A hydraulic pressure control method for an electronic hydraulic brake system of a new energy vehicle

Abstract

The present invention provides a hydraulic pressure control method for an electronic hydraulic brake system of a new energy vehicle, comprising: real-time acquisition of driving signals, denoising the driving signals using a Kalman filter, and calculating pedal speed, pedal acceleration, vehicle deceleration, and wheel speed fluctuation rate; calculating a target hydraulic pressure using a target pressure prediction model; obtaining a mode control output based on the pedal speed and wheel speed fluctuation rate, wherein the mode control output is a PID output in normal mode, a sliding mode control output in emergency mode, and an ABS / EBD collaborative output in ABS mode; performing feedforward control based on an inverse model of a motor-hydraulic actuator to generate a nonlinear pressure compensation amount; and calculating a final control amount based on the target hydraulic pressure, the mode control output, and the nonlinear pressure compensation amount. The present invention can improve the adaptability and stability of the electronic hydraulic brake system under complex operating conditions, while also enhancing the driving comfort of the driver.

Description

Technical Field

[0001] The present invention relates to the technical field of smart cars, and in particular to a method for controlling the hydraulic pressure of an electronic hydraulic brake system of a new energy vehicle. Background Art

[0002] With the rapid development of new energy vehicles and intelligent driving technologies, the electronic hydraulic braking system (EHB) has gradually replaced the traditional vacuum-assisted braking system due to its fast response and high-precision control potential, becoming the core executive component of the intelligent chassis.

[0003] Traditional PID control relies on pressure error feedback regulation, but the inherent nonlinear characteristics of the hydraulic system cause a lag in the control output. In the existing technology, although some studies have introduced feedforward compensation, the feedforward models are mostly based on linear assumptions and do not fully consider the dynamic coupling characteristics of the motor-hydraulic system, making it difficult to achieve accurate inverse model compensation. In addition, a single control mode cannot cover a variety of driving scenarios. On low-adhesion roads, when the ABS is triggered, the traditional control strategy lacks wheel speed-pressure coordinated control logic, which can easily lead to pressure oscillation and reduce braking comfort. When the driver's intention suddenly changes, the fixed parameter control cannot adjust the pressure gradient according to the pedal speed in real time, resulting in a mismatch between the braking intention and the system response. The existing solution relies on threshold judgment to switch between normal braking, emergency braking, and ABS modes, and does not combine the prediction of vehicle dynamics state, resulting in mode switching delays. Summary of the Invention

[0004] In view of this, the present invention provides a hydraulic pressure control method for an electronic hydraulic brake system of a new energy vehicle, so as to improve the adaptability and stability of the electronic hydraulic brake system under complex working conditions, while improving the driving comfort of the driver.

[0005] A method for controlling hydraulic pressure of an electronic hydraulic brake system of a new energy vehicle, comprising:

[0006] Step S1: real-time acquisition of driving signals, including driver pedal travel data, vehicle speed, vehicle mass, wheel speed, and brake master cylinder pressure. De-noising of the driving signals is performed using a Kalman filter, and pedal speed, pedal acceleration, vehicle deceleration, and wheel speed fluctuation rate are calculated.

[0007] Step S2, calculating the target hydraulic pressure using a target pressure prediction model based on the driver's pedal travel data, pedal speed, and vehicle mass;

[0008] Step S3, obtaining a mode control output based on the pedal speed and the wheel speed fluctuation rate, wherein the mode control output is a PID output in the normal mode, a sliding mode control output in the emergency mode, and an ABS / EBD coordinated output in the ABS mode;

[0009] Step S4, performing feedforward control based on an inverse model of the motor-hydraulic actuator to generate a nonlinear pressure compensation amount;

[0010] In step S5, based on the target hydraulic pressure obtained in step S2, the mode control output obtained in step S3, and the nonlinear pressure compensation amount obtained in step S4, the final control amount is calculated, and a motor control instruction is generated, which is then output to the actuator of the electronic hydraulic brake system.

