Systematic Evaluation of a Connected Vehicle-Enabled Freeway Incident Management System DOI Creative Commons
Hao Yang, Jinghui Wang

World Electric Vehicle Journal, Journal Year: 2025, Volume and Issue: 16(2), P. 59 - 59

Published: Jan. 21, 2025

Freeway incidents block road lanes and result in increasing travel time delays. The intense lane changes of upstream vehicles may also lead to capacity drop more congestion. Connected (CVs) offer a viable solution minimize the impact such via monitoring status providing real-time driving guidance. This paper evaluates performance an existing CV-enabled incident management system, which minimizes by effectively leading CVs bypass spots. study comprehensively quantifies effects system parameters (speed weight lane-changing inertia), control segment length, information-updating intervals. analysis identifies optimal settings for vehicle Additionally, this influence CV market penetration rates (MPRs), network volume-to-capacity ratios, understand benefits under varying connected environments traffic conditions. results reveal that with proposed overall delays can be reduced up 45% congestion caused mitigated quickly.

Language: Английский

State of the Art in Electric Batteries’ State-of-Health (SoH) Estimation with Machine Learning: A Review DOI Creative Commons
Giovane Ronei Sylvestrin, Joylan Nunes Maciel, Márcio Luís Munhoz Amorim

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(3), P. 746 - 746

Published: Feb. 6, 2025

The sustainable reuse of batteries after their first life in electric vehicles requires accurate state-of-health (SoH) estimation to ensure safe and efficient repurposing. This study applies the systematic ProKnow-C methodology analyze state art SoH using machine learning (ML). A bibliographic portfolio 534 papers (from 2018 onward) was constructed, revealing key research trends. Public datasets are increasingly favored, appearing 60% studies reaching 76% 2023. Among 12 identified sources covering 20 from different lithium battery technologies, NASA’s Prognostics Center Excellence contributes 51% them. Deep (DL) dominates field, comprising 57.5% implementations, with LSTM networks used 22% cases. also explores hybrid models emerging role transfer (TL) improving prediction accuracy. highlights potential applications predictions energy informatics smart systems, such as grids Internet-of-Things (IoT) devices. By integrating estimates into real-time monitoring systems wireless sensor networks, it is possible enhance efficiency, optimize management, promote practices. These reinforce relevance machine-learning-based resilience sustainability systems. Finally, an assessment implemented algorithms performances provides a structured overview identifying opportunities for future advancements.

Language: Английский

Citations

1
Systematic Evaluation of a Connected Vehicle-Enabled Freeway Incident Management System DOI Creative Commons
Hao Yang, Jinghui Wang

World Electric Vehicle Journal, Journal Year: 2025, Volume and Issue: 16(2), P. 59 - 59

Published: Jan. 21, 2025

Freeway incidents block road lanes and result in increasing travel time delays. The intense lane changes of upstream vehicles may also lead to capacity drop more congestion. Connected (CVs) offer a viable solution minimize the impact such via monitoring status providing real-time driving guidance. This paper evaluates performance an existing CV-enabled incident management system, which minimizes by effectively leading CVs bypass spots. study comprehensively quantifies effects system parameters (speed weight lane-changing inertia), control segment length, information-updating intervals. analysis identifies optimal settings for vehicle Additionally, this influence CV market penetration rates (MPRs), network volume-to-capacity ratios, understand benefits under varying connected environments traffic conditions. results reveal that with proposed overall delays can be reduced up 45% congestion caused mitigated quickly.

Language: Английский

Citations

0