Project Summary

The Internet of Things (IoT) has become one of the major future trends. Its proliferation has led to an explosive number of battery powered wireless devices. Battery life has always been one of the biggest limiting factors of those wireless devices which poses different challenges thourghout their operation.

This project deals with battery health management under battery group replacement requirement. In practice, there are many applications where IoT wireless devices (sensors in particular) are installed at hard-to-reach areas or remote locations, where the planning and logistics of a maintennace trip can be very costly. To reduce the cost, battery group replacement is often required in these scenarios, i.e. replace all batteries in a sensor network on a maintenance trip, instead of replacing just one or a few. Unfortunately, existing methods for battery management exclusively aim to extend lifetime of individual batteries as much as possible, lacking a system level view. A consequence of applying such algorithms is that batteries in a sensor network tend to fail at very different times, posing significant difficulty on planning and scheduling of group replacement activities.

The research objective of this project is to develop an active battery health management framework such that batteries in a sensor network will degrade more uniformly to achieve similar end-of-life times, which will significantly simplify the implementation of a group battery replacement policy. In addition, it will effectively extend lifetime of batteries as a group, as it reduces early failures of the battery individuals that cripples the sensor network and triggers a group replacement request. The controlled battery health degradation processes are made possible by dynamically adjusting the quality of service levels assigned to wireless nodes, based on the predicted battery remaining useful lifetime as a measure of battery health. The success of this project will significantly reduce the overall battery maintenance cost.

Leaders

1. Dr. Hongki Jo (PI) Associate Professor, Department of Civil Engineering University of Arizona,Tucson

2. Dr. Jian Liu (Co-PI) Associate Professor, Department of Systems and Industrial Engineering University of Arizona, Tucson

Contributors

1. Jong-Hyun Jeong CAEM Department, University of Arizona, Tucson

2. Tahsin Afroz Hoque Nishat PhD student in the CAEM Department, University of Arizona, Tucson

Articles

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