Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.10861 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866908769450983424 |
|---|---|
| author | D'Agostino, Brandon Chen, Jimmy Rajagopal, Ram |
| author_facet | D'Agostino, Brandon Chen, Jimmy Rajagopal, Ram |
| contents | The transition to electric vehicles (EVs) depends heavily on the reliability of charging infrastructure, yet approximately 1 in 5 drivers report being unable to charge during station visits due to inoperable equipment. While regulatory efforts such as the National Electric Vehicle Infrastructure (NEVI) program have established uptime requirements, these metrics are often simplistic, delayed, and fail to provide the diagnostic granularity needed by Charging Site Operators (CSOs). Despite their pivotal role in maintaining and improving site performance, CSOs have been largely overlooked by existing reporting standards. In this paper, we propose a suite of readily computable, actionable performance metrics-Fault Time, Fault-Reason Time, and Unreachable Time-that decompose charger behavior into operationally meaningful states. Unlike traditional uptime, these metrics are defined over configurable periods and distinguish between hardware malfunctions and network connectivity issues. We demonstrate the implementation of these metrics via an open-source tool that derives performance data from existing infrastructure without requiring hardware modifications. A case study involving 98 chargers at a California academic institution spanning 2018-2024 demonstrates that these metrics reveal persistent "zombie chargers" and high-frequency network instability that remain hidden in standard annual reporting. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_10861 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Beyond Uptime: Actionable Performance Metrics for EV Charging Site Operators D'Agostino, Brandon Chen, Jimmy Rajagopal, Ram Systems and Control The transition to electric vehicles (EVs) depends heavily on the reliability of charging infrastructure, yet approximately 1 in 5 drivers report being unable to charge during station visits due to inoperable equipment. While regulatory efforts such as the National Electric Vehicle Infrastructure (NEVI) program have established uptime requirements, these metrics are often simplistic, delayed, and fail to provide the diagnostic granularity needed by Charging Site Operators (CSOs). Despite their pivotal role in maintaining and improving site performance, CSOs have been largely overlooked by existing reporting standards. In this paper, we propose a suite of readily computable, actionable performance metrics-Fault Time, Fault-Reason Time, and Unreachable Time-that decompose charger behavior into operationally meaningful states. Unlike traditional uptime, these metrics are defined over configurable periods and distinguish between hardware malfunctions and network connectivity issues. We demonstrate the implementation of these metrics via an open-source tool that derives performance data from existing infrastructure without requiring hardware modifications. A case study involving 98 chargers at a California academic institution spanning 2018-2024 demonstrates that these metrics reveal persistent "zombie chargers" and high-frequency network instability that remain hidden in standard annual reporting. |
| title | Beyond Uptime: Actionable Performance Metrics for EV Charging Site Operators |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2601.10861 |