Mathematical Modeling for Holistic Convex Optimization of Hybrid Trains

TL;DR

This paper develops a comprehensive convex optimization framework for hybrid trains, incorporating novel thermal battery models and real-world data to minimize hydrogen fuel consumption while managing thermal constraints.

Contribution

It introduces a holistic convex modeling approach for hybrid trains, including a new battery thermal model and real-world data validation.

Findings

Convex models enable efficient optimization of hybrid train operation.

The thermal battery model helps extend battery lifetime.

Hydrogen fuel consumption is minimized effectively.

Abstract

We look into modeling fuel cell hybrid trains for the purpose of optimizing their operation using convex optimization. Models and constraints necessary to form a physically feasible yet convex problem are reviewed. This effort is described as holistic due to the broad consideration of train speed, energy management system, and battery thermals. The minimized objective is hydrogen fuel consumption for a given target journey time. A novel battery thermal model is proposed to aid with battery thermal management and thus preserve battery lifetime. All models are derived in the space-domain which along constraint relaxations guarantee a convex optimization problem. First-principle knowledge and real-world data justify the suitableness of the proposed models for the intended optimization problem.