Vehicle Yaw Control During Split-Mu Braking Using Slip Angle Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle control systems fail to effectively reduce braking distance in split-mu situations while maintaining stability, as they do not account for driver capabilities and vehicle dynamic behavior, leading to compromised stopping distances and stability.
Innovation Solution
A closed-loop control system that estimates slip angles and adjusts brake pressures based on driver inputs and vehicle dynamics, using feedback loops to optimize yaw motion and brake force distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If open loop control methods with predefined limits on brake force difference are used, then stopping distance is decreased, but driver capabilities and vehicle dynamic behavior are not utilized
Solution Approach 1:
The patent implements a closed-loop control system that continuously monitors vehicle state parameters (lateral acceleration, yaw rate, steering angle) and adjusts brake force distribution in real-time. This feedback mechanism enables the system to adapt to actual driver capabilities and vehicle dynamic behavior, resolving the contradiction by making the control adaptive rather than static.
Solution Approach 2:
The control system dynamically adjusts brake force limits based on real-time vehicle conditions and driver behavior patterns. Rather than using fixed predefined limits, the system modifies control parameters adaptively, allowing optimal performance across different driving scenarios and vehicle configurations.
2Productivity
If brake pressure difference between left and right side is increased to reduce stopping distance, then braking efficiency is improved, but vehicle stability is compromised
Solution Approach 1:
The system uses feedback from lateral acceleration and yaw rate sensors to continuously monitor vehicle stability. When instability is detected, the control algorithm automatically reduces the brake force difference, thereby maintaining stability while still achieving effective braking through optimized force distribution.
Solution Approach 2:
The control system dynamically changes brake force parameters based on real-time vehicle state. By adjusting brake pressure differences adaptively rather than using fixed high differences, the system achieves high braking efficiency while maintaining stability through continuous parameter optimization.
3Reliability
If predetermined brake pressure limits are applied based on worst-case scenarios, then vehicle stability is ensured, but braking distance increases
Solution Approach 1:
The system transitions from static worst-case scenario parameters to dynamic parameter adjustment based on actual vehicle conditions. By continuously adapting brake force limits to real-time conditions, the system achieves both high reliability and short braking distance, eliminating the need for conservative fixed limits.
Solution Approach 2:
The control algorithm dynamically changes brake pressure parameters based on actual vehicle state and driver behavior, rather than using fixed parameters designed for worst-case scenarios. This enables optimal braking performance across all conditions without compromising stability.
4Stability of the object's composition
If select low control strategy is used to minimize yaw-motion, then vehicle stability is maintained, but braking distance becomes longest
Solution Approach 1:
The system dynamically optimizes brake force distribution parameters based on real-time vehicle state and road conditions. Rather than consistently applying the conservative select low strategy, the system adjusts parameters to allow greater brake force on high-adhesion sides when conditions permit, thereby reducing braking distance while maintaining yaw stability through active control.
Solution Approach 2:
The closed-loop system continuously monitors yaw rate and lateral acceleration to detect actual vehicle response. This feedback enables the system to safely increase brake force differences when conditions allow, improving braking efficiency while maintaining stability through real-time adjustment rather than relying on the conservative select low approach.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The disclosure relates to a computer-implemented method and control system (10) for controlling a yaw motion of a vehicle (1) having at least one front and rear axle (2, 3) during braking, comprising, in a first control loop (100), providing a steering control signal (110) to the vehicle by a first controller (101) for controlling a steering behavior of the vehicle according to a driver's command, providing at least one first closed-loop feedback signal (120) indicative of a vehicle motion state to the first controller (101), in a second control loop (200), estimating at least one slip angle (α, β) of the vehicle in an estimation module (201) of a second controller (210) after initiating a braking of the vehicle and generating, in a control module (202) of the second controller (210), an output signal (215) of the second controller (210) based on the estimated slip angle (α, β), controlling at least one braking actuator (41, 42) of the vehicle in accordance with the output signal (215) of the second controller (210), and providing at least one second closed-loop feedback signal (220) indicative of a vehicle motion state to the estimation module (201) of the second controller (210) as an input signal for estimating the at least one slip angle (α, β).