Self-adaptive control vehicle braking control method and system

Abstract

The invention discloses a self-adaptive vehicle braking control method. The method comprises the steps that initial braking parameters are set before a braking system is started; the state of the vehicle is monitored in real time, and braking parameters of the vehicle are adjusted according to the monitored state of the vehicle; and after braking is triggered, braking control is conducted on the vehicle based on the adjusted braking parameters. The method has the advantages that the braking parameters are adjusted in a self-adaptive control mode, the braking reliability is improved, the requirement for braking stability in different road awakening and driving states is met, and the user experience of the braking system is improved.

Description

Technical Field

[0001] The invention relates to the field of automobile braking control, and in particular to an adaptively controlled vehicle braking control method and system. Background Art

[0002] Automobile braking is one of the safety functions of automobiles, and reliably and accurately meeting braking requirements is the top priority of vehicles. Traditional vehicle braking systems usually adopt a fixed parameter control strategy, that is, the parameters involved in braking remain unchanged after the brake is triggered. Regardless of the environment or driving status, the brakes are controlled in this mode. This brake control with fixed parameters will output the corresponding braking torque based on the fixed parameters, and output the same braking torque at the same pedal depth to achieve the same braking control. This method is suitable for traditional manual driving environments and is convenient for drivers to use.

[0003] However, with the development of intelligent and electrified automobile technology, automobile intelligence and automation technology have put forward higher requirements for the intelligence and adaptability of the braking system. The existing fixed-parameter braking control strategy cannot adapt to the changing driving conditions and vehicle status, resulting in unstable braking performance or reduced safety, affecting user experience and driving experience. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a vehicle braking control method and system with adaptive control, which adjusts the braking parameters by adaptive control, improves the reliability of braking, and meets the braking stability under different road conditions and driving conditions.

[0005] In order to achieve the above-mentioned purpose, the technical solution adopted by the present invention is: an adaptively controlled vehicle braking control method, including setting initial braking parameters before the braking system is started; monitoring the vehicle status in real time and adjusting the vehicle braking parameters according to the monitored vehicle status; after the braking is triggered, braking control of the vehicle is performed based on the adjusted braking parameters.

[0006] After the brake is triggered, the braking torque is calculated based on the adjusted braking parameters, and then the required braking pressure is calculated according to the braking torque. The braking pressure is converted into a control signal and sent to the brake actuator for braking execution.

[0007] After braking is completed, the actual braking effect is monitored in real time, and whether the braking meets the requirements is determined based on the actual braking effect. If not, the braking parameters of the vehicle are adjusted based on the braking effect.

[0008] Real-time monitoring of vehicle status includes monitoring the vehicle's speed, acceleration, load data, road conditions and external environmental data, and dynamically adjusting the vehicle's braking parameters based on the monitored vehicle's real-time speed, acceleration, load data, road conditions and external environmental data.

[0009] After braking is completed, the braking distance and braking stability parameters during the braking process are collected to evaluate the braking effect, and based on the braking effect, it is determined whether the braking requirements are met.

[0010] Vehicle status data is monitored using on-board sensors, including:

[0011] Speed ​​sensor: collects the vehicle's current speed data; acceleration sensor: collects the vehicle's acceleration data to determine the vehicle's dynamic changes; load sensor: monitors the vehicle's load status; road condition sensor: detects the type and condition of the road surface; environmental sensor: collects external environment data.

[0012] The control method includes an adaptive algorithm model configured to output corresponding braking parameters based on an input vehicle state.

[0013] A vehicle braking control system with adaptive control, the control system comprising a vehicle state acquisition module, an adaptive algorithm model, a calculation module, and an execution module; the vehicle state acquisition module is used to monitor the vehicle state, and its output end is connected to the adaptive algorithm model; the adaptive algorithm model adjusts the initial braking parameters based on the vehicle state to obtain adjusted braking parameters; the calculation module calculates the braking torque and braking pressure based on the adjusted braking parameters and converts them into corresponding control signals, and the execution module executes the control signals to achieve braking.