[0011] The hydraulic pressure control method of the electronic hydraulic brake system of a new energy vehicle provided by the present invention has the following beneficial effects:

[0012] (1) The present invention collects driving signals in real time and can identify drivers with different driving habits. It can switch between normal, emergency and ABS modes in real time based on the driving signals. It processes the driving signals through Kalman filtering and combines the target pressure prediction model to dynamically calculate the target hydraulic pressure, thus solving the delay problem of module switching in traditional solutions.

[0013] (2) In view of the nonlinear and dynamic coupling characteristics of the hydraulic system, the present invention designs an inverse model based on the motor-hydraulic actuator for feedforward control, generating a nonlinear pressure compensation to offset the influence of the system's nonlinear friction and oil compressibility, which can achieve more accurate inverse model compensation.

[0014] (3) In normal mode, the improved fuzzy PID control can dynamically adjust parameters based on pressure error and rate of change. Compared with traditional PID, the response time is shortened by 43% and the overshoot is reduced to 3.2%. In emergency mode, the introduction of step-by-step feedforward pulse and sliding mode variable structure control can achieve millisecond-level pressure surge while suppressing vibration. In ABS mode, the upper pressure limit is dynamically constrained based on the slip ratio and wheel speed change rate, and the closed-loop wheel speed regulation is achieved in conjunction with ESP.

[0015] (4) The present invention integrates the target hydraulic pressure, mode control output, and nonlinear pressure compensation to calculate the final control quantity, thereby improving the adaptability and stability of the electronic hydraulic brake system under complex working conditions and enhancing the driving comfort of the driver. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flow chart of a method for controlling hydraulic pressure in an electronic hydraulic brake system of a new energy vehicle provided by an embodiment of the present invention;

[0017] Figure 2 This is a comparison chart of pressure response in normal mode;

[0018] Figure 3 This is a comparison chart of the pressure rise response in emergency braking mode;

[0019] Figure 4 This is a comparison chart of the glide rate cooperative control in ABS mode;

[0020] Figure 5 This is a comparison chart of nonlinear compensation effects. DETAILED DESCRIPTION

[0021] The following describes embodiments of the present invention in detail, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the embodiments of the present invention, and should not be construed as limiting the present invention.

[0022] See also Figure 1 , an embodiment of the present invention provides a method for controlling the hydraulic pressure of an electronic hydraulic brake system of a new energy vehicle, comprising steps S1-S5.

[0023] In step S1, the driving signal is collected in real time, the driving signal is denoised by Kalman filtering, and the pedal speed, pedal acceleration, vehicle deceleration and wheel speed fluctuation rate are calculated.

[0024] Among them, the driving signal includes the driver's pedal travel data , vehicle speed , vehicle quality , wheel speed and brake master cylinder pressure .

[0025] Among them, the driving signal is denoised by Kalman filtering, satisfying the following expression:

[0026]

[0027] in, is the state vector at time k, and , is the pedal speed, represents transpose; is the state transfer matrix, which is used to describe the dynamic relationship between state variables; is the process noise, which represents the unmodeled dynamics such as actuator friction and hydraulic fluctuations; is the observation vector, which represents the original measurement value of the sensor; is the observation matrix, here is the wheel speed sensor proportional coefficient; is the observation noise, here the sensor electronic noise, is the state vector at time k-1.

[0028] The wheel speed volatility is calculated using the following formula:

[0029] ;

[0030] in, is the wheel speed fluctuation rate (unit: %), is the maximum wheel speed (unit: rad / s), is the minimum wheel speed (unit: rad / s), is the average wheel speed (unit: rad / s).

[0031] Step S2: Calculate the target hydraulic pressure using a target pressure prediction model based on the driver's pedal travel data, pedal speed, and vehicle mass.

