Vehicle Motion Control With MPC Actuator Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing motion control systems for vehicles with overactuated systems fail to achieve a global optimum due to separate driving dynamics controllers and simple, rule-based actuator allocations, leading to inefficiencies and suboptimal utilization of actuators.
Innovation Solution
A method for controlling vehicle wheel actuators using model-based predictive control, incorporating dynamic tire forces and wheel steering angles, with optimization-based allocation algorithms to coordinate actuators and account for various factors such as road conditions, passenger comfort, safety, and energy efficiency, ensuring coordinated actuator operation and optimal utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If separate driving dynamics controllers and simple rule-based actuator allocations are used, then the system structure is simple and ease of operation is maintained, but the actuator utilization is suboptimal and energy efficiency deteriorates
Solution Approach 1:
The patent combines the driving dynamics controller and actuator allocation into a single integrated motion control unit. This merging allows the system to optimize actuator utilization and energy efficiency through unified control algorithms while maintaining a manageable system structure through modular architecture.
Solution Approach 2:
The patent implements dynamic actuator allocation that continuously adapts to changing vehicle conditions, driver inputs, and road characteristics. This dynamic approach replaces static rule-based allocation, enabling optimal energy efficiency while maintaining ease of operation through automated adaptation.
2Device complexity
If separate driving dynamics controllers and simple rule-based actuator allocations are used, then the system complexity is reduced, but the actuator coordination and global optimization capability deteriorate
Solution Approach 1:
By merging the controller and allocation functions into one integrated unit, the patent improves actuator coordination and reliability through unified decision-making. The modular architecture maintains acceptable system complexity by organizing the integrated functions into manageable components.
Solution Approach 2:
The integrated motion control unit continuously monitors actuator states, vehicle dynamics, and road conditions to coordinate actuators optimally. This feedback mechanism enhances reliability by ensuring all actuators work together harmoniously while managing complexity through systematic information processing.
3Use of energy by moving object
If model-based predictive control with optimization algorithms is implemented, then energy efficiency and actuator utilization are improved, but the computational complexity and device complexity increase
Solution Approach 1:
The patent employs dynamic optimization algorithms that adapt computational effort to driving conditions. During normal driving, simpler models are used to reduce computational load, while more complex models engage only when needed for optimal energy efficiency, balancing performance with complexity.
Solution Approach 2:
The system changes computational parameters such as prediction horizon, model fidelity, and optimization constraints based on driving situation, vehicle state, and available computational resources. This allows the patent to achieve energy efficiency improvements while managing device complexity through adaptive parameter adjustment.
4Productivity
If continuous forecasting and advanced control methods are used, then the time response and productivity are improved, but the measurement precision requirements and device complexity increase
Solution Approach 1:
The patent uses continuous forecasting to predict future vehicle states and road conditions in advance, enabling proactive control decisions that improve time response and productivity. This preliminary action approach reduces the need for ultra-precise real-time measurements by anticipating future states.
Solution Approach 2:
The system employs feedback mechanisms that continuously compare predicted states with actual measurements, adjusting control actions to maintain accuracy. This feedback loop allows the patent to achieve fast response times while managing measurement precision requirements through continuous correction.
Data Source
AI summary
A method for controlling actuators acting on vehicle wheels of a motor vehicle comprisesascertaining a force to be brought about on a reference point of the motor vehicle on the basis of driver specifications,ascertaining wheel forces to be brought about on the vehicle wheels to implement the force to be brought about on the reference point of the motor vehicle by means of a first dynamic allocation by model-based predictive control (MPC),ascertaining setpoint values for wheel parameters from the ascertained wheel forces, andactuating the actuators of the motor vehicle so as to implement the setpoint values of the wheel parameters.