Optimal Fractional-Order Control Scheme for Hybrid Electric Vehicle Energy Management

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Authors: K. Dhananjay Rao, Kapu Venkata Sri Ram Prasad, Paidi Pavani, Subhojit Dawn, Taha Selim Ustun
Cited by: 1
References: 20

Abstract

The increasing need for energy-efficient and environmentally friendly electricity generation has led to the extensive use of hybrid electric systems. These systems integrate different energy sources in an effort to take advantage of the positives of each technology, as using a single source of energy comes with many limitations and disadvantages; hence, the popularity of hybrids has increased in recent times. In this regard, this paper proposes a lithium-ion battery (LIB) and ultracapacitor (UC)-based hybrid architecture considering an optimal energy management framework. In the transportation sector, hybrid vehicles (LIB and UC-based vehicles) effectively utilize the high energy density and power density of LIBs and UCs. This LIB and UC-based hybrid architecture provides an efficient power management solution considering the high power density of the LIB for smooth road profiles, and the high power density of the UC is driven during sudden spikes in load demand because the LIB will not function optimally during the sudden spikes due to lower power density. Furthermore, in order to achieve efficient utilization of the proposed hybrid system, an optimal energy management framework is used. In this regard, in this study, a fractional-order proportional–integral–derivative (FOPID) controller has been designed for effective and optimal energy management. Furthermore, the designed FOPID has been optimized using a metaheuristic technique, namely particle swarm optimization (PSO), to enhance LIB and UC-based hybrid electric vehicle energy management performance. Employing dynamic and optimal energy flow control, the FOPID-based system improves energy consumption, extends LIB life, and improves overall system performance and reliability.

Fields of Study & Subjects

Electric and Hybrid Vehicle Technologies Vehicle Dynamics and Control Systems Electric Vehicles and Infrastructure

Publication details

Journal / source
World Electric Vehicle Journal
Publisher
MDPI AG
Volume
17
Issue
4
Pages
197–197
Publication date
9 April 2026
Language
EN