[0032] Among them, the target hydraulic pressure is calculated by the target pressure prediction model, and the expression is:

[0033]

[0034] in, is the target hydraulic pressure; is the pedal stroke gain coefficient, the calibration range is 0.8-1.2; Driver pedal travel data; is the pedal speed gain coefficient, the calibration range is 0.05-0.15; is the pedal speed, is the vehicle mass, is the expected deceleration based on vehicle speed and road adhesion coefficient, is the piston area of ​​the brake master cylinder.

[0035] The calculation formula is:

[0036]

[0037] in, is the real-time road adhesion coefficient; is the acceleration due to gravity, take 9.8m / s 2 ; is the attenuation factor, which is 0.02s / m; For vehicle speed.

[0038] Among them, the real-time road adhesion coefficient Satisfy the following formula:

[0039]

[0040] in, Vehicle speed The differential of For time The differential of is the yaw angular velocity The differential of .

[0041] Step S3, obtaining a mode control output according to the pedal speed and the wheel speed fluctuation rate. The mode control output is a PID output in normal mode, a sliding mode control output in emergency mode, and an ABS / EBD coordinated output in ABS mode.

[0042] Wherein, step S3 specifically includes:

[0043] In normal mode, that is, when the pedal speed , and wheel speed fluctuation rate When the improved fuzzy PID control is activated, the pressure error between the target hydraulic pressure calculated in step S2 and the actual hydraulic pressure is calculated. and error rate of change Dynamically adjust the proportional, integral, and differential parameters to obtain PID output.

[0044] Specifically, the dynamic adjustment rule of the parameters of the improved fuzzy PID control is:

[0045] Input variables include: pressure error and error rate of change , , is the brake master cylinder pressure;

[0046] Output variables include: proportional coefficient increment , integral coefficient increment , differential coefficient increment ;

[0047] Fuzzy rule base based on and Size and change trend, online adjustment 、 and .

[0048] In this embodiment, 、 and Satisfy Table 1:

[0049] Table 1

[0050]

[0051] Among them, input variable 1, pressure error The value range of the fuzzy subset NB is <-8MPa, which is a large negative error and requires a large pressure increase; the value range of the fuzzy subset NM is greater than -8MPa< <-5MPa, which is a medium negative error and requires medium pressure boost; the value range of the fuzzy subset NS is -5MPa< <-2Mpa, which is a small negative error and requires slight pressure increase; the value range of the fuzzy subset ZO is -2MPa< <2MPa, belongs to the equilibrium area, maintain the current parameters; the value range of the fuzzy subset PS is 2MPa< <5MPa, which is a small positive error and requires a slight pressure reduction; the value range of the fuzzy subset PM is 5MPa< <8MPa, belongs to the positive error, and needs a moderate pressure reduction; the value range of the fuzzy subset PB is >8MPa is a large positive error and requires a significant pressure reduction.

[0052] Input variable 2, error rate of change The value range of the fuzzy subset NB is When the pressure is less than -80MPa / s, the pressure changes rapidly and requires emergency intervention; the value range of the fuzzy subset NM is -80MPa / s< When the pressure changes at a moderate speed, it will deteriorate and require strong intervention. The value range of the fuzzy subset NS is -50MPa / s< When the pressure is less than -20MPa / s, the pressure change slowly deteriorates and preventive adjustment is required; the value range of the fuzzy subset ZO is -20MPa / s< When the pressure is less than -20MPa / s, the pressure change is in a stable state and maintains the current trend; the value range of the fuzzy subset PS is 20MPa / s< When the pressure is less than 50MPa / s, the pressure change recovers slowly and needs to be adjusted carefully. The value range of the fuzzy subset PM is 50MPa / s< When the pressure is less than 80MPa / s, the pressure change recovers at a moderate speed and the control can be relaxed; the value range of the fuzzy subset PB is 80MPa / s< When the pressure changes, it recovers quickly and the control can be greatly relaxed.

[0053] Table 2 compares the results of the improved fuzzy PID control in the present invention and the traditional PID algorithm control.

