WO2014059806A1

WO2014059806A1 - Can bus-based drive-by-wire abs braking system and control method

Info

Publication number: WO2014059806A1
Application number: PCT/CN2013/079404
Authority: WO
Inventors: 张世兵
Original assignee: 奇瑞汽车股份有限公司; 芜湖普威技研有限公司
Priority date: 2012-10-16
Filing date: 2013-07-15
Publication date: 2014-04-24
Also published as: CN102862559A; CN102862559B

Abstract

A method for controlling a CAN bus-based drive-by-wire ABS braking system. The control method uses slip rate error and slip rate error change as a fuzzy input quantity, uses a voltage value of a system output motor as a fuzzy control output quantity, and decides in a fuzzy way the fuzzy control output quantity is an accurate control output quantity, converts the accurate control output quantity into a target current value of the motor, and sends same to a PID controller by means of a CAN bus for controlling a braking actuator. On account of the variability of ABS system working conditions and the non-linearity of tires, the control method uses a fuzzy control method, need not establish a precise mathematical model for the controlled object, and has a fast response speed, small overshoot, and better robustness and flexibility. Meanwhile, as regards the determination existing in the fuzzy control method that the performance for eliminating the steady-state error is relatively poor, the PID control is further combined to achieve higher control accuracy. Also disclosed is a control system using the control method.

Description

Wire-controlled ABS braking system and control method based on CAN bus

Technical field

The invention belongs to the technical field of automobile wire control, and particularly relates to a wire-controlled ABS braking system and a control method based on a CAN bus. Background technique

At present, most of the vehicle braking systems at home and abroad are based on hydraulic energy transmission systems to achieve vehicle braking. The control method is mostly based on the logic threshold control algorithm. This control method does not involve controlling the mathematical model, and the system has a fast response in real time, which has great advantages compared with other control methods. However, its control logic is complicated, debugging is difficult, control is not stable enough, and its switch control mode makes the brake system unable to continuously utilize the maximum adhesion of the ground, and this control mode has poor compatibility with the vehicle, and the hydraulic oil leaks to the environment. It is also the biggest drawback. Summary of the invention

The object of the present invention is to solve the problem that the control mode of the existing vehicle brake system adopts the logic threshold control algorithm has the problems of complicated control logic, difficult debugging, unstable control, and poor vehicle compatibility, and provides a CAN bus based method. The control method of the wire-controlled ABS brake system.

The technical solution adopted to solve the technical problem of the present invention is a control method of a wire-controlled ABS braking system based on a CAN bus, comprising the following steps:

SO, maps the system input slip rate error and the slip rate error rate of the fuzzy control system to its corresponding input domain, performs fuzzy quantization to obtain the fuzzy input quantity; maps the voltage value of the system output motor of the fuzzy control system To the corresponding output domain, perform fuzzy quantization to obtain the fuzzy output;

S l, performing fuzzy rule inference on the fuzzy input quantity, and obtaining a corresponding fuzzy control output quantity;

S2, the fuzzy control output is fuzzyly determined to accurately control the output;

S3, converting the precise control output into a target current value of the motor, and sending it to the CAN bus

PID controller for controlling the brake actuator.

The control method of the line control system based on CAN bus of the invention is directed to the variable condition of the ABS system and the nonlinearity of the tire, adopts the fuzzy control method, does not need to establish an accurate mathematical model for the control object, and the response speed is fast, overshoot Small amount, with good robustness and flexibility. At the same time, the performance of the fuzzy control method to eliminate the steady-state error of the system is relatively poor, and further combined with the PID control to achieve higher control accuracy.

Preferably, the control brake actuator is: adjusting the power of the brake motor through a current loop PID controller Flow is controlled.

Preferably, in the fuzzy quantization, the fuzzy input quantity and the fuzzy output quantity are converted by respective membership functions, and the membership function is a mean triangle function, and the triangular membership function The variable levels are all 5 levels.

