Research Projects

The aim of the "AI4HP" project was to develop a new generation of "smart heat pumps" that use artificial neural networks (ANNs) to adapt to changing operating conditions, thereby increasing energy efficiency whilst maintaining user comfort. | Duration: 09/2021 - 08/2024

Multi-family buildings offer largely untapped potential for energy savings and grid services in the US and in Europe. Against the backdrop of rapid electrification, the rise of heat pumps, and increasing regulatory pressure, the project "ABLM: Automated Building Load Modeling" project is developing physics-informed neural networks that can accurately predict the load flexibility of central consumers (heating, domestic hot water, cooling, e-mobility) with just a few input data. The hybrid approach overcomes the limitations of classic simulation and pure AI models and enables scalable, robust demand-side management. | Duration: 06/2025 - 06/2027

The construction sector is one of the most relevant areas when it comes to saving energy and reducing emissions. In this industry, large international companies coexist with SMEs, which account for 92 percent of the market. Although they represent 9 percent of the GDP of the European Union, digitalization in this sector exists only to a limited extent. In this context, the EU-funded project BIM4REN aims at the development and demonstration of user-friendly Building Information Modeling (BIM) tools and services in the field of building refurbishment and renewal. The project brings together 23 stakeholders from research institutes, universities, and small and large industrial companies in the construction sector. | Duration: 10/ 2018 - 09/2022

In the project "ADAPTeR," digital methods are being developed to operate heating systems in multi-family buildings more energy-efficiently and reliably. To achieve this, measurement data, maintenance information, and technical specifications are combined in a digital asset data sheet and analyzed using innovative data fusion and AI methods. The consortium, consisting of Green Fusion, B&O Service, HAW Hamburg, and Fraunhofer ISE, enables condition-based and predictive maintenance, reducing energy consumption, CO₂ emissions, and costs, while providing clear decision support for technical staff. | Duration: 11/2025 - 10/2028

In the heating, ventilation and air conditioning (HVAC) trade, consultation, stocktaking, planning and preparation of offers are very time-consuming processes, especially when upgrading existing systems. Each system must be individually configured and adapted to the technical conditions of the building and the habits of the users. This is especially true for complex and sustainable systems, such as heat pumps, fuel cells and solar-assisted hybrid systems. | Duration: 09/2021 - 08/2024

The heating and cooling supply systems of buildings are usually documented in schematics. These documents contain important information about the topology and the components of the systems that are useful for designers, building managers, and technical monitoring service providers along the complete building life cycle. However, these schematics are often only available in paper form, as CAD or pdf files and the information that they contain is almost not accessible digitally. This situation makes the data collection tedious and hampers the efficiency and cost-effectiveness of refurbishment or a technical monitoring projects. | Duration: 01/2023 - 12/2025

The digitalization of the building sector is a central element for reaching the energy transformation goals. In this project, we aim at establishing an integral systematic for linking the domains building services engineering and building information modelling (BIM) in order to safely achieve highly energy-efficient buildings. Within the project we demonstrate the developed approaches in the planning and operation phase of a real plus-energy building. | Duration: 12/2018 - 11/2021

It is the goal of the project to demonstrate new heating and cooling technologies within 3 case studies, one at a commercial compound and two at industry case studies. Additionally, new solutions to increase the energy efficiency within the buildings will be evaluated. With this project, the efficient coupling of electricity, heat and cooling will be demonstrated and thereby the untapped flexibility potential in the commercial sector as well as industry sector will be developed. To reach this goal, operation models will be developed, which will help to converge the commercial as well as industry sector to the power economy. Additionally, the identified flexibilities within building sector will be embedded in a regional energy system model, to develop strategies, how to increase the linkage between the energy system and commercial and industry compounds. | Duration: 10/2017 - 01/2021

As part of the “FoFeBat” project, a research production facility for battery cells is being set up. This covers all production steps from mixing the electrode materials to forming the cells. In sub-project 1, Fraunhofer ISE is supporting the development of research production in areas such as forming and end-of-line quality assurance as well as in the fields of energy-efficient building operation management, dry room design and the techno-economic evaluation of operating scenarios. In sub-project 2, Fraunhofer ISE is involved in technology screening for future innovation modules and the development of the pipeline process for their implementation. In sub-project 3, Fraunhofer ISE is planning and setting up a mini-environment test stand that will enable investigations into optimized air flow and energy-optimized operation. | Duration: 10/2019 - 12/2027

Technical monitoring (TMon) can reduce the energy consumption of buildings by up to 20%. However, a shortage of skilled workers and manual steps are slowing down widespread implementation. In the R&D project ‘GraphEET’, Fraunhofer ISE and Offenburg University of Applied Sciences are working with industry partners to develop a data-based TMon workflow. The aim is to develop hybrid AI methods for the recognition of data points and plant topologies and to map the recognised objects and structures in digital twins as knowledge graphs. This should enable test templates, fault diagnoses and mobile measurement tasks to be applied automatically. | Duration: 07/2025 - 06/2028