Open AccessDirect Model Predictive Control of Fuel Cell and Ultra-capacitor Based Hybrid Electric Vehicle
Author(s) -
Farrukh Zain ul Abideen,
Hassan Abdullah Khalid,
Muhammad Saud Khan,
Habibur Rehman,
Ammar Hasan
Publication year - 2024
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2024.3381219
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Considering climate change, hybrid electric vehicles (HEVs) provide a clean alternative for transportation. This study presents an HEV with a fuel cell and ultra-capacitor connected in a parallel-type configuration. Direct model predictive control is used to optimize the power flow between the energy sources and the motor. Notably, the proposed controller uses a global approach, i.e., a single controller for the regulation of both power converters, thereby enhancing overall performance. Furthermore, the controller design leverages a non-averaged state space model that explicitly incorporates the switching nature of the converters. A method for computing reference currents for the fuel cell and ultra-capacitor is also introduced, which utilizes the ultra-capacitor current to manage power demand transients. Simulation results show that the proposed technique produces better results in terms of overshoot, steady-state error, and response time compared to recent studies in the literature.