[0054] Table 2

[0055]

[0056] As can be seen from Table 2, the improved fuzzy PID control shortens the control response time by 43% and reduces the overshoot to 3.2% compared with the traditional PID algorithm.

[0057] In emergency mode, when the pedal speed , or vehicle deceleration When , the stepped feedforward pressure pulse and sliding mode variable structure control are activated to obtain the sliding mode control output.

[0058] Specifically, the process of step-by-step feedforward pressure pulse and sliding mode variable structure control is as follows:

[0059] Step S301: Step-wise feedforward pressure pulse injection:

[0060] In the initial stage of emergency braking, , Indicates time, is the start time of emergency braking mode, For the duration of emergency braking mode, a step-wise feedforward pulse is calculated based on the target hydraulic pressure. , the expression is:

[0061]

[0062] Step S302, sliding mode variable structure control:

[0063] Design sliding surface and control law , the expression is:

[0064]

[0065]

[0066] in, is the die surface adjustment coefficient, For time The differential of To switch the gain, is a saturation function, is the boundary layer thickness (in this embodiment, the value is 0.1).

[0067] In ABS mode, that is, when the wheel speed fluctuation rate When the ABS is turned on, the dynamic pressure upper limit constraint and wheel speed closed-loop adjustment are activated, and the wheel speed is adjusted in coordination with the electronic brake force distribution system (EBD), thereby obtaining ABS / EBD coordinated output.

[0068] Specifically, the dynamic pressure upper limit constraint and wheel speed closed-loop regulation are activated, and the wheel speed is adjusted in coordination with the electronic brake force distribution system, including:

[0069] Calculate slip ratio based on wheel speed sensor signal and wheel speed change rate , and dynamically set the upper pressure limit , the expression is:

[0070]

[0071] in, is the road adhesion coefficient related gain, is the base pressure;

[0072] Step S42, designing ABS and EBD coordinated control strategy based on the dynamically set pressure upper limit , combined with the wheel speed closed-loop adjustment algorithm to generate the target wheel cylinder pressure, and cooperate with the EBD system to achieve independent pressure adjustment and vehicle stability control for each wheel.

[0073] In step S4, feedforward control is performed based on the inverse model of the motor-hydraulic actuator to generate a nonlinear pressure compensation value. The nonlinear pressure compensation value is used to offset the nonlinear friction, inertial energy loss and oil compressibility of the system.

[0074] Among them, the nonlinear pressure compensation amount is adopted as follows:

[0075]

[0076] in, is the nonlinear pressure compensation, is the motor torque constant, is the comprehensive friction coefficient (including static friction and dynamic friction), is the motor rotor inertia, is the motor angular acceleration, is the effective bulk modulus of the oil, for The differential of For time The differential of .

[0077] In step S5, based on the target hydraulic pressure obtained in step S2, the mode control output obtained in step S3, and the nonlinear pressure compensation amount obtained in step S4, the final control amount is calculated, and a motor control instruction is generated, which is then output to the actuator of the electronic hydraulic brake system.

[0078] The final control quantity is calculated using the following formula: :

[0079]

[0080] in, is the mode weight coefficient, This is the mode control output.

[0081] Figure 2 This is a comparison chart of pressure response in normal mode. By simulating a stable driving scene, the target pressure is stepped to 10 MPa, and ±0.5 MPa Gaussian noise is added to simulate sensor interference. Figure 2It can be seen that, compared with the traditional PID control and the improved fuzzy PID control of the present invention, the improved fuzzy PID control of the present invention shortens the pressure rise time by 43%.

[0082] Figure 3 This is a comparison chart of the pressure rise response in emergency braking mode. A 100ms transient pressure response process is set to compare the basic control with the step-wise feedforward pressure pulse and sliding mode variable structure control of the present invention. The target pressure gradient is 100 MPa / s (millisecond-level response requirement). Figure 3 It can be seen that in the emergency mode, the stepped feedforward pressure pulse and sliding mode variable structure control of the present invention are used to reach the target pressure 15ms ahead of time, and the overshoot is reduced to 3.2%.

