ADAS Sensor Dimensional Control for Working Vehicle Misalignment
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Solution Overview
Problem
Current working vehicles face challenges in achieving robust and cost-effective dimensional control of advanced-driver assistance systems (ADAS) due to misalignment issues caused by suspension load variation, body variation, internal squint, and misalignment of the field of view, leading to impaired functionality, failed calibrations, and increased financial costs.
Innovation Solution
A system and method implementing a tolerance stack-up methodology and statistical analysis to evaluate and optimize the dimensional variation of ADAS sensors, using a one-dimensional tolerance stack-up tool and DPM calculator to assess and adjust sensor integration, ensuring compliance with misalignment limits and reducing calibration complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If strict dimensional control is implemented for sensory systems, then misalignment limits are satisfied and functionality is ensured, but manufacturing complexity and calibration costs increase significantly
Solution Approach 1:
The patent performs dimensional variation analysis and tolerance stack-up calculations before actual sensor installation and calibration. By predicting misalignment risks in advance using statistical methods and tolerance analysis, the system identifies critical sensors and installation locations that require special attention, allowing preventive measures to be taken rather than reacting to calibration failures after installation.
Solution Approach 2:
The patent divides the dimensional control process into separate analytical components: suspension load variation analysis, body variation analysis, internal squint analysis, and measurement system misalignment analysis. Each contributor is evaluated independently and then combined using tolerance stack-up methodology, allowing targeted control measures to be applied to specific sources of variation rather than implementing blanket strict control across all parameters.
2Measurement precision
If multiple types of metrology equipment are deployed for calibration, then measurement precision improves, but device complexity and costs increase
Solution Approach 1:
The patent develops a universal analytical framework using tolerance stack-up methodology and statistical analysis that can evaluate all sources of dimensional variation (suspension, body, internal squint, measurement system) through a single integrated approach. This multi-functional analysis system replaces the need for multiple specialized measurement equipment by providing a comprehensive predictive model that works across different sensor types and installation scenarios.
Solution Approach 2:
The patent replaces physical measurement and calibration equipment with a computational analysis system. Instead of using multiple types of metrology equipment to physically measure and adjust sensors, the system uses tolerance stack-up calculations and statistical analysis to predict misalignment and guide installation procedures, substituting mechanical measurement systems with information-based predictive modeling.
3Manufacturing precision
If sequential calibration of each sensor is performed, then individual sensor accuracy is ensured, but calibration time and productivity decrease
Solution Approach 1:
The patent performs tolerance stack-up analysis and identifies critical sensors that have the greatest impact on overall system performance before calibration begins. By predicting which sensors are most sensitive to dimensional variations, the system allows non-critical sensors to be calibrated more quickly or with less precision, while focusing detailed calibration efforts only on the identified critical sensors, thereby reducing overall calibration time while maintaining necessary accuracy.
Data Source
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AI summary
System (10) for dimensional control of a vehicular system (3) of a working vehicle (2); the vehicular system (3) comprises a sensory system (4) configured to output data for assisting a driver in driving the working vehicle (2). The system (10) comprises electronic processing resources configured to: acquire and process (20-24) the data outputted by the sensory system (4) to determine the occurrence of possible misalignments in the sensory system (4) and the design capability of the sensory system (4) of the vehicular system (3); determine (23-25) optimization parameters relative to an optimized design of the sensory system (4) based on the data outputted by the sensory system (4), the occurrence of possible misalignments in the sensory system (4) and the design capability of the sensory system (4); and output (26) a report indicative of the optimization and the calibration capability of the sensory system (4) of the vehicular system (3) for implementing any optimization of said sensory system (4) based on the optimization parameters, the occurrence of possible misalignments in the sensory system (4) and the design capability of the sensory system (4) .