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- Hochschule Ravensburg-Weingarten (7) (remove)
The power density of electric machines is a critical factor in various applications, i.e. like the power train. A major factor to improve the power density is boosting the electric current density, which increases the losses in the limited volume of the electric machine. This results in a need for an optimized thermal design and efficient cooling. The dissipation of heat can be achieved in a multitude of ways, ranging from air cooling to highly integrated cooling solutions. In this paper, this variety is shown and analyzed with a focus on water cooling. Further various structures in electric machines are presented.
A planar testbench is built to systematically analyze water cooling geometries. The focus lies in providing different power loss distributions along cooling channels, accurate temperature readings in a multitude of locations, as well as the pressure drop across the channel. The test bench results are aligned with simulations and simplified analytical evaluation to support the development process.
The main goal in this paper is to determine temperature gradients in the material close to the stator to quantize the potential for future cooling jacket designs. One question ,to answer is: How large the gradient is considering a realistic power loss distribution. Another sensible point are the different thermal expansions of aluminum used in cooling jackets and the steel core of the stator. This can be bypassed by using a steel cooling jacket. In this case, the performance of a steel cooling jacket compared to an aluminum version is investigated and also if light weight construction can compensate the lower thermal conductivity of steel.
After the analysis, an outlook about future changes of the measurement methods are given and first potentials for future cooling jackets are proposed.
Battery electric vehicle (BEV) adoption and complex powertrains
pose new challenges to automotive industries, requiring
comprehensive testing and validation strategies for reliability and
safety. Hardware-in-the-loop (HIL) based real-time simulation is
important, with cooperative simulation (co-simulation) being an
effective way to verify system functionality across domains. Fault
injection testing (FIT) is crucial for standards like ISO 26262.
This study proposes a HIL-based real-time co-simulation
environment that enables fault injection tests in BEVs to allow
evaluation of their effects on the safety of the vehicle. A Typhoon
HIL system is used in combination with the IPG CarMaker
environment. A four-wheel drive BEV model is built, considering
high-fidelity electrical models of the powertrain components
(inverter, electric machine, traction battery) and the battery
management system (BMS). Additionally, it enables validation of
driving dynamics, routes and environmental influences and provides
a precise analysis of the effect of powertrain system faults on driving
behavior. A possible case for a fault injection is to introduce a shootthrough fault in the inverter. Through the co-simulation, it is possible
to analyze the effects on the powertrain and the vehicle dynamics in
different driving situations (e.g. snow). This work demonstrates that
co-simulation is a valuable tool for the development and validation of
BEVs, and presents specific fault cases introduced into the
powertrain and the resulting effects tested under different driving
conditions. In addition, the study discusses the system's limitations
and future possibilities such as controller hardware integration
(Controller-HIL) and autonomous driving system validation.
Bicycle-drawn cargo trailers with an electric drive to enable the transportation of high cargo loads are used as part of the last-mile logistics. Depending on the load, the total mass of a trailer can vary between approx. 50 and 250 kg, potentially more than the mass of the towing bicycle. This can result in major changes in acceleration and braking behavior of the overall system. While existing systems are designed primarily to provide sufficient power, improvements are needed in the powertrain control system in terms of driver safety and comfort. Hence, we propose a novel prototype that allows measurement of the tensile force in the drawbar which can subsequently be used to design a superior control system. In this context, a sinusoidal force input from the cyclist to the trailer according to the cadence of the cyclist is observed. The novelty of this research is to analyze whether torque impulses of the cyclist can be reduced with the help of Model Predictive Control (MPC). In addition, the powertrain of the trailer is intended to support the braking process of the system with regenerative braking. In the context of this research, a first MPC controller design is carried out and analyzed with the help of a Hardware-in-the-Loop (HIL) approach where the microcontroller of the power electronics is included as hardware to ensure the vehicle dynamics control interacts properly with the lower-level field-oriented control. The battery and motor subsystems are simulated in a Typhoon HIL 604, which is supplemented by a vehicle dynamics model of the trailer that is integrated as a Functional Mock-Up Unit (FMU). First results indicate that the MPC longitudinal dynamics controller supports the driver during acceleration, attenuates the sinusoidal oscillations and reduces the force with which the trailer pushes the bicycle during braking.
In today's AI-driven era, computer vision, including autonomous driving, robotics, and healthcare, is prevalent. How-ever, acquiring ample data while managing resources and privacy constraints is challenging. This article proposes a solution: synthetic data generation. We use CAD software to craft intricate 3D models, process them in Blender, and evaluate quality using metrics like Structural Similarity and PSNR (Peak Signal to Noise Ratio). Synthetic data achieves up to 90% similarity with real data and an average PSNR of 21dB. Our method offers a streamlined, dependable ap-proach for enhancing computer vision, especially in object detection, addressing data acquisition challenges.
The vortex tube can separate a mass flow into a hot and cold mass flow. In this paper, the energy balance in the boundary layer of the vortex tube is analyzed with respect to a possible effect of temperature separation in the boundary layer by the viscous term of the enthalpy balance equation. A Large Eddy Simulation is used to generate the velocity profiles used for the computation of the viscous source terms. The dominant contributions of the source terms in the boundary layer of the vortex tube are identified and computed from the velocity fields. It is demonstrated how the strong velocity gradients in the boundary layer create a viscous flux of energy. An implementation of balance equations both with and without source term show the effect of energy separation in the boundary layer of the vortex tube.
Robotic grasping has been a prevailing problem ever since humans began creating robots to execute human-like tasks. The problems are usually due to the involvement of moving parts and sensors. Inaccuracy in sensor data usually leads
to unexpected results. Researchers have used a variety of sensors for improving manipulation tasks in robots.
This thesis focuses specifically on grasping unknown objects using mobile service robots. An approach using convolutional neural networks to generate grasp points
in a scene using RGBD sensor data is proposed. Two neural networks that perform grasp detection in a top down scenario are evaluated, enhanced and compared in
a more general scenario. Experiments are performed in a simulated environmentas well as the real world.
The results are used to understand how difference in
sensor data can affect grasping and enhancements are made to overcome these effects and to optimize the solution.
This thesis is an improvement on the works of Douglas Morrison, Peter Corke and Jürgen Leitner in their work Closing the Loop for Robotic Grasping: A Real-time,
Generative Grasp Synthesis Approach and Fu-Jen Chu, Ruinian Xu and Patricio A. Vela in their work Real-world Multi-object, Multi-grasp Detection.
The requirement of air conditioning in modern passenger cars need to fullfill enviromental standards with respect to refrigerant concerning global warming potential and ozone depletion with flour chlor carbon hydrogen mixtures.
This leads to compromises with respect to energy onsumption and cost of components.
As an alternative to standard refrigeration cycles, an inexpensive direct air cooling process is presented and discussed with respect to performance.
The process is specially suited for electric vehicles or vehicles equipped with an electric boosting device (E-charger).