Inlet Air Dynamics State Characterization via MAP Cycle Difference
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Solution Overview
Problem
Conventional methods for characterizing engine inlet air dynamics as steady-state or transient are prone to signal noise and delayed detection, leading to inaccurate cylinder inlet air rate estimation, especially during transient conditions.
Innovation Solution
A control system that estimates future firing event manifold absolute pressure and determines MAP cycle differences to characterize the inlet air dynamics state, using a combination of current and previous MAP, MAF, and moving averages to differentiate between steady-state and transient conditions, enabling accurate cylinder air rate estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single engine parameter (e.g., MAP) is used to detect steady-state entry and exit, then the detection method is simple, but signal noise results in inaccurate state detection
Solution Approach 1:
The patent divides the single-parameter detection approach into multiple independent detection modules, each monitoring different parameters (MAP, MAF, throttle position). This segmentation allows each parameter to be evaluated separately, reducing the impact of noise on any single measurement while maintaining overall detection accuracy.
Solution Approach 2:
The patent merges multiple parameter detections (MAP, MAF, throttle position) into a unified steady-state determination system. By combining these independent parameter assessments, the system achieves more reliable state detection that is less susceptible to noise in any single parameter, thereby improving measurement precision without excessive complexity.
2Measurement precision
If detailed analyses are performed to reduce noise sensitivity, then state detection becomes more accurate, but transition detection is delayed
Solution Approach 1:
The patent implements preliminary monitoring of multiple parameters simultaneously, preparing the detection system in advance by continuously tracking MAP, MAF, and throttle position. This preliminary action allows the system to quickly determine steady-state conditions without requiring time-consuming detailed analyses after transitions occur, thereby reducing detection delay while maintaining accuracy.
Solution Approach 2:
The patent enables the system to skip lengthy detailed analysis steps by using pre-established thresholds and relationships between multiple parameters. When parameter combinations clearly indicate steady-state or transient conditions, the system rapidly determines the state without performing exhaustive noise-filtering analyses, thus reducing transition detection time while preserving accuracy.
3Device complexity
If MAF sensor is used for cylinder air rate during transient conditions, then the measurement is simple, but accuracy is degraded due to manifold filling/depletion time constant and sensor lag
Solution Approach 1:
The patent introduces multiple intermediate parameters (MAP, throttle position, MAF) as mediators between the direct MAF measurement and the final cylinder air rate calculation. These intermediaries provide additional information about manifold conditions and allow the system to compensate for MAF sensor lag and manifold filling/depletion effects, improving accuracy without significantly increasing measurement complexity.
Solution Approach 2:
The patent replaces reliance on the mechanical MAF sensor alone with a computational model that uses multiple measured parameters (MAP, MAF, throttle position) to calculate cylinder air rate. This substitution of direct mechanical measurement with a multi-parameter computational approach compensates for sensor limitations and transient effects, improving precision while maintaining practical system complexity.
Data Source
AI summary
An inlet air dynamics (IAD) characterization control system for an internal combustion engine includes a first module that estimates a future firing event manifold absolute pressure (MAP) and a second module that determines a MAP cycle difference based on the future firing event MAP and a previous cycle MAP. A third module characterizes an IAD state based on the MAP cycle difference.