TY - JOUR
TI - Managing fuel consumption and emissions for hybrid electric vehicles through optimization of engine operation
AU - Milićević Stefan V
AU - Blagojević Ivan A
JN - Thermal Science
PY - 2025
VL - 29
IS - 5
SP - 3545
EP - 3560
PT - Article
AB - This paper presents a multi-objective optimization framework for improving internal combustion engine performance in hybrid electric vehicles, specifically targeting the minimization of fuel consumption and emissions (CO, NOx, HC, PM). The proposed method integrates normalized objective functions with weighted factors to develop a unified performance index, facilitating the simultaneous optimization of multiple conflicting objectives. Utilizing the NSGA-II algorithm, a diverse set of Pareto optimal points is generated, each representing different trade-offs between the objectives. The study’s results demonstrate significant improvements in engine performance through the application of the unified internal combustion engine operation map, showcasing a notable reduction in emissions with only a slight increase in fuel consumption. The methodology was validated via MATLAB simulations on two case studies involving parallel and series hybrid electric vehicles, employing a custom synthesized drive cycle for energy management strategy evaluation. The unified map enabled real-time control and efficiency improvements by balancing different emission parameters, thus optimizing internal combustion engine operation across various conditions.