A Power Split Strategy for a Vehicular Hybrid Energy Storage System Using Adaptive Neuro Fuzzy Inference System

Jiao Li, Lijun Zhang, Longzhi Yang, Bo Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This paper presents a real-time power split strategy for a battery-supercapacitor hybrid energy storage system. The objective of the proposed strategy is to alleviate battery degradation through effective supercapacitor utilization. The proposed strategy employs an adaptive neural fuzzy inference system, which is capable of learning a power split strategy from offline optimization results and distributing power in real-time. The performance of the strategy proposed and a low pass filtering technique is compared through simulations. The results demonstrate that the proposed method can effectively reduce battery capacity loss and perform well under unknown driving cycles in real time.
Original languageEnglish
Title of host publicationInternational Conference on Advanced Robotics and Mechatronics (ICARM)
Place of PublicationPiscataway, NJ, USA
Number of pages6
ISBN (Electronic)9798350300178, 9798350300161
ISBN (Print)9798350300185
Publication statusPublished - 8 Jul 2023

Cite this