Self-learning control for gear position of automotive AMT

For automotive AMT, the gear positions of gearbox are often different because of tolerances of manufacture and installation. And after a long-term use, the gear positions also change. So the original gear position parameters affect the shifting process. It is a cost-effective solution to add self-learning control into software and correct the gear position parameters adaptively. The paper proposes a self-learning control for gear positions, which has been tested and verified by simulation and experiment with satisfactory results.