Abstract
Friction press joining is an innovative joining process for bonding plastics and metals without additives in an overlap configuration. This paper presents for the first time a model-based approach for designing a multi-variable model predictive control (MPC) for friction press joining. For system modeling, a differential equation based on the heat flows was proposed and modeled as a torque-dependent function. With this model, it is possible to consider cross-effects between the axial force and the friction zone temperature. With this theoretical approach, adaptive model-predictive process control was implemented and validated for different material combinations (EN AW-6082-T6; EN AW-2024-T3; PE-HD; PA6-GF30; PPS-CF). It could be shown that the MPC has excellent control accuracy even when model uncertainties are introduced. Based on these findings, a 1D Finite Differential Method multi-layer model was developed to calculate the temperature in the plastic component, which is not measurable in situ (r = 0.93). These investigations demonstrate the high potential of the multi-variable MPC for plastic-metal direct joining.
Highlights
Lightweight design is and has always been a key technology in civil aviation
1D Finite Differential Method multi-layer model was developed to calculate the temperature in the plastic component, which is not measurable in situ (r = 0.93). These investigations demonstrate the high potential of the multi-variable model predictive control (MPC) for plastic-metal direct joining
The MPC force control of Meyer et al [3] will be extended by a temperature control, and possible interactions will be considered to guarantee a holistic, model-predictive, multi-variable control for Friction press joining (FPJ)
Summary
Lightweight design is and has always been a key technology in civil aviation. high-strength aluminum [1] and (fiber-reinforced) plastics are increasingly used in today’s aircraft models. To ensure the high and constant quality of the bond when using this joining technology, process control is indispensable For this reason, Meyer et al [3] dealt with a force-controlled process for FPJ. According to Taysom et al [4], this approach has enormous potential, especially as a multi-variable control, but has never been proven For this reason, the MPC force control of Meyer et al [3] will be extended by a temperature control, and possible interactions will be considered to guarantee a holistic, model-predictive, multi-variable control for FPJ. The MPC force control of Meyer et al [3] will be extended by a temperature control, and possible interactions will be considered to guarantee a holistic, model-predictive, multi-variable control for FPJ To this end, an MPC-based temperature control system is to be set up, and a model for calculating the temperature distribution in multi-layer systems is to be designed
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