Preferably, the fuzzy rule base used in the fuzzy rule inference is established based on a multi-input single-output fuzzy logic system, and the rules are:

R ^J '-if ^χ ι is and ·3⁄4 is and and is then y ^J is B

Where, denotes the jth fuzzy rule; j=l, 2, ..., k is the number of fuzzy rules;

= ( , , ''" ) _e f/ _C r is the input to the multi-input single-output fuzzy logic system; yeWcR is the output of the multi-input single-output fuzzy logic system; and ^ is the fuzzy language value defined on the respective domain.

Preferably,

Where f :UGR"→ ., corresponds to the point at which the maximum is obtained. where 0 ⁼ ( ^··, ) ^Τ as the tunable vector; ⁼ ^ ² '··Ά) ^Τ is the fuzzy basis function vector, ^ ( ^) is the value of the output membership function, 'the fuzzy subset argument field value of the corresponding control output f(x).

Preferably, the method of PID control is expressed as:

k

P( k) =K _p E(k) + E(j) + K _D [E(k) E(k 1)]

j=o

Where K _P , K _I; K _D are the proportional, integral and differential coefficients of the regulator, respectively, E (k), E (k-1) are the expected deviation values for the kth and k-1 times, respectively. (k) is the output of the regulator at the kth time.

Another object of the present invention is to solve the problem that the existing vehicle brake system has complicated control logic, difficult debugging, unstable control, and poor vehicle compatibility, and provides a wire-controlled ABS braking system based on CAN bus.

The technical solution adopted to solve the technical problem of the present invention is a wire-controlled ABS braking system based on CAN bus, which includes:

a master controller and a slave controller; the master controller includes a conversion module, a fuzzy inference module, and a fuzzy decision module, and the slave controller includes a PID control module, wherein

a conversion module for mapping a system input slip rate error and a slip rate error rate of the fuzzy control system To the corresponding input domain, fuzzy quantization is performed to obtain the fuzzy input quantity; it is used to map the voltage value of the system output motor of the fuzzy control system to its corresponding output domain, and perform fuzzy quantization to obtain the fuzzy output; fuzzy reasoning a module, configured to perform fuzzy inference on the fuzzy input quantity according to the fuzzy rule, to obtain a corresponding fuzzy control output quantity;

a fuzzy decision module, configured to ambiguously determine the fuzzy control output quantity to accurately control the output quantity;

a PID control module, configured to receive a precision output quantity of the fuzzy control module transmitted by the CAN network and convert the control output quantity into a target current value of the motor, and the PID control module controls the output according to the target current value of the motor Brake actuator.

Preferably, the brake actuator is an electric brake disposed on four wheels of the automobile, and the electric brake includes: a brake caliper body, a motor, a lead screw, a screw nut, and the motor drives the screw nut through the speed reduction mechanism Rotating, the screw nut drives the lead screw to perform the feed motion to achieve braking; the output shaft end of the motor is provided with a power-off brake.

Preferably, the outer end of the lead screw is provided with a butterfly spring.

The electric brake provided by the invention enables the vehicle brake system to continuously utilize the maximum adhesion of the ground, and the vehicle has good compatibility, and at the same time avoids environmental pollution caused by leakage of hydraulic oil of the hydraulic brake system. DRAWINGS

1 is a schematic flow chart of a general control procedure of a fuzzy control method;

2 is a schematic flow chart of a control step of a control method of a wire-controlled ABS braking system based on a CAN bus according to Embodiment 1 of the present invention;

3 is a diagram showing the division of the fuzzy domain and the design of the membership function of the input ( _Xl , x ₂ ) and the output (y) of the fuzzy control in the first embodiment of the present invention;

4 is a schematic flow chart of current loop PID regulation control in Embodiment 1 of the present invention;

5 is a schematic diagram showing the composition of a control system of a wire-controlled ABS braking system based on a CAN bus in Embodiment 2 of the present invention;

6 is a schematic structural view of an electric actuator of an actuator in a wire-controlled ABS braking system based on a CAN bus according to Embodiment 2 of the present invention;

Fig. 7 is a structural schematic view showing a speed reduction mechanism of an electric actuator of an actuator in a wire-controlled ABS braking system based on a CAN bus according to a second embodiment of the present invention.

