Active Air Flap Failure Detection via Cooling Water Temperature Variation
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Solution Overview
Problem
The existing active air flap system struggles to distinguish between freezing and failure accurately, leading to frequent false alerts and reduced reliability, which affects driver confidence and increases maintenance costs.
Innovation Solution
A method that optimizes the control logic by monitoring the temperature variation of engine-cooling water, voltage differences, and operational times of the air flap, using reference data maps to differentiate between freezing and failure, thereby minimizing unnecessary failure alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the conventional control logic uses only TAM temperature to determine freezing, then the diagnosis is simple, but the measurement precision is poor leading to excessive error range (±10°C) and inability to precisely distinguish freezing from failure
Solution Approach 1:
The diagnosis method is segmented into multiple independent detection dimensions: TAM temperature threshold check, temperature variation rate monitoring, and time-based state transition tracking. Each segment focuses on a specific aspect of flap behavior, allowing comprehensive analysis while maintaining individual simplicity.
Solution Approach 2:
The system transitions from single-dimension temperature checking to multi-dimensional diagnosis by adding time dimension (temperature variation over time) and state transition dimension (open/closed state changes). This dimensional expansion enables precise differentiation between freezing and failure without excessive complexity.
2Reliability
If the system generates failure alerts for all non-openable states, then reliability monitoring is improved, but false alerts increase reducing driver confidence and increasing maintenance costs
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring temperature variation rates and comparing them against reference values. The diagnosis result feeds back into the alert generation logic, allowing the system to adapt its alerting behavior based on the detected pattern, thereby reducing false alerts while maintaining reliable failure detection.
Solution Approach 2:
The system performs preliminary diagnosis actions by checking temperature variation trends and state transition patterns before generating failure alerts. This preliminary assessment filters out transient conditions like freezing that will resolve naturally, preventing premature or false alert generation.
3Object-generated harmful factors
If the active air flap range of application is reduced, then false alerts are minimized, but the versatility and fuel efficiency benefits are lost
Solution Approach 1:
The system dynamically adjusts diagnostic parameters such as temperature variation thresholds and reference values based on operating conditions. This parameter adaptation allows the system to maintain high accuracy across diverse applications and environments, preserving versatility while minimizing false alerts through context-aware diagnosis.
Data Source
AI summary
A method of determining a failure of an active air flap, including determining whether or not an active air flap is in a non-openable state, if the active air flap is in the non-openable state, continuously checking a variation of the temperature of engine-cooling water, and if the variation is below a reference variation, interrupting the generation of failure-alert, and if the variation of the temperature of engine-cooling water is above the reference variation, processing whether to generate the failure-alert such that if the time taken to reach the variation is above a reference temperature time, interrupting the generation of failure-alert, and if the time is below the reference temperature time, generating the failure-alert.