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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.

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