Motors and controls are used in many research applications. Our motion control systems serve the special properties and performance characteristics needed in demanding scientific experiments:
MACCON is an important partner of industry and of many Universities and research institutes, when special applications for Motion Control are demanded or Motion Control technologies themselves are to be improved.
We supply both fast and precise motor and positioning systems for research applications, including systems with many axes etc.
We are also involved in many research projects at national and European leave.
|Ongoing research projects||Duration||Logo/Image||Paper|
High-frequency inductive power transmission for autonomous electric drives
In automation technology, there are some challenging applications that require hermetic sealing of automated machines, such as placement robots in the semiconductor industry or in medical technology. Classic cable loops or sliding contacts can often not be used due to the requirements. The energy must then be transmitted wirelessly to the actuators in the automats.
Scalable Thermal Management and Drivetrain for Fuel Cell Commercial Vehicles
The project “SkalTABs” addresses scalable powertrain and thermal management architectures as well as the associated hardware components for future commercial vehicles with fuel cells. The optimization of the system architectures is based on a holistic view of the electrical and thermal energy flows, aiming for the highest possible overall efficiency. By combining a high overall efficiency with the scalable approach of the fuel cell system, a wide range of commercial vehicles from different application and power ranges are covered. In this way, the project helps making fuel-cell powertrains cost-efficient and thus accessible to smaller vehicle manufacturers in particular.
A central component for the entire powertrain management is the multiport DC/DC converter that regulates the energy flows between the fuel cell, battery and drive inverter. In addition to a high efficiency, dynamic control techniques for the converter and loss-reduction methods for the overall system are addressed.
Within the scope of the project, the following aspects, among others, are investigated in detail:
|08/2021 - 07/2024|
AI Methods for Optimized Control of Electric Traction Drives
The KIRA project (AI methods for optimized control of electric traction drives) focuses on the holistic optimization of the operation of electric traction drives by using methods based on artificial intelligence (AI). The focus is the development of novel actuation and control concepts, which require a fundamental revision of current methods and models. With its optimization methodology, KIRA addresses the key aspects of electric drive systems for vehicles: increasing efficiency, increasing power density, reducing noise and increasing torque accuracy. The project is funded by the German Federal Ministry for Economic Affairs and Energy (BMWi).
On the one hand, ISEA's goal in KIRA is to enable the control of acoustic emissions through AI-based acoustic modelling of the electrical machine. This offers the possibility to represent the complex multi-physical relationships from excitation to radiation of acoustic emissions in a simplified way. This allows real-time capability of the acoustic model while maintaining sufficiently high accuracy. On the other hand, the thermal behaviour of the electrical machine is investigated. Again, AI-based approaches such as neural networks offer the potential to significantly reduce the computational complexity of the models without negatively affecting the accuracy. Here, ISEA demonstrates that AI-based models provide comparable results to classical modelling approaches. Another goal of ISEA is to find the optimal generation of training data for the considered modelling approaches. Both model-based and empirical data are investigated.
|08/2021 - 07/2024|
|Completed research projects||Duration||Logo/Image||Paper|
“Next Generation GaN Power Module Project”
Gallium Nitride ”GaN” is a promising material to replace silicon in power electronics application in the 650V market sector. Power systems based on GaN are lighter, more compact, significantly more efficient and potentially cheaper than those based on Silicon. Within the GaNext project we aim to remove barriers for GaN adoption and demonstrate the higher efficiency and power density of GaN-based system in a range of applications. The heart of the project is the development of an intelligent GaN power module where the controller, drivers and protection circuits are co-packaged with the power devices.
High-performance magnetic materials based on SmCo and CoFe for highly efficient electric automotive engines and aircraft engines
The mobility of people and goods is an important prerequisite for our society. The necessary means of transport on land, water and in the air all require increasingly powerful engines. In road traffic and aviation in particular, huge amounts of fossil resources in the form of petrol, diesel and kerosene are still burned in engines and turbines. On the one hand, this is not sustainable because of the limited deposits and, on the other hand, the released CO2 accelerates climate change, both of which represent a heavy burden for future generations.
