Potential of statistical model verification, validation and uncertainty quantification in automotive vehicle dynamics simulations: a review

ABSTRACT

The modelling, simulation and analysis methods in automotive development are in the process of transformation. Increasing system complexity, variant diversity and efforts to improve efficiency lead to more complex simulations and depend on virtual vehicle development, testing and approval across a large application area. Consequently, the new key requirements of modern validation involve more precise reliability quantification of large application areas, achieved with reasonable effort of cost and time. This paper identifies that the neglection of uncertainties, low information in validation results, low extrapolation capability and the resulting small application area are preventing the state-of-the-art validation meeting those new requirements. In an extensive analysis examining more than twenty frameworks in detail, this paper shows that statistical methods exhibit a high potential to remedy these four key insufficiencies. The paper justifies comprehensively that consistent statistical validation is necessary, important and crucial for precise reliability quantification, which enables accurate model selection, knowledge building and decision making in modern automotive vehicle-dynamics simulations. An example is given explaining the basic principle and benefit of consistent statistical validation. Since automotive statistical methods are still at the beginning, the aim is to enable further investigation by showing their potential and providing deeper knowledge about this topic.

KEYWORDS:

• Modelling and simulation
• validation
• verification
• uncertainty quantification
• statistics
• automotive vehicle

Acknowledgements

This research is accomplished within the project ‘UNICARagil’ (FKZ 16EMO0288). We acknowledge the financial support for the project from the Federal Ministry of Education and Research of Germany (BMBF). The authors would like to thank Michael Viehof for the experienced advice and discussions during the preparation of the paper. As first author and initiator, B. D. developed the general concept of the paper and wrote a substantial part hereof. S. R. introduced the initial idea of using uncertainty frameworks and statistical validation in the automotive domain. B. D. and S.R. further analysed uncertainty quantification methods and deduced their potential in the automotive domain. M. L. made an essential contribution to the conception of the research project and revised the paper critically for important intellectual content. M. L. gave the final approval to the version to be published and agrees to all aspects of the work. As guarantor, M. L. accepts responsibility for the overall integrity of the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

We acknowledge the financial support for the project from the Federal Ministry of Education and Research of Germany (BMBF). This research is accomplished within the project ‘UNICARagil’ (FKZ 16EMO0288).