Parameter Matching Analysis of Hydraulic Hybrid Bergepanzers Based on RBF-Adaptive Artificial Immune Algorithm

Abstract

Due to the multiple types of support tasks and high-energy efficiency equipment, energy saving research in a Bergepanzer has attracted much attention in recent years. A hydraulic hybrid system is an effective way for these problems of Bergepanzers. The initial problem is to optimize the parameter optimization-matching for a new hydraulic hybrid Bergepanzers (NHHB), which is a relatively complex and variable time-varying nonlinear system. In this paper, an RBF-adaptive artificial immune algorithm (RBF&AAIA) is presented to solve the parameter optimization-matching problem, and the performance of algorithm is analyzed. Finally, the RBF&AAIA is successfully used for the NHHB to optimize the parameters of key components for the minimum energy consumption of system, and the optimal parameter matching group is obtained.