“Intelligent Car Body”: A Design Approach for Construction of a Virtual Car Body for Small Sized Vehicle Batch Production based on LS-DYNA simulations
With increase in demands for special purpose vehicles such as electric vehicles, small series production is gaining more importance in automotive industry. However, due to restricted amount of information available about the structural performance targets in the concept design phase of the vehicle, its design goes through multiple optimization loops. This in turn increases the development time and cost, which is a major disadvantage for small series vehicle manufacturers. The present design approach, “Intelligent Car Body (ICB)”, aims at reducing these problems, although not completely eliminating them, by integrating “Structural Intelligence or Knowledgebase” in the car body design process. Crash simulations performed on full vehicles and its components using LS-DYNA code are extensively used here to set up this knowledgebase. The ICB approach is based on the space frame construction concept and focuses mainly on the crush - crash loads imposed on the car body. It targets to implement “Structural Intelligence” mainly for two tasks in the car body design process, namely, to define the performance targets for the desired car body during various crash scenarios and to develop an analytical design tool which can design the car body components to match these predefined targets. In order to facilitate the process of target definition a benchmark is developed by simulating two vehicles for crash using LS-DYNA. This benchmark summarizes typical values of energy absorbed, load distribution paths and hence provides a basis for the target definition. The analytical design tool under development is also validated by simulating car body relevant components for crush and crash loads in LS-DYNA. The ICB approach connects various steps in the car body design process in a logical order and integrates “Knowledgebase” to guide the design at each of these steps. The “Intelligence” developed will be validated for an electric car “ec2go” currently under development.
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“Intelligent Car Body”: A Design Approach for Construction of a Virtual Car Body for Small Sized Vehicle Batch Production based on LS-DYNA simulations
With increase in demands for special purpose vehicles such as electric vehicles, small series production is gaining more importance in automotive industry. However, due to restricted amount of information available about the structural performance targets in the concept design phase of the vehicle, its design goes through multiple optimization loops. This in turn increases the development time and cost, which is a major disadvantage for small series vehicle manufacturers. The present design approach, “Intelligent Car Body (ICB)”, aims at reducing these problems, although not completely eliminating them, by integrating “Structural Intelligence or Knowledgebase” in the car body design process. Crash simulations performed on full vehicles and its components using LS-DYNA code are extensively used here to set up this knowledgebase. The ICB approach is based on the space frame construction concept and focuses mainly on the crush - crash loads imposed on the car body. It targets to implement “Structural Intelligence” mainly for two tasks in the car body design process, namely, to define the performance targets for the desired car body during various crash scenarios and to develop an analytical design tool which can design the car body components to match these predefined targets. In order to facilitate the process of target definition a benchmark is developed by simulating two vehicles for crash using LS-DYNA. This benchmark summarizes typical values of energy absorbed, load distribution paths and hence provides a basis for the target definition. The analytical design tool under development is also validated by simulating car body relevant components for crush and crash loads in LS-DYNA. The ICB approach connects various steps in the car body design process in a logical order and integrates “Knowledgebase” to guide the design at each of these steps. The “Intelligence” developed will be validated for an electric car “ec2go” currently under development.