[0014] The control system also includes a feedback adjustment module and a feedback parameter acquisition module. The feedback parameter acquisition module is used to collect braking distance and braking stability parameters during vehicle braking. The feedback adjustment module performs feedback fine-tuning on the adjusted braking parameters based on the braking distance and braking stability parameters.

[0015] The vehicle status data collected by the vehicle status acquisition module include: vehicle speed, acceleration, load, road surface condition, and driving environment parameters. The adaptive algorithm module adjusts the output braking parameters based on the vehicle speed, acceleration, load, road surface condition, and driving environment parameters.

[0016] The advantages of the present invention are: adjusting the braking parameters by means of adaptive control, improving the reliability of braking, meeting the braking stability under different road conditions and driving conditions, and improving the user experience of the braking system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The following is a brief description of the contents expressed in the drawings of the present invention and the symbols in the drawings:

[0018] Figure 1 This is a flow chart of the adaptive braking control method of the present invention;

[0019] Figure 2 This is a flow chart of parameter collection required by the control method of the present invention;

[0020] Figure 3 This is an optimized control flow chart of the adaptive braking control method of the present invention. DETAILED DESCRIPTION

[0021] The specific implementation of the present invention will be further explained in detail below by describing the optimal embodiment with reference to the accompanying drawings.

[0022] The prior art uses fixed braking parameters to brake the vehicle. For example, the braking torque output under the fixed braking parameters at the same pedal depth is fixed, and the braking is performed under any circumstances according to the braking force converted from the braking distance. However, in actual situations, the braking distances are different under the same braking torque on sunny days and rainy days, and the braking effects and distances on smooth roads and rough roads are also different under the same braking torque. Therefore, the traditional solution with fixed braking parameters cannot meet the braking requirements of reliability.

[0023] The braking parameters are actually a map that converts braking demand into braking distance, or a linear or nonlinear mathematical relationship. Adjusting the braking parameters is equivalent to adjusting the map or mathematical relationship. The adjusted braking parameters actually output the corresponding braking torque based on the braking demand. For example, the braking parameters can be understood as a mathematical relationship model between the brake pedal depth and the braking torque. After inputting a brake pedal depth, the corresponding braking torque is output. Adjusting this relationship is to adjust its control relationship. The braking parameters can be adjusted by lowering or increasing the braking torque at the same pedal depth.

[0024] In this embodiment, an adaptively controlled vehicle brake control system includes a vehicle state acquisition module, an adaptive algorithm model, a calculation module, and an execution module;

[0025] The vehicle status acquisition module is used to monitor the vehicle status, and its output end is connected to the adaptive algorithm model. The vehicle status data collected by the vehicle status acquisition module include: vehicle speed, acceleration, load, road surface condition, and driving environment parameters. It is implemented by using a variety of on-board sensors, such as a vehicle speed sensor to obtain vehicle speed. The road surface condition and driving environment can be identified through images collected by the camera to obtain corresponding parameters.

[0026] The adaptive algorithm module adjusts the braking parameters based on the vehicle's speed, acceleration, load, road surface conditions, and driving environment parameters. The adaptive algorithm model adjusts the initial braking parameters based on the vehicle's state to obtain the adjusted braking parameters; adjusting the braking parameters is to adjust a braking map or mathematical relationship. For example, the braking parameters are a comparison table map of brake pedal depth and braking distance. The adjustment is to keep the brake pedal depth unchanged, increase or decrease the braking distance corresponding to the brake pedal depth, and obtain a new comparison table map, which is the adjusted braking parameter.

