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By innovatively introducing the current speed information, the vehicle speed optimized fuzzy energy management strategy (VSO-FEMS) for HESS is proposed in this paper. Firstly, the pruned fuzzy rules are formulated by the SOC change of battery and super-capacitor to preallocate the required power of vehicle. Then, the real-time vehicle speed is used to optimize the pre-allocated results based on the principle of vehicle dynamics, so as to realize the optimal allocation of required power. To validate the proposed VSO-FEMS strategy for HESS, simulations were done and compared with other EMSs under the typical urban cycle in China (CYC-CHINA). Results show that the final SOC of battery and super-capacitor are optimized in varying degrees, and the total energy consumption under the VSO-FEMS strategy is 2.43% less than rule-based strategy and 1.28% less than fuzzy control strategy, which verifies the effectiveness of the VSO-FEMS strategy.<\/jats:p>","DOI":"10.1155\/2020\/2073901","type":"journal-article","created":{"date-parts":[[2020,7,24]],"date-time":"2020-07-24T23:31:24Z","timestamp":1595633484000},"page":"1-12","source":"Crossref","is-referenced-by-count":6,"title":["Vehicle Speed Optimized Fuzzy Energy Management for Hybrid Energy Storage System in Electric Vehicles"],"prefix":"10.1155","volume":"2020","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2261-5973","authenticated-orcid":true,"given":"Xizheng","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Electrical and Information Engineering, Hunan Institute of Engineering, Xiangtan, Hunan 411104, China"},{"name":"School of Robotics, Hunan 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