Multidisciplinary vehicle design optimization - aerodynamics, combustion, NVH

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

June 29, 2023

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.

May 10, 2023

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.

January 28, 2020

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.

By Martin Pauthenet, Application Engineer, pSeven SAS and Ciprian Crisan, Thermomechanical Simulation Engineer, Vitesco Technologies

July 6, 2018

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

November 20, 2019

Optimization and prediction of microstructure properties for Lithium-Ion secondary batteries

Optimization of lithium-ion batteries microstructure to improve their overall performance and using Data Fusion to build accurate predictive models of battery properties for different applications without heavy simulations.

by Kenta Aoshima, SCSK Corporation

Solutions for autonomous driving

July 29, 2019

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.

Anton Saratov, pSeven SAS and Leonhard Herrmann, FDTech

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.

Other automotive use cases

June 9, 2023

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.

May 23, 2023

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.

December 29, 2022

Optimization study of bumper structure

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

June 16, 2021

Webinar recording: Virtual Optimization of Suspension Parameters using Adams Car and pSeven

Joint webinar by MSC Software and Datadvance covering the benefits of integration between Adams Car and pSeven via an industrial use-case involving the optimization of an automotive suspension damper.

October 9, 2020

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

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

April 9, 2018

pSeven beats MOPTA08 automotive benchmark

pSeven performs on MOPTA08 multidisciplinary design optimization benchmark introduced by Don Jones from General Motors.

December 5, 2016

Calibration of Pacejka’s "Magic Formula"

The customer used to fit formula’s coefficients with a standard optimization algorithm, which made Formula 1 vehicle’s tire calibration process time-consuming. Explore the example of how pSeven accelerated this process form 24 to just 1 hour.

pSeven solutions for Automotive