| Autor: |
Zhang, Yutian, Gu, Shuxian, Li, Quan, Zeng, Haipeng |
| Zdroj: |
IEEE Computer Graphics and Applications; 2024, Vol. 44 Issue: 3 p54-68, 15p |
| Abstrakt: |
Promoting the development of electric vehicles requires the widespread deployment of charging infrastructure, which poses numerous technical and financial constraints. Despite extensive research focusing on optimizing charging station locations, few studies have accounted for charging station utilization and the factors that influence it. This study aims to evaluate charging station operations and explore charging station utilization to inform planning and facilitate better utilization of funds for expanding charging infrastructure. We present EVCSeer, a visual analytics system that utilizes representative predictive models and well-designed visualizations to analyze factors affecting charging station utilization, compare deployment strategies, and optimize utilization. The system also enables “what-if” analysis of charging station deployments. Two case studies, expert interviews, and a qualitative user study support the validity and usefulness of EVCSeer. |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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