Open Access

ARTICLE

Fuzzy Adaptive Filtering-Based Energy Management for Hybrid Energy Storage System

Xizheng Zhang^1,2,*, Zhangyu Lu¹, Chongzhuo Tan¹, Zeyu Wang¹

1 School of Electrical and Information Engineering, Hunan Institute of Engineering, Xiangtan, 411104, China
2 School of Robotics, Hunan University, Changsha, 410082, China

* Corresponding Author: Xizheng Zhang. Email:

Computer Systems Science and Engineering 2021, 36(1), 117-130. https://doi.org/10.32604/csse.2021.014081

Received 30 August 2020; Accepted 27 October 2020; Issue published 23 December 2020

Abstract

Regarding the problem of the short driving distance of pure electric vehicles, a battery, super-capacitor, and DC/DC converter are combined to form a hybrid energy storage system (HESS). A fuzzy adaptive filtering-based energy management strategy (FAFBEMS) is proposed to allocate the required power of the vehicle. Firstly, the state of charge (SOC) of the super-capacitor is limited according to the driving/braking mode of the vehicle to ensure that it is in a suitable working state, and fuzzy rules are designed to adaptively adjust the filtering time constant, to realize reasonable power allocation. Then, the positive and negative power are determined, and the average power of driving/braking is calculated so as to limit the power amplitude to protect the battery. To verify the proposed FAFBEMS strategy for HESS, simulations are performed under the UDDS (Urban Dynamometer Driving Schedule) driving cycle. The results show that the FAFBEMS strategy can effectively reduce the current amplitude of the battery, and the final SOC of the battery and super-capacitor is optimized to varying degrees. The energy consumption is 7.8% less than that of the rule-based energy management strategy, 10.9% less than that of the fuzzy control energy management strategy, and 13.1% less than that of the filtering-based energy management strategy, which verifies the effectiveness of the FAFBEMS strategy.

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Citations