Vehicle State Monitoring for Load Index and Component Life Estimation
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Solution Overview
Problem
Existing state monitoring devices for vehicles fail to accurately estimate the accumulation of load and life of vehicle components due to variations in usage patterns, leading to inconsistent maintenance and lifespan predictions.
Innovation Solution
A state monitoring device that uses a combination of sensors to specify status categories related to vehicle operation and field usage, updating a load index to accurately estimate load accumulation and component lifespan, incorporating machine learning for improved accuracy and maintenance scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single sensor or simple parameter is used to estimate vehicle load accumulation, then the device complexity is reduced, but the measurement precision and reliability of load estimation deteriorates
Solution Approach 1:
The vehicle status is segmented into multiple status categories (e.g., idle, low load, medium load, high load) based on combinations of sensor parameters. Each category represents a discrete operational state, allowing precise load estimation without requiring continuous complex calculations. The status specification section divides the continuous operational space into manageable segments.
Solution Approach 2:
Multiple sensor parameters (engine rotational speed, fuel injection amount, vehicle speed, acceleration) are merged into a single comprehensive status category determination. The status specification section integrates these multiple parameters to specify one or more status categories, achieving accurate load estimation through parameter combination rather than individual parameter analysis.
2Reliability
If detailed operational parameters are collected for each vehicle, then the reliability of life estimation is improved, but the loss of information storage and processing increases
Solution Approach 1:
The essential information for load estimation is extracted from detailed operational parameters by specifying status categories. Instead of storing and processing all raw sensor data, the system extracts the critical status category information that represents the essential operational state. This reduces information storage requirements while maintaining estimation reliability.
Solution Approach 2:
The system transforms continuous operational parameters into discrete status category parameters. By changing the parameter representation from continuous raw values to discrete categorized states, the system reduces data storage requirements and processing complexity while preserving the essential information needed for reliable load accumulation estimation.
3Measurement precision
If status categories are specified based on multiple sensor parameters, then the measurement precision of vehicle status is improved, but the device complexity and calculation requirements increase
Solution Approach 1:
The status categories are determined and prepared in advance based on expected operational conditions. The system pre-defines the mapping between sensor parameter ranges and status categories, so that during actual operation, the calculation unit only needs to compare current parameters against predefined thresholds rather than performing complex real-time analysis. This preliminary preparation reduces online calculation complexity.
Data Source
AI summary
This state monitoring device configured to monitor a current state of a vehicle includes: a storage configured to have stored therein a load index which is an index indicating an accumulation degree of a load having occurred in the vehicle; and a calculation unit configured to receive detection values of a plurality of sensors mounted on the vehicle, and configured to perform a predetermined calculation. The calculation unit includes: a status specification section configured to, by using the detection values of the plurality of sensors, specify, out of a plurality of status categories determined in advance and each indicating a status of use regarding running of the vehicle, one or more of the status categories; and an index update section configured to, on the basis of each specified status category, update the load index stored in the storage.