Abstract
Compared with traditional fuel vehicles, electric vehicles have the advantages of low carbon, low pollution and low noise. At present, major auto manufacturers are actively exploring the field of electric vehicles. In the future, electric vehicles will become the leading force in the automotive field. However, the problems of short battery life, insufficient cruising range and slow charging time of electric vehicles have been criticized. Battery capacity is an important indicator of battery health and directly reflects the health of the battery. This paper proposes a big data-based approach to assess the capacity of electric bus batteries. First by getting the vehicle’s history data, analysis the SOC change of the vehicle and battery discharge power relations, with a certain amount of data as the training set, the regression algorithm is used to construct the electric vehicle battery capacity prediction model. The model is used to determine the average capacity of vehicle batteries in stages. The average capacity is compared with the capacity values of different stages to achieve an assessment of the health status of the electric bus battery.
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Li, Y., Fang, W., Zou, F., Wang, S., Xu, C., Dong, W. (2020). State Evaluation of Electric Bus Battery Capacity Based on Big Data. In: Pan, JS., Lin, JW., Liang, Y., Chu, SC. (eds) Genetic and Evolutionary Computing. ICGEC 2019. Advances in Intelligent Systems and Computing, vol 1107. Springer, Singapore. https://doi.org/10.1007/978-981-15-3308-2_61
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DOI: https://doi.org/10.1007/978-981-15-3308-2_61
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