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ACTUAL ENGAGED GEAR IDENTIFICATION: A HYBRID OBSERVER APPROACH

2005; Elsevier BV; Volume: 38; Issue: 1 Linguagem: Inglês

10.3182/20050703-6-cz-1902.01890

2589-3653

A. Balluchi, Luca Benvenuti, Claudio Lemma, Alberto Sangiovanni‐Vincentelli, Gabriele Serra,

Iterative Learning Control Systems

The knowledge of the actual engaged gear is essential to achieve high-quality control of an automotive power train. In cars equipped with manual gear shift, this information is not directly available. A hybrid observer for on-line identification of the actual engaged gear is proposed. Two hybrid models of an automotive driveline, a detailed one for verification and a reduced-order one for synthesis, have been developed. The identification algorithm is based on a novel approach to observer design for hybrid systems. The algorithm was tested on experimental data obtained at Magneti Marelli Powertrain on an Opel Astra equipped with a Diesel engine and a robotized gearbox and yielded excellent results.