Adaptive design and implementation of fractional order PI controller for a multi-source (Battery/UC/FC) hybrid electric vehicle

ABSTRACT

In the modern era, where the massive utilization of fossils fuels is a serious threat to the global environment, the trend of clean and green technological innovations is highly necessitated. The hybrid electric vehicle (HEV) uses more than one means of propulsion, so it consumes less fuel and emits fewer hydrocarbons as compared to internal combustion engine (ICE) vehicles. Since, the overall design of HEV possesses non-linearities and the driving condition sometimes gets very challenging. This paper aims at the modeling and development of an adaptive fractional order PI (AFOPI) controller for speed tracking of a motor according to an Extra Urban Driving Cycle (EUDC) and Japanese 10–15 mode speed cycles. Whereas, conventional controllers lack the ability to track the driving cycles and show oscillation, chattering, and distortion. The AFOPI controller efficiently tracks the driving cycles with the help of a dragonfly searching algorithm (DSA), which optimizes its parameters based on the errors input. The proposed controller has shown an efficiency of 98.8% and its tests carried out at load, speed, and torque variations are then scrutinized and compared with primarily used proportional integer (PI) and field-oriented control (FOC)/vector control (VC) to show the competency and validity of the proposed method.

KEYWORDS:

• Hybrid electric vehicle (HEV)
• hybrid energy storage system (HESS)
• adaptive-fractional-order PI control (AFOPI)
• Extra Urban Driving Cycle (EUDC)
• Japanese 10-15 mode cycle
• dragonfly searching algorithm (DSA)

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Daud Sibtain

Daud Sibtain received B.Sc. and M.Sc. degrees from the University of Central Punjab (UCP), Lahore, Pakistan. He is currently working as Research Associate under ORIC at the University of Central Punjab (UCP). His research interests include the design of solar PV converters, IV curve tracing, Renewable based interconnected grid control designs, and Load Frequency Control (LFC) problems for a multi-areas power system. He is the author/coauthor of more than 13 publications.

Muhammad Ahsan Mushtaq

Muhammad Ahsan Mushtaq received a B.Sc. degree in Electrical Engineering from the University of Engineering & Technology (UET), Lahore, Pakistan in 2005 and an M.Sc. degree in Electrical Engineering with a specialization in power and control systems from the University of Central Punjab (UCP), Lahore, Pakistan in July 2022. During his master's degree, the primary focus of his research was on the control design of multi-source HEVs. His research interests include renewable energy sources, hybrid electric vehicles, automotive electronics, and nonlinear control systems.

Ali F. Murtaza

Ali Faisal Murtaza received a B.Sc. degree from the National University ofSciences and Technology (NUST), Rawalpindi, Pakistan, the M.Sc. degree from the University of Engineering and Technology (UET), Lahore, Pakistan, and the PhD degree from the Politecnico di Torino, Torino, Italy. He is currently working asDirector Research and Associate Professor (Faculty of Engineering) at the University of Central Punjab (UCP), Lahore, Pakistan. At UCP, a research group “Efficient Electrical Energy Systems” is active under his supervision. His research interests include the design of Solar Photovoltaic (PV) systems including DC microgrids, DC-DC converters, I-V Curve tracing, Maximum power point trackers, and partial shading effects. He is the author/co-author of more than 40 publications.