Vehicle Braking Control for Split-Friction Road Surfaces
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Solution Overview
Problem
Existing automated emergency braking systems (AEBS) struggle to accurately calculate braking target values due to variations in road surface friction coefficients, leading to potential collisions and oversteer issues when dealing with different friction coefficients between left and right wheels.
Innovation Solution
An apparatus and method for controlling vehicle braking force using sensors and deep learning algorithms to determine the road surface state for each wheel, allowing for differential braking forces to be applied based on the specific road conditions encountered by each wheel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed TTC threshold and uniform braking force are applied, then the system is simple to operate, but collision avoidance fails when road surface friction coefficients vary
Solution Approach 1:
The patent applies different braking forces to left and right wheels based on their respective road surface friction coefficients. The controller independently determines the friction coefficient for each wheel and calculates separate braking target values, ensuring each wheel operates optimally for its local road conditions rather than applying uniform braking across all wheels.
Solution Approach 2:
The system dynamically adjusts braking forces based on real-time detection of road surface conditions. By continuously monitoring wheel friction coefficients and adjusting braking target values accordingly, the system transitions from static fixed-threshold braking to dynamic adaptive braking that responds to changing environmental conditions.
2Stability of the object's composition
If emergency braking is performed with the same braking force on both sides, then the control system is simple, but oversteer occurs when left and right road surface friction coefficients differ
Solution Approach 1:
The patent implements differential braking where the left and right wheels receive different braking forces based on their respective friction coefficients. When one side encounters lower friction (e.g., ice, water, pothole), the system reduces braking force on that side to prevent oversteer and maintain vehicle stability.
Solution Approach 2:
The system uses feedback from wheel speed sensors and friction coefficient detection to continuously monitor vehicle behavior and road conditions. This feedback loop enables the controller to adjust braking forces dynamically, preventing oversteer by detecting imbalances between left and right wheel deceleration and correcting them in real-time.
3Reliability
If braking target values are calculated based on asphalt road friction coefficients, then the calculation method is simple, but braking distance increases on roads with lower friction coefficients
Solution Approach 1:
The system uses the vehicle's own wheel speed data and motor current information to self-determine road surface friction coefficients without requiring external sensors or manual input. The friction coefficient is calculated based on the relationship between motor current, wheel acceleration, and known vehicle parameters, enabling the system to adapt to different road surfaces using internally available data.
Solution Approach 2:
The patent changes the braking control parameter from fixed friction coefficient assumptions to dynamically calculated friction coefficients based on actual wheel behavior. By deriving friction coefficients from real-time wheel speed and motor current data, the system adapts braking target values to match actual road conditions, whether asphalt, wet pavement, ice, or other surfaces.
Data Source
AI summary
An apparatus for controlling a braking force of a vehicle is provided. The apparatus includes a sensor device that obtains information about an image in front of the vehicle and driving information of the vehicle and a controller that determines a road surface state including a left road surface state and a right road surface state based on the information about the image and the driving information and controls a braking force of left wheels of the vehicle and a braking force of right wheels of the vehicle respectively based on the left road surface state and the right road surface state of the vehicle.