Shared autonomous electric vehicle systems (SAEVS) combine autonomous driving technology with shared electric vehicle services to provide advantages over traditional shared vehicle systems, including autonomous vehicle relocation and rapid response to user needs. In this study, we seek to enhance the operational efficiency and profitability of SAEVS by considering trip selection and the potential opportunity cost associated with unmet user demands. An integer linear programming (ILP) model is developed using a spatio-temporal state network to optimize the system design planning (e.g., charging facility, vehicle fleet sizing and distribution) and operational decisions (e.g., vehicle operational relocation and trip selection strategy). To handle the computational complexities of this model, we propose a Lagrangian relaxation (LR) algorithm. The performance of the LR algorithm is evaluated through a case study. The results, along with a parameter sensitivity analysis, reveal several key findings: (ⅰ) Allocating vehicles to stations with concentrated early peak demand, distributing charging facilities to stations with high total demand throughout the day and implementing vehicle relocation after the early demand peak can mitigate uneven vehicle distribution; (ⅱ) Implementing trip selection enhances SAEVS profitability; (ⅲ) Increasing opportunity cost meets user demands but at the expense of reduced profit; (ⅳ) It is recommended that SAEVS be equipped with charging facilities of suitable charging power based on operational conditions.
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The sliding process in the friction pair involves highly nonlinear behavior, and the temperature field of the friction pair is affected by numerous parameters. To gain a comprehensive understanding of the temperature field distribution in the friction pair of a hybrid electric vehicle clutch, a thermal structure coupling analysis model of the hybrid electric vehicle clutch was constructed to simulate the sliding process. Building upon this model, an in-depth study was conducted to analyze the impact of various parameters, such as initial speed, engagement oil pressure, dual steel plate thickness, and friction lining material, on the temperature field of friction pair.
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