{"id":8599,"date":"2014-01-20T12:30:09","date_gmt":"2014-01-20T19:30:09","guid":{"rendered":"http:\/\/cafe.foundation\/blog\/?p=8599"},"modified":"2014-01-21T12:47:17","modified_gmt":"2014-01-21T19:47:17","slug":"8599","status":"publish","type":"post","link":"http:\/\/cafe.foundation\/blog\/8599\/","title":{"rendered":"Free Battery Software May Free Battery Designers"},"content":{"rendered":"

Your editor used to teach a class on technical writing.\u00a0\u00a0 One of its premises was that good technical writing should be so clear it helps us see the error of our ways.\u00a0 If the knights in Monty Python and the Holy Grail <\/i>had done a brief description and a few simple drawings before catapulting cows over their enemy\u2019s walls, they might have realized that they had supplied bovine bombs for the enemy to catapult back.<\/p>\n

To avoid similar defeats on the stored energy front, engineers at Washington University in St. Louis have cooked up a Cliff\u2019s Notes <\/i>of how different battery chemistries will behave when being charged.\u00a0 This \u201cback of the envelope calculation,\u201d as Venkat Subramanian, PhD<\/a>, associate professor of energy, environmental & chemical engineering and his team think of it, is an early predictor of success.<\/p>\n

\"WUSTL's<\/a>

WUSTL’s free software will help battery developers wend their way through the intricacies of cell design<\/p><\/div>\n

Best of all, \u201cThe team developed a freely available code that battery developers can use as a model to determine the optimal profile needed to charge a lithium-ion battery as well as any stresses that might be put on the materials used,\u201d Beth Miller reports in the University\u2019s Newsroom<\/i> article<\/a>.<\/p>\n

Subramiamaniam notes the same effects of charging batteries that Drs. Cui and Cho have explained in their works<\/a>, that in lithium-ion batteries, the lithium is stored in metallic form inside particles.\u00a0 As the battery charges and discharges, the lithium metal moves into and out of openings between the particles (intercalation), eventually stressing, cracking, and causing failure of the battery\u2019s electrodes.<\/p>\n

\u201cWith this model and algorithm, we can use materials that are newly developed and those currently thought of as bad materials because of significant stress generation,\u201d Subramanian says. \u201cCombining stress effects with optimization algorithms can help derive smart charging profiles that take advantage of stress dynamics in such a way that it ensures faster charging of a battery.\u201d<\/p>\n

The code, designed for a Windows platform, and covering many of the chemical, electrical and physical elements in charging batteries, is available for free download<\/a>.<\/p>\n

Subramanian explains the importance of early software development along with the physical research on batteries.\u00a0 \u201cWhen newer materials and systems are being developed for batteries, for solar and for storage, simultaneous development of software, algorithms and hardware are going to be important.\u00a0 We\u2019re not going to wait 10 years and find the best material and the best battery, and then start developing the software. You want to be able to start the software development as we develop the new model and algorithms and then adapt it to newer things as they come along.\u201d<\/p>\n

The research, also free to view, was recently published in\u00a0Physical Chemistry Chemical Physics<\/i> and includes this abstract<\/a>:<\/p>\n

\u201cThe cost and safety related issues of lithium-ion batteries require intelligent charging profiles that can efficiently utilize the battery. This paper illustrates the application of dynamic optimization in obtaining the optimal current profile for charging a lithium-ion battery using a single-particle model while incorporating intercalation-induced stress generation. In this paper, we focus on the problem of maximizing the charge stored in a given time while restricting the development of stresses inside the particle. Conventional charging profiles for lithium-ion batteries (e.g.<\/i>, constant current followed by constant voltage) were not derived by considering capacity fade mechanisms. These charging profiles are not only inefficient in terms of lifetime usage of the batteries but are also slower since they do not exploit the changing dynamics of the system. Dynamic optimization based approaches have been used to derive optimal charging and discharging profiles with different objective functions. The progress made in understanding the capacity fade mechanisms has paved the way for inclusion of that knowledge in deriving optimal controls. While past efforts included thermal constraints, this paper for the first time presents strategies for optimally charging batteries by guaranteeing minimal mechanical damage to the electrode particles during intercalation. In addition, an executable form of the code has been developed and provided. This code can be used to identify optimal charging profiles for any material and design parameters.\u201d<\/p>\n

The paper was co-written by Bharatkumar Suthar,\u00a0\u00a0Venkatasailanathan Ramadesigan,\u00a0\u00a0Sumitava De,\u00a0\u00a0Richard D. Braatzc\u00a0and\u00a0\u00a0Venkat R. Subramanian.<\/p>\n

Funding for this work was provided by the U.S. Department of Energy Advanced Research Projects Agency \u2013 Energy (ARPA-E) and the McDonnell International Scholar Academy at Washington University in St. Louis.<\/p>\n

Such openness, and open source software, may become an important part of bringing the next great leap in clean energy development.\u00a0 Thanks to Dr. Subramanian and his colleagues, that next step may be an easier one.<\/p>\n

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