Research team Electromobility and Learning Systems

Learning Systems are algorithms and methods that have the potential to acquire knowledge by themselves on basis of models and measured data. They are used to solve tasks that, due to their complexity and the high volume of data, can hardly be solved by humans and can be underdetermined and noisy in addition. For such methods, application fields are widely diversified. Especially in the context of automotive industry, they provide great optimization potential for existing and innovative fields of application. For example, by applying these artificial intelligence methods, operating strategies can be made more efficient. If one employs learning systems in the electric drive train, one gains knowledge of the various components, such as electric machine, power electronics and energy storage, and can thus increase the safety and lifetime, usually without price-driving additional sensors.