Offline model predictive control approach to micro-slip control in gearshifts of dual clutch transmission

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Abstract
Dual clutch transmission can avoid some noise vibration and harshness issues caused by other transmissions with single clutch. And applying micro-slip control on clutches can further improve the gearshift performance of transmission compared to the lock-up control. Considering the real-time characteristic of vehicle control, an offline model predictive controller designed by multi-parameter quadratic programming was creatively applied in dual clutch transmission to obtain both clutch torque at the same time with optimal control algorithm. In this way, while realizing the micro-slip state of the clutches, the fast response speed can be realized through the off-line controller, which makes it more feasible and practical for transmission control. A six degrees of freedom vehicle powertrain system model was built in MATLAB/Simulink to simulate the proposed control algorithm. The simulation results show that the micro-slip control avoid the negative torque compared to the lock-up control, which leads to a smoother shift process. In addition, compared with the proportional–integral–derivative micro-slip controller, the offline model predictive controller can achieve more stable control effects with less output torque fluctuation and shorter gearshift time.
Funding Information
  • National Natural Science Foundation of China (51675326)

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