EPS Zero Point Compensation via Linear Fitting
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Solution Overview
Problem
The accuracy of zero point compensation for Electric Power Steering (EPS) in autonomous vehicles is reliant on human experience, requiring significant manpower and lacking intelligence in control algorithms, which compromises the accuracy and adaptability of lateral control algorithms in unmanned driving systems.
Innovation Solution
A method and device for zero point compensation in EPS that calculates a compensation angle based on a linear relationship between smoothed lateral distance and longitudinal movement distance, using linear fitting and a preset steering wheel transmission ratio, with verification through a minimum residual error calculation to ensure the compensation angle meets acceptable deviation criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If zero point compensation value is added based on personnel experience, then the lateral control algorithm can be implemented, but the accuracy of compensation is insufficient and requires repeated adjustments
Solution Approach 1:
The system performs self-calibration by automatically collecting lateral distance data during vehicle operation, performing linear fitting to determine the zero point compensation value, and verifying the result through residual error calculation. This eliminates the need for manual experience-based adjustment and repeated calibration by personnel.
Solution Approach 2:
The system implements a closed-loop verification mechanism where the calculated zero point compensation value is tested by comparing actual path points with ideal path points. The residual error serves as feedback to confirm whether the compensation value meets the acceptable deviation threshold, ensuring accuracy without manual intervention.
2Adaptability or versatility
If algorithm personnel are involved in the whole calibration process, then the zero point compensation can be adjusted, but a lot of manpower is required to be consumed for the vehicle mass production
Solution Approach 1:
The calibration process is fully automated and executed by the control system itself during normal vehicle operation. The system collects data, performs linear fitting calculations, determines the zero point compensation value, and verifies results without requiring any personnel involvement, enabling seamless integration into mass production.
Solution Approach 2:
The manual calibration process involving personnel judgment and adjustment is replaced by an automated computational system that performs linear fitting algorithms and residual error calculations, substituting human labor with intelligent algorithmic processing.
3Reliability
If traditional feedback method is used for zero point compensation, then the control algorithm can correct deviations, but it is slow and cannot meet real-time control requirements
Solution Approach 1:
The system performs zero point compensation in advance by calculating the compensation value based on linear fitting of collected data and applies it before real-time control operations. This feedforward approach eliminates the need for slow feedback correction during critical control moments, meeting real-time requirements while maintaining accuracy.
Data Source
AI summary
Disclosed is zero point compensation method and device for EPS. The method includes: acquiring a value of lateral distance when a vehicle travels along an ideal path and obtaining a smoothed lateral distance value, for each control cycle; calculating a longitudinal movement distance value of the vehicle for each control cycle; performing linear fitting to obtain a linear relationship between the longitudinal movement distance value and the smoothed lateral distance value; calculating a zero point compensation angle for the EPS based on a first parameter in the linear relationship and a preset steering wheel transmission ratio, and compensating a steering control angle; and determining that the zero point compensation angle passes verification when a minimum residual error is less than a preset acceptable deviation. In this way, the time required for calibration can be reduced, and the accuracy and effectiveness of the control algorithm can be improved.