泰国电动摩托车对能源消耗的影响研究

Siriporn Ruensumruay, W. Pattaraprakorn, V. Chutiprapat, P. Bhasaputra
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引用次数: 4

摘要

为了防止能源安全问题,减少交通运输部门的温室气体排放,电动汽车是防止这一问题的对策途径。泰国一半以上的车辆是摩托车,包括私人和公共摩托车。本研究采用人工神经模糊推理系统(ANFIS)方法建立摩托车和电动摩托车的能耗模型。本研究中摩托车的物理和技术信息收集自曼谷和大都市区的问卷调查。利用方差分析技术确定影响摩托车能耗的显著因素,即发动机尺寸(cc.)、车龄(year)、行驶距离(km/day)、平均车速(km/hr)和载客量。选取这些显著因子作为模型的输入数据,输出数据为能耗(MJ/km)。研究结果表明,摩托车与电动摩托车的能源经济性比较。通过对未来摩托车和电动摩托车数量的多情景模拟,对交通运输领域的能源消耗进行了模拟。最后,建立的模型可以预测交通能耗,为未来的交通能源规划做准备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The study on the effect of electric motorcycle to energy consumption in Thailand
To prevent the energy security problem and reduce greenhouse gas from transportation sector, electric vehicle is the way of countermeasure to prevent this issue. Over half of all vehicles in Thailand are motorcycles which are private and public motorcycle. This research is developing the energy consumption model of motorcycle and electric motorcycle by used Artificial Neuro-Fuzzy Inference Systems (ANFIS) method. The physical and technical information of motorcycles in this study are collected from questionnaire that survey in Bangkok and metropolitan area. ANOVA technique is used to determine the significant factors that affect energy consumption of motorcycles which are engine size (cc.), age (year), distance (km/day), average speed (km/hr.) and number of passenger. These significant factors are selected to be the input data of the model whereas the output data is energy consumption (MJ/km.). The result of this research shown that the comparted energy economy of the motorcycle and electric motorcycle. Furthermore, energy consumption in transportation sector is simulated by multi scenario of the number of motorcycle and electric motorcycle in the future. Finally, this developed model can forecast the energy consumption in order to preparation of future transportation energy planning.
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