Supporting the Electric Motor of A Hybrid Autonomous Vehicle by Intelligent Speed Controller
أحمد عبدالهادي أحمد, علي عبدالرزاق عباس الطاهر, محمد الباقر نجم عبد ضيول
كلية الهندسة-جامعة كربلاء · العراق
Hybrid Electric Vehicles (HEVs) offer a promising solution to mitigate the transportation sector’s environmental impact by reducing greenhouse gas emissions. This thesis aims to enhance the performance and control systems of HEVs. A comprehensive investigation of permanent magnet synchronous motor (PMSM) motor control strategies was conducted. Lyapunov stability theory-based backstepping control is the most effective way to track motor speed accurately and efficiently, which is essential for HEV dynamics. This study explored advanced energy management strategies for HEV systems to optimize energy utilization. A hybrid energy storage system was investigated using a rechargeable battery, supercapacitor, and solar energy integration. After evaluating several Maximum Power Point Tracking (MPPT) algorithms, it was found that the Perturbation and Observation (P&O) method performed better at maximizing the power extracted from solar panels.Moreover, a comparative analysis of DC-DC converter topologies revealed the Super-Lift converter as the most efficient for voltage level conversion. The extracted power from the solar panel is increased to 15% when using P&O with a Super-lift Luo converter. Multi-level inverters were used to ensure smooth operation and reduce torque ripple. The torque ripple decreased to 0.083%. A fractional PID controller was employed for intelligent energy management. To further improve the capabilities of HEVs, this thesis investigated the viability of autonomous operation. An Adaptive Model Predictive Control (AMPC) strategy was developed and simulated to enable precise path tracking for Autonomous Hybrid Electric Vehicles (AHEVs). Simulation results demonstrated exceptional path-tracking accuracy of 99.2%, highlighting the potential of AMPC for safe and efficient autonomous driving. The proposed control strategies and energy management system were rigorously evaluated through MATLAB/Simulink simulations. The results show essential improvements in energy economy, motor performance, and overall HEV system performance. This thesis advances HEV technology by offering practical options for improved motor control, efficient energy management, and autonomous capabilities.