An AVH anti-slip compensation method based on a self-learning algorithm

Abstract

This invention discloses an AVH (Automotive Chassis Braking System) anti-rollback compensation method based on a self-learning algorithm, relating to the field of automotive chassis braking system control technology. It is implemented based on an AVH anti-rollback compensation system. The method involves: the AVH anti-rollback compensation system calculating the AVH parking time before rollback based on the AVH enable signal and wheel speed pulses; then calculating a leakage compensation coefficient based on the calculated AVH parking time and the designed maximum AVH pressure holding time; amplifying the AVH parking target pressure based on the calculated leakage compensation coefficient; and storing and retrieving the current leakage compensation coefficient. This invention, through the calculation and self-learning of the leakage compensation coefficient K, reduces prolonged AVH parking and rollback when the leakage of the isolation valve changes, increasing driver comfort and mitigating NVH problems caused by the system's active pressurization.

Description

Technical Field

[0001] This invention relates to the field of automotive chassis braking system control technology, and in particular to an AVH anti-rollback compensation method based on a self-learning algorithm. Background Technology

[0002] Automatic Parking (AVH) is an automatic braking function that helps the driver achieve a comfortable driving state. It can keep the vehicle stationary for a relatively long time on slopes or flat surfaces using hydraulic braking, and then automatically releases the brakes upon detecting a start signal. For example... Figure 1 The diagram illustrates the hydraulic principle of a prior art Electronic Stability Control (ESC) system. As shown, when the Automatic Parking (AVH) function is triggered, a software algorithm calculates the target parking pressure based on the parking slope. Once the wheel cylinders reach the target pressure, the isolation valves on both sides (isolation valve 1 and isolation valve 2) are energized and closed. Intake valves 3 and 4 are de-energized and closed, completely cutting off the hydraulic circuit between the master cylinder and the wheel cylinders, thus maintaining constant pressure within the wheels.

[0003] However, in engineering applications, due to durability and component consistency considerations, the leakage of isolation valves 1 and 2 varies throughout their lifespan. This leads to insufficient pressure holding capacity during prolonged AVH (Automatic Vehicle Hold) hill starts, causing the vehicle to roll backward. Traditional anti-rollback logic uses wheel speed sensor pulses to determine if rolling has occurred. Upon confirmation, it actively pressurizes the system via motors, pumps, and hydraulic valves to compensate for pressure loss caused by leakage from isolation valves 1 and 2. However, pressurization involves multiple components, resulting in noise (NVH) issues, and the rollback occurring before pressurization also affects ride comfort. Therefore, this invention proposes an AVH anti-rollback compensation method based on a self-learning algorithm to address these problems. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing an AVH anti-roll-off compensation method based on a self-learning algorithm. This method can fully consider the leakage of the isolation valve when calculating the AVH target pressure, thereby reducing the roll-off situation that causes the vehicle to automatically park (AVH) on a slope, thus ensuring comfort, and greatly optimizing NVH issues.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] An AVH anti-runaway compensation method based on a self-learning algorithm is implemented based on an AVH anti-runaway compensation system. The method is as follows: the AVH anti-runaway compensation system calculates the parking time before AVH runaway based on the AVH enable signal and wheel speed pulse, and then calculates the leakage compensation coefficient based on the calculated parking time before AVH runaway and the designed maximum pressure holding time of AVH. Based on the calculated leakage compensation coefficient, the target parking pressure of AVH is amplified, and the current leakage compensation coefficient is stored and read.

[0007] Furthermore, the AVH anti-slippage compensation system comprises three parts: a leakage compensation coefficient calculation module, an AVH pressure holding target calculation module based on leakage compensation, and a software state machine for transmitting compensation coefficients.

[0008] Furthermore, the leakage compensation coefficient calculation module calculates the duration of AVH before the slippage based on the AVH enable signal and the wheel speed pulse.

[0009] Furthermore, the leakage compensation coefficient calculation module calculates the leakage compensation coefficient based on the duration before the AVH slope and the designed maximum pressure holding time of the AVH.

[0010] Furthermore, the leakage compensation coefficient calculation module is also used to compensate for the leakage compensation coefficient and to protect the leakage compensation coefficient for maximum and minimum values.

[0011] Furthermore, the AVH pressure holding target calculation module amplifies the AVH parking target pressure through a leakage compensation coefficient.

