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The main task in the automotive industry is to organize a nonstop development of safer, better performing and more appealing vehicles within strict timelines and limited budgets. Key automotive challenges today are the development of electric vehicles and autonomous driving systems, fuel economy & emissions regulation, warranty expenses reduction, shortening product development cycles and reducing costs of production.

pSeven and pSeven Enterprise enable OEMs and part manufacturers (powertrain, transmission, chassis, electronics, HVAC, batteries, etc.) to address mentioned above challenges and allow to:

  • Automate repetitive engineering tasks, which results in a multiple reduction of simulation time and increases engineers' productivity.
  • Find the best product design parameters, design reliable and robust products with advanced Design Space Exploration techniques.
  • Reduce number of test runs, experiments, and simulations thanks to predictive ML/AI models built from simulation data or experimental measurements.
  • Reduce number of driving scenario simulations for advanced driver-assistance systems (ADAS) development.
  • Fasten 0D/1D systems simulation with 3D discipline models by creating and importing surrogate models to Systems Engineering software in C or FMI format for co-simulation.
  • Improve simulation reliability by recalibrating models on test bench data (data matching).
  • Identify problem and reduce product defects with the help of sensitivity analysis to identify input parameters and/or their combinations that affect quality the most.
  • Explore the limits of engine operating range using adaptive Design Space Exploration and ML predictions.

Time and cost reduction to get optimal designs

Automotive design process requires implementation of automated simulation workflows into development processes that consider different multidisciplinary effects and overall behavior of the system, like aerodynamics, combustion, acoustic, vibration and harshness (NVH), durability and other attributes.

pSeven and pSeven Enterprise offer predictive modeling, design optimization and SmartSelection technology (algorithms auto selection and tuning) to improve collaboration between departments and engineers and ultimately lead to development cycle and cost reduction. It can help identifying the ultimate vehicle body geometry and equipment characteristics, including optimization of:

  • External aerodynamics to reduce drag
  • Vehicle body elements and exhaust systems to reduce weight and minimize NVH
  • Radiator and heat exchangers geometry to reduce size and maximize heat transfer
  • Impellers in the turbocharger to maximize efficiency
  • Catalytic converter geometry to reduce emissions
  • Breaks geometry and materials to reduce squeal
  • Electric motor efficiency in different operating conditions
  • HVAC systems to enhance temperature and moisture comfort
  • Cams geometry to enhance shape of lift, velocity, acceleration, jerk curves and dozens of other characteristics in valve train
  • Valve and intake/exhaust channels geometry to enhance in-cylinder flows
  • Piston head geometry to enhance combustion
  • Car seat structures to reduce weight and improve reliability

Bolide suspension optimization

Another Use Case for Formula Student. In this project, a group of students from the Formula Student optimized the attachment points of the rear suspension of the new version of their racing bolide using pSeven.

Mechanical support optimization with tight simulation budget

Learn how to leverage simulation toolchain automation and data analysis to develop a process to improve design performances of a mechanical support of PCB in automotive.

Creating internal combustion predictive model for Mitsubishi Motors

pSeven was used to build a predictive model for Mitsubishi Motors to predict internal combustion pressure model parameters.

Electric vehicles development

Fast and accurate predictive models for system level simulation and Multidisciplinary Design Optimization with pSeven and pSeven Enterprise empower electric vehicles manufacturers to develop efficient and reliable electric vehicles’ components by meeting key success factors:

  • Keeping the energy balance
  • Making the traction motor highly efficient
  • Reducing battery cost and increasing life
  • Improve thermal/cooling efficiency of EV batteries

Solutions for autonomous driving

pSeven helps the developers of advanced driver-assistance systems and automated driving design safe, convenient and efficient systems by the means of predictive models for operating systems and fully automated workflows.

pSeven enables scalable test beds in the virtual testing environment with a variety of real-world driving scenarios. Fully automated workflows, Adaptive DoE technique and predictive modeling toolkit ensure full automation of the virtual testing, adaptive exploration and flexible setup of driving scenarios, collecting, storing and reusing the data. Reuse of automated workflows reduces the effort during further testing.

pSeven Enterprise, a cloud-native low-code platform, can be deployed on-premises or in the cloud to leverage additional computing power on-demand. Combining power of aDoE which globally reduces number of simulations on one hand, with scalable power of Cloud architecture on the other hand, can lead to drastic cycle reduction for ADAS validation campaigns.

