Stanford University researchers are developing the ability to measure power and storage capacity of batteries as they age, the university announced.
“Scientists at Stanford University offer a way to predict the true condition of a rechargeable battery in real-time. The new algorithm combines sensor data with computer modeling of the physical processes that degrade lithium-ion battery cells to predict the battery’s remaining storage capacity and charge level,” it noted.
Simona Onori, assistant professor of energy resources engineering in Stanford’s School of Earth, Energy & Environmental Sciences reported: “We have exploited electrochemical parameters that have never been used before for estimation purposes.” The research appears Sept. 11 in the journal IEEE Transactions on Control Systems Technology.
Currently automakers add spare capacity to meet unknown amounts of fading which adds to cost and the use of scarce, and sometimes toxic, materials. The research will help better estimate actual capacity allowing for smaller batteries and greater driving range in EVs.
“With our model, it’s still important to be careful about how we are using the battery system,” Onori explained. “But if you have more certainty around how much energy your battery can hold throughout its entire lifecycle, then you can use more of that capacity. Our system reveals where the edges are, so batteries can be operated with more precision.”
Accuracy of the predictions are within 2 percent of actual battery life from the experiments, according to the paper. This allows old electric car batteries to be used storing energy for the power grid. “As it is now, batteries retired from electric cars will vary widely in their quality and performance,” Onori said. “There has been no reliable and efficient method to standardize, test or certify them in a way that makes them competitive with new batteries custom-built for stationary storage.”
Electric car battery cells account for about 30 percent of the total vehicle cost. The research provides a more accurate method of measuring lithium battery degradation.
“The team focused their experiments on a type of lithium-ion battery commonly used in electric vehicles (lithium nickel manganese cobalt oxide) to estimate key internal variables such as lithium concentration and cell capacity. But the framework is general enough that it should be applicable to other kinds of lithium-ion batteries and to account for other mechanisms of battery degradation,” the research paper reported.
“We showed that our algorithm is not just a nice theoretical work that can run on a computer,” Onori said. “Rather, it is a practical, implementable algorithm which, if adopted and used in cars tomorrow, can result in the ability to have longer-lasting batteries, more reliable vehicles and smaller battery packs.”