Mr. Yuxi Li Profile

Yuxi Li

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Proceedings Article | 18 July 2023 Paper

Research on design of a mobile charging vehicle

Ji Zheng, Yuxi Li, Minjie Du

Proceedings Volume 12722, 1272252 (2023) https://doi.org/10.1117/12.2679370

KEYWORDS: Design and modelling, Data transmission

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With the increasing desire for intelligent goods, which has occurred numerous issues for technology developers, especially in the area of new energy vehicles. Several instances exist in which intelligent robots or autonomous vehicles may automatically patrol the line. However, few goods can be made a larger advance in the poor endurance. Through utilizing mobile refueling station as a starting point, this paper will establish a service that can offer mobile charging for automobiles during regular driving by following and chasing. Utilizing a pair of master-slave electric cars, the mobile charging design will be simulated. Additionally, The relative position between two vehicles is managed by overtaking and counter-overtaking and the trolley employs a five-way grayscale tracing module as its primary method of patrolling and track element detection. Adjustment parameter, the chasing and overtaking portion are utilized as ultrasonic distance measurement module to transmit back the distance information of two cars through the serial port in real time. From our extensive experimental results, we can conclude that the system as a whole accurately replicates the numerous functional needs of the actual world and attains excellent performance indices.

Proceedings Article | 25 May 2023 Paper

Application of particle swarm optimization algorithm in address, taking food delivery cabinets in communities with high-rise buildings neighbourhoods as an example

Yuxi Li, Ge Zhu, Ji Zheng

Proceedings Volume 12712, 127120J (2023) https://doi.org/10.1117/12.2679135

KEYWORDS: Particle swarm optimization, Buildings, Particles, Data modeling, Nonlinear optimization, Matrices, Mathematical modeling

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With the development of the takeaway industry, the demand for space to deposit takeaway food increases rapidly. Currently, an increasing number of office buildings and communities are equipped with food delivery cabinets. However, the conventionally inconsiderate site selection has incurred problems of poor experience for takeaway consumers. In this case, this paper applied the center-of-gravity method to build models for consumers' complaint rate and distance to the food delivery cabinet. The models are solved using particle swarm optimization (PSO) while they are subject to nonconvex functions due to the large volume of data. Compared with conventional site planning, this approach evades local optimal solution, and PSO starts to converge at a favorable rate from the early phase (the 40th iteration). Therefore, the PSO algorithm is efficient in the site planning practice of food delivery cabinets and generates accurate results, offering a brand-new perspective for it.

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