Electric Vehicle Cornering Stiffness & Lateral States Estimation Using Synchronized Adaptive Sliding Mode Observer and Kalman Filter

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. (C) 2021 INT TRANS J ENG MANAG SCI TECH.