控制策略下热冲压模具升温传热仿真
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摘要
应用ABAQUS软件,建立了B柱软区模具瞬态传热有限元仿真模型,以模具模面温度为优化目标、模面温度均匀分布为约束条件,结合Python二次开发工具,建立基于模面温度反馈控制的有限元仿真计算方法,分别实现了模糊控制与模糊PID控制下的模具升温过程有限元计算。仿真结果表明,模糊控制下模具模面温度50 min内达到(500±30)℃,而约束条件增强后的模糊PID控制下模具模面温度40 min即达到工艺要求,升温效率明显提高。应用模糊PID仿真控制程序控制模具进行升温实验,实验结果验证了仿真的准确性,成功地指导了模具升温控制的程序设计。
A transient heat transfer finite element model( FEM) of die in soft zone of automobile B-pillar was established by software ABAQUS. Then,taking the die surface temperature as the optimization target and the uniform distribution of die surface temperature as the constraint condition,the finite element simulation calculating method based on the die surface temperature feedback control was established by Python secondary development tool,and the finite element calculations of die heating process under fuzzy control and fuzzy PID control were realized,respectively. The simulation results show that under the fuzzy control,the die surface temperature reaches( 500 ±30) ℃ within fifty minutes,while under the fuzzy PID control with the enhanced constraint conditions,the die surface temperature reaches the process requirements after forty minutes,and the heating efficiency is significantly improved. Finally,through the die heating experiment controlled by the fuzzy PID simulation control program,the experiment result verifies the accuracy of the simulation,and the program design of the heating control of die is successfully guided.
A transient heat transfer finite element model( FEM) of die in soft zone of automobile B-pillar was established by software ABAQUS. Then,taking the die surface temperature as the optimization target and the uniform distribution of die surface temperature as the constraint condition,the finite element simulation calculating method based on the die surface temperature feedback control was established by Python secondary development tool,and the finite element calculations of die heating process under fuzzy control and fuzzy PID control were realized,respectively. The simulation results show that under the fuzzy control,the die surface temperature reaches( 500 ±30) ℃ within fifty minutes,while under the fuzzy PID control with the enhanced constraint conditions,the die surface temperature reaches the process requirements after forty minutes,and the heating efficiency is significantly improved. Finally,through the die heating experiment controlled by the fuzzy PID simulation control program,the experiment result verifies the accuracy of the simulation,and the program design of the heating control of die is successfully guided.
引文
[1]Merklein M,Wieland M,Lechner M,et al.Hot stamping of boron steel sheets with tailored properties:A review[J].Journal of Materials Processing Technology,2016,228:11-24.
[2]Merklein M,Wieland M.Investigations on austenitization parameters influencing wear behavior within hot stamping[J].Procedia Engineering,2014,81:1695-1700.
[3]包丽,蔡有杰,吴志东,等.变强度热冲压件数值仿真及其组织性能预测[J].塑性工程学报,2018,25(2):30-36.Bao L,Cai Y J,Wu Z D,et al.Numerical simulation and microstructure properties prediction of hot stamping parts with variable strength[J].Journal of Plasticity Engineering,2018,25(2):30-36.
[4]George R,Bardelcik A,Worswick M J.Hot forming of boron steels using heated and cooled tooling for tailored properties[J].Journal of Materials Processing Technology,2012,55(1):2386-2400.
[5]Abdollahpoor A,Chen X,Pereira M P,et al.Sensitivity of the final properties of tailored hot stamping components to the process and material parameters[J].Journal of Materials Processing Technology,2016,228:125-136.
[6]郝新,韩先洪,杨坤,等.热冲压过程中的模内传热现象[J].塑性工程学报,2014,21(2):98-101.Hao X,Han X H,Yang K,et al.Theoretical and experimental research on heat transfer phenomena in hot stamping[J].Journal of Plasticity Engineering,2014,21(2):98-101.
[7]Wang K,Zhu B,Wang L,et al.Tailored properties of hot stamping steel by resistance heating with local temperature control[J].Procedia Manufacturing,2018,15:1087-1094.
[8]Mori K,Maeno T,Fuzisaka S.Punching of ultra-high strength steel sheets using local resistance heating of shearing zone[J].Journal of Materials Processing Technology,2012,212(2):534-540.
