Engine Control System MPC Transition Strategy
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Solution Overview
Problem
Traditional engine control systems for internal combustion engines lack accuracy in controlling engine output torque and fail to provide rapid responses to control signals, as well as coordinate torque control among various devices effectively.
Innovation Solution
An engine control system that employs a model predictive control (MPC) module to generate target values for engine actuators, determining costs based on the difference between predicted engine output torque and requested torque, and transitions between MPC and non-MPC control methods to maintain system stability and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional engine control systems are used, then the system structure is simple, but the torque control accuracy is insufficient and response speed is slow
Solution Approach 1:
The control system is divided into multiple independent control modules (throttle control module, spark timing control module, fuel injection control module, EGR control module) that can operate autonomously or in coordination. Each module has dedicated processors and control algorithms, enabling precise torque control while maintaining modular system architecture that manages complexity.
Solution Approach 2:
The system dynamically selects between different control modes (open-loop, closed-loop, coordinated control) based on operating conditions and control requirements. The coordination level between modules can be adjusted in real-time, allowing the system to adapt its complexity to match the precision requirements of different operating scenarios.
2Speed
If traditional engine control systems are used, then the device complexity is low, but the response speed to control signals is slow
Solution Approach 1:
By segmenting the control system into dedicated modules with specialized processors, each module can independently process control signals and execute actions without waiting for sequential processing by other modules. This parallel architecture significantly reduces response time while the modular structure keeps system complexity manageable.
Solution Approach 2:
The control modules continuously monitor engine parameters and pre-calculate optimal control actions based on predicted operating conditions. When control signals are received, the modules can immediately execute pre-prepared control strategies, reducing the effective response time without requiring complex real-time computation.
3Adaptability or versatility
If traditional engine control systems are used, then the control coordination among devices is poor, but the system is easier to operate
Solution Approach 1:
The control modules are merged into an integrated system with a central coordination mechanism that manages interactions between throttle, spark timing, fuel injection, and EGR controls. This unified approach enables sophisticated coordination for optimal torque control while the system automatically handles the complexity, making operation straightforward for users.
Solution Approach 2:
The system implements multi-loop feedback mechanisms where each control module monitors its own performance and the performance of other modules. This feedback enables automatic coordination and adjustment of control strategies to achieve desired torque output, with the system self-regulating without requiring complex manual intervention.
Data Source
AI summary
An engine control system for a vehicle may include a sequence determination module that generates a first set of possible MPC target values and a second set of possible MPC target values. A cost module determines a first cost for the first set of possible MPC target values and a second cost for the second set of possible MPC target values. A selection module that selects MPC target values from one of the first and second sets of possible MPC target values based on the first and second costs. A transition module that receives the MPC target values, compares the MPC target values with a plurality of previous control requests, and selects a set of target values ranging from the previous control requests to the MPC target values that control a plurality of engine functions.