Future Of Electric Mobility: Air-cooled Drive Unit

2023 Author: Hannah Pearcy | [email protected]. Last modified: 2023-08-25 03:36

At stand D33 in hall 4.1, the engineers will be showing from 15 to 18. September using an axle demonstrator to present their solutions for a rim for cooling air support, an adaptive suspension damper and a concept for testing the adaptive axle.

Solutions for the future of electric mobility

As part of Fraunhofer System Research for Electromobility (FSEM II), 16 Fraunhofer institutes are jointly developing solutions for the future of electromobility. The three Fraunhofer Institutes for Durability and System Reliability LBF, for Integrated Systems and Component Technology (IISB) and for Manufacturing Technology and Applied Materials Research (IFAM) bundle their competencies for an innovative air-cooled electrified powertrain with adaptive suspension dampers in the "Powertrain / Chassis" cluster. This consists of an air-cooled wheel hub motor, an air-cooled drive converter, a multi-level DCDC converter, an adaptive chassis damper and a rim for cooling air support.

Picture gallery

Rim optimized for cooling air

The Fraunhofer LBF has investigated the influence of wheel disc design in order to improve the air flow and the associated forced convection on the wheel.

In addition to the cooling effect and better flow, the decisive criteria for the scientists were the result of the numerical fatigue strength calculation and the possible weight. They developed the rim according to the requirements resulting from the increased tire-sprung mass. Investigations in the wind tunnel showed a significant influence of the wheel design on the cooling behavior. Depending on the design goal, a design with propeller spokes proved to be advantageous for supporting the convection on the wheel side. Based on these results, the LBF scientists designed and built a lightweight rim in 20 inches, which is suitable, for example, for the use of wheel hub motors. It improves the cooling air flow by five percent and weighs only 11.3 kilograms.

Adaptive suspension damper

In order to reduce the influence of the increased tire-sprung masses and to achieve the highest driving comfort, the Fraunhofer LBF has developed a magnetorheological damper with a new and energy-efficient magnetic field guidance. Magnetorheological fluids (MRF) are suspensions of a carrier fluid and ferromagnetic particles. Under the influence of a magnetic field, solid-state bridges are formed, which lead to an increase in the transferable shear stress. The hybrid magnetorheological damper uses this effect to adjust the damper hardness in a vehicle: the stronger the magnetic field, the higher the damping force. If the damper hardness is to be adjusted over the long term when used in a vehicle, the permanent magnet can be adjusted. If this should happen quickly and quickly,the coil current can be changed.

Test concept for more efficient operational strength testing

Before components come into the automobile and are used there, these systems, which are subject to dynamic forces, must be tested for their operational strength. The problem: With the usual multi-channel servo-hydraulic test benches, it is often very complex to determine the control signals ("drive files") for the test bench before the actual test begins. Instead of mapping the system dynamics, as was previously the case, scientists at the Fraunhofer LBF have created a physical, non-linear model of the test bench and test object. It records the effects of non-linear system dynamics and is also able to map the dynamic behavior of (semi) active components, such as dampers.

Numerical studies with the model of a three-channel servo-hydraulic test bench and that of a semi-axis assembly with non-linear (semi) active / adaptive dampers showed several advantages: The iterative optimization of the drive file converges much faster than when using the previously usual linear transmission matrix. There is considerable potential for saving time and money in test preparation. Examples show a deviation of less than one percent after three iterations, instead of a deviation of 3.6 percent after ten iterations. In addition, the model captures continuously changing properties of (semi) active / adaptive components without any particular difficulty, which can now be displayed in the drive file generation. (yup)