Model-Based Exhaust Control for Lambda Deviation
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Solution Overview
Problem
Existing engine control systems using lambda control for exhaust gas aftertreatment devices, such as three-way catalytic converters, face delays in detecting deviations from the catalytic converter window, leading to delayed corrections and increased pollutant emissions, especially during dynamic operations.
Innovation Solution
A model-based control method with an adaptable pilot control is implemented, which adjusts fuel quantity based on the deviation between measured and modeled lambda values, allowing for early detection and correction of impending departures from the catalytic converter window, thereby reducing pollutant emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a conventional lambda control with setpoint control is used, then the system is simple to operate, but the response time to detect and correct deviations from the catalytic converter window is delayed
Solution Approach 1:
The patent applies preliminary action by using a model-based control that predicts future lambda values and detects impending departures from the catalytic converter window before they actually occur. The control unit continuously compares predicted lambda values with the catalytic converter window boundaries and initiates corrective fuel quantity adjustments in advance, rather than waiting for actual deviations to be detected by sensors.
Solution Approach 2:
The patent introduces an intermediary element - a mathematical model of the exhaust gas system - that mediates between the measured lambda values and the control decisions. This model predicts future system states and allows the control unit to anticipate deviations, effectively acting as an intermediary that provides early warning signals before actual departures occur.
2Measurement precision
If the output-side lambda sensor is used for detection, then the measurement is accurate, but the detection of departures from the catalytic converter window occurs relatively late
Solution Approach 1:
The patent uses preliminary action by predicting future lambda values based on current system state and model parameters. The control unit calculates anticipated lambda values and compares them with catalytic converter window boundaries before actual deviations occur, enabling early detection and corrective action without waiting for sensor feedback from the output side.
Solution Approach 2:
The patent inverts the conventional approach by not waiting for output-side sensor data to detect deviations. Instead, it uses input-side lambda sensor data combined with a system model to predict future states, effectively working backwards from current measurements to anticipate future deviations, thereby inverting the traditional detection sequence.
3Loss of time
If a model-based control with early detection is implemented, then the response time is reduced, but the control system becomes more complex
Solution Approach 1:
The patent applies self-service by using the system's own measured data and a mathematical model to perform self-diagnosis and self-correction. The control unit continuously monitors lambda values, predicts future states using the model, and automatically adjusts fuel quantity without external intervention or complex additional hardware, enabling the system to service itself in real-time.
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting the fuel quantity parameter based on predicted lambda values. The control unit modifies injection parameters in real-time based on model predictions, changing operational parameters proactively to maintain lambda values within the catalytic converter window, thereby reducing correction time without proportionally increasing hardware complexity.
Data Source
AI summary
A method for operating an engine system including an internal combustion engine and an exhaust gas aftertreatment device, including: carrying out a fill level control to control a fill level of the exhaust gas aftertreatment device as a function of a predefined fill level setpoint value; operating a pilot control for the fill level control; and adapting the pilot control as a function of a deviation between a measured lambda value and a modeled lambda value.