A method for the prediction of future driving conditions and for the energy management optimisation of a hybrid electric vehicle

被引：11
|
作者：
Donateo, Teresa [1 ]
Pacella, Damiano [1 ]
Laforgia, Domenico [1 ]
机构：
[1] Univ Salento, Dipartimento Ingn Innovaz, I-73100 Lecce, Italy
来源：
INTERNATIONAL JOURNAL OF VEHICLE DESIGN | 2012年 / 58卷 / 2-4期
关键词：
HEVs; hybrid electric vehicles; ecological vehicles; plug-in vehicles; energy management strategy; vehicular communications; traffic simulation; simulation-based prediction; genetic algorithm; clustering algorithm; K-Means algorithm;
D O I：
10.1504/IJVD.2012.047385
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
Vehicular communications are expected to enable the development of Intelligent Cooperative Systems for solving crucial problems related to mobility: road safety, traffic management etc. Information and Communication Technologies could also play an important role in order to optimise the energy management of conventional, hybrid and electrical vehicles and, thus, to reduce their environment impact. In particular, vehicular communications could be used to predict driving conditions with the objective to determine future load power demand. An adaptive energy management strategy for series Hybrid Electric Vehicles (HEVs) based on genetic algorithm optimised maps and the Simulation of Urban Mobility (SUMO) predictor is presented here.
引用
收藏
页码：111 / 133
页数：23
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