Coordinated control of upshift power of double clutch transmission for electric vehicle based on particle swarm optimization

A dynamic model of double clutch transmission during upshift process was established in this paper. The friction work and shock degree were used to establish the evaluating indicator in the form of weighted sum. Considering that the optimizing object of the electric vehicle integrated powertrain shifting control has strong nonlinearity, and that traditional optimizing methods based on gradient algorithm can hardly acquire good result, a particle swarm optimization method to optimize the upshift processing of double clutch transmission was used, in which motor was involved. In the optimizing process, Fourier base vector decomposition method was used to decompose the clutch torque trace and the motor torque trace to linear combination of base vectors. The particle swarm optimization algorithm was used to optimize these base vectors coefficients in order to scheme out the torque traces of DCT and electric motor output. And then an integrated control method of motor and double clutch transmission was proposed. With the vehicle test result, the new control method reduced the friction work by 9%, and kept shock degree within a reasonable range which satisfied the national standard. The optimized gear shifting time was also reduced and the quality of gear shifting was improved.