Engine State Detection Using Road-Adaptive Mapping
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Solution Overview
Problem
Existing state detection systems for internal combustion engines face challenges in accurately detecting variations in combustion state among cylinders, such as misfires or air-fuel ratio imbalances, due to vibrations from uneven road surfaces, which affect the accuracy of crankshaft rotational behavior analysis.
Innovation Solution
A state detection system that utilizes machine learning-based mapping data classified by road surface conditions to differentiate between rotational speed variations caused by combustion state changes and road surface vibrations, allowing for precise detection of misfires or air-fuel ratio imbalances by selecting appropriate mapping data based on road surface state variables.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single detection mapping is used for all road surface conditions, then the device complexity is reduced, but the measurement precision of combustion state variations deteriorates due to road surface vibration interference
Solution Approach 1:
The detection mapping is segmented into multiple mappings, each specialized for specific road surface conditions (e.g., paved road mapping, unpaved road mapping). This segmentation allows each mapping to be optimized for its specific condition, improving detection precision without requiring a single complex universal mapping structure.
Solution Approach 2:
The system dynamically selects and switches between different detection mappings based on the detected road surface condition. The mapping selection is updated in response to changes in road surface state, allowing the system to adapt to varying conditions and maintain high detection precision across different environments.
2Reliability
If road surface vibration effects are not accounted for, then the detection system is simpler, but the reliability of misfire and imbalance detection deteriorates
Solution Approach 1:
The system changes the parameters of the detection mapping based on road surface conditions. Different mappings are selected with different characteristic parameters (such as different frequency ranges or vibration thresholds) that are optimized for specific road surface types, allowing reliable detection while adapting to varying environmental conditions.
Solution Approach 2:
The system incorporates feedback from road surface condition detection to dynamically adjust the detection mapping selection. By continuously monitoring road surface state and updating the mapping selection accordingly, the system maintains high reliability in misfire and imbalance detection across varying road conditions.
Data Source
AI summary
A state detection system for an internal combustion engine is provided. Rotation waveform variables include information on a difference between cylinders in the rotational speed of a crankshaft during periods in which the respective cylinders generate combustion torque. An obtainment process obtains a value of the rotation waveform variables and a value of a road surface state variable based on an output of a sensor that detects a state of the road surface. A selection process selects, from a plurality of types of mapping data stored in the storage device, the mapping data that is associated with the road surface state variable as the detection mapping. A determination process determines whether the engine is in a predetermined operating state based on an output value of the selected detection mapping that takes the rotation waveform variables as inputs.