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A Yaw Rate Based Stability Control Tuning via Virtual Methods

A Yaw Rate Based Stability Control Tuning via Virtual Methods

A Teoresi Group project
Project

The collaboration with the Brembo team focused on integrating advanced adaptive algorithms used to estimate vehicle state variables, aiming to enhance the accuracy of vehicle lateral stability control algorithms. The verification, tuning, and testing of the software on the ECU using virtual simulation tools allowed for a thorough analysis of consistency across the various stages of algorithm development and validation.

Client

Brembo N.V.

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Industries
Scenario

In the context of evaluating and optimizing vehicle state estimators, it is crucial to ensure consistency and compare performance through a comprehensive use of tools and methodologies to test vehicle stability control algorithms. These activities include virtual Model-in-the-Loop simulations, Driver-in-the-Loop tests on driving simulators, and practical field tests at various proving grounds in Italy and abroad.

Challenges

Teoresi faced challenges related to the complexity of implementing a more varied, consistent, and repeatable development and validation chain, regardless of the testing context, while integrating early diagnosis capabilities for potential malfunctions. Specifically, the activities included:

  • Integration of the estimation algorithm into the ECU and theoretical and implementation reviews.
  • Validation through the standardization of testing tools (virtual validation and simulation environments) to ensure that tests aimed at evaluating consistency across environments and measuring performance were repeatable and consistent with direct vehicle activities.
Our added value

Teoresi demonstrated its expertise and experience in vehicle dynamics control, estimator development, and adaptive controls, adding value through the academic background of the team members (cf. ‪Gerardo Amato – ‪Google Scholar). For the client, value creation was achieved by implementing a more varied, consistent, and repeatable development and validation chain, regardless of the testing context, with integrated early diagnosis capabilities for potential malfunctions. Teoresi also played a key role in reducing time and optimizing resources in the testing chain required by internal processes during the release phase. Additionally, a new vehicle dynamics estimation algorithm was tested, contributing to the overall improvement of stability control performance.

 
Results

Qualitative improvements

  • Review and validation of the implementation and integration of estimation algorithms.
  • Review and standardization of simulation environments.
  • Resource optimization and reduction of road test times.

Quantitative improvements

  • Data collection and analysis (performance improvement evaluation through objective KPIs and consistency comparative analysis across different test/validation domains).
  • Contribution to the statistical analysis of results and evaluation of calculation tools.
  • Evaluation of improvements in stability performance and estimation of vehicle dynamic variables compared to previous software versions.
  • Drafting of technical reports on simulation activities and vehicle tests.

The project results have been collected into a Scopus-indexed paper, presented at the 16th International Symposium on Advanced Vehicle Control, September 2024, in Milan (AVEC24).

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