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Cast aluminum alloys are frequently used as materials for cylinder head applications in internal combustion gasoline engines. These components must withstand severe cyclic mechanical and thermal loads throughout their lifetime. Reliable computational methods allow for accurate estimation of stresses, strains, and temperature fields and lead to more realistic Thermomechanical Fatigue (TMF) lifetime predictions. With accurate numerical methods, the components could be optimized via computer simulations and the number of required bench tests could be reduced significantly. These types of alloys are normally optimized for peak hardness from a quenched state that maximizes the strength of the material. However due to high temperature exposure, in service or under test conditions, the material would experience an over-ageing effect that leads to a significant reduction in the strength of the material. To numerically account for ageing effects, the Shercliff & Ashby ageing model is combined with a Chaboche-type viscoplasticity model available in the finite-element program ABAQUS by defining field variables. The constitutive model with ageing effects is correlated with uniaxial cyclic isothermal tests in the T6 state, the overaged state, as well as thermomechanical tests. On the other hand, the mechanism-based TMF damage model (DTMF) is calibrated for both T6 and over-aged state. Both the constitutive and the damage model are applied to a cylinder head component simulating several cycles on an engine dynamometer test. The effects of including ageing for both models are shown.
High temperature components in internal combustion engines and exhaust systems must withstand severe mechanical and thermal cyclic loads throughout their lifetime. The combination of thermal transients and mechanical load cycling results in a complex evolution of damage, leading to thermomechanical fatigue (TMF) of the material. Analytical tools are increasingly employed by designers and engineers for component durability assessment well before any hardware testing. The DTMF model for TMF life prediction, which assumes that micro-crack growth is the dominant damage mechanism, is capable of providing reliable predictions for a wide range of high-temperature components and materials in internal combustion engines. Thus far, the DTMF model has employed a local approach where surface stresses, strains, and temperatures are used to compute damage for estimating the number of cycles for a small initial defect or micro-crack to reach a critical length. In the presence of significant gradients of stresses, strains, and temperatures, the use of surface field values could lead to very conservative estimates of TMF life when compared with reported lives from hardware testing. As an approximation of gradient effects, a non-local approach of the DTMF model is applied. This approach considers through-thickness fields where the micro-crack growth law is integrated through the thickness considering these variable fields. With the help of software tools, this method is automated and applied to components with complex geometries and fields. It is shown, for the TMF life prediction of a turbocharger housing, that the gradient correction using the non-local approach leads to more realistic life predictions and can distinguish between surface cracks that may arrest or propagate through the thickness and lead to component failure.
A Novel Approach of High Dynamic Current Control of Interior Permanent Magnet Synchronous Machines
(2019)
Harmonic-afflicted effects of permanent magnet synchronous machines with high power density are hardly faced by traditional current PI controllers, due to limited controller bandwidth. As a consequence, currents and lastly torque ripples appear. In this paper, a new deadbeat current controller architecture has been presented, which is capable to encounter the effects of these harmonics. This new control algorithm, here named “Hybrid-Deadbeat-Controller”, combines the stability and the low steady-state errors offered by common PI regulators with the high dynamic offered by the deadbeat control. Therefore, a novel control algorithm is proposed, capable of either compensating the current harmonics in order to get smoother currents or to control a varying reference value to achieve a smoother torque. The information needed to calculate the optimal reference currents is based on an online parameter estimation feeding an optimization algorithm to achieve an optimal torque output and will be investigated in future research. In order to ensure the stability of the controller over the whole area of operation even under the influence of effects changing the system’s parameter, this work as well focusses on the robustness of the “hybrid” dead beat controller.
Smart Cities und Big Data
(2019)
Unternehmerische Resilienz
(2019)
Sharing Economy
(2019)
Die Digitalisierung zeigt Auswirkungen auch auf die moderne Konzeption von Städten. Unter der Bezeichnung Smart City entwickeln die Verantwortlichen zusammen mit den Stadtplanern und Experten Plattformen, die nicht nur die internen Verwaltungsabläufe, sondern auch die Beziehung zu und das Miteinander zwischen den Stakeholdern einer Stadt verbessern sollen. Dabei entstehen integrative Konzepte, die die City-Governance, Organisation und Technologie bündeln und auf eine einheitliche Zielerreichung hin ausrichten. Im Anschluss an die generische Entwicklung einer Smart City behandelt der Beitrag die spanische Stadt Barcelona als Beispiel für eine entsprechende Umsetzung. Am Ende werden die Chancen und Risiken dieses Konzeptes zusammenfassend gewürdigt.