提高网联车辆能效以优化交通流

IF 7 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Zeinab Shahbazi, Slawomir Nowaczyk
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引用次数: 0

摘要

在城市环境中,交通灯的普及往往导致交通模式的波动和车辆之间能源利用的增加。认识到这一挑战,本研究通过引入基于多路口的生态方法和偏离策略(M-EAD)来解决交通信号灯对电动汽车(ev)能源效率的不利影响。这一创新策略旨在提高城市交通的各个方面,包括车辆能效、交通流量优化和电池寿命,同时确保令人满意的驾驶体验。M-EAD策略分为两个不同的阶段:首先,优化交通信号灯的环保绿色信号窗口,主要关注通过解决最短路径问题来最大限度地减少出行延误。随后,它采用后退地平线框架,并利用迭代动态规划算法来细化速度轨迹。总体目标是通过确定电动汽车在城市环境中的最佳速度轨迹,减少能源消耗和电池磨损。此外,研究还通过道路车辆试验验证了该方法在现实世界中的有效性,证明了其在实际道路场景中的可行性和实用性。在所提出的案例中,仿真结果显示出显著的成果,能耗降低了0.92%,电池磨损降至仅0.0017%。在城市交通能效亟待解决的背景下,本研究不仅提出了一种以M-EAD战略为形式的解决方案,同时也为城市交通可持续发展和电动汽车性能优化领域做出了贡献。通过解决交通信号灯带来的挑战,这项工作为提高城市交通系统的可持续性和效率提供了宝贵的见解和实际意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing Energy Efficiency in Connected Vehicles for Traffic Flow Optimization
In urban settings, the prevalence of traffic lights often leads to fluctuations in traffic patterns and increased energy utilization among vehicles. Recognizing this challenge, this research addresses the adverse effects of traffic lights on the energy efficiency of electric vehicles (EVs) through the introduction of a Multi-Intersections-Based Eco-Approach and Departure strategy (M-EAD). This innovative strategy is designed to enhance various aspects of urban mobility, including vehicle energy efficiency, traffic flow optimization, and battery longevity, all while ensuring a satisfactory driving experience. The M-EAD strategy unfolds in two distinct stages: First, it optimizes eco-friendly green signal windows at traffic lights, with a primary focus on minimizing travel delays by solving the shortest path problem. Subsequently, it employs a receding horizon framework and leverages an iterative dynamic programming algorithm to refine speed trajectories. The overarching objective is to curtail energy consumption and reduce battery wear by identifying the optimal speed trajectory for EVs in urban environments. Furthermore, the research substantiates the real-world efficacy of this approach through on-road vehicle tests, attesting to its viability and practicality in actual road scenarios. In the proposed case, the simulation results showcase notable achievements, with energy consumption reduced by 0.92% and battery wear minimized to a mere 0.0017%. This research, driven by the pressing issue of urban traffic energy efficiency, not only presents a solution in the form of the M-EAD strategy but also contributes to the fields of sustainable urban mobility and EV performance optimization. By tackling the challenges posed by traffic lights, this work offers valuable insights and practical implications for improving the sustainability and efficiency of urban transportation systems.
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来源期刊
Smart Cities
Smart Cities Multiple-
CiteScore
11.20
自引率
6.20%
发文量
0
审稿时长
11 weeks
期刊介绍: Smart Cities (ISSN 2624-6511) provides an advanced forum for the dissemination of information on the science and technology of smart cities, publishing reviews, regular research papers (articles) and communications in all areas of research concerning smart cities. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible, with no restriction on the maximum length of the papers published so that all experimental results can be reproduced.
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