Artificial Neural Networks-Based Torque Distribution for Riding Comfort Improvement of Hybrid Electric Vehicles

In an age characterized by a focus on environmental sustainability and technological advancement, the creation and integration of hybrid electric vehicles (HEVs) have become a significant solution in the realm of transportation and clean energy. This study introduces a method for optimizing the distribution of torque in HEVs through the utilization of artificial neural networks (ANN). Furthermore, it introduces an innovative design for the vehicle's drivetrain, enabling it to function in both rear-wheel and four-wheel drive configurations. The HEV is propelled by a permanent magnet synchronous machine (PMSM) and is controlled using direct torque control (DTC) due to its capability to provide rapid and precise responses. The results of simulations conducted using MATLAB/Simulink confirm the effectiveness of the proposed intelligent torque distribution strategy, demonstrating its capacity to enhance vehicle performance, driving comfort, and propulsion power.