Rüppel, Adrian KarlAdrian KarlRüppelTelha, YoussefYoussefTelhaMeurer, MarkusMarkusMeurerBergs, ThomasThomasBergs2025-07-242025-07-242025https://publica.fraunhofer.de/handle/publica/48991010.1016/j.procir.2025.03.0362-s2.0-105009408356Mechanistic force models describe the relation between process forces and geometrical engagement of the tool and workpiece in cutting processes. The model parameters are dependent on the tool's wear state, which results in constantly changing force model parameters during cutting. To account for this, previous studies developed a methodology to identify the force model parameters online using an ensemble Kalman filter (EnKF). The methodology relies on piezo-electric dynamometer-based force measurements, which have high accuracy but are also costly and not easily industrially applicable. Instead, this study uses current and voltage signals of the electrical motors. As these signals have less accuracy, both main spindle and feed drive axes are utilized and fused in an EnKF. The methodology is capable of identifying a mechanistic force model online with high accuracy and shows potential for force monitoring and control without dynamometer-based force measurement.enfalsecurrent-based force measurementmillingsensor fusionjournal article