A multibody simulation model for deep-groove ball bearings is presented. The model considers friction in both the raceway and cage contacts, resulting from radial and axial loads. The model is validated against experimental measurements for a 6319 bearing under oil-bath lubrication over a speed range of 500–3000 min⁻¹ and two load ratios ($C/P=10$ and 6.5). Predicted friction torques show good agreement with measurements, with deviations between 5.5% and 22% at moderate speeds. In addition, electrical contact capacitances are calculated for a 6208 bearing and compared with an analytical approach, showing deviations in the range of 10–14%. Beyond friction prediction, the fully dynamic approach enables time-resolved analysis of roller kinematics and the identification of instability limits under axial excitation. The developed tool therefore enables reliable bearing loss prediction, supports efficiency-oriented drivetrain design, and provides a basis for electro-tribological and stability investigations.

Improving the energy efficiency of rolling bearings requires a component-resolved understanding of loss mechanisms. While analytical models capture load-dependent losses, load-independent hydraulic losses demand a physics-based approach. This paper presents a computational fluid dynamics (CFD) methodology for the qualification of individual hydraulic loss contributions and to assess their sensitivity to operating conditions. The approach decomposes the total hydraulic loss of the spherical roller bearing 22320 into component-level shares and is benchmarked against dedicated experiments. The simulated results show good agreement with experimental measurements, supporting the validity of the methodology. The discrepancy between the measured and simulated friction torque values averaged at 2–7%, with a single outlier. Furthermore, CFD methods have been demonstrated to be capable of predicting trends in hydraulic losses resulting from variations in speed and temperature. A consistent finding across all investigated conditions is that the rolling elements dominate the hydraulic losses. Churning-induced losses of the rolling elements contribute for more than 50% of the hydraulic losses of the hole bearing in every test. The proposed methodology offers a reproducible way to assign losses individually, compare operating scenarios and guide targeted design measures for loss reduction in rolling bearings. Furthermore, dynamic kinematic simulations of rolling bearings can be equipped with component-resolved hydraulic losses. This is enabling more accurate predictive modelling of the bearing kinematics and detecting effects such as slippage.