Adaptive Engine Control Map Hypersurface Optimization
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Solution Overview
Problem
Internal combustion engine control systems face challenges in efficiently managing emissions and adapting to real-time operating conditions due to limited computing power and the complexity of after-treatment systems, which are typically addressed using time-invariant control maps that fail to account for part-to-part variations and unmeasured influences.
Innovation Solution
An internal combustion engine controller with a processor and memory that stores control maps defining hypersurfaces for actuator setpoints, featuring an engine setpoint module for open-loop control and a map updating module that calculates and updates these hypersurfaces based on real-time performance models using sensor data, allowing for optimized control across various operating points without direct actuator control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If time-invariant control maps are used for engine control, then the control system is simple to implement, but the system cannot account for part-to-part variations and unmeasured influences
Solution Approach 1:
The patent transforms static control maps into dynamic adaptive maps that are continuously updated during engine operation. The control map updating module modifies the control maps in real-time based on sensor feedback and performance data, allowing the system to adapt to part-to-part variations and changing operating conditions while maintaining the simplicity of map-based control structure.
Solution Approach 2:
The patent implements a feedback mechanism where sensor data from the engine is continuously fed back to the control map updating module. This feedback loop enables the system to learn from actual engine performance and unmeasured influences, automatically adjusting the control maps to compensate for variations without requiring complex manual recalibration.
2Measurement precision
If multiple different control maps are provided for different operating regimes, then the control accuracy is improved, but the calibration complexity and cost increase
Solution Approach 1:
The patent creates a universal control map structure that serves multiple operating regimes simultaneously. Instead of maintaining separate static maps for different conditions, the system uses a single adaptive control map framework that automatically adjusts its parameters based on operating regime, reducing calibration complexity while maintaining control accuracy across all conditions.
Solution Approach 2:
The patent changes the parameters of existing control maps dynamically rather than creating entirely separate maps for different operating regimes. The control map updating module modifies map parameters in real-time based on operating conditions, allowing the same map structure to accurately control multiple regimes without requiring extensive separate calibration for each condition.
3Adaptability or versatility
If model-based control is implemented to replace control maps, then real-time adaptation is achieved, but significant computational resources are required
Solution Approach 1:
The patent introduces control maps as an intermediary between the simple sensor feedback and complex model-based control. Rather than directly implementing computationally intensive model-based control, the system uses control maps as a mediator that can be gradually updated with learned parameters, achieving real-time adaptation with reduced computational burden compared to full model-based control.
Solution Approach 2:
The patent implements partial model-based control by updating only critical portions of the control maps rather than recalculating entire models in real-time. The control map updating module focuses computational resources on adjusting key parameters and regions that have the greatest impact on performance, achieving sufficient real-time adaptation without requiring excessive computational power.
Data Source
AI summary
An internal combustion engine controller comprising a memory and a processor is provided. The memory is configured to store a plurality of control maps, each control map defining a hypersurface of actuator setpoints for controlling an actuator of the internal combustion engine based on a plurality of input variables to the internal combustion engine controller. The processor comprises an engine setpoint module and a map updating module. The engine setpoint module is configured to output a control signal to each actuator based on a location on the hypersurface of the respective control map defined by the plurality of input variables. The map updating module is configured to calculate an optimised hypersurface for at least one of the control maps. The optimised hypersurface is calculated based on a real-time performance model of the internal combustion engine comprising sensor data from the internal combustion engine and the plurality of input variables. The map updating module further is configured to update the hypersurface of the control map based on the optimised hypersurface. A method of controlling an internal combustion engine is also provided.