A detailed roadmap can be found on the homepage of the THI.
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.
The research group Electromobility and Learning Systems (ELS) headed by Prof. Dr.-Ing. Christian Endisch investigates and develops application-driven methods for the development, the production and the operation of electric vehicles. This includes the powertrain, reaching from the individual battery cell to the electric engine. Thereby, powerful tools and procedures from mathematics, computer science and engineering are applied.
The ELS-group comprises about 20 research associates – among them 15 Ph.D. students – and is successfully financed by industries and publicly funded projects.
Head of Institute
You will find a general view about all vacancies for student work within the research group here.
PO Box 21 04 54
Visitors´Address (Location Donaukurier)
Technische Hochschule Ingolstadt
Stauffenbergstr. 2 A
Phone: +49 841 9348-7133