SDSU faculty member receives funding to study lithium-ion batteries

Lithium ion

Shabbir Ahmed, assistant professor in South à£à£Ö±²¥Ðã State University’s Department of Mechanical Engineering, has received a grant from the National Science Foundation to develop algorithms that will accurately measure a battery's state of charge. 

Lithium-ion batteries are widely considered one of the most impactful technological inventions of the last 100 years and have effectively transformed how we function as a society. From iPhones to laptops to electric vehicles, the lithium-ion battery is the most powerful rechargeable battery commercially available and is expected to be utilized even more in the future for sustainable transportation and energy.

South à£à£Ö±²¥Ðã State University assistant professor Shabbir Ahmed is one of the country's leading researchers of lithium-ion batteries and recently received funding from the to better understand the battery's charging capabilities.

"My research is looking to more accurately predict the state of charge and the state of health through different types of measurements," Ahmed said.

Ahmed, who earned his doctorate from Rensselaer Polytechnic Institute in New York, began this work as a postdoctoral scholar at Stanford University. At Rensselaer, he focused his research on modeling ultrasonic guided waves and developing robust algorithm through those models. He then applied that expertise to lithium-ion batteries at Stanford. 

Shabbir Ahmed
Shabbir Ahmed 

The will see Ahmed, a faculty member in the Jerome J. Lohr College of Engineering, utilize ultrasonic guided waves to study lithium-ion battery degradation and to develop robust algorithms for accurate predictions of state of charge, state of health and remaining useful life in real-time.

"The degradation or aging of battery is a natural process as the battery undergoes continuous charge and discharge process during service, limiting the battery’s capability of delivering rated energy and power," Ahmed explained. "This natural degradation may also lead to a poor estimate of state of charge and state of health of the battery, posing safety concerns for demanding applications such as electric vehicles, electric vertical takeoff and landing vehicles, drones and unmanned aerial vehicles."

Lithium-ion batteries function as lithium ions shuffle between the positive and negative sides of the battery via the separator. When a device is "on" (discharging) and providing an electric current, the anode — negative side of the battery — releases lithium ions to the cathode — the positive side — generating a flow of electrons. When the device is plugged in and charging, the opposite happens. Lithium ions are released by the cathode and received by the anode. The amount of charge remaining in a device is essentially the concentration of ions on either side. For example, a fully charged device would see all the lithium ions concentrated on the anode side of battery.

In a lab condition, Ahmed would have a precise measurement of the battery's lithium concentration and state of charge by using different techniques. But that's not feasible for real-world applications.

"When a lithium-ion battery is in use, only the voltage and current information is available, and using only this information, it is difficult to accurately infer the state of charge," Ahmed explained.

To get an accurate measurement, Ahmed places a small sensor on the outside of the battery to send an ultrasonic guided wave signal through the lithium-ion battery. The wave signal allows him to more accurately judge the lithium-ion concentration. The amplitude change of the wave signal give an indication of the lithium-ion concentration, providing an accurate measurement of the battery’s state of charge.

"By analyzing the wave signal's change, I can actually infer more accurately the battery’s state of charge and state of health," Ahmed said.

This information can then be used to develop efficient algorithms to accurately predict the state of health and state of charge in lithium-ion batteries. Companies, especially those producing electric vehicles, would be interested in the accuracy of these algorithms, Ahmed noted.

Republishing

You may republish SDSU News Center articles for free, online or in print. Questions? Contact us at sdsu.news@sdstate.edu or 605-688-6161.