A smart vehicle longitudinal speed tracking control method considering ride comfort

Abstract

The application discloses a kind of intelligent vehicle longitudinal speed tracking control methods of considering ride comfort in the field of automatic driving, and is divided into four parts: control domain judge, speed tracking controller, drive brake separator, comfort compensation controller;The application considers the influencing factors of the influence of the passengers ride comfort, designs a kind of intelligent vehicle longitudinal speed tracking control method considering ride comfort, to improve the ride comfort of passengers when speed tracking vehicle.This application uses fuzzy PID algorithm to control the vehicle longitudinal drive braking torque based on actual speed and acceleration, to achieve high-precision speed tracking effect.Considering comfort, in order to reduce the discomfort caused by "sudden lifting head" when vehicle accelerates and "frequent nodding" when decelerates, the application also uses fuzzy control algorithm to compensate the drive braking torque for comfort, so as to achieve the purpose of improving the ride comfort of passengers.

Description

Technical Field

[0001] This invention relates to the field of autonomous driving technology, specifically to a longitudinal speed tracking control method for intelligent vehicles that takes into account passenger comfort. Background Technology

[0002] Today, the traditional automotive industry is facing a severe blow due to energy shortages and environmental damage. Coupled with the steady increase in car ownership, social problems such as urban congestion and frequent traffic accidents are driving the development of intelligent vehicles. As a product of the new era, intelligent vehicles can solve the environmental and social problems brought about by the ever-increasing number of cars. As an important means of transportation for the future, the main research objective of intelligent vehicles is to achieve fully autonomous driving, and one of the core issues in the field of autonomous driving technology is vehicle motion control.

[0003] Longitudinal motion control, as a component of motion control, primarily achieves speed tracking by combining drive and braking control. Existing longitudinal motion control methods mainly include PID control, fuzzy control, sliding mode control, LQR control, and model predictive control. The performance of these methods is primarily evaluated based on two key indicators: control accuracy and the smoothness of the executed actions. Regarding control accuracy, current methods can meet high precision requirements and achieve good speed tracking. However, considering the passenger experience—ride comfort—two discomforts exist: one is discomfort caused by excessive acceleration during gear changes, and the other is discomfort caused by speed jitter during speed tracking. In other words, the smoothness of the executed actions during control is poor, and most control methods cannot yet achieve good smoothness during speed tracking. Based on this, this invention designs an intelligent vehicle longitudinal speed tracking control method that considers passenger comfort to solve the above problems. Summary of the Invention

[0004] The purpose of this invention is to provide a longitudinal speed tracking control method for intelligent vehicles that takes into account ride comfort, thereby solving the problems mentioned above.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a longitudinal speed tracking control method for intelligent vehicles that takes into account ride comfort, comprising four parts: a control domain determiner, a speed tracking controller, a drive-brake separator, and a comfort compensation controller;

[0006] The control domain determiner judges the error range, performs control outside the error range, and does not perform additional control within the allowable error range, and transmits the judgment data to the speed tracking controller;

[0007] The speed tracking controller uses fuzzy control to output parameters from fuzzy to decipherable. It outputs PID control parameters through Kp, Ki, and Kd parameters to avoid discomfort caused by a long braking response due to exceeding the expected speed by too much.

[0008] The drive-brake separator separates the signal output by the controller into a drive signal and a brake signal, and converts them into a percentage signal of the maximum torque before outputting them to the controlled vehicle.

[0009] The comfort compensation controller mainly adopts a fuzzy control algorithm, taking the pitch rate error e (desired pitch rate - actual pitch rate) and the error change rate ec as inputs to the fuzzy control, and the output is the compensation torque T.

[0010] Preferably, the control domain determiner sets an allowable error range for the control algorithm as [-R, +R] (R>0).

[0011] Preferably, in the speed tracking controller, the universe of discourse for the speed error E and the rate of change of error EC is [-3, +3], and the quantization factor K... E =0.2, K EC =0.2, the corresponding fuzzy set is [NB, NM, NS, ZO, PS, PM, PB], the universe of discourse of parameters Kp, Ki, Kd is [-4.5, 4.5], and the scaling factor K Kp =5.56, K Ki =2.78, K Kd =0.56, and the corresponding fuzzy set is [NB, NM, NS, ZO, PS, PM, PB].

