Optimal control strategy for electric vehicle platoons in dynamic wireless charging lane considering charge demand differences

Yang Wang, Minghui Ma, Shidong Liang, Yansong Wang and Ningning Liu

Physica A: Statistical Mechanics and its Applications, 2024, vol. 655, issue C

Abstract: During peak traffic hours in merging areas, traffic demand often exceeds supply, making it difficult to eliminate traffic congestion, though it can be mitigated to some extent. As a result, congestion is inevitable. Deploying Dynamic Wireless Charging (DWC) lanes in these low-speed zones can provide electric vehicles with more charging time during unavoidable congestion. Based on this analysis, DWC lanes could be strategically located near frequently congested merging areas. However, by applying certain control measures and guiding vehicles to adjust their speed during congestion, low-battery vehicles can receive more charging time, while high-battery vehicles can accelerate through the merging area, creating a win-win scenario. Existing research focuses on intersections and single-vehicle charging, overlooking potential applications near merging areas and the varying charging needs among vehicles. To address this gap, this paper introduces an optimized control strategy for electric vehicle platoons considering their charging requirements. The proposed scheme assumes DWC lanes are deployed ahead of merging areas in congested ways, leveraging low-speed movement during merging for charging. We assign different charging values to each vehicle based on battery levels, providing a solid basis for control. In order to manage platoons with varying battery capacities, we propose two control schemes for platoon leaders: Self-oriented Control and Group-oriented Control. At the microscopic level, we consider the impact of car-following models on fleet behavior, employing a different car-following models for control. At the macroscopic level, we design experiments on mainline and ramp sections under various Market Penetration Rates (MPRs) to assess the impact of intelligent connected vehicle penetration on traffic flow. Finally, we validate the proposed control strategies using SUMO simulations. Self-oriented Control and Group-oriented Control each prove effective in different scenarios. Furthermore, inappropriate selection of car-following models during simulations may lead to erroneous conclusions. This study underscores the potential of connected and autonomous vehicles in addressing diverse charging needs on DWC facilities.

Keywords: Connected automated electric vehicle; Human driving electric vehicle; Electric vehicle platoon; Dynamic wireless charging; Car-following model (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:655:y:2024:i:c:s037843712400699x

DOI: 10.1016/j.physa.2024.130190

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