Research on Speed Estimation Method for Distributed Electric-Drive Loaders Based on Finite-State Machine.

Area of Science:

• Robotics and Control Systems
• Automotive Engineering
• Sensor Fusion Technology

Background:

• Accurate speed estimation is vital for the control of distributed electric-drive loaders in complex operational environments.
• Inconsistent wheel conditions (e.g., slipping) frequently lead to significant inaccuracies in conventional speed estimation methods.
• Articulated steering introduces relative motion between vehicle bodies, complicating accurate speed estimation from sensor data.

Purpose of the Study:

• To develop a robust multi-sensor fusion speed estimation method for electric-drive loaders.
• To enhance vehicle control and operational safety by improving speed estimation accuracy.
• To address the challenges posed by varying road conditions and articulated steering dynamics.

Main Methods:

• A Finite State Machine (FSM) is employed to dynamically identify individual wheel states (slipping or non-slipping).
• Adaptive switching between weighted averaging (for non-slipping wheels) and acceleration integration (for all slipping wheels) ensures accurate speed calculation.
• An articulated steering projection method is utilized to process IMU signals, compensating for inter-body relative motion.

Main Results:

• The proposed FSM-based method demonstrates accurate vehicle speed estimation across diverse road conditions.
• Significant improvements in speed estimation accuracy, exceeding 75%, were observed under low-adhesion conditions with all wheels slipping.
• The method outperforms traditional techniques like simple averaging, selective averaging, and pure integration, particularly in challenging scenarios.

Conclusions:

• The multi-sensor fusion method based on FSM provides a reliable solution for accurate speed estimation in electric-drive loaders.
• The adaptive strategy effectively handles complex scenarios, including widespread wheel slippage and articulated steering.
• This advancement contributes to improved vehicle performance, control, and safety in demanding applications.