Trajectory Prediction of the Upshifting Process of Two Speed Dual Clutch Transmission in Electric Vehicles
Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023
Electric vehicles (EVs) have been fueled by the environmental crisis resulting from conventional vehicles. In EVs, dual clutch transmission (DCT) has emerged as a prevalent type of automatic transmission, which employs a clutch-to-clutch control strategy for gear shifting by engaging and separating two clutches. Therefore, clutch performance is critical to the shifting process and directly affects the quality of gear shifts. In this study, we investigate and analyze the power-on upshifting process of a two-speed DCT in an EV model and the criteria for evaluation of the shifting quality. A simulation model is constructed to validate the upshifting process analysis in MATLAB and Simulink and demonstrate satisfactory results. To predict the trajectory of the second clutch slip speed, a support vector machine (SVM) is constructed based on the data simulated by the simulation model. Additionally, considering the conditions in which the noisy measurement occurs, the Kalman filter is also employed as another helpful method to estimate the slip speed of the second clutch based on the obtained data. It can be seen from both results that the predicted values are in line with the simulation data and that the prediction models are effective.
Open Access Status
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