基于卫星信息的电动汽车远程瞬时功耗估算

IF 2.9 Q2 ROBOTICS
Robotics Pub Date : 2023-11-08 DOI:10.3390/robotics12060151
Franco Jorquera, Juan Estrada, Fernando Auat
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引用次数: 0

摘要

瞬时功耗(IPC)对于理解电动汽车(ev)的自主性和高效能源使用至关重要。然而,有效的车辆管理需要事先知道它们是否能完成一条轨迹,这就需要估计沿途的IPC消耗。提出了一种基于卫星信息的电动汽车IPC估计方法。该方法包括研究区域的地理定位和地理参考,轨迹规划,从地图中提取高度特征以创建高度剖面图,收集地形特征,并最终计算IPC。在粘土地形上获得了最准确的估计,与测量值相比误差为5.43%。对于路面和砾石地形,误差分别为19.19%和102.02%。该方法利用卫星信息提供了三种不同地形的IPC估计,并与现场实验相证实。这显示了它在工业环境下电动汽车管理的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Remote Instantaneous Power Consumption Estimation of Electric Vehicles from Satellite Information
Instantaneous Power Consumption (IPC) is relevant for understanding the autonomy and efficient energy usage of electric vehicles (EVs). However, effective vehicle management requires prior knowledge of whether they can complete a trajectory, necessitating an estimation of IPC consumption along it. This paper proposes an IPC estimation method for an EV based on satellite information. The methodology involves geolocation and georeferencing of the study area, trajectory planning, extracting altitude characteristics from the map to create an altitude profile, collecting terrain features, and ultimately calculating IPC. The most accurate estimation was achieved on clay terrain with a 5.43% error compared to measures. For pavement and gravel terrains, 19.19% and 102.02% errors were obtained, respectively. This methodology provides IPC estimation on three different terrains using satellite information, which is corroborated with field experiments. This showcases its potential for EV management in industrial contexts.
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来源期刊
Robotics
Robotics Mathematics-Control and Optimization
CiteScore
6.70
自引率
8.10%
发文量
114
审稿时长
11 weeks
期刊介绍: Robotics publishes original papers, technical reports, case studies, review papers and tutorials in all the aspects of robotics. Special Issues devoted to important topics in advanced robotics will be published from time to time. It particularly welcomes those emerging methodologies and techniques which bridge theoretical studies and applications and have significant potential for real-world applications. It provides a forum for information exchange between professionals, academicians and engineers who are working in the area of robotics, helping them to disseminate research findings and to learn from each other’s work. Suitable topics include, but are not limited to: -intelligent robotics, mechatronics, and biomimetics -novel and biologically-inspired robotics -modelling, identification and control of robotic systems -biomedical, rehabilitation and surgical robotics -exoskeletons, prosthetics and artificial organs -AI, neural networks and fuzzy logic in robotics -multimodality human-machine interaction -wireless sensor networks for robot navigation -multi-sensor data fusion and SLAM
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