Fusion of Chassis Sensor Data with Vehicle Dynamics
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Solution Overview
Problem
Existing methods for processing sensor data in vehicles do not effectively combine and enhance the information content from different sensor types, such as chassis and vehicle dynamics sensors, leading to limitations in accuracy and reliability, especially in environments without GPS signals.
Innovation Solution
A method that filters and combines vehicle dynamics data and chassis sensor data, including position, speed, and acceleration data, using techniques like Kalman filters and particle filters to increase information content, and incorporates ride height and body acceleration sensors to improve vertical dynamics data, allowing for enhanced data validation and error correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If chassis sensor data and vehicle dynamics data are processed separately, then each sensor system operates independently, but the information content and accuracy of vehicle position and vertical dynamics data are limited
Solution Approach 1:
The patent combines chassis sensor data (ride height sensors, body acceleration sensors) with vehicle dynamics sensor data (inertial sensors) into a unified processing system. This merging allows the system to leverage complementary information from both sensor types, increasing the overall information content about vehicle position and vertical dynamics while resolving the limitation of separate processing
2Reliability
If GPS signals are used for vehicle localization, then absolute position data can be obtained, but the system fails in environments without GPS signals such as multi-storey car parks or underground car parks
Solution Approach 1:
The patent introduces an intermediary system that uses chassis sensor data (particularly ride height sensors) to bridge the gap between GPS-based absolute positioning and inertial sensor-based relative positioning. This intermediary approach allows the system to maintain localization capability in GPS-denied environments by using the chassis sensors to validate and supplement inertial navigation data
Solution Approach 2:
The system prepares for GPS signal loss by maintaining chassis sensor data processing capabilities that can independently provide position information. This prior cushioning ensures that when GPS signals are unavailable, the system already has the necessary sensor fusion infrastructure in place to continue operating without interruption
3Measurement precision
If ride height sensors are used to detect vertical position, then information about vehicle position over roadway can be obtained, but errors in metrological acquisition can occur
Solution Approach 1:
The patent implements a feedback mechanism where chassis sensor data (ride height and body acceleration) is continuously compared with vehicle dynamics sensor data. This feedback loop allows the system to detect discrepancies and errors in real-time, validating the accuracy of vertical position measurements and correcting errors through data fusion
4Speed
If body acceleration sensors are used to detect vertical movements, then active chassis response can be enabled, but the earth's gravity field compensation needs improvement
Solution Approach 1:
The patent merges body acceleration sensor data with inertial sensor data to simultaneously achieve fast response speeds and accurate gravity field compensation. By combining these sensor types, the system leverages the high-speed response capability of body acceleration sensors while using inertial sensors to provide accurate reference data for gravity field compensation
Data Source
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AI summary
The invention relates to a method for processing sensor data (8, 16, 26, 28) in a vehicle (2), said method comprising: - detection (14, 22, 24) of vehicle dynamics data (16) and chassis sensor data (26, 28) of the vehicle (2), - filtering (30) of the vehicle dynamics data (16) or the chassis sensor data (26, 28) on the basis of the chassis sensor data (26, 28) or the vehicle dynamics data (16).