Design, Modelling And Control Of Hybrid Energy Storage System For Electric Vehicles

Taha Mohammed, Ahmed Sadeq (2021) Design, Modelling And Control Of Hybrid Energy Storage System For Electric Vehicles. PhD thesis, UTAR.

Preview

PDF Download (8Mb) | Preview

Abstract

The energy storage system (ESS) is a critical factor in electric vehicle (EV) applications. Batteries represent a wide solution for clean energy, and they are among the most popular energy storage devices. Low power density and limited life-time are the main defects in Pure Battery Electric Vehicles (PBEVs). The Hybrid energy storage system (HESS) is the solution to the disadvantages of the single energy storage system in EV applications. In HESS, the battery is used to supply the low traction power and steady-state load current; whereas the supercapacitor is used to supply the peak demand current and absorb the regenerative energy during braking. This research aims to design a batterysupercapacitor HESS for EV. A semi-active topology had been used to interface the battery and supercapacitor with the DC bus. The energy consumption of the selected drive cycles was estimated considering the topographical information. The contour positioning system (CPS) was used to extract the road slope of the selected drive cycle along the journey. The proposed energy management strategy of HESS includes three control layers. The standard rule-based controller, the optimal adaptive rule-based controller, and the fuzzy adaptive rule-based controller were proposed to manage the energy flow of the HESS. The linear quadratic regulator (LQR) was designed to control the current flow iv of the DC-DC converter. To validate the proposed control strategies, the system was modelled and tested in Matlab/Simulink environment. The proposed control algorithms were tested in three real drive cycles (uphill, downhill, and city-tour) at three different speeds (50, 60, and 70 Km/h) and in three different standard drive cycles (UDDS, NYCC, and Japan1015). The results of the proposed energy management system proved that the controller succeeded in reducing the battery stress compared to that of the single energy storage battery system. The results of the proposed HESS using the optimal adaptive controller succeed to extend the number of possible drive cycles compared to those of the rule-based controller and the fuzzy adaptive controller.

Actions (login required)