The transition to battery electric vehicles (BEVs) is enabling the significant redesign of key subsystems, including braking systems. This work presents a physics-based optimization framework for the preliminary design of a distributed electro-hydraulic brake-by-wire (DEHB) system tailored for electric vehicles. The DEHB system is modeled as a two-phase actuation process captured through a coupled electro-mechanical and hydraulic model: initial pad-disc clearance closure and subsequent pressure buildup. Sensitivity analysis is employed to identify critical design parameters, and a multi-objective genetic algorithm is used to minimize electrical power consumption, peak current, and maximum torque while satisfying performance constraints. The optimized configuration is benchmarked against commercially available solutions and validated against a multiphysics simulation, showing deviations below 8% for current and power. A dynamic analysis incorporating vehicle-level ABS logic demonstrates the improved performance and energy efficiency of the DEHB system during emergency braking, with a reduction of 50% in required power if compared to a non-optimized system. The results confirm the effectiveness of the proposed method for early-stage sizing and highlight the potential of DEHB architectures in future electric vehicle platforms.
Physics-Oriented Optimization of a Distributed Electro-Hydraulic Brake System for Electric Vehicles
Giannini, Gregorio;Belloni, Mattia;Ghigi, Marco;Vignati, Michele;Braghin, Francesco
2026-01-01
Abstract
The transition to battery electric vehicles (BEVs) is enabling the significant redesign of key subsystems, including braking systems. This work presents a physics-based optimization framework for the preliminary design of a distributed electro-hydraulic brake-by-wire (DEHB) system tailored for electric vehicles. The DEHB system is modeled as a two-phase actuation process captured through a coupled electro-mechanical and hydraulic model: initial pad-disc clearance closure and subsequent pressure buildup. Sensitivity analysis is employed to identify critical design parameters, and a multi-objective genetic algorithm is used to minimize electrical power consumption, peak current, and maximum torque while satisfying performance constraints. The optimized configuration is benchmarked against commercially available solutions and validated against a multiphysics simulation, showing deviations below 8% for current and power. A dynamic analysis incorporating vehicle-level ABS logic demonstrates the improved performance and energy efficiency of the DEHB system during emergency braking, with a reduction of 50% in required power if compared to a non-optimized system. The results confirm the effectiveness of the proposed method for early-stage sizing and highlight the potential of DEHB architectures in future electric vehicle platforms.| File | Dimensione | Formato | |
|---|---|---|---|
|
applsci-16-00506-v2.pdf
accesso aperto
:
Publisher’s version
Dimensione
1.87 MB
Formato
Adobe PDF
|
1.87 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


