Fuel cell commercial vehicles, owing to their advantages such as long driving range, short refueling time, and zero emissions, are regarded as an important technological pathway for low-carbon transformation in the heavy-duty freight sector. However, the contradiction between the insufficient durability of fuel cell systems and the vehicle's hydrogen economy significantly hinders their large-scale commercial application. The energy management strategy, as the core technology coordinating power distribution between the fuel cell and auxiliary energy sources, directly determines the vehicle's overall performance and the degradation rate of core components. This paper systematically analyzes the degradation mechanisms of fuel cells and traction batteries under commercial vehicle operating conditions, reviews the current mainstream rule-based, optimization-based, and learning-based energy management strategies, and focuses on collaborative control methods that balance service life and performance. Research indicates that multi-objective hierarchical strategies based on health awareness, model predictive control, and reinforcement learning methods can effectively suppress the dynamic degradation of the fuel cell while meeting vehicle power demands, achieving a Pareto optimum between vehicle economy and system durability. This paper provides a theoretical reference for further enhancing the lifecycle economy of fuel cell commercial vehicles.