My main job in this role was to oversee the testing and processing of second-life Nissan Leaf batteries. The Nissan Leaf was a fully electric car and as many of the car batteries are reaching the end of their lifetimes and being swapped out for newer ones, Nissan ends up having lots of extra lithium modules from these cars on their hands. When the old batteries are decommissioned, they are only at 80% of their original health, so they potentially still have a lot of usefulness left in them. Usually, car manufacturers end up throwing away or recycling these old batteries, but our lab hopes to use them to store renewable energies for use when that power is needed.
I would run tests on these batteries that worked to rapidly age the batteries by quickly charging and discharging them in order to see how they perform with more degradation. This method of testing was called cycle testing and also required me to process the data recorded during the charge and discharge cycles using python in order to extract relevant characteristics of the batteries like the state of health of the cells and internal resistance of the cells.
Our lab was also contracted by Cummins, a corporation that designs power generation products, to test their batteries in a similar way to the Nissan Batteries. The processing of this data was also done through Python.
Most of my other responsibilities were related to miscellaneous tasks around the lab which varied from weekto week. One week could have been organizing the proper materials needed to ship some of our batteries to a partner lab in Utah, another week could have been asapting some of our processing code that was in MATLAB to Python, or another week could have been designing a testing rig for some ultracapacitors.
My biggest takeaways from working at this lab had to do with learning how to process data in Python and MATLAB. Before working here, I had a decent amount of experience programming in Python and MATLAB through various classes I took during high school and college, which did help me greatly for this lab, but I had never used these programs for significant data processing tasks. Learning how to automate code to speed up the processing and make it as hands-off as possible really helped me learn Python better for real-life applications and taught me how to use some libraries like NumPy and matplotlib.