The suspension load deviation control method for high-power locomotives via Harris Hawk optimization.

Area of Science:

• Railway Engineering
• Mechanical Engineering
• Control Systems

Background:

• Static secondary spring load adjustment is crucial for railway vehicle stability and performance.
• Existing models for six-axle railway vehicles are complex and computationally intensive.
• Optimizing suspension load control is essential for improving operational efficiency and reducing wear.

Purpose of the Study:

• To establish a universal theoretical model for static secondary spring load adjustment in six-axle railway vehicles.
• To develop a simplified supporting structure model to reduce computational complexity.
• To introduce and evaluate the Harris hawk optimization method for railway vehicle suspension load control.

Main Methods:

• Development of a theoretical model applicable to all six-axle railway vehicles.
• Simplification of the 12-point supporting structure to a 4-point model.
• Application of the Harris hawk optimization algorithm for load control.

Main Results:

• The proposed model and Harris hawk optimization significantly improve performance over classical methods.
• Key performance indicators such as maximum force difference and root mean square error are reduced.
• Calculation efficiency is substantially increased, and padding workload is minimized.

Conclusions:

• The established theoretical model and simplified structure provide an efficient approach to static secondary spring load adjustment.
• The Harris hawk optimization method offers superior performance in railway vehicle suspension load control.
• The study demonstrates a significant advancement in improving the efficiency and reducing the workload of static secondary spring load deviation control.