Abstract
This paper proposes a hierarchical sizing method and a power distribution strategy of a hybrid energy storage system for plug-in hybrid electric vehicles (PHEVs), aiming to reduce both the energy consumption and battery degradation cost. As the optimal size matching is significant to multi-energy systems like PHEV with both battery and supercapacitor (SC), this hybrid system is adopted herein. First, the hierarchical optimization is conducted, when the optimal power of the internal combustion engine is calculated based on dynamic programming, and a wavelet transformer is introduced to distribute the power between the battery and the SC. Then, the fuel economy and battery degradation are evaluated to return feedback value to each sizing point within the hybrid energy storage system sizing space, obtaining the optimal sizes for the battery and the SC by comparing all the values in the whole sizing space. Finally, an all-hardware test platform is established with a fully active power conversion topology, on which the real-time control capability of the wavelet transformer method and the size matching between the battery and the SC are verified in both short and long time spans.
Highlights
The electrification of the automobile industry is a critical step toward addressing the energy dilemma and protecting the environment [1, 2]
An all-hardware HESS platform is designed and implemented to verify the real-time control capability of the wavelet transformer (WT) and to prove the effectiveness of the size matching between the battery and SC
The bus voltage of the SC system and that of the battery system are approximately stable in the test, which indicates that the proposed energy management system (EMS) coordinates the operation of the SC and battery system reasonably, and the power requirements of driving motor (DM) are satisfied in real-time
Summary
The electrification of the automobile industry is a critical step toward addressing the energy dilemma and protecting the environment [1, 2]. Reference [10] proposed a back-to-back competitive learning mechanism-driven fuzzy logic-based energy storage approach to increase the fuel efficiency of a hybrid electric vehicle. The hybrid energy storage system has been developed with a strong prospect of enhancing the economic performance of PHEV, power electronics and supercapacitor (SC) technology [8, 16, 17]. To fill these research gaps, this paper proposes a new strategy to improve both fuel efficiency and battery longevity in PHEV energy management. Eldeeb et al [29] developed a multi-objective optimization approach for minimizing the HESS system cost on a PHEV, in which weight and volume were taken into account while determining the best battery unit and SMES size.
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