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Oskar Eklund

CAE Engineer, Vehicle Dynamics, ÅF Industry/Automotive Projects

Oskar received his masters degree in Automotive Engineering from Chalmers University of Technology in 2014. Since then he has been working as a consultant CAE Engineer, analysing vehicle dynamics in several development projects using multibody dynamics simulations together with optimization tools.


Method development for early architectural optimization of a wheel suspension system
Industries [Automotive]
Sala Acqua, Tue, 17/05/2016 - 17:20 - 17:40

A wheel suspension in a car transmits all forces from the road to the car body (the sprung mass) and at the same time limits the six degrees of freedom of the wheel to two or three. The task of the suspension is to give the car good driving characteristics and comfort with a minimum of disturbing vibrations and noise. At the same time the suspension should be of light weight, cost efficient, robust, easy to assemble and maintain and also have a sufficient life span. A wheel suspension is also affected by a great number of boundary conditions that leads to many requirements.

The main purpose of this study was to add an early optimization phase in a vehicle development project, to optimize the layout on system level, affecting the hard points and geometry of the whole vehicle platform architecture. Traditionally, optimization tools has been used on component level, when the available space and the loads to the component are already defined. A challenge with all multi-disciplinary optimization problems solved with numerical methods is model size and problem complexity. A typical process generates a massive amount of CPU hours and data. Available hardware resources will in many cases limit the scoop of the problem. Therefore, it is essential to make the problem setup as slim as possible with regards to model complexity (simulation run time) and optimization setup complexity (optimization run time). In order to address this, a two-phase optimization approach was developed.

The first phase is handling the problem on system level, which contains a high number of optimization responses and objectives. Therefore, model complexity must be low in order to achieve a process with practical use. The primarily goal of phase 1 is to find the optimal geometry for the system that gives the best performance measures. In addition to the geometry, bushing stiffness will be defined. This will be done with design of experiments (DOE) and multi objective / multi-disciplinary optimization (MOO/MDO) in order to meet complete vehicle dynamics and NVH demands.

In the second step, phase 2, the shape and material selection for the ingoing components is optimized in order to meet requirements for lowest cost and weight. This presentation focuses on the first phase, the second one is based on more traditional optimization.

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