[0012] Furthermore, the software state machine stores the current leakage compensation coefficient when the controller is powered off and reads the leakage compensation coefficient when the controller is powered on.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: In the present invention, the AVH anti-slip compensation system can calculate and self-learn the leakage compensation K value through three parts: a leakage compensation coefficient calculation module, an AVH pressure holding target calculation module based on leakage compensation, and a software state machine for compensation coefficient transmission. This enables the system to fully consider the leakage of the isolation valve when the leakage amount changes, and to perform AVH anti-slip compensation based on the calculated and self-learned leakage compensation coefficient, thereby reducing the situation of AVH function holding on the slope for a long time and slipping. It also increases the driver's comfort and solves the NVH problem caused by the system's active pressurization. Attached Figure Description

[0014] Figure 1 This is a hydraulic schematic diagram of a vehicle stability system in the prior art.

[0015] Figure 2 This is a schematic diagram of the leakage compensation coefficient calculation module in this invention;

[0016] Figure 3 This is a schematic diagram of the AVH pressure holding target calculation module based on leakage compensation in this invention;

[0017] Figure 4 This is a schematic diagram of the working process of the software state machine for the compensation coefficient transfer of the present invention. Detailed Implementation

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0019] Based on the fact that the leakage of the isolation valve changes during its life cycle, which leads to driver comfort issues caused by the vehicle's automatic parking (AVH) rolling back on a slope during prolonged parking, and the NVH (noise, vibration, and harshness) issues caused by the automatic parking system actively pressurizing to prevent rolling back, this application proposes an AVH anti-rollback compensation method based on a self-learning algorithm to solve the above problems.

[0020] An AVH anti-slip compensation method based on a self-learning algorithm is implemented based on an AVH anti-slip compensation system, which includes three parts: a leakage compensation coefficient calculation module, an AVH pressure holding target calculation module based on leakage compensation, and a software state machine for compensation coefficient transfer.

[0021] The method is summarized as follows: The AVH anti-slippage compensation system calculates the AVH parking time before slippage based on the AVH enable signal and wheel speed pulse. Then, based on the calculated AVH parking time before slippage and the designed maximum pressure holding time of the AVH, it calculates the leakage compensation coefficient. Based on the calculated leakage compensation coefficient, the AVH parking target pressure is amplified, and the current leakage compensation coefficient is stored and read. This realizes the calculation and self-learning of the leakage compensation coefficient, so as to reduce the situation of AVH function parking and slippage for a long time when the isolation valve leaks.

[0022] The functions of each module in the AVH anti-slip compensation system will be described in detail below:

[0023] The leakage compensation coefficient calculation module calculates the duration of AVH before the sloping based on the AVH enable signal and wheel speed pulse, calculates the leakage compensation coefficient based on the duration of AVH before the sloping based on the designed maximum pressure holding time of AVH, and is used to compensate for the leakage compensation coefficient and to protect the maximum and minimum values ​​of the leakage compensation coefficient.

[0024] Specifically: such as Figure 2As shown, the first step is to send an Avh (Avh) hill-holding enable signal based on the vehicle's own Avh logic module. Timing starts when the Avh hill-holding enable signal is true. At the same time, the wheel speed sensor sends wheel speed pulses to determine whether the vehicle is rolling backwards and sends a rolling backwards status signal. Timing stops when the rolling backwards status signal is true.

[0025] The second step is to calculate the duration t before the vehicle rolls down the slope based on the time from the start of the timer to the end of the timer. If the maximum Avh target holding time Tmax is reached at this point, thus triggering the AVH enable EPB (Electronic Parking Brake) to engage, then record t = Tmax.

[0026] The leakage compensation coefficient K is calculated using the following formula. original :

[0027]

[0028] The third step involves combining the original leakage compensation coefficient and the leakage compensation coefficient based on the power-on NVM, and updating the leakage compensation coefficient based on the limitation compensation to obtain the updated leakage compensation coefficient.

[0029] Based on a certain leakage compensation coefficient step size, namely the increase step size StepAdd and the decrease step size StepMinus, as well as the maximum value K_max and minimum value K_min of the leakage compensation coefficient, a limit protection is applied to the leakage compensation coefficient K. The specific formula is as follows:

[0030] When K original When K ≥ K,

[0031] K = max(K + max((K)) original -K),StepAdd),K_max);

[0032] When K original When < K,

[0033] K = min(K - min((K)) original -K),StepMinus),K_min).

