Methodology for Fast-Running, Time-Resolved Simulation of Non-Exhaust Particle Emissions from Brake Wear Abrasion

Non-exhaust particle emissions, particularly those generated by brake wear, are a significant source of fine particulate matter in urban environments. These emissions contribute to air pollution and pose serious health risks, particularly in densely populated areas. While vehicle exhaust emissions have been extensively studied and regulated, the contribution of non-exhaust sources, including brake wear, remains a critical factor in air quality management. This paper presents a novel methodology for fast-running, time-resolved simulation of non-exhaust particle emissions, specifically those from brake wear abrasion. A 3D CFD model computes the turbulent flow field around the disc brake. The resulting information on the convective air cooling is applied as boundary conditions on a 3D thermal model. This thermal simulation setup is compared and verified with experimental data from literature. The 3D numerical models produce data and boundary conditions for an efficient 1D numerical approach that models the dynamic processes of brake temperature development. The average temperature deviation between the 3D and 1D simulation is less than 1.5 °C in the validated section of the WLTP. The 1D simulation is coupled with data-based models of brake-induced non-exhaust emissions. This combination enables the generation of detailed, time-resolved emission profiles that account for the variability in driving conditions, such as speed and braking intensity. The methodology further explores and models the key impact factors influencing brake-induced particulate emissions, including material properties, brake system design, and environmental conditions. By providing time-resolved output, the methodology offers a more precise analysis of emission-relevant events in real-world driving scenarios, compared to traditional emission factor approaches, which typically assume constant emission rates. This approach captures the temporal variability of particle emissions during different driving phases. The speed and computational efficiency of the method make it suitable for large-scale simulations, while maintaining high accuracy when validated against experimental data.