b'Engineer Innovation | SimcenterModel-based system testing Optimizing complex systems by combining physical prototypesand simulation models throughout the development cycle. To cope with market demands for energy efficiency, active safety systems, mass customization and high performance, new generations of vehicles include an ever-increasing amount of mechatronics. Established manufacturers need to continuously rethink processes and reassess development activities. The classic verification-centric engineering approaches with separate workflows for test and simulation require many iterations and lack the necessary efficiency and flexibility to successfully handle current product complexity. Model-based system testing (MBST) exploits the synergies of combining testflexible bodies within an hour. State-of- MBST validates functional performance and simulation throughout thethe-art system simulation solutions canusing proven analytics and can be development cycle. Using MBST helpsaccurately simulate the multi-physicalleveraged at any stage of design to test and simulation engineersnature of systems by embedding allconsistently perform attribute successfully perform the attributerelevant physical phenomena (mechanics,engineering on virtual models, engineering of vehicle systems andelectrics, hydraulic, pneumatics, etc.) incombined virtual-physical systems and subsystems. Using MBST ensuresone solver. Although simulation hasphysical prototypes. productivity of, and provides detailedbecome the centerpiece of any engineering insights into, a model-basedengineering approach, real measuredThe combined use of test and simulation development (MBD) approach. data is more important than ever forcan be categorized in three main confirming modeling accuracy andcategories: (1) Testing for simulation, (2) The complexity, innovation andcompleting the models, especially whentesting with simulation and (3) personalization of car design means thereexploring uncharted design areas. Testingsimulation for testing.are more variants, components andremains essential to identify model systems, as well as increasingly innovativeparameters to provide realistic modelTesting for simulation covers a wide design exploration and attention toinputs and validate numerical models.range of approaches in which measured quality issues. As the complexity of carsdata is used to endorse modeling increases, it is highly inefficient toTo efficiently master system engineeringaccuracy. Test data is primarily used to repeatedly create and test physicalcomplexity during product developmentbuild, validate, improve and drive prototypes to validate designs and solveand be successful as a team, test andsimulation models. The delivery of problems. Instead, predictive methods aresimulation engineers need to align theirultrarealistic, multiphysics models for rapidly gaining ground. Over the lastworkflows and exploit synergies theysystems engineering is the final goal.decades, the speed and fidelity ofcreate by combining their tools. This simulation solutions have drasticallykeeps the product development cycle asIn the second category, testing with improved. Modern multibody simulationshort as possible and brings consistencysimulation, the physical and virtual software can simulate realistic scenariosto the processing of system dataworlds interact, complementing each for systems composed of hundreds ofthroughout the development cycle.other. This approach is of interest for 8'