Journal
ENERGY
Volume 198, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2020.117298
Keywords
Hybrid energy storage system; Driving patterns recognition; Transient power; Adaptive wavelet transform; Fuzzy logic control
Categories
Funding
- National Natural Science Foundation, China [51775393]
- Liuzhou Science and Technology Planning Project, China [2018BC20501]
- Innovative Research Team Development Program of Ministry of Education of China, China [IRT_17R83]
- 111 Project, China [B17034]
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To achieve optimal power distribution of hybrid energy storage system composed of batteries and supercapacitors in electric vehicles, an adaptive wavelet transform-fuzzy logic control energy management strategy based on driving pattern recognition (DPR) is proposed in view of the fact that driving cycle greatly affects the performance of EMS. The DPR uses cluster analysis to classify driving cycles into different patterns according to the features extracted from the historical driving data sampling window and utilizes pattern recognition to identify real-time driving patterns. After recognition results are obtained, an adaptive wavelet transform is employed to allocate the high frequency components of power demand to supercapacitor which contains transient power and rapid variations, while the low frequency components are distributed to battery accordingly. The use of fuzzy logic control is to maintain the SOC of supercapacitor within desired level. The simulation results indicate that the proposed control strategy can effectively decrease the maximum charge/discharge current of battery by 58.2%, and improve the battery lifetime by 6.16% and the vehicle endurance range by 11.06% compared with conventional control strategies. Further demonstrate the advantage of hybrid energy storage system and the presented energy management strategy. (C) 2020 Elsevier Ltd. All rights reserved.
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