Active Steering Control Using MPC for Vehicle Stability
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Solution Overview
Problem
Existing vehicle steering systems lack effective stability control, particularly in adverse conditions, leading to untimely and inaccurate control inputs that can cause accidents.
Innovation Solution
A system and method using model predictive control (MPC) and a non-linear bicycle model to calculate vehicle states, including yaw rate and sideslip angle, to generate steering control values, enhancing vehicle stability and handling through active steering assist.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If model predictive control with non-linear bicycle model is implemented to calculate vehicle states and generate steering control values, then vehicle stability and handling are improved, but device complexity increases
Solution Approach 1:
The patent replaces traditional mechanical steering control with a model predictive control system that uses a non-linear bicycle model to calculate vehicle states (sideslip angle, yaw rate) and generates optimal steering control values. This substitution of mechanical control with intelligent control algorithms improves vehicle stability while managing system complexity through software-based solutions.
Solution Approach 2:
The system dynamically adjusts steering control values based on calculated vehicle states including sideslip angle and yaw rate. By continuously monitoring and adjusting these parameters in real-time, the system maintains optimal vehicle stability and handling characteristics under varying driving conditions.
2Device complexity
If existing sensors are utilized without yaw rate sensors to calculate vehicle states, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent uses the non-linear bicycle model as an intermediary to estimate vehicle states (yaw rate, sideslip angle) from available sensor data. Instead of directly measuring these parameters with dedicated sensors, the model computes them as intermediate values based on steering input and vehicle speed, reducing sensor requirements while maintaining adequate measurement precision for control purposes.
Solution Approach 2:
The system creates a virtual copy of the vehicle's dynamic behavior through the non-linear bicycle model. This mathematical model replicates the complex vehicle dynamics and allows calculation of states like yaw rate and sideslip angle without physical sensors, providing sufficient accuracy for steering control while simplifying the hardware configuration.
Data Source
AI summary
A method for steering control includes receiving at least one steering input value, receiving at least one vehicle speed value, and determining, based on the at least one steering input value and the at least one vehicle speed value, a vehicle sideslip angle and a yaw rate. The method also includes generating an initial steering control value based on the vehicle sideslip angle, the yaw rate, and a reference yaw rate value. The method also includes determining a final steering control value based on the initial steering control value and the at least one steering input value, and selectively controlling at least one aspect of a vehicle steering system based on the final steering control value.