Reference mark:

1. caliper body 2. screw nut 3. lead screw 4. butterfly spring

5. Speed reduction mechanism 6. Power loss brake 7. Motor 71. Connection plate 8. Reduction wheel 9. Gear implementation

The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

The invention provides a control method of a wire-controlled ABS braking system based on a CAN bus, comprising the following steps: S0, mapping a system input slip rate error and a slip rate error change rate of a fuzzy control system to its corresponding input theory Domain, performing fuzzy quantization to obtain fuzzy input quantity; mapping the voltage value of the system output motor of the fuzzy control system to its corresponding output domain, performing fuzzy quantization to obtain the fuzzy output;

Sl, performing fuzzy rule inference on the fuzzy input quantity, and obtaining a corresponding fuzzy control output quantity;

52, the fuzzy control output is fuzzyly determined to accurately control the output;

53. Convert the precise control output into a target current value of the motor, and send it to the PID controller through the CAN bus to control the brake actuator. Example 1

The main control objective of the electromechanical brake system is to have the actual slip ratio S always follow the desired slip ratio during the entire braking process to produce the maximum road surface adhesion coefficient, so that it can be obtained under various road conditions. Better braking performance.

The comprehensive design of the traditional automatic control controller should be based on the accurate mathematical model of the controlled object (ie transfer function model or state space model), but in practice, many systems have many influencing factors, it is difficult to find out Precise mathematical model. In this case, fuzzy control has an important advantage. Because fuzzy control does not require the establishment of a mathematical model, it does not require prior knowledge of the mathematical model of the process.

In view of the variable operating conditions of the ABS system and the non-linear characteristics of the tires, it is especially suitable to use the fuzzy control method for control. The general control step flow of the fuzzy control method is as shown in FIG. 1, and includes: a fuzzy quantization step of the control system input, a control rule processing step, and a fuzzy decision step, wherein

XI , x ₂ : input of fuzzy control (precise quantity);

Xi , X ₂ : the amount of blur after fuzzy quantization processing;

U: the amount of fuzzy control obtained after fuzzy control rules and approximate reasoning;

u: the amount of control (accurate amount) obtained after the fuzzy decision;

Y: The output of the object.

As shown in FIG. 2, the control method of the CAN bus-based wire-controlled ABS braking system of the embodiment includes The following five steps. The five steps will be described in detail below.

Step S101, the main controller receives the measured values of the wheel speed and the vehicle speed sensor, and calculates the slip rate error _X1 and the slip rate error change rate.

The main controller receives the wheel speed value measured by the wheel speed sensor, and the body speed measured by the vehicle speed sensor calculates the slip ratio S according to the following formula:

Where ^ω is the body speed, m/s; is the actual angular velocity of the wheel, rad/s; r is the wheel rolling radius, m. The slip rate error and the slip rate error rate are calculated according to the following formula:

The slip rate error is _Xl = SS _T , where S is the slip ratio, S _T is the optimal slip ratio set by the system; and the slip rate error rate is

, where n is the number of detection cycles.

The control principle of the vehicle ABS is to control the slip ratio S of the wheel near the optimal slip ratio S _T to obtain a higher longitudinal and lateral adhesion coefficient to reduce the braking distance and ensure the directional stability of the vehicle when braking.

The calculated slip ratio error _X1 and the slip ratio error change rate calculated above are used as inputs of the fuzzy control. Step 102: The main controller performs the above-calculated slip ratio error _X1 and the slip ratio error change rate x ₂ on the blur quantization process, and performs the fuzzy quantization process on the voltage value of the system output motor by the same method.

The slip ratio error _X1 and the slip rate error change rate described above are mapped to the respective input universes to obtain the fuzzy input amount and X ₂ .

