{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T13:20:50Z","timestamp":1781788850066,"version":"3.54.5"},"reference-count":42,"publisher":"SAGE Publications","issue":"9","license":[{"start":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T00:00:00Z","timestamp":1746489600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T00:00:00Z","timestamp":1746489600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Transactions of the Institute of Measurement and Control"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:p>This study presents a second-order sliding mode observer (SOSMO) framework developed to improve the estimation of lateral tire forces in vehicles. The framework incorporates two distinct approaches for approximating the sideslip angle: one based on dynamical equations and another employing an inverse model estimation technique with a new tire model. The suggested tire model captures the nonlinear characteristics of tire\u2013road friction, enabling a more accurate representation of lateral force behavior. Comparative evaluations are conducted using a single-track vehicle model based on the Pacejka formula under two scenarios: the open-loop steering pad maneuver and the lane change maneuver. Simulation results demonstrate the superior performance of the proposed methods compared to two established observers, namely, the extended Kalman filter and the state-dependent Riccati equation (SDRE) filter, even in the absence of detailed tire\u2013road interaction models. Notably, in a steady-state circular driving scenario, the second approach achieves a 99% smaller error compared to the first approach and a 99.38% smaller error relative to the SDRE filter. In a transient maneuver scenario, the second approach achieves a 10.71% smaller error than the first approach and a 99.63% smaller error compared to the SDRE filter. Robust studies under external disturbances further confirm the proposed methods\u2019 precision and reliability in estimating sideslip angle and lateral tire forces, offering a cost-effective alternative to traditional tire\u2013road interaction models.<\/jats:p>","DOI":"10.1177\/01423312251326643","type":"journal-article","created":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T06:32:28Z","timestamp":1746513148000},"page":"2032-2044","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Development of sliding mode observers for estimating sideslip angle and lateral forces in road vehicles"],"prefix":"10.1177","volume":"48","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-4372-2740","authenticated-orcid":false,"given":"Hamid","family":"Razmjooei","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, McMaster University, Canada"},{"name":"Department of Electrical, Electronic, and Information Engineering, University of Bologna, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gianluca","family":"Palli","sequence":"additional","affiliation":[{"name":"Department of Electrical, Electronic, and Information Engineering, University of Bologna, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Salvatore","family":"Strano","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of Naples Federico II, Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ciro","family":"Tordela","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of Naples Federico II, Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,5,6]]},"reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3344868"},{"key":"e_1_3_3_3_1","doi-asserted-by":"publisher","DOI":"10.1080\/00423114.2010.527994"},{"key":"e_1_3_3_4_1","first-page":"1","article-title":"Nonlinear tyre model-based sliding mode observer for vehicle state estimation","author":"Ben Moussa H","year":"2024","unstructured":"Ben Moussa H, Bakhti M (2024) Nonlinear tyre model-based sliding mode observer for vehicle state estimation. 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