Semi-Automated Transmission Control for Motorcycle Gearshift: Design, Data-Driven Tuning, and Experimental Validation

This brief addresses the gearshifting problem for semi-automated manual transmissions (S-AMTs) in powered two wheelers, a powertrain setup that allows fast and smooth gear shifts with minimal modifications to the traditional manual powertrain layout. We show that with a proper synchronization between the electronic clutch and engine torque, excellent gearshift performance can be obtained, but requires precise parameter calibration. We thus propose the use of a data-driven approach with constrained Bayesian optimization (CBO) to optimize control parameters. The procedure’s effectiveness is demonstrated on a real vehicle, assessing performance in terms of optimality, convergence rate, and repeatability.