Optimization of Hybrid Electric Vehicle Power Train using Model-Based Control and Model Predictive Control Techniques

A. A. Abdullahi, A. Abdulkarim, P. U. Okorie

Abstract


Optimizing hybrid electric vehicle (HEV) powertrains is essential for enhancing fuel economy, lowering emissions, and extending battery life. This study presents an Energy Management System (EMS) that employs Model-Based Control (MBC) and Model Predictive Control (MPC) to optimize real-time power distribution between the internal combustion engine (ICE) and the electric motor (EM). The proposed framework combines a mathematical HEV powertrain model with simulation in MATLAB/Simulink. The results demonstrate that the MPC-based EMS achieves an 18.5% reduction in fuel consumption and a 21% improvement in battery lifespan, surpassing traditional rule-based EMS. This study confirms the effectiveness of MPC and MBC techniques in providing adaptive and efficient energy management for HEVs.


 


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