Wireless Sensor System for Battery Packs
Lawrence Livermore National Laboratory (LLNL)
Battery Management System with Distributed Wireless Sensors
Today's electric vehicle batteries are expensive and prone to unexpected failure. Batteries are complex systems, and developing techniques to cost-effectively monitor and manage important performance measures while predicting battery cell degradation and failure remains a key technological challenge. There is a critical need for breakthrough technologies that can be practically deployed for superior management of both electric vehicle batteries and renewable energy storage systems.
Project Innovation + Advantages:
LLNL is developing a wireless sensor system to improve the safety and reliability of lithium-ion (Li-Ion) battery systems by monitoring key operating parameters of Li-Ion cells and battery packs. This system can be used to control battery operation and provide early indicators of battery failure. LLNL's design will monitor every cell within a large Li-Ion battery pack without the need for large bundles of cables to carry sensor signals to the battery management system. This wireless sensor network will dramatically reduce system cost, improve operational performance, and detect battery pack failures in real time, enabling a path to cheaper, better, and safer large-scale batteries.
If successful, LLNL's wireless sensor network for large Li-Ion battery packs would improve the safety and reliability of electric energy storage systems.
Advances in energy storage management could reduce the cost and increase the adoption of electric vehicles and renewable energy storage technologies, which in turn would reduce our nation's dependence on foreign sources of energy.
Improving the reliability and safety of electric vehicles and renewable energy storage facilities would enable more widespread use of these technologies, resulting in a substantial reduction in carbon dioxide emissions.
Enabling alternatives to conventional sources of energy could insulate consumers, businesses, and utilities from unexpected price swings.