The fuzzy control established by the present embodiment achieves the fuzzification of the input quantity and the output variable by the formula fuzzy quantity = (^^ ^-0&)/2]/[0&)/2], where [a, b] for the actual range of the controller input variables ( _Xl , x ₂ ), [m, n] is the fuzzy subset domain, transform the actual input sum into the variables in the fuzzy subset theory and ^ then subordinate to the triangle The function is transformed into the fuzzy value of the input variable sum; the fuzzy output quantity U is obtained by the same method as the voltage value of the output motor of the system, and the membership function of the fuzzy output quantity U of the fuzzy controller also adopts the triangular membership function. The system inputs and the system output triangle membership functions have the same number of levels and are defined as needed. In this embodiment, the variable ranks of the triangular membership functions are all 5 levels, and the membership functions of the input variables ^ and the output variable y are evenly distributed.

The division of the system input ( _Xl , χ ₂ ) and output (y) fuzzy domain and the design of the membership function in this embodiment are shown in Fig. 3, wherein the fuzzy language value NB means "negative large" and NS means "negative small". ", Z means "moderate", PS means "small", and PB means "positive". Step 103: Perform fuzzy rule inference on the fuzzy input quantity and the fuzzy input quantity X ₂ to obtain a fuzzy control output quantity U corresponding to the voltage value of the output domain motor.

Generally for multi-input single-output MISO fuzzy logic systems (FLS), the fuzzy rules can be expressed as follows: R ^J '-if ^χ ι is and ·3⁄4 is and and is then y ^J is B

Where ^ is the "' fuzzy rule _; "'=1,2,...,1^ is the number of fuzzy rules; ^.,3⁄4)et/cR" is the input to FLS; y ^{eW c ?} is FLS The output; and is the fuzzy language value defined on the respective domain.

At this point, define the fuzzy basis function as:

Where ^ is a fuzzy basis function; ^^(^) is a membership function value.

In this embodiment, fuzzy rule inference is performed according to the characteristics of the input and output of the fuzzy system and the ABS control law, and 25 fuzzy control rules are established, as shown in Table 1.

Table 1 Fuzzy Control Rule Table

In Table 1, the fuzzy control rules are arranged in ascending order from left to right, for example, row 1 and column 1 are R ¹ ; row 5 and column 5 are R ²⁵ . The design principle of the control rule is: When the error is large, the control quantity should reduce the error as quickly as possible. When the error is small, in addition to eliminating the error, the stability of the system must also be considered to avoid unnecessary overshoot and oscillation. Specifically, when the error ^ is large, the output U should reduce the error as quickly as possible, and when the error 1 is small, the control of the output U is dominated, and the larger the x ₂ is, the smaller the output U is.

Preferably, in the current system, only 9 control rules of R1, R6, R11, R12, R13, R14, R15, R20, and R25 are used. Step 104: The fuzzy control output quantity U is subjected to fuzzy determination to accurately control the output quantity 1!. The result obtained by fuzzy inference is a fuzzy set or membership function, but in the actual use of fuzzy logic control, a certain value must be used to control the servo mechanism. In the fuzzy set obtained by reasoning, the process of taking a single value that can represent the fuzzy set is called defuzzification or fuzzy decision. The method of fuzzy decision in this embodiment is as follows:

A fuzzy system using single-point fuzzification, product inference, and weighted average fuzzy decision is expressed as:

=

Where f :UcR ⁿ →K. corresponds to the point at which the maximum value is obtained. Where 0 ⁼ ^^ ₂ ,···, ) ^Τ as a tunable vector; ⁼ ^ ² '··Ά) ^Τ is a fuzzy basis function vector, ^^'(^) is the value of the output membership function, θ" is the corresponding The fuzzy subset argument domain value of the control output f(x).

The fuzzy control output f is ambiguously determined by the above fuzzy decision to accurately control the output u. Step 105: Convert the above-mentioned precise control output u into a motor target current value, and send it to the PID control module through the CAN bus to perform closed-loop control on the actuator.