Systems modeling

Growing need for systems modeling, sharing information and models in simple and understandable way and preserving intellectual property rights: fast and robust predictive models can answer this need and drastically speed up system simulation. Models created in pSeven products from simulation, analytical and experimental data can be exported for use in external software products like Systems Engineering modeling software via C, FMU or native format for co-simulation, or can be sent to contractors to develop auxiliary equipment.

Use cases

Bolide suspension optimization

Another Use Case for Formula Student. In this project, a group of students from the Formula Student optimized the attachment points of the rear suspension of the new version of their racing bolide using pSeven.

Virtual optimization of suspension parameters using Adams Car and pSeven

pSeven based project that allowed create an automated workflow for parametric analysis and optimization of car suspension dampers in order to ensure passenger vibration comfort and smooth vehicle behavior on the road.

Tire dynamics model identification

pSeven based project for Formula Student, a student engineering competition held annually all over the world. The results allowed increasing the accuracy of the mathematical model of the longitudinal movement of the racing car, which even closer brought it to the real model of the car's behavior on the track.

Benefits of optimization with parametric mesh morphing: ANSA and META integration in pSeven

Benefits of optimization with parametric mesh morphing: ANSA and META integration in pSeven. The Use Case that demonstrates the benefits of parametric mesh morphing in optimization studies compared to the typical CAD-based parameterization of geometry modifications.

Optimization study of bumper structure

Recording of the presentation Optimization Study of Bumper Structure by Güven Nergiz, CFD Engineer, BIAS

Recording of the presentation "Optimization of microstructure properties for Lithium-Ion secondary batteries using GeoDict"

Presentation by Kenta Aoshima, Engineer, SCSK, Rio Shimojou, Sales Representative, SCSK

Recording of the presentation "Design Space Exploration for harness components" by LEONI

Presentation by Antoine Porot, R&D Engineer, Simulation Specialist, LEONI.

Mechanical support optimization with tight simulation budget

Learn how to leverage simulation toolchain automation and data analysis to develop a process to improve design performances of a mechanical support of PCB in automotive.

Virtual test bed automation and adaptive exploration of driving scenarios using pSeven

Automated reusable workflow, Adaptive DoE techniques and Predictive Modeling toolkit of pSeven ensured a full automation of the virtual testing, its’ flexible setup, execution, collecting, storing and reusing data.

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Publications

P7UC2023 - The power of combining SPDM with engineering workflow automation

Michael S. Murgai, Executive Board Member, PDTec
pSeven User Conference 2023

P7UC2022 - Enabling Digital Transformation in Engineering: Trends and Challenges

Donald Tolle, Director, Simulation-Driven Systems Development Practice
pSeven User Conference 2022

P7UC2022 - Automatic Generation of Stability Charts for Telehandler Vehicles

Joan Mas Colomer, Application engineer, on behalf of Manitou company
pSeven User Conference 2022

P7UC2022 - Optimization Study of Bumper Structure

Güven Nergiz, CFD Engineer, BIAS
pSeven User Conference 2022

P7UC2022 - 20 years of SPDM in production - towards a convergence of SPDM and PIDO

Mark Norris, CEng MIMechE MBA, theSDMconsultancy
pSeven User Conference 2022

DUC2020 - Design Space Exploration for harness components

Antoine Porot, R&D Engineer, Simulation Specialist, LEONI
DATADVANCE User Conference 2020

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