• Video
  • 15-Feb-2012 07:34 EST

Advances of Virtual Testing and Hybrid Simulation in Automotive Performance and Durability Evaluation


Purchase Required to View Video

Short Preview Below

Virtual testing is a method that simulates lab testing using multi-body dynamic analysis software. The main advantages of this approach include that the design can be evaluated before a prototype is available and virtual testing results can be easily validated by subsequent physical testing. The disadvantage is that accurate specimen models are sometimes hard to obtain since nonlinear components such as tires, bushings, dampers, and engine mounts are hard to model. Therefore, virtual testing accuracy varies significantly. The typical virtual rigs include tire and spindle coupled test rigs for full vehicle tests and multi axis shaker tables for component tests. Hybrid simulation combines physical and virtual components, inputs and constraints to create a composite simulation system. Hybrid simulation enables the hard to model components to be tested in the lab. As a result, it greatly reduces the requirement for an accurate analysis model and increases the chance for obtaining more accurate results. Mechanical Hardware-in-the-Loop (mHIL) is one of the hybrid simulation approaches. It has been developed to enable actual physical components to replace selected components for Real-Time vehicle dynamic simulation. In this approach, the virtual to physical coupling is accomplished in real-time allowing an accurate vehicle dynamics simulation to be conducted in a hybrid environment. The disadvantage of this approach is that the real-time requirement poses significant constraints on the model and test rig. To address the limitation of real-time techniques, an alternative technique, Hybrid System Response Convergence (HSRC), has been developed. The HSRC method uses an iterative approach to develop a solution that satisfies the equations of motion for the hybrid system. The iterative approach allows the physical and virtual systems to run sequentially as open-loop systems, rather than simultaneously, thus avoiding the requirement to run in real-time. The disadvantage of this method is that an iterative approach is more time consuming. Another approach address the limitation of real-time is to use a software named OpenFresco and a predictor-corrector algorithm to connect dynamic analysis software and a test system. If the solving speed cannot meet the requirement of real time, the predictor-corrector algorithm slows down the actuator to allow more time for the model to be solved. This approach is called soft real time hybrid simulation. The disadvantage of this approach is that it still requires the hybrid simulation to be conducted at the near �real-time� speed.

Shawn S. You, MTS Systems Corp.

Purchase to View
HTML for Linking to Page
Page URL
Rate It
No ratings yet

View More Video

Edgewater Computer Systems Inc. product RTEdge Platform 1.2 is a software toolset supporting proof based engineering, implementation and deployment of software components, built using the RTEdge AADL Microkernel modeling subset. This is a small subset of the AADL component model and execution semantics, covering threads and thread-groups communicating solely through asynchronous event ports and through explicitly shared data ports. Threads behavior is expressed as state machines and dispatch run time semantics is encoded in a Run-time Executive, enforcing pre-emptive priority dispatch based on statically assigned event priorities, with ceiling priority protocol access to shared data. This simple AADL microkernel semantic core can support all dispatch policies, communication and synchronization mechanisms of a fully fledged AADL run time environment, permitting the systematic use of the RTEdge static analysis tools for AADL compliant software components.
In support of the U.S Department of Energy's Vehicle Technologies Program, numerous vehicle technology combinations have been simulated using Autonomie. Argonne National Laboratory (Argonne) designed and wrote the Autonomie modeling software to serve as a single tool that could be used to meet the requirements of automotive engineering throughout the development process, from modeling to control, offering the ability to quickly compare the performance and fuel efficiency of numerous powertrain configurations. For this study, a multitude of vehicle technology combinations were simulated for many different vehicles classes and configurations, which included conventional, power split hybrid electric vehicle (HEV), power split plug-in hybrid electric vehicle (PHEV), extended-range EV (E-REV)-capability PHEV, series fuel cell, and battery electric vehicle.
In recent years, all major microprocessor manufacturers are transitioning towards the deploymenet of multiple processing cores on every chip. These multi-core architectures represent the industry consensus regarding the most effective utilization of available silicon resources to satisfy growing demands for processing and memory capacities. Porting off-the-shelf software capabilities to multi-core architectures often requires significant changes to data structures and algorithms. When developing new software capabilities specifically for deployment on SMP architectures, software engineers are required to address specific multi-core programming issues, and in the ideal, must do so in ways that are generic to many different multi-core target platforms. This talk provides an overview of the special considerations that must be addressed by software engineers targeting multi-core platforms and describes how the Java language facilitates solutions to these special challenges.
The System Architecture Virtual Integration (SAVI) program is a collaboration of industry, government, and academic organizations within the Aerospace Vehicle System Institute (AVSI) with the goal of structuring a new integration process that relies on a single-truth architectural framework. The SAVI approach of Integrate, then Build provides a modern distributed development environment which arrests the propagation of requirements errors through the development life cycle. It does so by capturing design assumptions and shared properties of the system design in an authoritative, annotated architectural model. This reference model provides a common, analyzable framework for confirming that system requirements remain complete, consistent, and correct at all levels of system decomposition. Core concepts of SAVI include extensive use of model-based system engineering tools and use of a single-truth reference architectural model.

Related Items

Technical Paper / Journal Article
Training / Education
Training / Education
Technical Paper / Journal Article