Backlash estimation with application to automotive powertrains

In automotive powertrains, backlash imposes well-known limitations on the quality of control and, hence, on vehicle driveability. High-performance controllers for backlash compensation require high-quality measurements of the current state of the powertrain. Information about the size of the backlash is also needed. In this paper, nonlinear estimators for backlash size and state are developed, using the Kalman filtering theory. A linear estimator for fast and accurate estimation of the angular position of a wheel and the engine is also described. It utilizes standard engine speed sensors and the antilock brake system speed sensors and event-based sampling at each pulse from these sensors. The estimators are validated through experiments on a real vehicle and the results show that, the estimates are of high quality, and hence, useful for improving backlash compensation functions in the powertrain control system.