yaiLab (runner-up)
For companies that operate large batteries for grid applications, we developed a platform that ingests readily available battery operational data (current, voltage, temperature) to estimate and predict battery health and degradation. Our AI models can also optimize battery degradation vs revenues depending on intended use e.g. batteries used for frequency response. Because we take a data-driven approach our solution is transferable to any battery chemistry and operating condition; that way it can accommodate future battery technologies too. Compared to current solutions, our solution achieves an increased lifetime revenue of 70% whilst simultaneously decreasing battery degradation by 30%.