English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This work investigates the utility and efficiency of simplified vehicle dynamics models in the Electronic Stability Control (ESC) context. The focus is not merely on the correlation between simplified and complex models but on the added value such models can bring to the automotive industry. By comparing the simplified models based on bicycle representation with a high-fidelity VI-CarRealTime (VI-CRT) model, this paper demonstrates that the simplified models have good correlation and offer computational advantages. This approach addresses the key dynamics essential for ESC and considers a generic sedan vehicle model to simulate standard maneuvers widely performed by the automotive industry. All the proposed models are nonlinear and include tire modeling based on the Magic Formula, with parameters derived from experimental tests. The paper also introduces a methodology for parameter optimization, enhancing the model's accuracy and reliability. The results indicate that the simplified models can be a viable alternative for specific applications such as control strategy tuning, rapid prototyping, and early-stage development. This work aims to fill the gap in the literature concerning the practical applicability and limitations of simplified vehicle dynamics models, thereby making a significant contribution to the field.

Analysis and Virtual Validation of Vehicle Dynamics Models for Electronic Stability Control