[0027] The calculation module calculates the braking torque and braking pressure based on the adjusted braking parameters and converts them into corresponding control signals, and the execution module executes the control signals to achieve braking. The calculation module is a virtual module integrated in the vehicle controller. Its main function is to calculate and obtain the braking torque based on the braking parameters at this time, such as the brake pedal depth. Then, the hydraulic brake pressure required for braking is calculated based on the braking torque, and then the brake pressure is converted into a control signal that can be executed by the execution module to control the execution of the execution module to complete the braking control. The execution module is the vehicle's braking system. The execution module realizes the braking of the vehicle based on the executed control signal. Modules such as the brake system and the hydraulic brake system are execution modules.

[0028] An initial braking parameter is set, and the initial braking parameter is preliminarily adjusted based on the adaptive algorithm module to obtain the adjusted braking parameter, and then the state after the braking is executed is monitored to judge the effect of the braking execution, and feedback adjustment is performed based on the braking execution effect, and the braking parameter is further adjusted to achieve the purpose of feedback adjustment of the braking parameter. The accuracy and reliability of the vehicle braking parameter are met through the adjustment of the braking parameter in both directions, and feedback learning adjustment can be performed each time based on the vehicle state parameters and the effect after braking until an optimal braking parameter is reached after multiple adjustments to meet the braking requirements. For this solution, a feedback adjustment module and a feedback parameter acquisition module are set. The feedback parameter acquisition module is used to collect the braking distance and braking stability parameters of the vehicle during braking. The feedback adjustment module performs feedback fine-tuning on the adjusted braking parameter based on the braking distance and braking stability parameters.

[0029] The braking effect is judged based on one or a combination of braking distance and braking stability parameters, and its judgment strategy can be pre-calibrated. In this scheme, the braking stability parameter is used alone as the evaluation of the braking effect, and the braking stability parameter is judged based on the deceleration change rate during the braking process. The deceleration at each moment in the braking process is calculated, and the deceleration change rate is obtained by dividing the deceleration difference between the latter moment and the previous moment by the time difference between the previous and the next moment. The calculated deceleration change rate with the largest absolute value is selected. If the maximum deceleration change rate is greater than the set parameter threshold, it is judged that the braking effect does not meet the requirements, otherwise it is judged that the braking effect meets the requirements. At this time, the adjusted braking parameters are feedback-adjusted to further adjust the braking parameters. At this time, the corresponding relationship of the braking parameters is fine-tuned, and the corresponding relationship in the braking parameters can be increased or decreased. In the adjustment process, the increase or decrease is determined based on the positive or negative of the maximum deceleration change rate; taking the braking parameters as the corresponding map of pedal depth and braking torque as an example, when the maximum deceleration change rate is positive, the brake pedal depth is kept unchanged in the map, and a fine-tuned value is added to the braking torque corresponding to each brake pedal depth, and the new map is obtained, which is the brake parameter after feedback adjustment. Otherwise, when the maximum deceleration change rate is negative, the brake pedal depth is kept unchanged in the map, and a fine-tuning value is subtracted from the braking torque corresponding to each brake pedal depth to obtain a new map, which is the braking parameter after feedback adjustment.

[0030] The present solution also provides an adaptively controlled vehicle braking control method, including setting initial braking parameters before the braking system is started; monitoring the vehicle state in real time, and adjusting the vehicle braking parameters according to the monitored vehicle state; after the braking is triggered, the vehicle is braked based on the adjusted braking parameters. After the braking is triggered, the braking torque is calculated based on the adjusted braking parameters, and then the required braking pressure is calculated based on the braking torque, and the braking pressure is converted into a control signal and sent to the braking actuator for braking execution.

