Air-path coordination in engine with EGR and turbo control
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Solution Overview
Problem
Current air-path control systems in combustion engines face complexity and inefficiency due to multivariable and nonlinear control problems, particularly in managing low-pressure exhaust gas recirculation (EGR) flow paths, which complicates the control of torque and emissions.
Innovation Solution
The implementation of a controller structure that includes an airpath coordinator with model predictive control modules, an EGR estimator, and a turbo speed estimator, which coordinates throttle, EGR, and turbocharger kinetic energy control signals to optimize air flow and EGR flow, using a cost function to minimize deviations from target operating conditions over different time horizons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a low pressure EGR flow path is implemented with multiple control components (throttle, EGR valve, turbocharger), then emissions control and torque optimization are improved, but system complexity and control difficulty increase due to multivariable and nonlinear interactions
Solution Approach 1:
The control system is segmented into three independent model predictive control modules: a reference governor for turbocharger kinetic energy control, a throttle-EGR coordinator for charge flow and EGR flow control, and an EGR estimator. Each module operates with its own cost function and time horizon, dividing the complex multivariable control problem into manageable segments that can be solved independently while maintaining overall system optimization.
Solution Approach 2:
The patent introduces intermediate control variables (turbocharger kinetic energy setpoint, charge flow setpoint, EGR flow setpoint) that act as mediators between the desired torque signal and the actual actuator positions. These intermediaries simplify the nonlinear control relationships by creating a hierarchical control structure where each layer handles specific aspects of the control problem.
2Measurement precision
If additional sensors are added at numerous locations to directly measure pressure and temperature throughout the system, then measurement precision improves, but system cost and complexity increase
Solution Approach 1:
The patent creates virtual copies of physical sensor measurements through estimation algorithms. The EGR estimator and turbo speed estimator use models and available sensor data to generate accurate estimates of EGR flow and turbocharger speed without requiring additional physical sensors. This approach provides the necessary measurement information while avoiding the cost and complexity of extensive sensor installation.
Solution Approach 2:
The patent replaces physical measurement systems (additional pressure and temperature sensors) with computational estimation systems. Model predictive control algorithms substitute for direct mechanical sensing, using mathematical models to infer unmeasured variables from measured ones, thereby reducing hardware requirements while maintaining control accuracy.
3Device complexity
If embedded platforms with memory and processing limitations are used for engine control, then device complexity is reduced, but the ability to implement reliable optimization methods is compromised
Solution Approach 1:
The optimization algorithm is segmented into multiple independent model predictive control modules that can be executed sequentially on resource-constrained embedded platforms. Each module solves a simpler sub-problem with its own cost function and time horizon, reducing the computational burden on any single processing cycle while maintaining the overall optimization objective.
Solution Approach 2:
The patent applies partial optimization at each control level rather than attempting full system optimization simultaneously. The reference governor optimizes turbocharger kinetic energy within its time horizon, the throttle-EGR coordinator optimizes charge and EGR flows within its shorter time horizon, and the EGR estimator provides necessary estimates. This hierarchical partial optimization approach reduces computational requirements while achieving the desired control goals.
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 enables more efficient and reliable control of engine torque and emissions by optimizing air flow and EGR flow, reducing system complexity and improving engine performance.
Implementation Method 1
a compressor having a compressor outlet, the compressor adapted for compressing air into charged air
Implementation Method 2
a charge air cooler configured to cool charged air from the compressor outlet
Implementation Method 3
a turbine positioned to receive exhaust gas from the exhaust manifold
Data Source
AI summary
Systems and controllers providing air-path controls in combustion engines. Some examples may be directed to use in gasoline engines including a turbocharger, whether mechanical-only or including electrical assist) and a low-pressure exhaust gas recirculation flow path. Control signals for a wastegate or variable nozzle turbine are generated from a turbocharger kinetic energy controller.