[0012] Preferably, in the speed tracking controller, the error E directly affects the value of the proportional coefficient Kp. When E>0, Kp is positively correlated with E; when E≤0, Kp is negatively correlated with E and makes corresponding adjustments according to the change of EC; when E>0, if |E| is too large, the system response time is accelerated; when E≤0, the system overshoot is reduced.

[0013] Preferably, in the speed tracking controller, a larger differential coefficient is used when the absolute value of the error is large, and a smaller integral coefficient is used when the absolute value of the error is small, and appropriate adjustments are made according to the change of EC.

[0014] Preferably, in the speed tracking controller, a larger Kd value is used when the system overshoot is large, and a smaller Kd value is used when the system overshoot is small.

[0015] Preferably, in the drive-brake separator, the output is a drive signal when the signal is positive and a brake signal when the signal is negative.

[0016] Preferably, in the comfort compensation controller, the universe of discourse for the pitch angular velocity error e and the rate of change of error ec is [-2, +2], the quantization factors Ke = 0.5 and Kec = 0.05, and the corresponding fuzzy sets are [NB, NS, ZO, PS, PB]. The universe of discourse for the compensation torque is [-3, +3], and the scaling factor K... T =63.3, and the corresponding fuzzy set is [NB, NS, ZO, PS, PB].

[0017] Preferably, in the comfort compensation controller, the fuzzy control is as follows: when e>0, T<0, the larger e is, the larger |T| is; when e<0, T>0, the larger e is, the larger |T| is.

[0018] Compared with the prior art, the beneficial effects of the present invention are:

[0019] This invention considers the factors affecting the comfort of drivers and passengers, and designs an intelligent vehicle longitudinal speed tracking control method that takes into account the comfort of passengers, so as to improve the comfort of passengers when the vehicle is tracking speed.

[0020] This invention employs a fuzzy PID algorithm to control the longitudinal driving and braking torque of the vehicle based on actual vehicle speed and acceleration, achieving a high-precision speed tracking effect. Considering comfort, to reduce the discomfort caused by the vehicle's sudden nose-up during acceleration and frequent nose-down during deceleration, this invention also uses a fuzzy control algorithm to compensate for the driving and braking torque, thereby improving passenger comfort. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the technical route of the present invention;

[0023] Figure 2 This is a schematic diagram of the control domain determiner of the present invention;

[0024] Figure 3 This is a schematic diagram of the membership function of the present invention E;

[0025] Figure 4 This is a schematic diagram of the membership function of EC in this invention;

[0026] Figure 5 This is a schematic diagram of the membership function of Kp in this invention;

[0027] Figure 6 This is a schematic diagram of the membership function of Ki in this invention;

[0028] Figure 7 This is a schematic diagram of the membership function of Kd in this invention;

[0029] Figure 8 This is a logic block diagram of the speed tracking controller of the present invention;

[0030] Figure 9 This is a schematic diagram of the drive-brake separator of the present invention;

[0031] Figure 10 This is a block diagram of the comfort compensation control logic of the present invention;

[0032] Figure 11 This is a schematic diagram of the membership function of the present invention e;

[0033] Figure 12 This is a schematic diagram of the membership function of the ec in this invention;

[0034] Figure 13 This is a schematic diagram of the membership function of T in this invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] This invention provides a technical solution: Addressing the shortcomings of existing control methods, this invention considers factors affecting passenger comfort and designs an intelligent vehicle longitudinal speed tracking control method that prioritizes passenger comfort during speed tracking. This invention employs a fuzzy PID algorithm to control the vehicle's longitudinal driving and braking torque based on actual vehicle speed and acceleration, achieving high-precision speed tracking. Considering comfort, to reduce the discomfort caused by sudden nose-up during acceleration and frequent nose-down during deceleration, this invention further uses a fuzzy control algorithm to compensate for the driving and braking torque, thereby improving passenger comfort. The specific technical approach is as follows: Figure 1 As shown, it is mainly divided into four parts: control domain controller, speed tracking controller, drive-brake separator, and comfort compensation controller.

[0037] like Figure 2The diagram shows a control domain determiner, which sets an allowable error range [-R, +R] (R>0) for the control algorithm. Control is performed outside the error range, and no additional control is performed within the allowable error range.