[0031] After the braking is completed, the actual braking effect is monitored in real time, and whether the braking meets the requirements is determined based on the actual braking effect. If not, the braking parameters of the vehicle are adjusted based on the braking effect. After the braking is completed, the braking distance and braking stability parameters during the braking process are collected to evaluate the braking effect, and whether the braking requirements are met is determined based on the braking effect. The braking effect is determined based on one or a combination of the braking distance and braking stability parameters, and the judgment strategy can be pre-calibrated. This scheme uses the braking stability parameter alone as the evaluation of the braking effect, and determines the braking stability parameter based on the deceleration change rate during the braking process. The deceleration at each moment in the braking process is calculated, and the deceleration change rate is obtained by dividing the deceleration difference between the next moment and the previous moment by the time difference between the previous and next moments. The calculated deceleration change rate with the largest absolute value is selected. If the maximum deceleration change rate is greater than the set parameter threshold, it is determined that the braking effect does not meet the requirements, otherwise it is determined that the braking effect meets the requirements. At this time, the adjusted braking parameters are feedback-adjusted to further adjust the braking parameters. At this time, the corresponding relationship of the braking parameters is fine-tuned, and the corresponding relationship in the braking parameters can be increased or decreased. During the adjustment process, the increase or decrease is determined based on the positive or negative value of the maximum deceleration change rate; taking the braking parameter as the pedal depth and the braking torque corresponding map as an example, when the maximum deceleration change rate is a positive number, the brake pedal depth is kept unchanged in the map, and a fine-tuning value is added to the braking torque corresponding to each brake pedal depth, and the new map is the braking parameter after feedback adjustment. Otherwise, when the maximum deceleration change rate is a negative number, the brake pedal depth is kept unchanged in the map, and a fine-tuning value is subtracted from the braking torque corresponding to each brake pedal depth, and the new map is the braking parameter after feedback adjustment.

[0032] Real-time monitoring of vehicle status includes monitoring the vehicle's speed, acceleration, load data, road conditions and external environmental data, and dynamically adjusting the vehicle's braking parameters based on the monitored vehicle's real-time speed, acceleration, load data, road conditions and external environmental data. The vehicle status data is monitored using on-board sensors, including:

[0033] Speed ​​sensor: collects the vehicle's current speed data; acceleration sensor: collects the vehicle's acceleration data to determine the vehicle's dynamic changes; load sensor: monitors the vehicle's load status; road condition sensor: detects the type and condition of the road surface; environmental sensor: collects external environment data.

[0034] The control method includes an adaptive algorithm model, which is configured to adjust the output corresponding braking parameters based on the input vehicle state. The adaptive algorithm model is implemented by a pre-built adaptive algorithm, and the initial braking parameters are fine-tuned based on the different vehicle states to meet the braking parameters under different vehicle states. For example, the initial state is set to the braking parameters under clear weather. When it is recognized that it is a rainy day, the braking parameters are automatically adjusted to meet the braking needs under rainy days.

[0035] The design of the braking control method under the adaptive algorithm of this scheme needs to include:

[0036] 1. Design principle of adaptive control algorithm: This invention proposes an adaptive control algorithm based on vehicle dynamics model and environmental perception data. The algorithm can analyze factors such as vehicle speed, acceleration, road conditions, load changes, etc. in real time and dynamically adjust the braking torque and braking pressure.

[0037] 2. Algorithm implementation method: The algorithm adopts advanced control theories, such as fuzzy logic control, neural network control or adaptive PID control, to achieve precise control of the braking process. The algorithm also includes a self-learning capability that can optimize control parameters based on historical data.

[0038] 3. Application scenarios: This algorithm is applicable to various types of vehicles, including passenger cars, commercial vehicles and special vehicles. It is particularly suitable for braking control under complex and changeable road conditions and extreme weather conditions.

[0039] 4. Technical advantages: Compared with traditional braking systems, the adaptive control algorithm of the present invention can significantly improve the braking response speed, shorten the braking distance, and improve the braking stability under different road conditions.

[0040] This solution provides detailed algorithm implementation process and parameter setting guidance, including algorithm initialization, real-time data acquisition, control parameter calculation, actuator control and other steps. The specific solution is as follows:

[0041] like Figure 1 As shown, creating a flowchart of an adaptive control algorithm for a braking system involves multiple steps and components. The following is a simplified flowchart description to show the basic principles and steps of the algorithm:

[0042] This flowchart begins at the "Start" node and describes the main steps of the adaptive control algorithm:

[0043] 1. Initialization parameters: Set the initial braking parameters before starting the braking system.