The control table is obtained by the above process, and is placed in the fuzzy controller, corresponding to different actual slip rate errors and error change rates, and the output Y of the fuzzy controller can be obtained through the table, and the output quantity 百分比 is a percentage form. That is the amount of control of the motor. The actuator in this embodiment is an electric brake provided on four wheels and a motor for controlling the pressing force of the brake.

In this embodiment, the voltage value of the motor is converted into a target current value of the motor, and sent to the PID control module through the CAN bus to control the magnitude of the input current of the motor, thereby controlling the output torque of the motor, and then according to the output torque of the motor and the speed reduction mechanism. The transmission relationship thus controls the clamping force of the brake disc, and finally achieves an accurate and stable braking effect of the braking force on the wheel. The motor current is collected multiple times during the control cycle and the current loop PID closed-loop control of the motor is realized. The control process is shown in Fig. 4.

The discrete form of the PID expression in this embodiment is:

k

k) =K _P E(k) + Κ _τ ^ E(j) + K _D [E(k) - E(k - 1)]

j=°

Where K _P , Κ _Ι; K _D are the proportional, integral and differential coefficients of the regulator, E (k), E (k-1) The expected deviation values for the kth and k-1 times, respectively, P (k) is the output of the regulator at the kth time.

The function of the proportional link is to react to the deviation of the signal instantaneously. The larger the K _p is, the stronger the control effect is. However, the excessive Κ _ρ will cause the system to oscillate and damage the stability of the system. Although the function of the integral link can eliminate the static error, it will also reduce the response speed of the system, increase the overshoot of the system, and even cause the system to have equal amplitude oscillation. The reduction can reduce the overshoot of the system, but it will slow down the system. Response process. The function of the differential link is to prevent the variation of the deviation, help to reduce the overshoot, overcome the oscillation, and stabilize the system, but it is sensitive to interference and is not conducive to the robustness of the system. Example 2

As shown in FIG. 5, the embodiment provides a control system for a wire-controlled ABS braking system based on a CAN bus, including:

The main controller and the slave controller are included; wherein the main controller receives the signal of the sensor, and calculates the slip rate error and the slip rate error rate. Information about the master and slave controllers is passed through the controller area network (CAN).

The main controller includes a conversion module, a fuzzy inference module, and a fuzzy decision module, and the slave controller includes a PID control module, wherein

a conversion module, configured to map a system input slip rate error and a slip rate error change rate of the fuzzy control system to its corresponding input domain, perform fuzzy quantization to obtain a fuzzy input amount; and use the system output of the fuzzy control system The voltage value of the motor is mapped to its corresponding output domain, and fuzzy quantization is performed to obtain a fuzzy output;

a fuzzy inference module, configured to perform fuzzy inference on the fuzzy input quantity according to the fuzzy rule, and obtain a corresponding fuzzy control output quantity;

The brake actuator described above is an electric brake disposed on the four wheels of the automobile. As shown in FIG. 6, the electric brake includes a caliper body 1 and a motor 7, and further includes a lead screw 3 and a screw nut 2, and the motor can pass The speed reduction mechanism 5 drives the screw nut 2 to rotate, and the screw nut drives the lead screw to perform a feed motion to achieve braking. A power loss brake 6 is provided at the end of the motor output shaft. A butterfly spring 4 is provided at the outer end of the screw.

When the brake operation is performed, the electric brake 6 is energized, the motor 7 rotates the output torque, and the torque is transmitted to the screw nut 2 after being decelerated and increased by the speed reduction mechanism 5, and the screw nut 2 rotates to drive the screw 3 to feed the movement. . At the same time, when the power-off brake 6 is energized, the butterfly spring 4 releases the pre-tightening pressure, and pushes the lead screw 3 for the feed motion, that is, The motor 7 and the butterfly spring 4 are coupled to each other to push the lead screw 3 for the feed motion. The lead screw 3 performs an axial feed motion, which pushes the friction plate to rub against the brake disc to generate a brake clamping force for braking. The preload of the butterfly spring 4 is released during braking, enabling braking with a large brake clamping force in a short response time. After the braking is completed, the motor 7 reversely drives the lead screw 3 to move, so that the butterfly spring 4 is in a compressed state, and controls the power-off brake 6 to suck and lock the output shaft of the motor 7, after the power-off brake 6 is engaged The rotation of the motor 7 is stopped to prevent the preload of the butterfly spring 4 from rotating in the reverse direction to maintain the preloading effect of the butterfly spring 4.

