Crankcase Ventilation Fault Detection via Pressure Modeling
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Solution Overview
Problem
Existing methods for diagnosing crankcase ventilation systems in internal combustion engines fail to accurately differentiate between blockages and disconnections in the ventilation line, leading to inefficiencies and potential emissions, as they often require additional components like switching valves or lambda sensors and cannot quickly detect faults without comparing multiple idling phases.
Innovation Solution
A method that compares measured intake manifold pressure with a modeled pressure using acquired operating variables and a crankcase model, determining if the connecting line between the crankcase and intake manifold is blocked or disconnected by analyzing pressure changes during negative load conditions, without needing additional components like switching valves or lambda sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional components like switching valves or lambda sensors are used for fault detection, then diagnostic accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The control unit utilizes existing sensor data (intake manifold pressure, operating variables) that are already present in the engine management system to perform self-diagnosis of the crankcase ventilation system. No additional sensors or switching valves are required, as the system serves its own diagnostic needs using readily available information.
Solution Approach 2:
The control unit performs multiple functions: it manages normal engine operation and simultaneously conducts diagnostic checks of the crankcase ventilation system. The same control unit and existing sensors are used for both primary engine control and secondary diagnostic purposes, eliminating the need for dedicated diagnostic components.
2Reliability
If multiple idling phases are compared for fault detection, then diagnostic reliability is improved, but diagnostic time increases
Solution Approach 1:
The diagnostic method uses a crankcase model that predicts expected pressure values based on current operating variables. By comparing measured pressure against pre-calculated model values in real-time, the system can detect faults immediately without needing to accumulate data across multiple idling phases, thus maintaining reliability while reducing diagnostic time.
Solution Approach 2:
The system continuously compares measured intake manifold pressure with model-predicted pressure values and uses this feedback to detect faults. The control unit monitors the deviation between actual and expected pressure, and when the deviation exceeds a threshold, a fault is detected. This continuous feedback mechanism enables rapid fault detection without requiring multiple measurement cycles.
Data Source
AI summary
Various embodiments may include a method for checking the plausibility of the functionality of a crankcase ventilation system of an internal combustion engine, wherein crankcase ventilation system has a crankcase, an intake tract equipped with an intake manifold, and a connecting line arranged between the crankcase and the intake manifold, the method comprising: detecting an occurrence of a negative load change; in response, comparing a measured intake manifold pressure with a modelled intake manifold pressure using acquired operating variables of the internal combustion engine and of a crankcase model; and determining on the basis of the comparison result whether the connecting line arranged between the crankcase and the intake manifold becomes blocked or drops out.