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:: International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies
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ISSN 2228-9860
eISSN 1906-9642
CODEN: ITJEA8
FEATURE PEER-REVIEWED ARTICLE
Vol.12(2) (2021) |
Electric Vehicle Cornering Stiffness & Lateral States Estimation Using Synchronized Adaptive Sliding Mode Observer and Kalman Filter
Junaid Iqbal (Department of Mechanical Engineering, QUEST, Larkana-Campus, PAKISTAN),
Khalil Muhammad Zuhaib (Department of Electronic Engineering, QUEST, Larkana-Campus, PAKISTAN),
Ahsin Murtaza Bughio (Department of Electronic Engineering, QUEST, Nawabshah-Campus, PAKISTAN),
Syed Abid Ali Shah (Department of Electrical Engineering, QUEST, Larkana-Campus, PAKISTAN),
Muhammad Tarique Bhatti (Department of Mechanical Engineering, QUEST, Larkana-Campus, PAKISTAN).
Disciplinary: Electric Vehicle Engineering and Technology, Mechanical Engineering, Electronic Engineering.
doi: 10.14456/ITJEMAST.2021.34
Keywords: Adaptive Sliding Mode Observer (ASMO); EV; Kalman Filter (KF); Electric vehicle driving test; Tire cornering stiffness; Lateral states.
AbstractThe information of tire cornering stiffness and lateral states plays a key role in driver-assist technology. However, this information does not remain the same; and varies with the tire-road condition and driving environment. Therefore, in this paper, a robust estimator scheme is established to adapt the varying tire-road conditions; and estimate the real-time information of tire cornering stiffness and lateral states of an Electric Vehicle (EV). Then, the proposed scheme's estimation accuracy is evaluated over two different driving tests, in which varying tire-road conditions are simulated along with distinct steering inputs. Finally, the simulation results exhibited an excellent estimation performance against uncertain driving conditions.Paper ID: 12A2M
Cite this article:
Iqbal, J., Zuhaib, K. M., Bughio, A. M., Shah, S. A. A., and Bhatti, M. T. (2021). Electric Vehicle Cornering Stiffness & Lateral States Estimation Using Synchronized Adaptive Sliding Mode Observer and Kalman Filter. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 12(2), 12A2M, 1-11. DOI: 10.14456/ITJEMAST.2021.34
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Other issues:
Vol.12(2)(2021)
Vol.12(1)(2021)
Vol.11(16)(2020)
Vol.11(15)(2020)
Vol.11(14)(2020)
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