2021/04/13 by Daniel Kloeser, Juri Martschin, Kloeser, Daniel +5
Engineering · #35Q93 #FOS: Electrical engineering #FOS: Mathematics #Laser and Thermal Forming Techniques #Metal Forming Simulation Techniques #Metallurgy and Material Forming #Optimization and Control (math.OC) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2104.06098
openalex publication_date 2021/04/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A concise approach is proposed to determine a reduced order control design\noriented dynamical model of a multi-stage hot sheet metal forming process\nstarting from a high-dimensional coupled thermo-mechanical model. The obtained\nreduced order nonlinear parametric model serves as basis for the design of an\nExtended Kalman filter to estimate the spatial-temporal temperature\ndistribution in the sheet metal blank during the forming process based on\nsparse local temperature measurements. To address modeling and approximation\nerrors and to capture physical effects neglected during the approximation such\nas phase transformation from austenite to martensite a disturbance model is\nintegrated into the Kalman filter to achieve joint state and disturbance\nestimation. The extension to spatial-temporal property estimation is\nintroduced. The approach is evaluated for a hole-flanging process using a\nthermo-mechanical simulation model evaluated using LS-DYNA. Here, the number of\nstates is reduced from approximately 17 000 to 30 while preserving the relevant\ndynamics and the computational time is 1000 times shorter. The performance of\nthe combined temperature and disturbance estimation is validated in different\nsimulation scenarios with three spatially fixed temperature measurements.\n