A14
Automotive 2

Back to overview

17:35
conference time (CEST, Berlin)
Using Superelement Approach to Improve Automotive FEA
27/10/2021 17:35 conference time (CEST, Berlin)
Room: A
E. Czerlunczakiewicz (Valeo, POL)
E. Czerlunczakiewicz (Valeo, POL)
As product development time in the automotive industry becomes shorter, the customers require more rapid and accurate FEA results. Simultaneously, FE models are frequently getting larger and more complex, in order to represent the engineering problem closely. It is becoming more and more challenging to meet these requirements. One of the possible solutions, to avoid a significant increase of computing resources and calculation time without losing accuracy in the results of the analyzed fields, is substructuring. Authors try to show that implementation of superelements in FE models is neither more complicated nor too time consuming in comparison to achievable benefits. To demonstrate the validity of superelement usage some practical examples, from the automotive industry, are gathered in this paper. In the presented cases, substructures improved FE results and in some, helped to meet project timing deadlines. Particular case studies are presented in the area of linear dynamics. Substructure replaced parts that are not in the area of FEA engineer interest and are not covered in the data post-processing. However, these components should not be skipped for reflecting real physical behavior of the analysed system. Applying superelements in linear dynamic analysis allowed to obtain better results without significantly increasing computing resources. A part of the paper is dedicated to handling substructures for optimization purposes. Optimization step is an iterative process, and in a lot of cases to gain acceptable results, hundreds or thousands of increments have to be calculated. Calculating a high complexity model with numerous variables can result in an unsolvable task. Fortunately, with implementing superelements, it is possible to focus only on components to be optimized while taking into account global model behavior. The last part of the presentation will present an example of new opportunities to use superelements in our applications.
FEA, superelement, substructure, structural simulations, optimization, linear dynamic, CAE
17:55
conference time (CEST, Berlin)
Co-simulation of Semi-active Dampers for Durability Road Load Simulations
27/10/2021 17:55 conference time (CEST, Berlin)
Room: A
H. Kolera-Gokula (MSC Software, USA); J. Zakrisson (Volvo, SWE); T. Nygards (Hexagon Manufacturing Intelligience, SWE)
H. Kolera-Gokula (MSC Software, USA); J. Zakrisson (Volvo, SWE); T. Nygards (Hexagon Manufacturing Intelligience, SWE)
Active chassis systems are becoming the norm today, especially in the premium car segments. These systems provide the ability to adapt to varying road conditions. It is critical to have CAE methods that model active systems since they significantly influence the accuracy of computed durability road loads used in vehicle design. There is a certain amount of complexity associated with creating simulation models of active vehicle systems. To enhance prediction accuracy, full-fidelity models of the controls guiding the active systems have to be included. These control models are often delivered as black boxes from the supplier. The first part of the presentation outlines the CAE strategy for active systems at Volvo Cars Durability Centre, with a particular focus on co-simulation of semi-active dampers. The co-simulation strategy forms the basis for simulation-led predictions of strength, endurance, durability, and road loads characteristics of vehicles with active chassis systems. The co-simulation approach is compared and contrasted against a simpler approach involving passive simulations. The incremental improvement in the accuracy of the computed road loads using the co-simulation approach is detailed under various road conditions and vehicle events. These include single-sided vertical impact, driving through a pothole, drop-off rebound, and the Belgian Pave. The second part of the presentation describes the implementation of a customized simulation process at Volvo Cars Durability Centre that enables efficient co-simulation, at scale, with minimal computational overhead. Processes and methods have been developed previously at Volvo Cars Durability Centre to automatically submit a whole suite of fatigue simulation events. Still, for co-simulation methods, the only option had been primarily manual. A customized process enhancement is presented in the new implementation, which seamlessly integrates cross-platform co-simulation into Volvo Cars' current automated simulation processes with minimal additional computational overhead. This process implementation will serve as a framework for similar co-simulation implementations in the future at Volvo.
Multi Body Dynamics, MBSE, Durability,Co-Simulation, Systems Modeling
18:15
conference time (CEST, Berlin)
