Prithvi Reddy

TL;DR: This work develops a practical Kalman filter-based backlash size estimator for automotive drivelines that does not require any additional sensors, and uses available speed measurements from the vehicle CAN bus.

TL;DR: A Kalman filter-based estimator for the backlash position is developed, utilizing readily available speed measurements from the vehicle CAN bus, and the robustness of the system to CAN jitter in the speed measurements is verified.

TL;DR: In this paper , an innovative Kalman filter-based lash size estimator that uses readily available speed and torque signals from the vehicle CAN bus is proposed. And the authors evaluate the efficacy of the proposed estimator using both simulations and test vehicle data, and evaluate the robustness of the estimator to variations in the actuator torque trajectory and the calculated road load torque, presence of CAN jitter in the measured speed signals, and variations in backlash size, driveshaft compliance, and tire-road interaction.

TL;DR: This study integrates nonlinear model predictive engine and reference governor-based driveline controllers to minimize driveline clunk and shuffle, demonstrating improved performance and coordinated control over traditional, rule-based algorithms.