Vehicle Controller Crosswind Compensation via Steering and Suspension
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Solution Overview
Problem
Crosswind conditions pose a challenge for vehicle control, requiring drivers to make complex steering and throttle adjustments, leading to increased workload and discomfort, as existing systems struggle to effectively correct for these conditions.
Innovation Solution
A vehicle controller estimates crosswind using driver steering inputs and crosswind disturbance inputs, and when the estimated crosswind exceeds a threshold, it automatically corrects the condition by adjusting the steering angle and/or suspension stiffness to reduce driver workload and improve comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the driver manually corrects for crosswind conditions using steering and throttle inputs, then the vehicle can maintain desired heading and speed, but the driver experiences increased workload and discomfort
Solution Approach 1:
The vehicle control system automatically detects crosswind conditions and applies corrective steering and suspension adjustments without requiring driver intervention. The system monitors vehicle motion parameters, estimates crosswind disturbance, and autonomously compensates for it by adjusting steering angle and suspension stiffness, allowing the vehicle to correct its own course while maintaining driver comfort.
Solution Approach 2:
The system continuously monitors vehicle motion parameters (lateral acceleration, yaw rate, steering angle) and uses this feedback to estimate crosswind disturbance in real-time. Based on the estimated crosswind, the control system dynamically adjusts steering and suspension parameters, creating a closed-loop control system that automatically compensates for crosswind effects while reducing driver workload.
2Ease of operation
If the system automatically corrects for crosswind conditions, then driver workload is reduced, but the system complexity increases
Solution Approach 1:
The vehicle controller integrates multiple functions into a single control unit that can detect crosswind conditions, estimate disturbance parameters, calculate corrective actions, and control both steering and suspension systems. This multi-functional approach consolidates what would otherwise require separate systems, reducing overall complexity while providing comprehensive automatic crosswind compensation.
Solution Approach 2:
The system combines crosswind detection, disturbance estimation, and corrective control into a unified control algorithm that operates within the existing vehicle controller. By merging these functions and leveraging existing sensors and actuators, the system achieves automatic crosswind compensation without requiring entirely new hardware, thus limiting the increase in system complexity.
3Measurement precision
If advanced estimation methods like recursive-least-squares are used to improve crosswind detection accuracy, then sensitivity and accuracy increase, but computational requirements increase
Solution Approach 1:
The system applies recursive-least-squares estimation selectively based on detected crosswind conditions. The advanced estimation algorithm is activated when crosswind disturbance exceeds a threshold, providing high accuracy when needed. During normal conditions without significant crosswind, the system uses simpler detection methods, reducing computational energy consumption while maintaining sufficient accuracy for the operational context.
Data Source
AI summary
A device may estimate crosswind by a vehicle controller according to driver steering inputs indicative of driver intention and crosswind disturbance inputs indicative of a potential crosswind condition. The device may, if the estimated crosswind exceeds a predetermined threshold, utilize the vehicle controller to correct the crosswind condition to reduce vehicle control demand on the driver, the automatic correction including at least one of a steering angle adjustment and suspension stiffness adjustment.