Fuzzy Supervisory Based Variable Frequency Control Strategy for Active Battery/Supercapacitor Combination in Electric Vehicles

Zhang Qiao, Weiwen Deng, Jian Wu, Feng Ju, Jingshan Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper describes a novel power management control strategy of battery and supercapacitor hybrid energy storage system to improve system efficiency and battery lifetime. In the presented research, the high and low frequency power demand in the load is separated by a Haar wavelet transform algorithm to overcome the problem of battery overload work and associated degeneration in battery lifetime resulting from an ineffective distribution between battery and supercapacitor. The purpose of frequency distribution is that the supercapacitor is used to share high frequency power components of load power demand to smooth the power demand applied to battery. However, the sole frequency control often fails to realize the optimal utilization of supercapacitor because of the uncertain variation in the driving cycle. Therefore, the power demand distributed to supercapacitor is designed to be changeable along with the variation of its voltage, which is another important advantage of the proposed control strategy. The idea is to utilize different decomposition levels of wavelet transform algorithm, which is adjusted by using a fuzzy-logic controller to reduce the adverse influence of both high frequency transition and peak power from the load power demand on battery system. Finally, Simulation is conducted to verify the effectiveness of the proposed strategy.

Original languageEnglish (US)
Title of host publicationSAE 2016 World Congress and Exhibition
PublisherSAE International
StatePublished - Apr 5 2016
Externally publishedYes
EventSAE 2016 World Congress and Exhibition - Detroit, United States
Duration: Apr 12 2016Apr 14 2016


OtherSAE 2016 World Congress and Exhibition
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering


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