Predicting the Power Load of EV in Public Transportation Sector Based on Fuzzy Clustering Analysis

Abstract:

The electric demand of EV in the public transportation sector is increasingly important to the future city’s power distribution and even infrastructure construction. According to the characteristic of public transportation, this paper analyzed the influence factors of EV power load and they were divided into three parts. Then a predicting model of EV power load in public transportation based on fuzzy clustering analysis method was put forward. We used BP (Back Propagation) neural network algorithm to solve the fuzzy clustering analysis problem. Finally the predicting model was operated in a practical example. Results showed that this predicting model of EV power load in public transportation based on fuzzy clustering analysis could be appropriately applied in reality.

• Periodical: Advanced Materials Research (Volumes 953-954)
• Pages: 1349-1353
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.953-954.1349
• Online since: June 2014
• Authors: Jun Chen, Chun Lin Guo, Wen Chen, Zhe Ci Tang, Zong Feng Li, Qing Hai Ou, Zi Guan Zhou, Yan Zhen
• Keywords: Electric Vehicle (EV), Fuzzy Clustering, Load Predicting, Public Transportation

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