Autonomous Electric-Vehicle Control Using Speed Planning Algorithm and Back-Stepping Approach

Autonomous electric vehicles (AEVs) have garnered increasing attention in recent years as they hold significant promise for transforming the transportation sector. However, despite advances field, effective vehicle drive control remains a critical challenge that must be addressed to realize full potential of AEVs. This study presents novel approach AEV concurrently generating suitable speed profile and controlling along planned path takes into account various driving circumstances mimic real-world driving. The designed strategy is divided two parts: first part proposed planning algorithm (SPA) works on developing an adequate navigation; first, uses identifying sharp curves predefined trajectory; secondly, based dynamic properties these curves, it generates appropriate ensure smooth travel across entire trajectory with varying velocities. second proposes new back-stepping technique space vector modulation (SVM) induction motor (IM) traction AEV. A load torque observer has been enhance speed-tracking task, while system stability proven using Lyapunov theory. Through series experiments simulations MATLAB/Simulink software dSPACE 1104 real-time interface, we demonstrate effectiveness SPA combined highlight its advance field technology. Our findings important implications design implementation AEVs provide foundation future research this exciting area study.