Engine Actuator Control via Model Predictive Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional engine control systems fail to accurately control engine output torque and do not provide rapid responses to control signals, nor do they coordinate torque control among various devices effectively, leading to suboptimal fuel efficiency and emissions management.
Innovation Solution
A model predictive control (MPC) module is used to generate and optimize target actuator values for engine actuators, predicting operating parameters such as emissions levels and exhaust system parameters, and selecting the best set of values based on cost analysis while ensuring constraint satisfaction, thereby coordinating the control of actuators that affect combustion and emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional engine control systems are used to control engine output torque, then the control system is simple, but the torque control accuracy is insufficient and response speed is slow
Solution Approach 1:
The control system is segmented into multiple independent controllers, each responsible for controlling a specific actuator (throttle valve, swirl flap, intake/exhaust valve phasers, wastegate, EGR valves, spark timing, fueling). This segmentation allows each controller to independently optimize its control algorithm for maximum torque control accuracy without complicating the overall system architecture unduly.
Solution Approach 2:
The system performs preliminary determination of target values for all actuators based on a requested amount of torque before actual engine operation. This pre-calculation of optimal actuator positions and parameters enables rapid response when torque demands change, improving both accuracy and response speed without requiring complex real-time control algorithms.
2Speed
If traditional engine control systems are used, then the system structure is simple, but the response speed to control signals is slow
Solution Approach 1:
The system pre-determines target values for all actuators based on the requested torque before engine operation begins. This preliminary calculation enables the system to respond immediately to torque demands without complex real-time computation, achieving fast response speed while maintaining relatively simple control system architecture.
Solution Approach 2:
The system continuously monitors actual engine torque output and compares it with the requested torque, using this feedback to adjust actuator positions in real-time. This feedback mechanism ensures rapid response to control signals while maintaining system simplicity through straightforward control logic.
3Reliability
If traditional engine control systems are used, then the control architecture is simple, but the coordination among various actuators is poor
Solution Approach 1:
The control system is divided into multiple independent controllers, each dedicated to a specific actuator (throttle valve, swirl flap, valve phasers, wastegate, EGR valves, spark timing, fueling). This segmentation enables each controller to independently optimize its control strategy while maintaining overall system coordination through shared torque targets, improving reliability without excessive complexity.
Solution Approach 2:
The control system uses a universal approach where all actuators are controlled based on a common requested torque value. Each actuator controller receives the same torque demand and independently determines its optimal setting, creating a multi-functional control architecture that coordinates all actuators effectively while maintaining relative simplicity.
4Loss of energy
If actuator values are not optimized, then the control system is simple, but fuel efficiency is suboptimal and emissions are not well managed
Solution Approach 1:
The system optimizes fuel efficiency and emissions by dynamically adjusting multiple parameters including throttle valve opening, swirl flap position, intake/exhaust valve timing, wastegate opening, EGR valve positions, spark timing, and fueling rates. These parameter changes are coordinated based on operating conditions to maximize fuel efficiency while maintaining relatively simple control logic through rule-based adjustments.
Data Source
AI summary
A system according to the present disclosure includes a model predictive control (MPC) module and an actuator module. The MPC module generates a set of possible target values for an actuator of an engine and predicts an operating parameter for the set of possible target values. The predicted operating parameter includes an emission level and/or an operating parameter of an exhaust system. The MPC module determines a cost for the set of possible target values and selects the set of possible target values from multiple sets of possible target values based on the cost. The MPC module determines whether the predicted operating parameter for the selected set satisfies a constraint and sets target values to the possible target values of the selected set when the predicted operating parameter satisfies the constraint. The actuator module controls an actuator of an engine based on at least one of the target values.