ADMM-Based Decentralized Electric Vehicle Charging with Trip Duration Limits

He, Gaoqi; Chai, Zhifu; Lu, Xianju; Kong, Fanxin; Bing, Sheng

doi:10.1109/rtss46320.2019.00020

Cited by 4 publications

(1 citation statement)

References 30 publications

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“…Although EVs have the advantages of environmental protection and low usage cost, there are still many technical problems to be solved urgently. The charging problem is one of the most prominent difficulties 7,8 . On the one hand, it takes a long time to fully charge an EV.…”

Section: Introductionmentioning

confidence: 99%

Charging stations‐oriented electric vehicle charging strategy based on battery characteristics

Sun

Chen

et al. 2021

Softw Pract Exp

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Summary In recent years, electric vehicles (EVs) receive intensive attention due to their environment‐friendly nature and outstanding energy efficiency. However, there are still obstacles in EVs' popularity. Battery related issues are most concerned from users' perspective. While the evolution in battery technology may help to address the aforementioned problems eventually, other solutions are in urgent demand for the time being. In this paper, we propose an innovative charge scheduling method that could significantly improve EV users' charging experience with the nowadays battery technology. Specifically, the proposed method takes into account the characteristics of the batteries to be charged as well as the constraints of the external power grid; thus, a plan can be devised for efficiently allocating the power of the charging station to the EVs through cyber‐physical system. Our method prioritizes jobs based on their marginal utilities to maximize user satisfaction with limited power resource. The power allocation in our method is managed globally and constrained by specific rules to avoid waste or overload in the power grid. Lastly, we simulate several power scheduling methods in charging stations, which validates that the user satisfaction under our method is higher than that of other traditional method.

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Section: Introductionmentioning

confidence: 99%

Charging stations‐oriented electric vehicle charging strategy based on battery characteristics

Sun

Chen

et al. 2021

Softw Pract Exp

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Optimizing Cross-Line Dispatching for Minimum Electric Bus Fleet

Wang

Song

Fan

et al. 2023

IEEE Trans. on Mobile Comput.

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Real-time Attack-recovery for Cyber-physical Systems Using Linear-quadratic Regulator

Zhang

Kong

et al. 2021

ACM Trans. Embed. Comput. Syst.

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The increasing autonomy and connectivity in cyber-physical systems (CPS) come with new security vulnerabilities that are easily exploitable by malicious attackers to spoof a system to perform dangerous actions. While the vast majority of existing works focus on attack prevention and detection, the key question is “what to do after detecting an attack?”. This problem attracts fairly rare attention though its significance is emphasized by the need to mitigate or even eliminate attack impacts on a system. In this article, we study this attack response problem and propose novel real-time recovery for securing CPS. First, this work’s core component is a recovery control calculator using a Linear-Quadratic Regulator (LQR) with timing and safety constraints. This component can smoothly steer back a physical system under control to a target state set before a safe deadline and maintain the system state in the set once it is driven to it. We further propose an Alternating Direction Method of Multipliers (ADMM) based algorithm that can fast solve the LQR-based recovery problem. Second, supporting components for the attack recovery computation include a checkpointer, a state reconstructor, and a deadline estimator. To realize these components respectively, we propose (i) a sliding-window-based checkpointing protocol that governs sufficient trustworthy data, (ii) a state reconstruction approach that uses the checkpointed data to estimate the current system state, and (iii) a reachability-based approach to conservatively estimate a safe deadline. Finally, we implement our approach and demonstrate its effectiveness in dealing with totally 15 experimental scenarios which are designed based on 5 CPS simulators and 3 types of sensor attacks.

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ADMM-Based Decentralized Electric Vehicle Charging with Trip Duration Limits

Cited by 4 publications

References 30 publications

Charging stations‐oriented electric vehicle charging strategy based on battery characteristics

Charging stations‐oriented electric vehicle charging strategy based on battery characteristics

Optimizing Cross-Line Dispatching for Minimum Electric Bus Fleet

Real-time Attack-recovery for Cyber-physical Systems Using Linear-quadratic Regulator

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