Thermal characteristics analysis and cooling model optimization of motorized spindle

Aiming at the influence of poor cooling conditions and traditional cooling control strategy on motorized spindle temperature and machining performance. Firstly, the heat transfer model of the motorized spindle cooling system is studied. Secondly, the influence of coolant inlet flow rate and temperature on the thermal characteristics of the motorized spindle is studied. Then, a thermal network model is established to solve the temperature of each temperature measuring point. Finally, the thermal characteristic experiment of the motorized spindle is carried out, and the cooling fluid flow optimization model is established based on the particle swarm optimization algorithm and simulated annealing algorithm. The results show that the temperature difference of the motorized spindle does not exceed 45 degrees C, the thermal deformation does not exceed 40.2 mu m, and the thermal elongation is inhibited by 36 %. The maximum error of the Thermal Network Method and Finite Element Method(FEM)is 14.24 %. The utilization of the average logarithmic temperature difference for assessing the cooling effectiveness of optimal flow rates revealed that the particle swarm optimization algorithm demonstrates a comparatively lower average logarithmic temperature difference in comparison to the simulated annealing algorithm. The heat exchange efficiency of the motorized spindle is higher under the optimal flow rate obtained by the particle swarm algorithm.