[9]Mori K,Maeno T,Mongkolkaji K.Tailored die quenching of steel parts having strength distribution using bypass resistance heating in hot stamping[J].Journal of Materials Processing Technology,2013,213(3):508-514.
[10]龚健虎.基于模糊自适应PID的聚丙烯模具温度控制仿真[J].计算机仿真,2013,30(8):376-379.Gong J H.Simulation of PP plastic mold temperature control based on fuzzy adaptive PID[J].Computer Simulation,2013,30(8):376-379.
[11]Juang C F,Huang S T,Duh F B.Mold temperature control of a rubber injection-molding machine by TSK-type recurrent neural fuzzy network[J].Neurocomputing,2006,70:559-567.
[12]Everett S E,Dubay R.A sub-space artificial neural network for mold cooling in injection molding[J].Expert Systems with Applications,2017,79:358-371.
[13]Zadeh L A.Fuzzy sets[J].Information and Control,1965,65(8):338-353.
[14]Khan A A,Rapal N.Fuzzy-PID controller:Design,tuning and comparison with conventional PID controller[A].Proceedings of the 2006 IEEE International Conference on Engineering of Intelligent System[C].Islamabad,Pakistan,2006.
[2]Merklein M,Wieland M.Investigations on austenitization parameters influencing wear behavior within hot stamping[J].Procedia Engineering,2014,81:1695-1700.
[3]包丽,蔡有杰,吴志东,等.变强度热冲压件数值仿真及其组织性能预测[J].塑性工程学报,2018,25(2):30-36.Bao L,Cai Y J,Wu Z D,et al.Numerical simulation and microstructure properties prediction of hot stamping parts with variable strength[J].Journal of Plasticity Engineering,2018,25(2):30-36.
[4]George R,Bardelcik A,Worswick M J.Hot forming of boron steels using heated and cooled tooling for tailored properties[J].Journal of Materials Processing Technology,2012,55(1):2386-2400.
[5]Abdollahpoor A,Chen X,Pereira M P,et al.Sensitivity of the final properties of tailored hot stamping components to the process and material parameters[J].Journal of Materials Processing Technology,2016,228:125-136.
[6]郝新,韩先洪,杨坤,等.热冲压过程中的模内传热现象[J].塑性工程学报,2014,21(2):98-101.Hao X,Han X H,Yang K,et al.Theoretical and experimental research on heat transfer phenomena in hot stamping[J].Journal of Plasticity Engineering,2014,21(2):98-101.
[7]Wang K,Zhu B,Wang L,et al.Tailored properties of hot stamping steel by resistance heating with local temperature control[J].Procedia Manufacturing,2018,15:1087-1094.
[8]Mori K,Maeno T,Fuzisaka S.Punching of ultra-high strength steel sheets using local resistance heating of shearing zone[J].Journal of Materials Processing Technology,2012,212(2):534-540.
[9]Mori K,Maeno T,Mongkolkaji K.Tailored die quenching of steel parts having strength distribution using bypass resistance heating in hot stamping[J].Journal of Materials Processing Technology,2013,213(3):508-514.
[10]龚健虎.基于模糊自适应PID的聚丙烯模具温度控制仿真[J].计算机仿真,2013,30(8):376-379.Gong J H.Simulation of PP plastic mold temperature control based on fuzzy adaptive PID[J].Computer Simulation,2013,30(8):376-379.
[11]Juang C F,Huang S T,Duh F B.Mold temperature control of a rubber injection-molding machine by TSK-type recurrent neural fuzzy network[J].Neurocomputing,2006,70:559-567.
[12]Everett S E,Dubay R.A sub-space artificial neural network for mold cooling in injection molding[J].Expert Systems with Applications,2017,79:358-371.
[13]Zadeh L A.Fuzzy sets[J].Information and Control,1965,65(8):338-353.
[14]Khan A A,Rapal N.Fuzzy-PID controller:Design,tuning and comparison with conventional PID controller[A].Proceedings of the 2006 IEEE International Conference on Engineering of Intelligent System[C].Islamabad,Pakistan,2006.