Motor Vehicle Controller Dynamic Operating Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for analyzing motor vehicle operating situations are limited by focusing on static parameter sets without considering time profiles, leading to incomplete or inaccurate assessments of dynamic conditions.
Innovation Solution
A method that determines a set of time profiles of parameters by analyzing statistical deviations from reference sets, using various data sources including CAN data and external devices, to characterize and predict operating situations, allowing for dynamic analysis and prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a predetermined set of parameters is analyzed at a stationary point in time, then the analysis is simple and quick, but important dynamic parameters and time profiles are not determined
Solution Approach 1:
The system performs preliminary data collection and stores time profiles of parameters in memory before analysis is required. This allows the actual analysis to be performed quickly by comparing stored time profiles against reference patterns, rather than collecting and analyzing raw data in real-time.
Solution Approach 2:
The system transitions from static parameter analysis to dynamic time-profile analysis by continuously recording parameter changes over time. The analysis method evaluates temporal patterns and deviations from reference time profiles, enabling detection of dynamic operating situations and faults that occur during vehicle operation.
2Reliability
If all available sensor data and time profiles are collected and analyzed, then comprehensive operating situation analysis is achieved, but the system complexity and data processing requirements increase
Solution Approach 1:
The system extracts only the essential time profile characteristics and compares them against reference patterns, rather than processing all raw sensor data. The analysis focuses on key temporal patterns and deviations from normal operating profiles, filtering out unnecessary data while maintaining diagnostic accuracy.
Solution Approach 2:
The controller is designed to perform multiple functions: collecting data from various sensors, storing time profiles, comparing against reference patterns, and identifying different types of faults and operating situations using the same basic analysis framework. This multi-functional approach reduces overall system complexity compared to having separate specialized systems for each function.
Data Source
Figure 1
Figure 2~3
AI summary
Method (1) for analyzing an operating situation of a motor vehicle (2), comprising: determining (32) a set of temporal profiles of parameters (5), wherein the set of temporal profiles of parameters (5) characterizes an operating situation of the motor vehicle (2), for analyzing the operating situation of the motor vehicle (2) by determining a statistical deviation of the set of temporal profiles of parameters (5) from at least one reference set of temporal reference profiles of parameters (7).