[0044] 2. Real-time monitoring of vehicle status: Continuously monitor the vehicle's speed, acceleration, load and other status.

[0045] 3. Judgment conditions: Determine whether the braking parameters need to be adjusted based on the monitored status.

[0046] 4. Adjust braking torque: Dynamically adjust braking torque according to vehicle status and external conditions.

[0047] 5. Calculate brake pressure: Calculate the required brake pressure based on the braking torque.

[0048] 6. Control actuator: Send control signals to the brake actuator to perform braking operations.

[0049] 7. Execute braking operation: The actuator brakes according to the control signal.

[0050] 8. Monitor braking effect: monitor the actual effect after braking, such as braking distance and stability.

[0051] 9. Effect evaluation and adjustment: If the braking effect is not good, adjust the control parameters; if the effect is good, record the data.

[0052] 10. End: One braking cycle is completed.

[0053] like Figure 2 As shown, creating a schematic diagram of vehicle status and environmental perception data collection requires showing the interaction between the vehicle and the surrounding environment and the process of data collection. The following is a simplified schematic description: This diagram starts with the vehicle and describes the process of data collection and processing:

[0054] 1. Vehicle: as the subject of data collection.

[0055] 2. Sensor collection: Various sensors installed on the vehicle to collect vehicle status and environmental data.

[0056] 3. Speed ​​sensor: collects the vehicle's current speed data.

[0057] 4. Acceleration sensor: collects the vehicle's acceleration data to determine the dynamic changes of the vehicle.

[0058] 5. Load sensor: monitors the load status of the vehicle, which may affect the braking performance.

[0059] 6. Road condition sensor: detects the type and condition of the road surface, such as dry, slippery or icy.

[0060] 7. Environmental sensor: collects external environmental data such as temperature, humidity, light, etc., which may affect braking performance.

[0061] 8. Data processing unit: receives data from sensors and performs preliminary processing.

[0062] 9. Adaptive control algorithm: Dynamically adjust braking parameters based on processed data.

[0063] 10. Actuator: performs braking operations according to the instructions of the control algorithm.

[0064] 11. Vehicle status and environment database: stores historical data for algorithm learning and optimization.

[0065] like Figure 3 As shown, creating a schematic diagram of dynamic adjustment of control parameters can help understand how the adaptive control algorithm adjusts the braking system based on real-time data: This flowchart starts from the "Start" node and describes the main steps of dynamic adjustment of control parameters:

[0066] 1. Real-time data collection: The system starts running and collects data on vehicle status and environmental conditions in real time.

[0067] 2. Vehicle status: including speed, load, acceleration and other parameters.

[0068] 3. Environmental conditions: including parameters such as road conditions, weather, and traffic conditions.

[0069] 4. Vehicle status assessment: Assessment is performed based on the collected vehicle status data.

[0070] 5. Environmental conditions assessment: Assessment is conducted based on the collected environmental conditions data.

[0071] 6. Braking torque adjustment: Dynamically adjust the braking torque based on the evaluation results of vehicle status and environmental conditions.

[0072] 7. Brake pressure calculation: Based on the adjusted braking torque, calculate the required brake pressure.

[0073] 8. Actuator control: Send control signals to the brake actuator.

[0074] 9. Braking operation execution: The actuator brakes according to the control signal.

[0075] 10. Braking effect monitoring: monitor the actual effect of braking operation.

[0076] 11. Control parameter optimization: Optimize control parameters based on the feedback of braking effect.

[0077] 12. End / Loop: Determine whether further adjustment of control parameters is required. If necessary, return to the control parameter adjustment step; if the system is stable, end the loop.

[0078] 13. System stability: indicates that the current control parameters have reached the optimal level and no further adjustment is required.