5G-DRIVE: 5G HarmoniseD Research and TrIals for serVice Evolution between EU and China
The global deployment and market adoption of 5G in one of the industry’s main priorities, but a global technology consensus and spectrum harmonisation still remains a key issue before 5G standardisation is finally approved. International collaboration and alignment among key regions are essential to facilitate this process, with Europe and China being two of the main regions in this regard.
The European Commission (EC) has taken the first step to boost 5G global cooperation with many countries and regions, including through jointly funded projects, global 5G events and other initiatives. The EC and China have agreed to fund joint projects on 5G trials to address two of the most promising 5G deployment scenarios, namely enhanced Mobile Broadband (eMBB) and Vehicle-to-Everything (V2X) communications. 5G-DRIVE, in collaboration with its Chinese twinning counterpart , has the ambition to fulfil this goal.
5G-DRIVE will bridge current 5G developments in Europe and China through joint trials and research activities to facilitate technology convergence, spectrum harmonisation and business innovation before the large-scale commercial deployment of 5G networks occurs. 5G-DRIVE will develop key 5G technologies and pre-commercial testbeds for eMBB and V2X services in collaboration with the Chinese twinning project. Trials for testing and validating key 5G functionalities, services and network planning will be carried out in Europe and China.
|ADEPT||Advanced Electric Powertrain Technology||09/2017 - 10/2019|
|TEMA-UAV||Design and Evaluation of Fault-Tolerant Electro-Mechanical Actuators for Flight Controls of Unmanned Aerial Vehicles|
|AktiWa||Advanced Electric Powertrain Technology|
|E-SEMA||Electric Smart Electro-Mechanical Actuator for gas turbine engines|
|MaTE||Magnet-free traction motors for electromobility|
|PitchER||Magnetless pitch drive in wind turbines by using electric transverse flux reluctance machines.|
|SKLEWU (Komrol)||SCalable SiC power electronics for converters and inverters (compact and robust power electronics)|
|Transinno||Innovative linear motor of high force density with passive stator based on transversal technology|
We are also a R&D partner of the early development departments of the German automobile industry.
The proposed identification method allows for a simultaneous estimation of nonlinear output voltage deviations in voltage source inverters (VSIs) and nonlinear synchronous machine models. Based on the identified characteristics with the help of physically inspired structured artificial neural networks (ANNs), an efficient tuning of the current control system can be performed and the nonlinear voltage deviations caused by parasitic effects and dead-time distortions can be accurately compensated for. The identification is performed without position sensor while the rotor is mechanically locked by utilising measured phase currents and reference machine voltages only. Experiments for an interior permanent magnet synchronous machine (IPMSM) and a reluctance synchronous machine (RSM) show that the proposed method is capable of identifying the current dependent self-axis and cross-axis flux linkages, differential inductances and the nonlinear VSI voltage deviations as well as the phase resistance at the same time. The proposed method is fast and generic. Besides the rated machine current, voltage and frequency, no prior system knowledge is required making it applicable for the self-commissioning of any electrical synchronous machine drive.
Electro-mechanical actuators (EMAs) are a primary actuation technology for unmanned aerial vehicles (UAVs). Intensive research has been conducted for designing and evaluating fault-tolerant EMAs for flight controls of UAVs to ensure their compliance with new airworthiness requirements for safe operation over civilian zones. The state-of-the-art research involves several fault-tolerant architectures for EMAs based on parallel electric motors or a single motor with internal fault-tolerant features. In this study, a fault-tolerant architecture is introduced, comprised of two serial electric motors driven by two isolated controllers and a health monitoring system. The procedures of developing various fault-tolerant features are discussed with a deep focus on designing health monitoring functions and evaluating their influence on the overall actuator stability and availability. This work has been conducted and evaluated based on operational data for ALAADy: a heavy gyrocopter-type UAV at DLR (German Aerospace Center).
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