Energy Management for Unmanned Tracked Vehicles Based on Global Path

Shaohang Xu, Junqiang Xi, Huiyan Chen, Ziye Zhao, Shaojian Han

Abstract: Energy management is one of the critical considerations in the development of hybrid electric vehicles. Although energy management strategies have been extensively studied in manned vehicles, these strategies are not suitable for unmanned ones. In this paper, a new method of energy management for unmanned tracked vehicles (UTV) is proposed based on the global path of unmanned driving. Firstly, a method of global speed profile generation based on global path for energy management is proposed using nonlinear optimization, and the demand power of UTV is estimated based on the generated global speed profile and the tracked vehicle model. Secondly, energy allocation and control rules are made based on the global predicted power. Finally, the proposed energy management method is verified by a real-time field experiment with our UTV. The experimental results show that the proposed energy management strategy can meet the energy requirement of UTV, maintain the stability of battery SOC and reduce fuel consumption.