Optimal Power Allocation-based Sizing Method with High Computation Efficiency for Fuel Cell EMU Intercity Train Considering the Power Source Degradation

Parameter sizing is critical for fuel cell hybrid system. However, the traditional static sizing method does not consider the impact of the system sizing scheme on the optimal power allocation solution, making it difficult to deeply optimize the system energy efficiency and service life. Therefore, this paper establishes the bi-loop system sizing method based on the optimal power allocation. Following two measures are proposed to improve the optimality and operability. Firstly, this paper establishes a total cost of ownership model for a fuel cell hybrid system to comprehensively consider the fuel consumption cost and power source degradation cost of the hybrid system. Secondly, in order to obtain the theoretical optimal solution for power allocation and reduce the computational burden, a computationally efficient dynamic programming algorithm is proposed based on reachable state sets and vectorized calculations strategies. At last, this paper carries out the feasibility verification of the proposed method based on the actual train parameters and obtains the Pareto Front of the optimal sizing schemes. On this basis, this paper presents the recommended sizing scheme according to the analysis of the obtained Pareto Front. Finally, a comparison study with traditional sizing methods is carried out to prove the superiority of the proposed method.