Vehicle Motion Control With MPC-Based Wheel Force Allocation
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Solution Overview
Problem
Existing motion control systems for vehicles do not fully exploit the potential of available actuators due to suboptimal allocation of control variables, leading to inefficiencies in energy consumption, safety, and driving dynamics.
Innovation Solution
A method for controlling vehicle wheel actuators using model-based predictive control with inverse dynamics and dynamic allocation, incorporating continuous forecasting and optimization-based algorithms to coordinate longitudinal and lateral dynamics within physical limits, considering factors like actuator performance, road conditions, and passenger comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static, direct allocation of control variables is used, then device complexity is reduced, but actuator utilization efficiency deteriorates
Solution Approach 1:
The patent implements dynamic allocation of control variables to actuators based on real-time vehicle state and actuator capabilities. The control system continuously optimizes the distribution of control commands to multiple actuators (steering, braking, drive, dampers) according to current operating conditions, enabling adaptive utilization of available actuators rather than static assignment. This dynamic approach maximizes actuator effectiveness while maintaining coordinated vehicle control.
2Productivity
If model-based predictive control with dynamic allocation is implemented, then actuator utilization efficiency is improved, but device complexity increases
Solution Approach 1:
The control system performs predictive optimization by forecasting future vehicle states and actuator requirements. Model-based predictive control calculates optimal actuator allocation in advance based on predicted vehicle dynamics and constraints, allowing the system to prepare control commands that maximize actuator utilization while considering future operating conditions. This preliminary action enables proactive optimization rather than reactive adjustment.
Solution Approach 2:
The patent implements closed-loop feedback control where the actual vehicle response is continuously measured and compared with predicted behavior. The feedback information is used to update the predictive model and adjust actuator allocation dynamically. This feedback mechanism ensures that the complex control system adapts to real-world variations and maintains optimal actuator utilization despite uncertainties in vehicle dynamics or external disturbances.
3Reliability
If centralized control of all actuators is implemented, then driving dynamics are improved, but device complexity increases
Solution Approach 1:
The patent segments the control system into hierarchical levels with a centralized motion control unit coordinating multiple semi-active actuators (steering, braking, drive, dampers). Each actuator group can be controlled independently to a degree, but the centralized unit optimizes their coordinated operation. This segmentation allows improved driving dynamics through coordinated control while managing complexity through modular architecture and defined control boundaries for each actuator system.
Data Source
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AI summary
The invention relates to a method for controlling actuators acting on vehicle wheels of a motor vehicle (1), wherein the method comprises the following steps: - ascertaining a force (Fxd, Fyd, Mzd) to be brought about on a reference point of the motor vehicle on the basis of driver specifications (axd, δfd), - ascertaining wheel forces (Fxid, Fyid) to be brought about on the vehicle wheels in order to implement the force (Fxd, Fyd, Mzd) to be brought about on the reference point of the motor vehicle by way of a first dynamic allocation using model-based predictive control (MPC), - ascertaining setpoint values for wheel parameters (Tmjd, Tbjd) from the ascertained wheel forces (Fxid, Fyid), and - actuating the actuators of the motor vehicle so as to implement the setpoint values of the wheel parameters (Tmjd, Tbjd).