[0038] The design of the control domain discriminator can reduce the jitter of the system response to a certain extent, thereby saving control energy consumption and improving the riding comfort of passengers.

[0039] Considering the impact of speed error E (E = desired speed - actual speed) and error change rate EC on speed tracking, both are used as inputs to the fuzzy PID controller, with outputs of parameters Kp, Ki, and Kd. The universe of discourse for speed error E and error change rate EC is [-3, +3], with quantization factors KE = 0.2 and KEC = 0.2, corresponding to fuzzy sets [NB, NM, NS, ZO, PS, PM, PB]. The membership functions for each fuzzy set are as follows: Figure 3 As shown in Figure 4, the universe of discourse for parameters Kp, Ki, and Kd is [-4.5, 4.5], the scaling factors KKp = 5.56, KKi = 2.78, and KKd = 0.56, and the corresponding fuzzy sets are [NB, NM, NS, ZO, PS, PM, PB]. The membership functions for each fuzzy set are as follows: Figure 5 As shown in 6 and 7.

[0040] The logic block diagram of the speed tracking controller is as follows: Figure 8 As shown. Fuzzy rules are the core of the entire controller, and the specific design concept is as follows:

[0041] In PID control, the three parameters P, I, and D have different effects on the system: P affects the system's response speed, I affects the system's steady-state error, and D affects the system's overshoot. Considering these characteristics,

[0042] First, the error E directly affects the value of the proportional coefficient Kp. When E > 0, Kp is positively correlated with E; when E ≤ 0, Kp is negatively correlated with E, and adjustments are made accordingly based on changes in EC. The purpose of this design is to: when E > 0, if |E| is too large, accelerate the system's response time; when E ≤ 0, reduce the system's overshoot, avoiding discomfort caused by a prolonged braking response due to excessively exceeding the expected speed. Specific fuzzy rules are shown in Table 1.

[0043] Table 1: Fuzzy rules of Kp relative to E and EC

[0044]

[0045]

[0046] Secondly, considering that the integral coefficient Ki acts on the accumulated past error and can be used to eliminate the steady-state error of the system, but an excessively large integral coefficient can also lead to excessive system overshoot, affecting the ride comfort of the car. Therefore, the design approach is to use a larger differential coefficient when the absolute value of the error is large, and a smaller integral coefficient when the absolute value of the error is small. Furthermore, appropriate adjustments are made based on changes in EC, and the specific fuzzy rules are shown in Table 2.

[0047] Table 2: Fuzzy rules for Ki relative to E and EC

[0048]

[0049]

[0050] Finally, considering the effect of the differential coefficient Kd on the rate of change of error, choosing an appropriate Kd value can suppress system overshoot. The design principle is: when the system overshoot is large, a larger Kd value is used; when the system overshoot is small, a smaller Kd value is used. Specific fuzzy rules are shown in Table 3.

[0051] Table 3: Fuzzy rules of Kd relative to E and EC

[0052]

[0053]

[0054] Since the controller ultimately outputs a single signal, while the vehicle's movement is controlled by the drive and braking systems, the controller's output signal is separated into drive and braking signals, which are then converted into percentage signals of maximum torque before being output. Design concept: When the signal is positive, the output is a drive signal; when the signal is negative, the output is a braking signal. The drive-brake separator is as follows: Figure 9 As shown.

[0055] The logic block diagram of the comfort compensation controller is as follows: Figure 10 As shown, fuzzy control algorithm is mainly adopted. Considering comfort, in order to reduce the discomfort caused by the "sudden nose-up" during vehicle acceleration and the "frequent nose-down" during deceleration, the pitch rate error e (desired pitch rate - actual pitch rate) and the error change rate ec are used as inputs to fuzzy control, and the output is the compensation torque T. The universe of discourse for pitch rate error e and error change rate ec is [-2, +2], the quantization factors Ke = 0.5 and Kec = 0.05, and the corresponding fuzzy sets are [NB, NS, ZO, PS, PB]. The membership functions for each fuzzy set are as follows: Figure 11 As shown in Figure 12, the universe of discourse for the compensation torque is [-3, +3], the scaling factor KT = 63.3, and the corresponding fuzzy sets are [NB, NS, ZO, PS, PB]. The membership functions for each fuzzy set are as follows: Figure 13 As shown.

