Toward electric vehicle trip prediction for a charging service provider

O. Sundstrom, Olivier Corradi, C. Binding
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引用次数: 12

Abstract

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.
基于充电服务提供商的电动汽车行程预测研究
本文概述了对插电式电动汽车进行行程预测的必要性和要求,以优化推导插电式电动汽车的充电行为。给出了充电服务提供商行程预测所需的信息,提出了一种新的行程预测模型。提出的模型是一个半马尔可夫模型,预测下一个到达地点和当前地点的等待时间。结合对能量需求的预测和到预测地点的行程持续时间,为确定充电行为提供了基础。将提出的预测模型与使用昨天行程预测今天行程的朴素预测器进行比较。结果表明,该模型预测下一个位置的准确率为84%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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