Muhamad Fajar Imanul Haq, Faiza Latifah, Mulia Pratama, Dewi Indriati Hadi Putri, Muhammad Rizalul Wahid, Bambang Wahono, Achmad Praptijanto, Yanuandri Putrasari, Ahmad Dimyani, Arifin Nur, Muhammad Khristamto Aditya Wardana, Suherman
The rise of Advanced Driver Assistance Systems (ADAS) has emphasized the need for technologies such as Automatic Emergency Braking (AEB) and Adaptive Cruise Control, both of which require brake activation without driver input. Since 2016, automotive manufacturers, particularly in the U.S., have been incorporating AEB technologies in response to safety demands. Bosch's iBooster, an electromechanical brake booster, has gained prominence for its role in autopilot and braking systems, notably in Tesla's Model S and X. The iBooster system can generate full braking pressure in just 120 milliseconds and allows for electronic control while still maintaining manual override capabilities. Tesla's iBooster Gen1, used in its autopilot system, operates via a Controlled Area Network (CAN), though the exact method is not publicly available. Honda has also adopted the iBooster Gen1 in the 2018 CR-V, utilizing it for the Brake Assist feature, although details on Honda's CAN network usage remain limited. This paper explores reverse engineering of the iBooster to uncover key hardware and software technologies. The reverse engineering operation entails altering the system's control loop, capturing the pedal sensor signal, and replicating this signal using an Arduino. Additionally, it includes designing circuit schematics and PCBs. The results demonstrate the success of this reverse engineering approach, which uses a work cycle and Pulse Width Modulation (PWM) to interact with the iBooster Gen1. The method produced identical responses to the iBooster with PWM values set at 30%, 40%, and 50%. © 2024 IEEE.
Program Study of Mechatronics and Artificial Intelligence, Universitas Pendidikan Indonesia, Purwakarta, Indonesia; Research Organization of Electronics and Informatics, National Research and Innovation Agency, Research Center for Smart Mechatronics, Bandung, Indonesia; Mechatronics and Artificial Intelligence, Universitas Pendidikan Indonesia, Purwakarta, Indonesia
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