Model-Based Wheel Torque and Backlash Estimation for Drivability Control

Marcello Canova, Cristian Rostiti, Luca D'Avico, Stephanie Stockar, Gang Chen, Michael Prucka, Hussein Dourra

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


To improve torque management algorithms for drivability, the powertrain controller must be able to compensate for the nonlinear dynamics of the driveline. In particular, the presence of backlash in the transmission and drive shafts excites sharp torque fluctuations during tip-in or tip-out transients, leading to a deterioration of the vehicle drivability and NVH. This paper proposes a model-based estimator that predicts the wheel torque in an automotive drivetrain, accounting for the effects of backlash and drive shaft flexibility. The starting point of this work is a control-oriented model of the transmission and vehicle drivetrain dynamics that predicts the wheel torque during tip-in and tip-out transients at fixed gear. The estimator is based upon a switching structure that combines a Kalman Filter and an open-loop prediction based on the developed model. The estimator relies only on measurements and signals that are commonly available in production vehicles, and in this paper is implemented in real-time using a rapid prototyping ECU. The estimator is verified experimentally on a test vehicle on a chassis dynamometer.

Original languageEnglish (US)
Pages (from-to)1318-1327
Number of pages10
JournalSAE International Journal of Engines
Issue number3
StatePublished - Mar 28 2017

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Fuel Technology


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