摘要
Energy management is an important issue in the operation of hybrid electric trains.To achieve optimal energy utilization,this paper proposes a dynamic programming approach considering state space reduction to solve the optimization problem.Dynamic programming,as an exact algorithm,has a clear advantage in terms of solution accuracy,but its efficiency is low when dealing with large-scale optimization problems.Firstly,the paper introduces the topology and operation modes of hydrogen fuel cell hybrid trains,as well as the basic principles and computational steps of dynamic programming.Secondly,several state reduction strategies are designed to improve solution efficiency,and an objective function considering both passenger experience and operational costs is proposed.The numerical experimental results demonstrate that the proposed method not only solves the inherent problems of dynamic programming but also outperforms traditional dynamic programming and level set-based optimization methods in terms of computational accuracy and time.Furthermore,experimental results based on real driving conditions validate the applicability of the proposed method.