[0056] The design concept of fuzzy control is as follows:

[0057] When e > 0, T < 0, the larger e is, the larger |T| is; when e < 0, T > 0, the larger e is, the larger |T| is. The specific fuzzy rules are shown in Table 4.

[0058] Table 4: Fuzzy rules of T relative to e and ec

[0059]

[0060]

[0061] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0062] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent vehicle longitudinal speed tracking control method considering ride comfort, characterized in that, The application is applied to a longitudinal motion control system, which comprises a control domain determinator, a speed tracking controller, a drive-brake separator, and a comfort compensation controller. The control method comprises the following steps: first, the control domain determinator determines the error range, controls outside the error range, does not perform additional control within the error range, and transmits the determination data to the speed tracking controller; second, the speed tracking controller outputs the parameters to be fuzzified based on fuzzy control, outputs the PID control parameters through fuzzy control, and avoids the discomfort caused by the long brake response due to the excessive expected speed; third, the drive-brake separator separates the signal output by the speed tracking controller into a drive signal and a brake signal, converts the signals into percentage signals of the maximum torque, and outputs the signals to the controlled vehicle; and the comfort compensation controller mainly adopts a fuzzy control algorithm, takes the pitch angle speed error e, i.e., the expected pitch angle speed minus the actual pitch angle speed, and the error change rate ec as the inputs of the fuzzy control, and outputs a compensation torque T to the speed tracking controller. 2.The intelligent vehicle longitudinal speed tracking control method considering ride comfort according to claim 1, wherein: The control domain determinator sets an error range allowed by a control algorithm as [-R, +R] (R>0). 3.The intelligent vehicle longitudinal speed tracking control method considering ride comfort of claim 1, wherein: In the speed tracking controller, the domain of the speed error E and the error change rate EC is [-3, +3], the quantization factor K E = 0.2, K EC = 0.2, the corresponding fuzzy set is [NB, NM, NS, ZO, PS, PM, PB], the domain of the parameters Kp, Ki, Kd is [-4.5, 4.5], the quantization factor K Kp = 5.56, K Ki = 2.78, K Kd = 0.56, the corresponding fuzzy set is [NB, NM, NS, ZO, PS, PM, PB]. 4.The intelligent vehicle longitudinal speed tracking control method considering ride comfort of claim 3, wherein: In the speed tracking controller, the error E directly affects the value of the proportional coefficient Kp, Kp is positively correlated with E when E>0, Kp is negatively correlated with E when E≤0, and appropriate adjustment is made according to the change of EC; when E>0, the response time of the system is accelerated when |E| is too large; when E≤0, the overshoot of the system is reduced. 5.The intelligent vehicle longitudinal speed tracking control method considering ride comfort according to claim 4, characterized in that: In the speed tracking controller, a larger differential coefficient is taken when the absolute value of the error is large, a smaller integral coefficient is taken when the absolute value of the error is small, and appropriate adjustment is made according to the change of EC. 6.The intelligent vehicle longitudinal speed tracking control method considering ride comfort according to claim 5, wherein: In the speed tracking controller, a larger Kd value is taken when the overshoot of the system is large, and a smaller Kd value is taken when the overshoot of the system is small. 7.The intelligent vehicle longitudinal speed tracking control method considering ride comfort of claim 1, wherein: In the drive-brake separator, a drive signal is output when the signal is positive, and a brake signal is output when the signal is negative. 8.The intelligent vehicle longitudinal speed tracking control method considering ride comfort of claim 1, wherein: In the comfort compensation controller, the argument range of pitch angle velocity error e and error change rate ec is [-2, +2], the quantization factor Ke=0.5, Kec=0.05, the corresponding fuzzy set is [NB, NS, ZO, PS, PB], the argument range of compensation moment is [-3, +3], the proportional factor K T =63.3, the corresponding fuzzy set is [NB, NS, ZO, PS, PB]. 9.The intelligent vehicle longitudinal speed tracking control method considering ride comfort of claim 8, wherein: In the comfort compensation controller, the fuzzy control is as follows: when e>0, T<0, |T| is larger when e is larger; when e<0, T>0, |T| is larger when e is larger.

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