Multi-Object Optimization of Battery Management for Electric Vehicle Platooning Considering Energy Consumption and Battery Health

IF 2.5 4区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Zhicheng Li, Huawei Niu, Haoyu Miao, Yang Wang
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Abstract

It is a critical problem to improve battery energy management for electric vehicle platooning systems. Moreover, different from internal combustion engine vehicles, regenerating braking is widely used to recover part of the energy in the electric vehicle when it is braking. This paper presents the optimization method of battery energy management for electric vehicle platooning with regenerating braking. By investigating the force analysis of platooning and the battery model, a new optimization strategy is presented to minimize the cost of the battery for both charging and maintaining. The cost of the battery is not only related to the state of charge (SoC) but also concerned with the state of health (SoH) due to the battery aging phenomenon. Thus, a new cost function concerned with SoC and SoH consumption is presented. Further, the optimization problem is addressed by the dynamic programming method combined with the successive convex approximation method. Finally, it is discussed how to choose the trade-off weights to adapt to different actual situations, and simulation results are provided to verify the effectiveness and advantages of the proposed methods.

Abstract Image

Abstract Image

Abstract Image

考虑能量消耗和电池健康的电动汽车队列行驶电池管理多目标优化
提高电池能量管理水平是电动汽车队列行驶系统的关键问题。而且,与内燃机汽车不同的是,电动汽车在制动时广泛采用再生制动来回收部分能量。提出了带再生制动的电动汽车队列行驶中电池能量管理的优化方法。通过对车队动力分析和电池模型的研究,提出了一种新的优化策略,使电池的充电和维护成本最小化。电池的成本不仅与电池的荷电状态(SoC)有关,还与电池老化现象导致的健康状态(SoH)有关。因此,提出了一种新的SoC和SoH消耗成本函数。在此基础上,采用动态规划法结合逐次凸逼近法解决了优化问题。最后,讨论了如何根据不同的实际情况选择权衡权值,并通过仿真结果验证了所提方法的有效性和优越性。
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来源期刊
IET Intelligent Transport Systems
IET Intelligent Transport Systems 工程技术-运输科技
CiteScore
6.50
自引率
7.40%
发文量
159
审稿时长
3 months
期刊介绍: IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following: Sustainable traffic solutions Deployments with enabling technologies Pervasive monitoring Applications; demonstrations and evaluation Economic and behavioural analyses of ITS services and scenario Data Integration and analytics Information collection and processing; image processing applications in ITS ITS aspects of electric vehicles Autonomous vehicles; connected vehicle systems; In-vehicle ITS, safety and vulnerable road user aspects Mobility as a service systems Traffic management and control Public transport systems technologies Fleet and public transport logistics Emergency and incident management Demand management and electronic payment systems Traffic related air pollution management Policy and institutional issues Interoperability, standards and architectures Funding scenarios Enforcement Human machine interaction Education, training and outreach Current Special Issue Call for papers: Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf
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