Model Predictive Control for Engine Torque Response
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Solution Overview
Problem
Traditional engine control systems fail to accurately control engine output torque and do not provide rapid responses to control signals, leading to inefficiencies in adjusting torque output among various engine devices.
Innovation Solution
A model predictive control (MPC) system that includes an MPC module and an actuator module, which generates predicted parameters and adjusts actuators based on desired operating conditions, optimizing target values to achieve precise torque control by determining costs and selecting the most effective set of target values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional engine control systems are used, then the system structure is simple, but the response time is slow and torque control accuracy is poor
Solution Approach 1:
The control system is segmented into multiple independent SISO controllers, each responsible for controlling a specific engine device (throttle, fuel injector, spark plug, etc.). This segmentation allows each controller to operate independently and rapidly, improving overall response time while maintaining manageable complexity through modular architecture
Solution Approach 2:
The MPC module serves as a universal coordination layer that manages multiple SISO controllers simultaneously. It generates coordinated control signals for various engine devices based on desired torque output, enabling the system to achieve rapid and accurate torque control without requiring complete system redesign
2Manufacturing precision
If traditional engine control systems are used, then the control system is easy to implement, but the torque control accuracy is insufficient
Solution Approach 1:
The MPC module continuously receives feedback from the engine control system about actual torque output and compares it with the desired torque. Based on this feedback, it dynamically adjusts control signals to multiple engine devices, ensuring accurate torque control while maintaining system coordination
Solution Approach 2:
The system uses pre-calibrated lookup tables that store optimal control parameter combinations for different operating conditions. When torque control is needed, the system quickly retrieves pre-computed values from these tables, enabling rapid and accurate torque adjustment without complex real-time calculations
3Productivity
If multiple SISO controllers are coordinated, then the response speed improves, but the coordination complexity among devices increases
Solution Approach 1:
Multiple SISO controllers are merged under a single MPC module that handles coordination centrally. The MPC module receives the desired torque output as a single input and generates coordinated control signals for all engine devices simultaneously, simplifying the coordination complexity while maintaining rapid response capabilities
Data Source
AI summary
A system according to the principles of the present disclosure includes a model predictive control (MPC) module and an actuator module. The MPC module generates predicted parameters based on a model of a subsystem and a set of possible target values. The MPC module generates a cost for the set of possible target values based on the predicted parameters and at least one of weighting values and references values. The MPC module adjusts the at least one of the weighting values and the reference values based on a desired rate of change in an operating condition of the subsystem. The MPC module selects the set of possible target values from multiple sets of possible target values based on the cost. The actuator module adjusts an actuator of the subsystem based on at least one of the target values.