Adaptive Energy Management System based on Pontryagin's Minimum Principle for Battery/Supercapacitor Electric Vehicle Considering Topographic Information

In this work an Energy Management System (EMS) is designed for Hybrid Energy Storage System (HESS) involving Battery/Supercapacitor (SC) for Electric Vehicles (EVs). The main aim of this research is to enhance the efficiency and performance of HESS by designing adaptive EMS based on Pontryagin's Minimum Principle (PMP) and Fuzzy Logic Control (FLC) while taking real life topographical data into account. Contour Positioning System (CPS) is utilised to obtain the slope data of the road travelled by EV. The solution of an open loop constrained control problem is adjusted according to changing real time conditions to control the power allocation between battery and SC. The designed technique is tested on three real road slope conditions namely city tour, uphill and downhill under UDDS and NYCC drive cycles. The developed technique is analysed on the basis of energy consumption and the results are evaluated on the basis of battery parameters such as Root Mean Square (RMS) value of battery current and Ampere hour (Ah) throughput of the battery. The proposed technique showed a reduction of 22.98%, 23.80% and 45.28% in Ah throughput of battery in city tour, downhill and uphill conditions respectively as compared to PMP based controller. This shows that the designed Adaptive PMP (APMP) technique is able to manage the real time situations in a better way as compared to open loop PMP technique and improve the performance of battery over a wide range of road slopes and speeds.