Power Allocation based on ANN for Hybrid Battery and Supercapacitor Storage System in EV - Rahmawan, Hanif Adi; Lystianingrum, Vita; Adityanugraha, Dimas Febry; Pamuji, Feby Agung (Department of Electrical Engineering ITS and FORTEI, 2024)
The paper focuses on presented an ArtificialNeural Network (ANN) approach to allocate power for a hybridenergy storage system (HESS) in an Electric Vehicle (EV). TheHESS is comprised of a battery and supercapacitor, and theANN algorithm aims to optimize power allocation between thesetwo energy storage devices. The data for ANN training wasbased on cost optimization-based power allocation fromprevious research. While optimization can often take highcomputational resource and time, it is expected that a welltrained ANN can allocate power for the EV HESS more quickly.In this research, the inputs to the ANN are the required powerderived from the drive cycle, energy and power capacity of thebattery and supercapacitor, and state of charge (SoC) of thebattery and supercapacitor. The trained ANN was trained withvarious inputs not used in the training and it shows satisfactoryperformance.