Optimal Component Sizing Strategy for Fuel Cell Hybrid Truck Powertrain System Based on Multi-Population Gray Wolf Algorithm

To reduce the cost of proton exchange membrane fuel cells (PEMFCs), this paper develops a cost-optimized approach for determining the optimal sizes of various components in the hybrid power system. Firstly, a model of the PEMFC-battery hybrid power system is established to capture both static and dynamic characteristics. An energy management strategy, based on the Pontryagin's minimum principle, is proposed to ensure a real-time balance between instantaneous power demand and supply while maintaining the battery state of charge at a reasonable level. Subsequently, an optimization problem is formulated to minimize the component costs of the hybrid power system, satisfying the constraints imposed by vehicle power performance. To enhance the global search capability and local optimization ability of the traditional grey wolf algorithm, a multi-population grey wolf algorithm is proposed to solve the presented constrained optimization problem. Finally, the effectiveness of the proposed method are validated through simulation results.