Lateral Velocity Estimation Fault Detection
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Solution Overview
Problem
Conventional methods for estimating vehicle lateral velocity are complex, redundant, and prone to uncertainties due to road conditions, tire models, and time-varying tire parameters, often relying on additional sensors and constant acceleration residual thresholds, which can lead to bias-type faults.
Innovation Solution
A control module and method that utilize existing vehicle sensors to generate real-time fault flags for lateral velocity estimation, processing acceleration and longitudinal speed data to create thresholds for bias-type and drift-type fault detection, independent of road, wheel torque, tire model, and tire wear information, and confirm flag stability over time frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods use multiple tire models and vehicle type models to estimate lateral velocity, then measurement precision is improved, but device complexity increases and reliability decreases due to road friction uncertainties and time-varying tire parameters
Solution Approach 1:
The patent extracts and eliminates the complex tire models, vehicle type models, and road condition dependencies from the lateral velocity estimation system. By using only acceleration sensor data and longitudinal velocity information, the system removes the disturbing elements (tire parameter uncertainties, road friction variations) while maintaining estimation capability through a simplified physics-based approach.
Solution Approach 2:
The patent replaces expensive, complex modeling approaches with a simple, computationally lightweight estimation method that uses readily available sensor data. The estimation algorithm is designed to be computationally efficient and does not require redundant sensors or complex model calculations, making it suitable for real-time implementation in cost-effective systems.
2Device complexity
If conventional methods employ acceleration based estimations with constant acceleration residual thresholds, then device complexity is reduced, but reliability worsens due to bias-type faults
Solution Approach 1:
The patent introduces dynamic, adaptive thresholds for fault detection that adjust based on operating conditions, replacing the static constant thresholds. The system monitors multiple parameters (lateral acceleration residuals, pneumatic trail, slip angle) and adapts the detection criteria to distinguish between normal vehicle behavior and actual faults, thereby improving reliability without requiring complex additional hardware.
Solution Approach 2:
The patent implements a feedback mechanism where the system continuously monitors estimation residuals and compares them against adaptive thresholds. The fault detection system uses feedback from multiple sensor measurements to dynamically adjust detection sensitivity and generate fault flags only when genuine anomalies are detected, reducing false positives while maintaining simplicity.
3Measurement precision
If additional sensors and road condition sensors are added to improve lateral velocity estimation, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent makes the existing acceleration sensors and longitudinal velocity sensors serve multiple functions: they provide both the primary vehicle control data and the basis for lateral velocity estimation and fault detection. By designing the estimation algorithm to extract lateral velocity information from standard sensors already present in the vehicle, the system achieves multi-functionality without adding dedicated lateral velocity sensors or road condition sensors.
4Reliability
If conventional methods use redundant estimations and measurements to validate lateral velocity, then reliability is improved, but productivity and real-time performance worsen
Solution Approach 1:
The patent performs preliminary fault detection by continuously monitoring multiple parameters (lateral acceleration residuals, pneumatic trail variations, slip angle changes) and comparing them against adaptive thresholds in real-time. The system is prepared with pre-defined detection criteria and adaptive threshold mechanisms that enable immediate fault identification without requiring redundant post-processing estimations or additional validation measurements.
Data Source
AI summary
Methods and systems are provided for an improved system and method for validating vehicle lateral velocity estimation. The provided system and method employ an efficient validation algorithm to detect lateral velocity estimation faults. The method and system are robust to road uncertainties and do not require redundant estimations or measurements. The provided system and method offer a technological solution for real time validation of lateral velocity estimation using already existing vehicle sensors, and are independent of (i) road condition information, (ii) wheel torque information, (iii) tire model information, and (iv) tire wear information.