Supercharge Your Innovation With Domain-Expert AI Agents!

Automobile anti-lock braking control method and device realized based on neural network algorithm, vehicle and storage medium

A neural network algorithm and anti-lock braking technology, applied in the direction of brakes, etc., can solve problems such as long-time debugging, low accuracy of wheel cylinder pressure control, and inability to quickly apply new models

Inactive Publication Date: 2021-06-08
的卢技术有限公司
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The traditional anti-lock braking system usually realizes the function by collecting the braking data of the real vehicle and manually coding and designing the braking rules, which requires a lot of manpower and material resources to realize the function, and does not have the ability of self-learning
The products of today's mainstream anti-lock braking system companies are accumulated and designed year after year. Quickly apply to new models
[0009] The traditional anti-lock braking system brakes through the "point brake" mode of "brake-release-brake-release..." cycle, which controls the current braking and the length of time for releasing the brake. However, the actual braking force acting on the wheels is determined by the braking pressure on the wheel cylinder, and the braking pressure is controlled through time in disguise. One consequence of this operation is that the actual wheel cylinder pressure control accuracy is not high, resulting in the actual braking process. tire lockup

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Automobile anti-lock braking control method and device realized based on neural network algorithm, vehicle and storage medium
  • Automobile anti-lock braking control method and device realized based on neural network algorithm, vehicle and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0038] figure 1 The "vehicle sensor" is the on-board sensor, which can obtain data such as body speed, wheel speed, acceleration, vehicle forward angle, angular velocity, angular acceleration, etc., and "observation data" is the braking-related data obtained from the sensor. In the data input algorithm, the algorithm gives the corresponding brake control signal, and the "brake actuator" performs pressure regulation and control according to the above signal. "Wheel brake" means that the brake pressure acts on the wheel to achieve braking. The "brake pedal" is the brake activation device. Compared with the architecture diagram of the algorithm work figure 1 , when the algorithm is trained figure 2 With more data collection and algorithm training process, "brake data collection" refers to the data collection during the braking process, which may be different from "observation data", because the training results need to be observed during the training process, and other data m...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides an automobile anti-lock braking control method achieved based on a neural network algorithm. The method comprises the following steps that automobile observation data in the automobile braking / braking process are obtained; the preprocessed observation data are inputted into a neural network algorithm model to obtain a brake pressure value; and according to the brake pressure value, anti-lock brake control is conducted on the vehicle. According to the method, the anti-lock braking strategy is automatically learned from the automobile braking data by using the neural network, the design time of a manual coding anti-lock braking / braking system can be obviously shortened, and the automatic learning mode can be considered more comprehensively compared with manual coding, the learned anti-lock braking strategy can achieve an effect better than that of manual coding; in addition, the control quantity outputted by the algorithm is a brake pressure target value, and compared with a snub control mode of a traditional anti-lock braking system, control accuracy can be improved, and better control is achieved.

Description

technical field [0001] The invention belongs to the field of automobile control, and in particular relates to an automobile anti-lock braking control method, device, vehicle and storage medium based on a neural network algorithm. Background technique [0002] With the development of society, automobiles have been integrated into all aspects of people's daily life, providing great convenience for human production and life. Wet and slippery roads such as waterlogged roads and icy and snowy roads are very common on roads where cars are driving. When a car brakes suddenly on such roads, it is prone to sideslip, and in some extreme cases, violent deflection will occur. When the braking / braking force given by the braking system is too large, the wheels will be locked, causing the driver to lose control of the direction of the car. At this time, it is possible to drive out of the lane or into the reverse lane, and the ability to avoid obstacles will be greatly reduced. When the w...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): B60T8/1761
CPCB60T8/1761B60T8/17616
Inventor 董舒
Owner 的卢技术有限公司
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More