Abstract: | The control accuracy of the electronic transmission range select (ETRS) system is affected by the part dimensional errors and assembly errors in the automatic transmission and the gear box actuator. The theoretical positions of the parking gear, reverse gear, neutral gear and drive gear cannot match the actual results after assembly, which will not only affect the control precision of the ETRS system, but also have the risk of shift failure after long-term use. Therefore the hardware architecture was designed and the gear position recognition method and the key self-learning control algorithm were proposed for the ETRS system.The control algorithm achieves uniform speed control of the DC motor, sampling of H-bridge drive current data, gear position identification at the slot bottom, multi-turn scanning of the slot bottom and the gear position verification. The simulation and experimental results show that the error of the gear position identification is less than 0.15°. By applying the self-learning control algorithm, the difference between the
mean value from the actual vehicle test results using big data and the theoretical angle is within 0.3°, meeting
the long-term requirements on accuracy and durability for the ETRS system. |