The structure of the above-described speed reduction mechanism is as shown in Fig. 7, in which the gear 9 on the motor shaft 71 transmits torque to the reduction wheel 8 and then performs deceleration and torque increase. It is to be understood that the above embodiments are merely exemplary embodiments employed to explain the principles of the invention, but the invention is not limited thereto. Various modifications and improvements can be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and improvements are also considered to be within the scope of the invention.

Claims

Claim

A control method for a wire-controlled ABS braking system based on a CAN bus, characterized in that it comprises the following steps:

S0, mapping the system input slip rate error and the slip rate error change rate of the fuzzy control system to its corresponding input domain, performing fuzzy quantization to obtain the fuzzy input amount; mapping the voltage value of the system output motor of the fuzzy control system To the corresponding output domain, perform fuzzy quantization to obtain the fuzzy output;

53. Convert the precise control output into a target current value of the motor, and send it to the PID controller through the CAN bus to control the brake actuator.

2. The control method of a CAN-based wire-controlled ABS braking system according to claim 1, wherein said control brake actuator is:

The current of the brake motor is controlled by the current loop PID controller.

The control method of the CAN bus-based wire-controlled ABS braking system according to claim 1, wherein in the fuzzy quantization, the fuzzy input amount and the fuzzy output amount are passed The membership function is transformed by the respective membership function, and the membership function is a uniform trigonometric function, and the trigonometric membership functions have a variable level of 5 levels.

The method for controlling a wire-controlled ABS braking system based on a CAN bus according to claim 1, wherein the fuzzy rule base used in the fuzzy rule inference is established based on a multi-input single-output fuzzy logic system. The rules are:

R ^J '- if ^χ ι is and ·3⁄4 is and and is then y ^J is B

Where R ' represents the jth fuzzy rule; j = l, 2, . .., k is the number of fuzzy rules;

= ( , ,···, ) ε ί/ ^ ^Τ is the input to the multi-input single-output fuzzy logic system; ye W c R is the output of the multi-input single-output fuzzy logic system; and 'is defined on the respective domain Fuzzy language value.

5. The control method of a CAN-based wire-controlled ABS braking system according to claim 1, wherein the method of fuzzy decision is: Where f is UcR ⁿ →K., corresponding to the point at which the maximum is obtained, where 0 ⁼ ^^ ₂ ,···, ) ^Τ as the tunable vector; ⁼ ^ ² '··Ά) ^Τ is the fuzzy basis function The vector, ^^/(^^) is the value of the output membership function, and the value of the fuzzy subset is the corresponding control output f(x).

A control method for a wire-controlled ABS braking system based on a CAN bus according to claim 1, wherein said PID control method is expressed as:

k

P( k =K _p E(k) + Kj E(j) + K _D [E(k) E(k 1)]

7. A control system for a wire-controlled ABS braking system based on a CAN bus, comprising: a main controller and a slave controller; wherein the main controller comprises a conversion module, a fuzzy inference module, and a fuzzy decision module. The slave controller includes a PID control module, wherein

8. The control system of a CAN bus-based wire-controlled ABS brake system according to claim 7, wherein said brake actuator is an electric brake disposed on four wheels of a vehicle, said electric brake include: The brake caliper body, the motor, the lead screw and the screw nut, the motor drives the screw nut to rotate through the speed reduction mechanism, and the screw nut drives the lead screw to perform the feed motion to realize the braking; the motor output shaft end is provided with the electric brake.

9. The CAN bus based control system for a wire-controlled ABS braking system according to claim 8, wherein: the outer end of the lead screw is provided with a butterfly spring.