Vehicle physical parameter identification based on an improved Harris hawks optimization and the transfer matrix method for multibody systems.

The Harris Hawk Optimization (HHO) is an excellent algorithm, but it also has the possibility of being trapped in local optima and premature convergence. To increase the accuracy of vehicle parameter identification, an improved HHO is proposed to enhance exploration and exploitation, named MPHHO. The algorithm integrates two unique operations of the Marine Predators Algorithm, which are the strategy affected by fish aggregating devices (FADs) and the marine memory storage strategy. According to the characteristic of HHO that the exploration ability decreases linearly with the advance of the iteration and completely converts to exploitation ability in the second half iteration, the step size control parameter of the strategy considering FADs effect is modified by a concave-convex cos function to further intensify the performance. The superiority of the MPHHO is proved by comparing the results of 23 classic test functions with other advanced nine algorithms. Moreover, the variant of HHO is combined with the transfer matrix method for multibody systems (MSTMM) for the first time to identify the physical parameters of a vehicle model. Good agreements are achieved that the average relative errors of the determined vehicle parameters and the modal parameters are all within 1%, which demonstrates the hybrid method based on the MPHHO and the MSTMM has an excellent performance in vehicle parameter identification. [ABSTRACT FROM AUTHOR]