Energy Management in Plugin Hybrid Electric Vehicles with Hybrid Energy Storage System Using Hybrid Approach

Abstract

Herein, an optimal control approach for the energy management of hybrid energy storage system (HESS) like battery, supercapacitor (SC), and integrated charging unit in plugin hybrid electric vehicle (PHEV) is proposed. The proposed approach is the combination of both the jellyfish search optimizer (JS) and gradient boosting decision tree algorithm (GBDT) and it is termed as JS‐GBDT approach. The high energy density battery and high power density SC are combined for satisfying the demand of vehicle. To balance the charging, an uncontrolled rectifier with DC to DC buck converter, and to guarantee smooth transition of energy, two bidirectional DC–DC buck–boost converters are utilized. To meet the load requirements, GBDT approach predicts and integrates the total power supply and the charging level of the power source. The output voltage regulation, reference generation, and smooth tracking of current are performed by the energy management of PHEV using JS approach. The proposed methodology is executed on MATLAB/Simulink working platform. The performance of the HESS is evaluated by utilizing the comparison analysis with existing systems. From the analysis, the proposed approach provides less stress for primary and secondary sources and improves the charging unit performance and enhances the battery life.