Redesign and Optimization of an Electrohydraulic Silo Cutter Using IMOGWO-Based Multi-Objective Optimization and FluidSIM Co-Simulation

Conventional hydraulic systems of silo cutters are associated with several limitations, including low control precision, high operator exposure to hazardous environments, and suboptimal energy efficiency. This study presents a comprehensive redesign and multi-objective optimization of a Gonella electrohydraulic silo cutter using high-fidelity FluidSIM 4.2 co-simulation. The system was upgraded with six proportional directional valves, replacing traditional solenoid control, enabling precise remote joystick operation. Experimental tests were conducted at flow rates of 30–50 L/min and an extended pressure range of 80–120 bar. Results showed that increasing flow rate significantly improved boom linear velocity (65.48–69.72%) and cutting rotor speed (66.67–75.48%). Temperature-dependent viscosity modeling (Vogel equation at 20–80°C) revealed notable nonlinear effects, with velocity reductions up to 22% at low temperatures. Simulation results demonstrated strong agreement with experiments. An Improved Multi-Objective Grey Wolf Optimizer (IMOGWO), incorporating chaotic initialization, dimension learning-based hunting, and Lévy flight, was integrated with FluidSIM. The robust Pareto front (low standard deviation across 30 runs) achieved simultaneous improvements of 21.8% in energy efficiency, 68.2% in positioning accuracy, 81.0% in cutter speed stability, and 17.4% in harvesting productivity. Proportional valves also reduced boom retraction speed by 30% for safer operation. This IMOGWO–FluidSIM framework provides a practical, cost-effective pathway toward autonomous, safer silage-harvesting systems in agriculture.