Development of a Hardware-in-the-Loop vehicle traction control using Machine learning techniques for embedded systems

This work aims to describe the design of an ECU using a 32 bits microcontroller STM32H743ZIT6, for use in a traction control system in HiL mode to control two BLDC wheels of a hybrid vehicle. The data used to train the algorithm were obtained through simulation software Carsim® in conjunction with mathematical software Matlab/Simulink®. The controller was developed using Machine Learning technique and used a 3-layer LSTM network working in the embedded system of ECU to control the traction of the vehicle.