摘要
A wavelet-based power management system is proposed in this paper with a combination of the battery and ultracapacitor(UC)hybrid energy storage system(HESS).The wavelet filter serves as a frequency-based filter for distributing the power between the battery and UC.In order to determine the optimal level of wavelet decomposition as well as the optimal activation power of the wavelet controller,an optimization procedure is established.The proposed frequency-based power management system moderates the usage of battery current,consequently improving its lifetime.Compared with the conventional threshold-based power management systems,the proposed system has the advantage of enhanced battery and UC power management.A LiFePO4 battery is considered and its life loss is modeled.As a case study,an electric motorcycle is evaluated in the federal test procedure(FTP)driving cycle.Compared with a conventional energy storage system(ESS)and a state of available power(SoP)management systems,the results show an improvement for the battery lifetime by 115%and 3%,respectively.The number of battery replacements is increased,and the energy recovery is improved.The 10-year overall costs of the proposed HESS strategy using wavelet are1500 dollars lower,compared with the ESS.
A wavelet-based power management system is proposed in this paper with a combination of the battery and ultracapacitor（UC） hybrid energy storage system（HESS）. The wavelet filter serves as a frequency-based filter for distributing the power between the battery and UC. In order to determine the optimal level of wavelet decomposition as well as the optimal activation power of the wavelet controller, an optimization procedure is established. The proposed frequency-based power management system moderates the usage of battery current,consequently improving its lifetime. Compared with the conventional threshold-based power management systems,the proposed system has the advantage of enhanced battery and UC power management. A LiFePO4 battery is considered and its life loss is modeled. As a case study, an electric motorcycle is evaluated in the federal test procedure（FTP） driving cycle. Compared with a conventional energy storage system（ESS） and a state of available power（SoP） management systems, the results show an improvement for the battery lifetime by 115% and 3%, respectively. The number of battery replacements is increased,and the energy recovery is improved. The 10-year overall costs of the proposed HESS strategy using wavelet are1500 dollars lower, compared with the ESS.
基金
supported by the Automotive Engineering Research Center(AERC)of Iran University of Science and Technology(IUST)
the Vehicle,Fuel and Environment Research Institute(VFERI)of The University of Tehran.