Design Exploration and Prediction of Automotive Hood Designs based on Non-Uniform Feature Parameters
27/10/2021 18:15 conference time (CEST, Berlin)
Room: A
S. Ramnath, A. Li, J. Shah (The Ohio State University, USA); D. Detwiler (Honda R&D Americas, USA)
S. Ramnath, A. Li, J. Shah (The Ohio State University, USA); D. Detwiler (Honda R&D Americas, USA)
The design of automotive structures is a multi-objective problem that includes, light weighting, manufacturability and overall performance. Light weighting, while not compromising crash worthiness, requires careful placement of features in automotive body components. The current design process of automotive hoods involve the use of designs from previous generations as benchmark upon which new designs are evolved. The design obtained from this evolution process must meet the required performance targets. However, in this process of design by evolution, it becomes impossible to generate new designs or adapt design ideas from other models. In addition, the lack of information on performance for a set of mix and match of features from other designs, make it difficult to adapt features by cross designing. There is a gap needed to be filled to assist designers with cross designing of hood models so that the features from one hood can be used on another. The uniqueness of each design and presence of non-uniform parameters makes it difficult to compare two or more designs and extract useful feature information. It is necessary to use unconventional methods to compare the performance and pick the best suitable design. This paper aims to fill this gap by introducing an innovative approach to use a non-uniform parametric study for design exploration in order to make valuable suggestions to the designer. The proposed method uses data sets produced from finite element analysis (FEA), for a given set of loads. Based on designer preference, the response data generated from this FEA can be processed in three ways: 1) analyze for a specific hood model 2) analyze for a larger set that includes features from multiple hoods at the same time 3) analyze based on specific hood attributes (area, curvature, etc.) instead of individual feature parameters. The final predictions will provide the designer with parameterized surface models with potentially new designs adapted from a range of models. This method can be extended to other components and domains that use feature-based parametric designs.
Design Exploration, Design Automation, Feature based Design
18:35
conference time (CEST, Berlin)
Intrusion Vehicle Body Optimization Combining Frontal and Side Crash Responses
27/10/2021 18:35 conference time (CEST, Berlin)
Room: A
F. Leonov S. López (LURI Engineering, MEX)
F. Leonov S. López (LURI Engineering, MEX)
Automobile Manufacturers are required to design their vehicles for safety so that the occupants will survive of a variety of crash scenarios. Computer simulated crash analysis evolved over the years to help augment the crash rest programs and to give engineers to insight into the crash events. These nonlinear simulations have become commonplace during the design phase to save time and design cost. Designing an automobile for compliance with these safety standards along with fuel efficiency standards is hard because of some contradiction between these requirements. Today, to improve the design, analysts and engineers are using analyses and coupling them with general purposes optimization packages, hence, several crash conditions simultaneously can be defined to obtain the last response of the structure and utilizing optimization tools. Crash simulations typically require a significant amount of computational time and resources, as a result, there is an important interest in using approximate models to deal with optimization processes. An approximated model is constructed from a limited set of simulations and used during the optimization to obtain an improved design. But in normal conditions, there is a limitation on the number of independent design parameters that can be used because of the accuracy of the approximate models. This research describes a design system to optimize the non-linear responses computed from a Nonlinear software and General Purpose Optimization packages using various optimization techniques, especially with large-scale (large number of design variables) optimization. With the Nonlinear package software will be implemented to perform equivalent static loads (ESL Method) based on a Nonlinear analysis responses. The optimization package will be used to optimize the structure under frontal and side crash while decreasing intrusions at nodal outputblocks. Equivalent Static load method will require multiple iterations process of non linear structural analysis and Optimization. Large scale optimization techniques, such as, sizing, topometry and topography will be implemented easily.
Sizing, Topographic, Large scale optimization, Equivalent Static Loads, Nonlinear
×

[TITLE]

[LISTING

[ABSTRACT]

[DATE]

[ROOM]

[KEYWORDS]