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Electric Vehicle Cornering Stiffness & Lateral States Estimation Using Synchronized Adaptive Sliding Mode Observer and Kalman Filter |
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| รหัสดีโอไอ | |
| Creator | Junaid Iqbal, Khalil Muhammad Zuhaib, Ahsin Murtaza Bughio, Syed Abid Ali Shah, and Muhammad Tarique Bhatti |
| Title | Electric Vehicle Cornering Stiffness & Lateral States Estimation Using Synchronized Adaptive Sliding Mode Observer and Kalman Filter |
| Contributor | - |
| Publisher | TuEngr Group |
| Publication Year | 2564 |
| Journal Title | International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies |
| Journal Vol. | 12 |
| Journal No. | 2 |
| Page no. | 12A2M: 1-11 |
| Keyword | Adaptive Sliding Mode Observer (ASMO), EV, Kalman Filter (KF), Electric vehicle driving test, Tire cornering stiffness, Lateral states. |
| URL Website | http://TuEngr.com/Vol12_2.html |
| Website title | ITJEMAST V12(2) 2021 @ TuEngr.com |
| ISSN | 2228-9860 |
| Abstract | The 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. |