[0034] The AVH pressure holding target calculation module amplifies the AVH parking target pressure through a leakage compensation coefficient. Its principle is as follows: Figure 3 As shown, the vehicle's lmu sends a slope signal, and the vehicle's own AVH algorithm calculates the theoretical parking pressure P based on the slope signal. original Theoretical parking pressure P originalAfter correction, based on the maximum target parking time, the parking pressure is adjusted. Combined with the original AVH target parking pressure and the leakage compensation coefficient calculated by the leakage compensation coefficient calculation module, the original AVH target parking pressure is updated through the leakage compensation module, resulting in the compensated AVH target parking pressure P. target The compensated AVH target parking pressure P target The signal is transmitted to the isolation valve control module to determine the target current for the solenoid valve.

[0035] Among them, P target The calculation formula is:

[0036] P target =P original +P corr *K

[0037] By taking into full account the leakage of the isolation valve when calculating the AVH target pressure, the likelihood of the vehicle rolling back on the ramp when automatically parking is reduced.

[0038] The software state machine stores the current leakage compensation coefficient when the controller is powered off and reads the leakage compensation coefficient when the controller is powered on. The software state machine for transmitting the compensation coefficient is as follows: Figure 4 As shown, when the controller is powered on and initialized, it reads the leakage compensation coefficient K value from the NVM module as the initial value of K for that power-on cycle. In the same power-on cycle, the leakage compensation coefficient calculation module calculates the leakage compensation coefficient K in real time. When the controller is powered off, the current leakage compensation coefficient K value is stored. This enables the leakage compensation coefficient K to learn itself throughout the product lifecycle.

[0039] In summary, the invention presented in this application can calculate and self-learn the leakage compensation coefficient K value to ensure that the pressure loss caused by the leakage of the isolation valve is compensated. This reduces the situation of the AVH function being stuck on the slope for a long time and slipping when the leakage of the isolation valve changes, and reduces the frequency of active pressurization of vehicle components.

[0040] Furthermore, the reduction in rollback reduces discomfort for users, increases user comfort, and enhances the driving experience. It also effectively reduces noise issues caused by the movement of multiple components involved in active supercharging, resulting in significant optimization of NVH (Noise, Vibration, and Harshness).

[0041] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An AVH (Advanced Vacuum-and-Hole) slope protection compensation method based on a self-learning algorithm, characterized in that, Based on the AVH anti-runaway compensation system, the method is as follows: the AVH anti-runaway compensation system calculates the parking time before AVH runaway based on the AVH enable signal and wheel speed pulse, and then calculates the leakage compensation coefficient based on the calculated parking time before AVH runaway combined with the designed maximum pressure holding time of AVH. Based on the calculated leakage compensation coefficient, the AVH parking target pressure is amplified, and the current leakage compensation coefficient is stored and read. The AVH anti-slip compensation system comprises three parts: a leakage compensation coefficient calculation module, an AVH pressure holding target calculation module based on leakage compensation, and a software state machine for transmitting compensation coefficients. The leakage compensation coefficient calculation module calculates the duration of AVH before the slippage based on the AVH enable signal and the wheel speed pulse.

2. The AVH anti-slip compensation method based on a self-learning algorithm according to claim 1, characterized in that, The leakage compensation coefficient calculation module calculates the leakage compensation coefficient based on the duration before the AVH slope and the designed maximum pressure holding time of the AVH.

3. The AVH anti-slip compensation method based on a self-learning algorithm according to claim 1, characterized in that, The leakage compensation coefficient calculation module is also used to compensate for the leakage compensation coefficient and to protect the maximum and minimum values ​​of the leakage compensation coefficient.

4. The AVH anti-slip compensation method based on a self-learning algorithm according to claim 1, characterized in that, The AVH pressure holding target calculation module amplifies the AVH parking target pressure through a leakage compensation coefficient.

5. The AVH anti-slip compensation method based on a self-learning algorithm according to claim 1, characterized in that, The software state machine stores the current leakage compensation coefficient when the controller is powered off and reads the leakage compensation coefficient when the controller is powered on.

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