Modeling and Identification of an Electric Vehicle Braking System: Thermal and Tribology Phenomena Assessment 2020-01-1094
A rapidly shifting market and increasingly stringent environmental regulations require the automotive industry to produce more efficient low-emission Electric Vehicles (EVs). Regenerative braking has proven to be a major contributor to both objectives, enabling the charging of the batteries during braking and a reduction of the load and wear of the brake pads. The optimal sizing of such systems requires the availability of good simulation models to improve their performance and reliability at all stages of the vehicle design. This enables the designer to study both the integration of the braking system with the full vehicle equipment and the interactions between electrical and mechanical braking strategies. This paper presents a generic simulation framework for the identification of thermal and wear behaviour of a mechanical braking system, based on a lumped parameter approach. The thermal behaviour of the system is coupled back to the friction coefficient between the pad and the disk to assess its effect on braking performance. Additionally, the effect of wear and temperature on the generation of airborne particles is investigated. Subsequently, experimental data collected on a real EV is used to validate and tune the previously described simulation model, following a proposed validation procedure. The instrumentation method and challenges, as well as the experimental procedure used to collect the data on a chassis dynamometer and in real-world driving conditions, are described. Finally, simulation results for different driving scenarios are used to compare virtual and experimental results.
Citation: D’hondt, T., Forrier, B., Sarrazin, M., Favilli, T. et al., "Modeling and Identification of an Electric Vehicle Braking System: Thermal and Tribology Phenomena Assessment," SAE Technical Paper 2020-01-1094, 2020, https://doi.org/10.4271/2020-01-1094. Download Citation
Thomas D’hondt, Bart Forrier, Mathieu Sarrazin, Tommaso Favilli, Luca Pugi, Lorenzo Berzi, Riccardo Viviani, Marco Pierini
Siemens Industry Software NV, Università degli Studi di Firenze