Energy-efficient design and power flow analysis of electro-hydraulic steering systems for heavy-duty wheeled vehicles via parameter identification

The growing demand for energy efficiency, environmental protection in the heavy transportation sector, particularly in large-scale projects, highlights the importance of improving steering systems for vehicles. A pump-controlled electro-hydraulic steering system is proposed, offering significant advantages in energy efficiency under high power. However, it leading to soft speed-load characteristics, reduced circuit stiffness, and compromised performance. To address challenges, an improved back-pressure-controllable BPC-PC-EHSS is introduced, the dynamic and power flow models are established. But it increases power loss, conflicting with the energy-saving objectives. Therefore, back-pressure parameter identification that balances both high performance and low energy-consumption is crucial. The energy-saving boundary is analyzed using the hydraulic conductivity factor, a parallel-input multilayer neural network (PIM-NN) is designed for nonlinear system back-pressure identification. Experimental results show that the proposed system significantly improves steering performance and energy-efficiency with minimal change in pump peak pressure and reduced pressure-vibrations. Specifically, under 6 tons load the error is 1°,which is improved by 55.6 % compared to the non-identification. Compared with valve-controlled and pump-valve systems under same-typical-conditions, significant energy-saving advantages and steering economy are demonstrated. Additionally, the real-world driving hardware environment is reconstructed, it is validated that the total steering input energy is reduced by 76.19 % on the experimental road.