An increasing number of real word engineering problems can hardly be solved by physical-based approaches or numerical simulations, due to high calculation efforts or inaccurate material properties and physical boundary conditions.
By using data-driven techniques and artificial intelligence on measured or simulated data precise predictions of complex physical processes can be provided:
■ State of charge (SoC) prediction of lithium-ion battery cells and modules using long short-term memory (LSTM) and WaveNet approaches
■ Electric circuit metamodeling via fully connected neural networks
■ Defect detection on measured and simulated images, for instance of power electronic devices, lithography masks, and wafers