Virtual Engine Torque Estimation from Cylinder Pressure and Exhaust Heat
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Solution Overview
Problem
Existing systems for estimating engine performance, particularly in internal combustion engines, face challenges in achieving accurate measurements due to limitations of physical sensors, such as inability to measure parameters inside the engine cylinder or in harsh environments, leading to inaccuracies and impracticality in certain areas like turbochargers or exhaust manifolds.
Innovation Solution
A computer-implemented method and system that uses a cylinder combustion model to estimate piston side load and friction, and a convective heat transfer model to estimate engine torque, based on cylinder pressure and exhaust heat transfer values, respectively, to provide more accurate performance estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical sensors are used to measure engine parameters, then measurement capability is provided, but measurement precision and reliability deteriorate due to sensor limitations in harsh environments and inability to measure certain parameters
Solution Approach 1:
The patent creates virtual copies of physical sensors through mathematical models. Instead of placing physical sensors in harsh environments where they fail, the system uses computational models (thermodynamic models, heat transfer models, fluid dynamics models) to create virtual sensor readings that replicate what physical sensors would measure, thereby achieving both measurement capability and reliability
Solution Approach 2:
The patent replaces physical sensing mechanisms with computational modeling approaches. Rather than using mechanical/physical sensors that degrade in harsh environments, the system substitutes mathematical models that compute engine parameters based on available data, eliminating the reliability issues associated with physical sensor deployment in extreme conditions
2Loss of information
If physical sensors are deployed inside cylinders or in turbochargers, then direct measurement capability is achieved, but device complexity and practicality worsen due to harsh physical conditions degrading sensors
Solution Approach 1:
The patent introduces mathematical models as intermediaries between available sensor data and desired internal engine parameters. Instead of directly placing sensors inside cylinders or turbochargers, the system uses thermodynamic models and heat transfer models that compute internal parameters based on measurements from accessible locations, serving as a computational intermediary that bridges the information gap
3Adaptability or versatility
If model-based diagnostics are used to estimate engine performance, then measurement capability is extended to inaccessible areas, but measurement precision deteriorates due to inaccurate results from regression or system identification techniques
Solution Approach 1:
The patent transitions from using regression coefficients and system identification parameters to using fundamental thermodynamic, heat transfer, and fluid dynamics parameters. By changing the basis of the models from empirical correlations to first-principles physics, the system achieves both adaptability to measure inaccessible parameters and improved precision through physically accurate relationships
Solution Approach 2:
The patent replaces empirical diagnostic models (regression analysis, system identification) with physics-based computational models. This substitution replaces data-driven approximations with fundamental scientific principles, thereby extending measurement capability to inaccessible areas while maintaining or improving measurement precision through physically accurate modeling
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy of engine torque estimation and overcomes the limitations of physical sensors by leveraging virtual sensor models to provide precise calculations even in areas where physical sensors are impractical or inaccurate.
Implementation Method 1
receiving, via a cylinder combustion model, a cylinder pressure of a cylinder associated with operation of an internal combustion engine
Implementation Method 2
receiving, via a convective heat transfer model, an exhaust heat transfer value indicative of a cumulative heat transfer from an exhaust manifold
Data Source
AI summary
A system for estimating engine performance is configured to receive, via a cylinder combustion model, a cylinder pressure of a cylinder associated with operation of an internal combustion engine. The system estimates a liner bending moment based at least in part on the cylinder pressure, generates a piston side load associated with the cylinder based at least in part on the liner bending moment, and estimates a piston friction value for a piston associated with the cylinder. The piston friction value may be based at least in part on the cylinder pressure and an engine speed of the internal combustion engine. The system receives, via a convective heat transfer model, an exhaust heat transfer value indicative of a cumulative heat transfer from an exhaust manifold, and estimates an engine torque value based at least in part on the exhaust heat transfer value.