[0083] Figure 4 This is the effect diagram of the slip rate coordinated control in ABS mode, simulating a low-adhesion road surface, with the slip rate fluctuating between 0.05-0.25 and the initial wheel speed of 80 rad / s. Figure 4 It can be seen that in ABS mode, the dynamic pressure upper limit constraint of the present invention successfully limits the slip ratio to ≤ 0.25, and the wheel speed fluctuation rate is reduced by 72%.

[0084] Figure 5 This is a comparison chart of nonlinear compensation effects. Figure 5 It can be seen that the nonlinear compensation of the present invention reduces the phase lag by 80%.

[0085] In summary, the hydraulic pressure control method for the electronic hydraulic brake system of a new energy vehicle according to the above embodiment has the following beneficial effects:

[0086] (1) The present invention collects driving signals in real time and can identify drivers with different driving habits. It can switch between normal, emergency and ABS modes in real time based on the driving signals. It processes the driving signals through Kalman filtering and combines the target pressure prediction model to dynamically calculate the target hydraulic pressure, thus solving the delay problem of module switching in traditional solutions.

[0087] (2) In view of the nonlinear and dynamic coupling characteristics of the hydraulic system, the present invention designs an inverse model based on the motor-hydraulic actuator for feedforward control, generating a nonlinear pressure compensation to offset the influence of the system's nonlinear friction and oil compressibility, which can achieve more accurate inverse model compensation.

[0088] (3) In normal mode, the improved fuzzy PID control can dynamically adjust parameters based on pressure error and rate of change. Compared with traditional PID, the response time is shortened by 43% and the overshoot is reduced to 3.2%. In emergency mode, the introduction of step-by-step feedforward pulse and sliding mode variable structure control can achieve millisecond-level pressure surge while suppressing vibration. In ABS mode, the upper pressure limit is dynamically constrained based on the slip ratio and wheel speed change rate, and the closed-loop wheel speed regulation is achieved in conjunction with ESP.

[0089] (4) The present invention integrates the target hydraulic pressure, mode control output, and nonlinear pressure compensation to calculate the final control quantity, thereby improving the adaptability and stability of the electronic hydraulic brake system under complex working conditions and enhancing the driving comfort of the driver.

[0090] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the patent for this invention shall be determined by the appended claims.

Claims

1. A hydraulic pressure control method for an electronic hydraulic brake system of a new energy vehicle, characterized in that: include: Step S1: real-time acquisition of driving signals, including driver pedal travel data, vehicle speed, vehicle mass, wheel speed, and brake master cylinder pressure. De-noising of the driving signals is performed using a Kalman filter, and pedal speed, pedal acceleration, vehicle deceleration, and wheel speed fluctuation rate are calculated. Step S2, calculating the target hydraulic pressure using a target pressure prediction model based on the driver's pedal travel data, pedal speed, and vehicle mass; Step S3, obtaining a mode control output based on the pedal speed and the wheel speed fluctuation rate, wherein the mode control output is a PID output in the normal mode, a sliding mode control output in the emergency mode, and an ABS / EBD coordinated output in the ABS mode; Step S4, performing feedforward control based on an inverse model of the motor-hydraulic actuator to generate a nonlinear pressure compensation amount; In step S5, based on the target hydraulic pressure obtained in step S2, the mode control output obtained in step S3, and the nonlinear pressure compensation amount obtained in step S4, the final control amount is calculated, and a motor control instruction is generated, which is then output to the actuator of the electronic hydraulic brake system.

2. The hydraulic pressure control method of the electronic hydraulic brake system of a new energy vehicle according to claim 1, characterized in that: In step S2, the target hydraulic pressure is calculated using the target pressure prediction model, and the expression is: in, is the target hydraulic pressure, is the pedal stroke gain coefficient, is the driver's pedal travel data, is the pedal speed gain coefficient, is the pedal speed, is the vehicle mass, is the expected deceleration based on vehicle speed and road adhesion coefficient, is the piston area of ​​the brake master cylinder.

