Optimization matching of wheel drive hydraulic hybrid vehicle components based on adaptive simulated annealing genetic algorithm

Compared with the traditional vehicle, a wheel drive hydraulic hybrid vehicle (WDHHV) based on the technique of hydrostatic secondary regulation has the advantages of improved fuel consumption, traction performance and active stability. The parameters of the key components in its drivetrain such as hydraulic pump/motors, accumulators, etc. determine the overall efficiency and performance of the vehicle. To optimize the matching of a WDHHV's components, the adaptive simulated annealing genetic algorithm (ASAGA) was adopted. According to different optimization objectives, the parameters were calculated and imported into the corresponding Simulink model to simulate the characters. The comparison between the results calculated by ASAGA and those by the traditional engineering test method proves that ASAGA enhances the overall searching speed and capability effectively, and is thus a better method for the optimization of the vehicle drivetrain's parameters.