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Potential of Tire Prediction Modeling in Virtual Prototyping: A Review Jilin University
- Format:
- Book
- Conference/Event
- Author/Creator:
- Yin, Hengfeng, author.
- Conference Name:
- WCX SAE World Congress Experience (2025-04-08 : Detroit, Michigan, United States)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2025
- Summary:
- Virtual prototyping enables tires to be involved in automotive research and development (R&D) at an early stage, eliminating the trial-and-error process of physical tire samples and effectively reducing time and costs. Semi-empirical/empirical tire models are commonly used to evaluate vehicle-tire virtual mating. To parameterize these models, finite element (FE) simulations are necessary, involving combinations of sideslip, camber, and longitudinal slip under various loads. This paper identifies that when multiple inputs are combined, the FE simulation conditions become complex and numerous, presenting a significant challenge in virtual prototyping applications. Through an extensive analysis of more than ten tire prediction modeling methods and models in detail, this paper demonstrates the significant potential of tire prediction modeling in addressing this challenge. We begin with an overview of the current state of research in tire virtual prototyping, reviewing its application status and research endeavors in various tire companies and research teams are reviewed. Subsequently, we discuss tire prediction methods and models, including those based on detailed tire characteristics such as inner tire strain, as well as methods like Similarity, Combinator, Dynamic Friction Separation (DFS), Camber Equivalent (CE), and other method that predict based on external tire characteristics. Finally, we compare the calculation results of different prediction methods with the test data to verify the accuracy of the model in predicting the mechanical characteristics of tires under various conditions. The validation demonstrates that tire prediction modeling can be implemented using fewer and more focused FE simulation results, significantly enhancing efficiency while ensuring accuracy
- Notes:
- Vendor supplied data
- Publisher Number:
- 2025-01-8280
- Access Restriction:
- Restricted for use by site license
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