ISMR December 2023 / January 2024 | Page 22

CONTROL TECHNOLOGIES

overall score . It could handle input of over 350 parameters .
In this new project , Simcenter Engineering Services expanded on this work to apply it to the chassis . Using the targets provided by HMG , Simcenter engineers generated over 200,000 simulation models in Simcenter Amesim and validated them against real vehicles . They saved the simulation results in a high-performance computing ( HPC ) environment to make them run faster in the future .
“ Simcenter Amesim was the driving force behind our decision to select Siemens Digital Industries Software for this project ,” explained Jeong . “ Only Simcenter Amesim had the capabilities to perform the number of simulations we needed , as well as the flexibility for attributes such as NVH frequency . Simcenter Amesim was also advantageous because it enabled us to work with our own templates rather than a pre-packaged one . When it came to flexibility and simulation time , Simcenter Amesim was the best choice .”
Using Simcenter Reduced Order Modelling software , Simcenter Engineering Services created and trained a neural network to deliver simulation results that enable direct optimisation of models later in the process . This neural network integrates with HEEDS™ software to assist HMG engineers in identifying the ideal vehicle configuration .
“ If our targets or parameters change , we will no longer need to start the entire process from scratch ,” explained Jeong . “ We can now find the optimal parameter set very quickly by searching through the neural network built by Simcenter Engineering Services . The ability to easily retrieve these simulation results means we can give very quick feedback to each subsystem team on the ideal configuration . Later in development , we will also be able to efficiently compare the vehicle ’ s driving performance to our targets by using the benchmarking data retrieved by the neural network .”
Above : Simcenter engineers generated over 200,000 simulation models in Simcenter Amesim .
Later in development , we will also be able to efficiently compare the vehicle ’ s driving performance to our targets by using the benchmarking data retrieved by the neural network
Genesis has unveiled the GV80 Coupe and the re-designed GV80 in Korea in September 2023 .
AI-enabled time savings
The collaboration with Simcenter Engineering Services and the use of Simcenter software has led to significant engineering process benefits for Jeong ’ s team .
“ Before this project , one requirement evaluation took two minutes to run in simulation ,” said Jeong . “ Using the neural network developed by Simcenter Engineering Services , this was reduced to one-tenth of a second . Similarly , our subsystem parameter optimisation process used to take a week . With the help of Simcenter Engineering Services , this has been reduced to 15 minutes .”
Together , Jeong and the Simcenter Engineering Services team are working to reap even more efficiency benefits from this neural network . They will soon integrate Teamcenter ® software with the neutral network to fully link to and provide traceability for parameters and requirements ( HEEDS and Teamcenter are also part of Siemens Xcelerator ). This will enable a programme manager with no knowledge of simulation to directly input their requirements and use parameters from a previous project to run simulations directly on the web . They can then predict system performance or optimise parameter sets for subsystems , bringing the power of system simulation to non-experts .
“ Siemens ’ Simcenter portfolio and Simcenter Engineering Services will continue to be a special development partner for HMG ,” said Jeong . “ Our companies have a strong relationship and I look forward to collaborating on future projects .” n

Challenges

✓ Evolve vehicle models from ICE to battery .
✓ Analyse hundreds of parameters to optimise chassis performance .
✓ Adjust component design to changing parameters early in development .

Keys to success

✓ Develop neural networks to define requirements at the concept stage .
✓ Use AI to efficiently analyse parameters and suggest optimised configuration .
✓ Use Simcenter products and services to streamline sensitivity analysis .

Results

✓ Reduced subsystem parameter optimisation process from one week to 15 minutes .
✓ Streamlined target setting and eliminated need to start process over for design changes .
✓ Compared driving performance to targets by using the benchmarking data retrieved by the neural network .
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