Vehicle Dynamic Modeling for High-Lateral-Acceleration Path Control
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Solution Overview
Problem
Advanced driving assist systems (ADAS) and autonomous driving features for electric vehicles (EVs) face challenges in accurately predicting and controlling vehicle behavior during high-performance maneuvers, such as sharp cornering, due to limitations in existing vehicle dynamic models that assume constant cornering stiffness, which is not accurate at higher lateral accelerations.
Innovation Solution
The enhanced vehicle dynamic model optimizes cornering stiffness using a sigmoid function and adjusts front and rear steering angles to account for roll steer and compliance steer, based on vehicle testing data, allowing for more precise control and warning indicators during high-performance maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If constant cornering stiffness is assumed in vehicle dynamic models, then model simplicity is maintained, but accuracy deteriorates at higher lateral accelerations
Solution Approach 1:
The patent applies the Dynamics principle by transitioning from a static cornering stiffness assumption to a dynamic model where cornering stiffness varies with lateral acceleration. The sigmoid function C(ay) = C0 / (1 + exp(-k*(ay - ay0))) enables the cornering stiffness to adapt dynamically based on the current lateral acceleration state, improving prediction accuracy during high-performance maneuvers while maintaining computational efficiency through a closed-form solution.
Solution Approach 2:
The patent implements Parameter changes by modifying the cornering stiffness parameter from a constant value to a variable that changes with lateral acceleration. This is achieved through the sigmoid function relationship C(ay), which transforms the cornering stiffness parameter based on the lateral acceleration input, allowing the model to capture nonlinear tire behavior at high lateral accelerations without requiring complex multi-parameter models.
2Device complexity
If roll steer and compliance steer effects are neglected, then steering angle calculation is simplified, but control accuracy deteriorates during high-performance maneuvers
Solution Approach 1:
The patent applies Segmentation by decomposing the total steering angle into distinct components: the kinematic steering angle and the compliance/roll steer correction term. This segmentation allows the system to calculate the primary steering angle using simple kinematics while adding a separate correction term that accounts for roll and compliance effects, thereby improving accuracy without requiring a complete redesign of the steering model.
Solution Approach 2:
The patent implements Partial action by selectively including only the necessary correction terms for roll steer and compliance steer in the steering angle calculation. Rather than modeling all possible steering effects, the patent adds a targeted correction term that addresses the specific high-performance maneuver characteristics, achieving improved accuracy with minimal additional computational complexity.
Data Source
AI summary
Operation and motion control, by a vehicle's ADAS or AD features, is improved in ways suitable to EVs having higher driving and handling performance. The vehicle dynamic model for high rates of lateral acceleration (e.g., sharp cornering or taking curves having a small radius of curvature as faster speeds) is improved by one or more of optimizing time cornering stiffness with a sigmoid function and/or altering front/rear steering angle to account for roll steer and compliance steer, based on vehicle testing. Indicators for lane departure warning or collision warning, evasive steering, or emergency braking are therefore reliably extended to allow higher performance maneuvers.