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首页> 外文会议>COTA international conference of transportation professionals >The Prediction Model of Electric Vehicle Charging Demand in Cold Regions Considering Environmental Adaptability
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The Prediction Model of Electric Vehicle Charging Demand in Cold Regions Considering Environmental Adaptability

机译：考虑环境适应性的寒冷地区电动汽车充电需求预测模型

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Cold environments affect electric vehicle battery performance and hinder charging demand predictions using ordinary models. To improve forecasting accuracy of charging demand in cold regions, this paper constructs a model by analyzing the change of charging demand in low temperatures. The two-part model consists of one represented by electric buses and the other represented by social electric vehicles. Charging demand of electric buses is determined by fixed line and unit mileage power consumption, but charging demand of social electric vehicles is more complicated, making it necessary to consider their travel behavior, users' charging preference, battery life, and related factors affecting fast and slow charging demand. Monte Carlo method is used to simulate trip and charging decision-making processes of electric vehicles to obtain time-space distribution of charging demand. Results can be superimposed to get the final cold area electric vehicle charging demand forecast. Validity is proved by example analysis.
机译：寒冷的环境会影响电动汽车的电池性能，并妨碍使用普通模型的充电需求预测。为了提高寒冷地区充电需求的预测准确性，本文通过分析低温充电需求的变化，构建了一个模型。该模型分为两部分，其中一个以电动公交车代表，另一个以社交电动车代表。电动公交车的充电需求由固定线路和单位里程的功耗决定，但是社交电动车的充电需求更为复杂，因此有必要考虑其行驶行为，用户的充电偏好，电池寿命以及影响快速和快速行驶的相关因素。充电需求缓慢。蒙特卡罗方法用于模拟电动汽车的行程和充电决策过程，以获得充电需求的时空分布。可以叠加结果以获得最终的寒冷地区电动汽车充电需求预测。通过实例分析证明了有效性。

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