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<p>To improve the thermal characteristics of CNC machine tools structurally, reduce the impact of thermal errors on machining accuracy, and lower energy consumption (EC), this paper proposes a thermal design method for spindle systems incorporating energy consumption control factors. Firstly, the thermal characteristics and EC models of the spindle system are established. Experimental verification shows that the maximum relative error of temperature is 4.67% and that of Z-direction thermal deformation is 3.467%, confirming the validity of the models. Secondly, sensitivity analysis is used to select dimensional parameters with significant impacts on optimization objectives as decision variables. The Box-Behnken Design is employed to obtain experimental data for improving computational efficiency, while a function fitting relationship between decision variables and performance indicators was established through response surface methodology. Finally, the entropy weight-G1 combined weighting method is used to find the optimal solution, and the Multi-Objective Pelican Optimization Algorithm is applied to solve the optimization model, revealing the influence of design variables on optimization objectives. Results indicate that the proposed optimization method reduces the maximum temperature, temperature difference, thermal deformation, and EC of the optimized spindle system by 7.11%, 10.43%, 8.70%, and 6.37% respectively compared to the original model, providing a reference for thermal design, energy conservation, and emission reduction of spindle systems.</p>

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A Novel Method of Thermal Design of CNC Machine Tool Spindle System Considering Energy Consumption Control

  • 期刊论文

  • 发表日期：

    2026年3月17日

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  • Xiaolei Deng,
  • Xuanyi Wang,
  • Weiwei Gao,
  • Zhongyu Piao,
  • Honglie Ma,
  • Xiaoliang Lin,
  • Huan Lin

摘要

To improve the thermal characteristics of CNC machine tools structurally, reduce the impact of thermal errors on machining accuracy, and lower energy consumption (EC), this paper proposes a thermal design method for spindle systems incorporating energy consumption control factors. Firstly, the thermal characteristics and EC models of the spindle system are established. Experimental verification shows that the maximum relative error of temperature is 4.67% and that of Z-direction thermal deformation is 3.467%, confirming the validity of the models. Secondly, sensitivity analysis is used to select dimensional parameters with significant impacts on optimization objectives as decision variables. The Box-Behnken Design is employed to obtain experimental data for improving computational efficiency, while a function fitting relationship between decision variables and performance indicators was established through response surface methodology. Finally, the entropy weight-G1 combined weighting method is used to find the optimal solution, and the Multi-Objective Pelican Optimization Algorithm is applied to solve the optimization model, revealing the influence of design variables on optimization objectives. Results indicate that the proposed optimization method reduces the maximum temperature, temperature difference, thermal deformation, and EC of the optimized spindle system by 7.11%, 10.43%, 8.70%, and 6.37% respectively compared to the original model, providing a reference for thermal design, energy conservation, and emission reduction of spindle systems.