Dynamic Deep Cycling Testing: The Use of Dynamic Deep Cycling Testing to Predict Battery State-of-Health in Outside Plant Environments (2023)

By Michael Nispel, Comcast Cable; Alexander Falcon, Comcast Cable; Kang Lin, Comcast Cable; Paul Schauer, Comcast Cable; Cory Thompson, Comcast Cable

Battery health is critical to the reliability of the outside plant network for cable internet providers. Unfortunately, the health of a battery is continuously being degraded due to use, environment, abuse, and many other known and unknown factors. This makes the change in battery performance variable and difficult to predict, with a battery’s calendar age an ineffective method to determine performance. Although discharge events can be tracked readily, the challenge is that the vast majority of outages result in partial battery discharges, with power restored at inconsistent and variable times. To address this challenge, Comcast set out to use a partial discharge analysis to determine the state-of-health (SoH) for each battery powering the over 250 thousand outside plant power supplies in its network. SoH is defined here as the percentage capacity (or runtime) a battery can deliver as compared to its new or original rating. This was done without removing the battery from the site, without the need for any external equipment, without the need to visit the site, and without ever having the downstream load unprotected. Previously, the replacement approach for power supply batteries was based on the calendar age of the battery. This did not account for the many factors that may have degraded the battery prematurely. As such, it may have resulted in the early replacement of batteries in good health or the delay in removing batteries in poor health, which translates directly to a false sense of reliability. The absence of a view into battery health made capital planning more difficult, as battery attributes (model, count, age, etc.) were the only information available to justify replacement. By providing a health score for batteries, long-range capital planning can focus on the true condition of batteries rather than their calendar age. This view into asset condition allows for the most effective use of resources by targeting the locations of greatest need. Views into future years’ battery replacement quantities are much more predictable using current battery health metrics and their degradation rate. The replacement of the batteries of greatest need also significantly improves the reliability of the outside plant powering network. Power supplies can withstand commercial power interruptions more effectively when poor performing batteries are identified and replaced. Improved power supply reliability directly impacts customers who may have a backup generator available or may continue to have commercial power during isolated power outages. Providing front line maintenance technicians with a view into each battery’s SoH promotes an effective, efficient, and proactive maintenance strategy for power supply battery replacements. A SoH assessment was accomplished by developing a unique algorithm used to predict the performance of outside plant batteries when subjected to a controlled, partial discharge event, specific to the power supply’s unique load. In this way, Comcast will be improving the reliability of the outside plant network by advancing beyond a calendar age replacement cycle. Access to this information aids in the continued effort to improve infrastructure reliability. The use of a dynamic deep cycle battery discharge test with a prediction of the battery state-of-health will continue to improve Comcast’s best-in-class powering network.

By clicking the "Download Paper" button, you are agreeing to our terms and conditions.

Similar Papers

A New Model for Power Plant and Health Estimation
By Kang Lin, PhD, Michael Nispel; Comcast
2022
Photon Avatars in the Comcast Cosmos: An End-to-End View of Comcast Core, Metro and Access Networks
By Venk Mutalik, Steve Ruppa, Fred Bartholf, Bob Gaydos, Steve Surdam, Amarildo Vieira, Dan Rice; Comcast
2022
Key Learnings from Comcast’s Use of Open Source Software in the Access Network
By Louis Donofrio & Qin Zang, Comcast Cable; Vignesh Ramamurthy, Infosys Consulting
2020
Two Years Of Deploying ITV/EBIF Applications – Comcast’s Lessons Learned
By Robert Dandrea, Ph.D., Comcast Cable
2010
Comcast Underground: Innovative Fiber Deployments Over Existing Underground Critical Infrastructure
By Venk Mutalik, Pat Wike, Doug Combs, Alan Gardiner, Dan Rice; Comcast
2022
Machine Learning and Telemetry Improves Outside Plant Power Resiliency for More Reliable Networks
By Stephanie Ohnmacht, Matthew Stehman; Comcast
2022
Operational Practices for Energy Conservation/Sustainability Measures in the Cable Outside Plant
By Daniel Howard, Enunciant, LLC; Chris Day, Analog Devices; Kevin Gantt, CommScope; John Holobinko, Cisco; Rob Howald & Dan Marut, Comcast; Dick Kirsche, ConsultKirsche; Todd Loeffelholz, Alpha; Kathleen Miles, PG&E; Rene Spee, Coppervale; Dean Stoneback, SCTE•ISBE; John Ulm, Arris; Lamar West & Dan Whitehouse, Hitachi Consulting
2018
Intelligent Outside Plant Power Operations with Machine Learning
By Matthew Stehman, Comcast; Chris D’Andrea, Comcast; Ilana Weinstein, Comcast
2023
Eating the Energy Elephant One Byte at A Time: Managing Energy Consumption Across the Cable Network
By Katie Flynn, Comcast Cable; Budd Batchelder, Comcast Cable
2023
Watts In An ID? Utility-Tied, Energy Consuming Asset Life Cycle Management
By Richard Grivalsky, Comcast Cable; Anusha Nukala, Comcast Cable; Alexander Falcon, Comcast Cable; Shaju Kezakykanirakat, Comcast Cable
2023
More Results >>