A15
Automotive 3

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08:35
conference time (CEST, Berlin)
Virtual Design of SMC Parts Suitable for Automotive Mass Production
28/10/2021 08:35 conference time (CEST, Berlin)
Room: A
S. Wehler, J-H. Langer (Volkswagen AG, DEU); D.Hühn, S. Müller, A. Berger (Engineering System International Group, DEU)
S. Wehler, J-H. Langer (Volkswagen AG, DEU); D.Hühn, S. Müller, A. Berger (Engineering System International Group, DEU)
The transition from combustion engine vehicles (CEV) to battery electric vehicles (BEV) generates new challenges for the design process of crash management systems (CMS). The absence of supporting sub structures, like the engine, in combination with the diversity of the vehicle mass due to different types of batteries provide various boundary conditions and load scenarios. One approach to overcome the new challenges for CMS is the usage of hybrid structures made of metals supported by short or long fiber-reinforced polymers (SFRP/LFRP). In particular, the usage of chopped LFRP, like sheet molding compounds (SMC), allow for a cost-efficient production while keeping flexibility in the design of complex structures. In addition, SMC materials have an excellent weight to strength ratio. The SMC, consisting of a thermoset resin matrix including filling material and the reinforcing copped fibers, is manufactured in a compression molding process, whereby the final structural properties of the component arise through the manufacturing process itself. Consequently, manufacturing effects such as fiber-matrix segregation may lead to an inhomogeneous fiber matrix distribution and fiber orientation. Both have a major influence on the structural performance and need to be considered in a structural analysis. Apart from cost-efficient production, new materials and their combinations also demand the virtual design of new structures by numerical simulation. While a profound knowledge exists for the structural simulation of metal components, uncertainties are reality for the description of hybrid joints and on the effective mechanical behavior of SMC parts. In this regard new methods for the virtual design of hybrid structures are developed. They cover the complete chain from the design of the manufacturing process, to the actual production of parts and finally the assessment of the structural performance. The present contribution will focus on the virtual prediction of the mechanical behavior of the SMC, based on data defined by the manufacturing process. Here, the key information (fiber orientation, fiber distribution, fiber volume content) is extracted from a micro computed tomography (µCT) analysis. In combination with experimental data obtained from mechanical tests of the pure matrix material and from SMC coupon tests under various loading conditions, the parameter of the numerical model are determined. The calibrated material model is subsequently validated by a test series of SMC honeycombs and the results as well as numerical influences are discussed.
Multiscale Simulation; Virtual Prototyping; SMC; The Digital Twin; Virtual Material Design
08:55
conference time (CEST, Berlin)
Improving Collaboration in Vehicle Performance Simulation Process Through the Introduction of a System Centric Digital Thread
28/10/2021 08:55 conference time (CEST, Berlin)
Room: A
E. Mottola (Toyota Motor Europe NV/SA, BEL)
E. Mottola (Toyota Motor Europe NV/SA, BEL)
Automotive OEMs have established, over the years, standardized processes to coordinate and optimize the development schedule, with clear roles and responsibilities in each function. This constant refinement of requirements and processes has proven effective to develop attractive products for the customers. However, the increasing complexity of product development scenarios, such as Connected, Autonomous, Shared and Electrified (CASE) poses new challenges: the requirements of the systems and their interactions grow to a size which is challenging to manage with traditional approaches. New mobility business models require thinking about a vehicle not just as a product, but rather as a system within a complex system-of-systems. Model Based Development provides the framework to develop the vehicle using holistic systems thinking and to better manage the risks from that complexity using simulation for continuous exploration and validation. Recently, there has been a growing interest in technologies like co-simulation and engineering data management. However, practical industrial implementation still needs to deal with fundamental issues such as domain and subsystem "silos". Often, it is difficult to maintain up-to-date models with high quality data, validating the simulation scenarios against realistic operating conditions of the vehicle. Silos are a barrier to adopting Systems Thinking and to reusing knowledge across the enterprise. The authors propose approaches and platform characteristics that increase the smoothness of the information flow across domains, and between system designers and simulation engineers, through the realization of a custom, domain-independent, system-centric digital thread. This flexible data model provides confidence in up to date system specification data and it enables the simulation engineers to generate simulation models automatically, including variants; it can be further expanded to connect related data and processes; for example, it can trace the link between new requirements, affected systems, their evolutions, and overall product performance. Such digital thread not only enables re-use of previous data; it also provides the foundation for future data mining and AI applications to further accelerate the development process.
MBD, MBSE, Simulation, Collaboration, Digitalisation
09:15
conference time (CEST, Berlin)
Effective Use of Simulation in Root Cause Investigations for Automotive Sensors
28/10/2021 09:15 conference time (CEST, Berlin)
Room: A
M. Van Noorden (Sensata Technologies, NLD)
M. Van Noorden (Sensata Technologies, NLD)
Sensata Technologies is a world leading supplier of sensors and controls across a broad range of markets and applications. These highly engineered devices satisfy the world’s growing need for safety, energy efficiency, and a clean environment. Sensata designs and manufactures a broad range of automotive sensors, high voltage switches and fuses for the EV market that leaders in the industry depend on for safety, comfort and affordability. Supporting the sensor design teams in Sensata is the Simulation Centre of Excellence (SCoE) which has been established to bring together simulation skills from across the company. It also supports the understanding of previously unknown failure modes in our products by simulation. These types of analysis are typically nonlinear (failure) and/or multi physics due to the nature of our products (sensors and actuators), which bridge the gap between the realms of physics. Field returns in the automotive market can quickly turn into a high escalation, since it involves large numbers and can pose a high (economical) risk. Sensata is using several tools to find the root cause in the most optimal way. This toolbox is called ‘diagnostic problem solving’ and consists of statistical tools, failure tree and simulation. The toolbox was developed in conjunction with external tools experts and is highly praised by our automotive customers. Simulation is a key part of this toolbox and is used to: a) give insights in how realistic a root cause mechanism might be b) optimize testing by calculating responses upfront c) recreate experiments and vary ‘hard to control’ parameters d) enable the creation of a Pareto of individual confound contributors Over the years several cases have successfully been solved in a timely matter, showing the power of combining traditional, statistical and simulation tools. Examples of these cases are: Modelling of crack propagation in epoxies under thermal cycling, prediction of ceramic diaphragm deterioration in the first grain layer after exposure to exhaust gasses, parasitic capacity calculation of sensor shift due to buckling of flexible circuit board, leakage in turbo charge temperature sensor interface after high temperature exposure.
physics of failure, multi physics, problem solving, automotive, root cause finding
09:35
conference time (CEST, Berlin)
Traction Motor Design Using an Integrated Simulation Approach
28/10/2021 09:35 conference time (CEST, Berlin)
Room: A
G. Damblanc (Siemens PLM)
G. Damblanc (Siemens PLM)
For many years the automotive industry has been focused on reducing emissions of combustions engines in line with stringent regulations. One of the major challenges is in the development of new electrified powertrain of which electrical machines is an integral component.
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