Nested FOPI and PI Controller Comparison and Battery Energy Management for EV Traction System

A Master of Science thesis in Electrical Engineering by Faris Ata Allah entitled, “Nested FOPI and PI Controller Comparison and Battery Energy Management for EV Traction System”, submitted in November 2023. Thesis advisor is Dr. Habib Ur Rehman and thesis co-advisor is Dr. Shayok Mukhopadhyay. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).

Abstract

This work investigates first the use of nested Fractional Order Proportional Integral (FOPI) and conventional integer order Proportional Integral (PI) controllers and examines the effect of having both controllers in inner and outer loops. Ziegler-Nichols (ZN) and Cohen-Coon (CC) rules are used for the PI combinations on a prototype EV traction system consisting of an Indirect Field-Oriented Control (IFOC) based induction motor (IM) drive system. The speed regulation and power consumption of seven different combinations of controllers’ cases are analysed and compared. Then, the focus shifts towards two of the seven cases, where a comparison is made of the battery bank temperature and overall speed regulation performance, when motor speed is controlled via a ZN-PI based integer order controller against an FOPI controller tuned via existing rules in the literature. Furthermore, the FOPI controller is made to use the same gains as the ZN-PI controller, but only the order of the integral is varied to non-integer values lesser than unity. An EV traction system model with battery temperature sensing is developed and intensive simulation results show that ZN-PI gains based FOPI controller has lesser battery temperature rise and State of Charge (SOC) reduction without sacrificing speed regulation performance, which proved that changing the order of the integral to values lower than unity, has positive effect on battery temperature, and SOC, without sacrificing speed regulation performance. Hardware implementation of the three simulated cases is conducted to verify the simulations results. Finally, a novel temperature aware Energy Management System (EMS) using Fuzzy Logic Control (FLC), is proposed to reduce temperature rise and SOC depletion of the EV Lithium-ion (Li-ion) battery bank. This work has the potential to help in protecting and extending the EV battery bank life. Because small temperature rise and fast SOC depletion if sustained over a long period of time, may significantly harm an EV’s battery bank.