f s of the target curve respectively, and n is the nth new sampling point within 1 / f s, n = 0, 1..., N - 1; Step 3: Construct the throttle pedal control model: The control model of the throttle pedal adopts the form of an incremental proportional-derivative controller, as shown in Equation (3): Among them, speed_error is the speed error as shown in Equation (4), and pre_speed_error is the preview speed error as shown in Equation (5). is the acceleration at the moment of t + t1 corresponding to the preview time t1, a des is the target acceleration, a act is the actual acceleration, K p is the proportionality coefficient, K d is the differential coefficient, w1 and w2 are influence weights, 0 ≤ w1 ≤ 1, 0 ≤ w2 ≤ 1; speed_error = v des -v act (4) where, v des is the target speed, and v act is the actual speed at the current moment t; Among them, is the speed at the moment of t + t1 corresponding to the preview time t1; Step 4: Determine the control strategy: The vehicle is a complex non-linear hysteresis system. Considering the actual working state of the vehicle comprehensively, the control strategy for the vehicle to achieve autonomous speed tracking includes the following three aspects: The first case: In response to the problem of slow vehicle start-up, when starting the vehicle, the preview time is increased to t2 (t2 > t1), and an early start prediction is made according to the speed at the moment of t + t2. Make an early start prediction accordingly. The second case: For the problem that the sensitivity of the vehicle speed to the change in the throttle control variable is different during the low-speed and high-speed movement of the vehicle, different proportional coefficients and differential coefficients are set for the high-speed stage and the low-speed stage to determine the throttle control variable CtrValue; The third case: To address the problem that the vehicle cannot quickly and stably decelerate to 0, based on the speed at the future time t + t2 determine whether the throttle control amount CtrValue is 0. If CtrValue = 0.

2. The control method for a vehicle to achieve autonomous speed tracking according to claim 1, characterized in that: It also includes Step 5: Based on the vehicle throttle control model constructed in Step 1, the throttle pedal control model constructed in Step 3, and the control strategy determined in Step 4, extend it to the actual working conditions. Combining with a specific autonomous driving robot platform, without modifying the vehicle's internal control unit, assist the vehicle to complete more autonomous driving tasks, and achieve the speed tracking test and durability performance test before the vehicle leaves the factory.

3. A control method for a vehicle to achieve autonomous speed tracking as claimed in claim 1, characterized in that: On the premise of knowing the target speed curve, use both the speed and acceleration errors as the basis for the control variables. Consider both the error between the target value and the actual value at the current moment and the error between the target value at a future preview moment and the actual value at the current moment, and determine different weight coefficients. Establish an incremental preview feedforward proportional-derivative controller, determine the throttle and brake pedal control variables, formulate a vehicle speed tracking control strategy in combination with the autonomous driving robot control platform, and automatically adjust the controller parameters in the low-speed and high-speed situations of the vehicle.

4. The control method for a vehicle to achieve autonomous speed tracking according to claim 1, characterized in that: Based on the influence of multiple errors, highlight the role of future speed and future acceleration. Use the turning point of the speed change rate calibrated according to the vehicle parameters as the criterion for judging high speed and low speed. In the low-speed stage and the high-speed stage, automatically adjust the parameters of the controller according to the characteristics of the vehicle speed response. The controller in the low-speed stage accelerates the change of the control variable, and the controller in the high-speed stage reduces the change of the control variable.

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