A novel power management strategy for hybrid off-road vehicles

Hybrid off-road vehicles generally use an engine and an energy storage system (e.g., ultracapacitor) as the power sources for propulsion. By optimally splitting power demand to different actuators (i.e., electric motors), fuel economy can be improved greatly. Thus, the control strategies of hybrid vehicles play an important role in fuel savings. While many optimal control strategies have been proposed, two major concerns present themselves: the need for prior knowledge of future driving conditions and the slow computation speed. In this paper, a novel near-optimal power management strategy, called efficiency-based evaluation real time control strategy (EERCS), is developed to rapidly obtain near-optimal fuel economy. We formulate the normalized efficiency of power flow as the criterion. By maintaining high system efficiency under all conditions, the controller can obtain near-optimal fuel economy with no need for prior knowledge. To validate the control effect, the proposed novel controller is compared with dynamic programming (DP) and power-weighted efficiency analysis for rapid sizing (PEARS+). A complex mull-mode power-split hybrid track-type dozer is selected for the case study. Simulation results show that the new power management strategy produces results similar to those of DP and PEARS+ together, with a faster computation speed. Two distributed drive cycles are used to verify the robustness of EERCS. The resulting control law can also be applied online as a static mapping function of the powertrain state. The proposed novel strategy is also a promising control tool that can be extended to other types of hybrid electric vehicles.