[0079] The present invention relates to an adaptive control algorithm, which is particularly suitable for vehicle braking systems to improve braking performance and safety. The algorithm dynamically adjusts braking parameters by real-time monitoring of vehicle status and environmental conditions to achieve optimal braking effect. This patent describes in detail the design principle, implementation method and application scenarios of the adaptive control algorithm.

[0080] Obviously, the specific implementation of the present invention is not limited to the above-mentioned methods. As long as various non-substantial improvements are made using the method concept and technical solution of the present invention, they are all within the protection scope of the present invention.

Claims

1. A vehicle braking control method with adaptive control, characterized in that: It includes setting the initial braking parameters before the braking system is started; monitoring the vehicle status in real time and adjusting the vehicle's braking parameters according to the monitored vehicle status; and after the brakes are triggered, controlling the vehicle's braking based on the adjusted braking parameters.

2. The vehicle braking control method of claim 1, wherein: After the brake is triggered, the braking torque is calculated based on the adjusted braking parameters, and then the required braking pressure is calculated according to the braking torque. The braking pressure is converted into a control signal and sent to the brake actuator for braking execution.

3. The vehicle braking control method of adaptive control according to claim 2, characterized in that: After braking is completed, the actual braking effect is monitored in real time, and whether the braking meets the requirements is determined based on the actual braking effect. If not, the braking parameters of the vehicle are adjusted based on the braking effect.

4. A vehicle braking control method with adaptive control as claimed in any one of claims 1 to 3, characterized in that: Real-time monitoring of vehicle status includes monitoring the vehicle's speed, acceleration, load data, road conditions and external environmental data, and dynamically adjusting the vehicle's braking parameters based on the monitored vehicle's real-time speed, acceleration, load data, road conditions and external environmental data.

5. The vehicle braking control method of any one of claims 1 to 3, characterized in that: After braking is completed, the braking distance and braking stability parameters during the braking process are collected to evaluate the braking effect, and based on the braking effect, it is determined whether the braking requirements are met.

6. The vehicle braking control method of adaptive control according to any one of claims 1 to 3, characterized in that: Vehicle status data is monitored using on-board sensors, including: Speed ​​sensor: collects the vehicle's current speed data; acceleration sensor: collects the vehicle's acceleration data to determine the vehicle's dynamic changes; load sensor: monitors the vehicle's load status; road condition sensor: detects the type and condition of the road surface; environmental sensor: collects external environment data.

7. The vehicle braking control method of any one of claims 1 to 3 with adaptive control, characterized in that: The control method includes an adaptive algorithm model configured to output corresponding braking parameters based on an input vehicle state.

8. An adaptively controlled vehicle braking control system, characterized in that: The control system includes a vehicle state acquisition module, an adaptive algorithm model, a calculation module, and an execution module; the vehicle state acquisition module is used to monitor the vehicle state, and its output end is connected to the adaptive algorithm model; the adaptive algorithm model adjusts the initial braking parameters based on the vehicle state to obtain adjusted braking parameters; the calculation module calculates the braking torque and braking pressure based on the adjusted braking parameters and converts them into corresponding control signals, and the execution module executes the control signals to achieve braking.

9. The vehicle brake control system with adaptive control as claimed in claim 8, characterized in that: The control system also includes a feedback adjustment module and a feedback parameter acquisition module. The feedback parameter acquisition module is used to collect braking distance and braking stability parameters during vehicle braking. The feedback adjustment module performs feedback fine-tuning on the adjusted braking parameters based on the braking distance and braking stability parameters.

10. The vehicle brake control system with adaptive control according to claim 8 or 9, characterized in that: The vehicle status data collected by the vehicle status acquisition module include: vehicle speed, acceleration, load, road surface condition, and driving environment parameters. The adaptive algorithm module adjusts the output braking parameters based on the vehicle speed, acceleration, load, road surface condition, and driving environment parameters.

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