3. The hydraulic pressure control method of the electronic hydraulic brake system of a new energy vehicle according to claim 2, characterized in that: Step S3 specifically includes: In normal mode, that is, when the pedal speed Less than or equal to the pedal speed threshold, and the wheel speed fluctuation rate When the wheel speed fluctuation rate is less than or equal to the wheel speed fluctuation rate threshold, the improved fuzzy PID control is activated and the pressure error between the target hydraulic pressure calculated in step S2 and the actual hydraulic pressure is calculated. and error rate of change Dynamically adjust the proportional, integral, and differential parameters to obtain PID output; In emergency mode, when the pedal speed Greater than the pedal speed threshold, or vehicle deceleration When it is greater than the deceleration threshold, the step-wise feedforward pressure pulse and sliding mode variable structure control are activated to obtain the sliding mode control output; In ABS mode, that is, when the wheel speed fluctuation rate When the speed is greater than the wheel speed fluctuation threshold, the dynamic pressure upper limit constraint and wheel speed closed-loop adjustment are activated, and the wheel speed is adjusted in coordination with the electronic brake force distribution system to obtain ABS / EBD coordinated output.

4. The hydraulic pressure control method of the electronic hydraulic brake system of a new energy vehicle according to claim 3, characterized in that: In step S3, the improved fuzzy PID control parameter dynamic adjustment rule is: Input variables include: pressure error and error rate of change , , is the brake master cylinder pressure; Output variables include: proportional coefficient increment , integral coefficient increment , differential coefficient increment ; Fuzzy rule base and Size and change trend, online adjustment 、 and .

5. The hydraulic pressure control method of the electronic hydraulic brake system of a new energy vehicle according to claim 3 is characterized in that: In step S3, the process of step-by-step feedforward pressure pulse and sliding mode variable structure control is as follows: Step S301: Step-wise feedforward pressure pulse injection: In the initial stage of emergency braking, , Indicates time, is the start time of emergency braking mode, For the duration of emergency braking mode, a step-wise feedforward pulse is calculated based on the target hydraulic pressure. , the expression is: Step S302, sliding mode variable structure control: Design sliding surface and control law , the expression is: in, is the die surface adjustment coefficient, For time The differential of To switch the gain, is a saturation function, is the boundary layer thickness.

6. The hydraulic pressure control method of the electronic hydraulic brake system of a new energy vehicle according to claim 3, characterized in that: In step S3, the dynamic pressure upper limit constraint and wheel speed closed-loop regulation are activated, and the wheel speed is adjusted in coordination with the electronic brake force distribution system, specifically including: Calculate slip ratio based on wheel speed sensor signal and wheel speed change rate , and dynamically set the upper pressure limit , the expression is: in, is the road adhesion coefficient related gain, is the base pressure; Step S42, designing ABS and EBD coordinated control strategy based on the dynamically set pressure upper limit , combined with the wheel speed closed-loop adjustment algorithm to generate the target wheel cylinder pressure, and cooperate with the EBD system to achieve independent pressure adjustment and vehicle stability control for each wheel.

7. The hydraulic pressure control method of the electronic hydraulic brake system of a new energy vehicle according to claim 3, characterized in that: In step S4, the nonlinear pressure compensation amount is calculated using the following formula: in, is the nonlinear pressure compensation, is the motor torque constant, is the comprehensive friction coefficient, is the motor rotor inertia, is the motor angular acceleration, is the effective bulk modulus of the oil, for The differential of For time The differential of .

8. The hydraulic pressure control method of the electronic hydraulic brake system of a new energy vehicle according to claim 7, characterized in that: In step S5, the final control amount is calculated using the following formula: : in, is the mode weight coefficient, This is the mode control output.

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