Steering Controller Axle Dynamics Compensation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current steering systems with electric steering assistance do not account for front axle dynamics, leading to instability and loss of steering feel, requiring unstable parameterization of the steering controller without knowledge of these dynamics.
Innovation Solution
A method that determines a compensation value based on a model to actively compensate for front axle dynamics by using information about rack travel, which is derived from conventional sensors, allowing for improved control without more expensive solutions like stiffer ball screw drives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional electric steering assistance is used without considering front axle dynamics, then the steering system is simpler to implement, but the system becomes unstable and loses steering feel
Solution Approach 1:
The control method calculates a compensation value based on a model of front axle dynamics before the actual steering action occurs. This preliminary compensation is integrated into the setpoint variable for steering assistance, allowing the system to pre-correct for expected dynamic effects rather than reacting to instability after it occurs.
Solution Approach 2:
The system uses feedback from measured values (rotor position, torque on torsion bar, angular positions) to continuously update the compensation value. A Kalman filter processes sensor fusion data to determine rack travel information, which feeds back into the compensation calculation, creating a closed-loop control system that maintains stability.
2Reliability
If the steering controller is parameterized to be stable with unknown front axle dynamics, then the system is more stable, but the control response is slower and less precise
Solution Approach 1:
By pre-calculating the compensation value based on the model and current state, the system prepares the correct control adjustment before disturbances fully manifest, enabling faster response without sacrificing stability.
Solution Approach 2:
The system dynamically adjusts the setpoint variable by adding the compensation value, which changes parameters of the control signal based on real-time rack travel information and model predictions, allowing adaptive response to varying dynamic conditions.
3Reliability
If stiffer connection of ball screw drive is used to achieve more robust control, then the control system becomes more stable, but the system cost increases
Solution Approach 1:
The patent replaces mechanical stiffening solutions (stiffer ball screw connections) with a control-based approach. The compensation value calculated from the model and sensor data substitutes for mechanical reinforcement, achieving the same stability goal through software/control algorithms rather than hardware modifications.
Solution Approach 2:
The compensation value acts as an intermediary that mediates between the steering input and the actual steering assistance output. This virtual compensation mechanism achieves robust control without requiring physical modifications to the mechanical components.
Data Source
AI summary
The disclosure relates to a method and to a device for controlling a steering system and to a steering system having electric steering assistance, wherein a reference variable for the steering assistance is predefined by a steering controller, the steering system is controlled as a function of the reference variable, a compensation value to compensate for a dynamic behavior of an axle steered by the steering system is determined on the basis of a model, the reference variable is determined as a function of the compensation value. The disclosure further relates to a method and to a device for emulating dynamics of the steered axle.