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Toward electric vehicle trip prediction for a charging service provider

机译:面向充电服务提供商的电动汽车行程预测

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This paper outlines the need for and the requirements of trip prediction to optimally derive the charging behavior of plug-in electric vehicles. The information required for trip prediction by a charging-service provider is shown, and a novel trip prediction model is proposed. The proposed model is a semi-Markov model that predicts the next arrival location and the waiting time at the current location. Combining this with a prediction of the energy need and the duration of the trip to the predicted location provides a basis for determining the charging behavior. The proposed prediction model is compared with a naive predictor that uses yesterday's trips to predict today's trips. It is shown that the proposed model predicts the next location with 84% accuracy.
机译:本文概述了对行程预测进行优化得出插电式电动汽车充电行为的需求和要求。显示了收费服务提供商进行行程预测所需的信息,并提出了一种新颖的行程预测模型。所提出的模型是半马尔可夫模型,可预测下一个到达位置和当前位置的等待时间。将此与能量需求的预测以及到预测位置的行程持续时间相结合,为确定充电行为提供了基础。将拟议的预测模型与使用昨天的行程来预测今天的行程的幼稚预测器进行比较。结果表明,提出的模型以84%的精度预测下一个位置。

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