Stochastic optimisation-based methods for the identification of the physical parameters of a metal hydride tank.

In this paper, three optimisation methods are used to determine the parameters of a commercial metal hydride hydrogen tank, considered as a grey box in which the thermophysical parameters are unknown. These parameters are essential for the development of energy management strategies and the study of tank ageing. A model of the hydride tank containing an AB 5 intermetallic was developed and experimentally validated. An absorption test campaign of the studied tank was carried out to collect data necessary for the optimisation algorithms. A comparative study was carried out in accordance with the speed of convergence and precision between the three stochastic optimisation methods: Particle Swarm Optimisation (PSO), Genetic Algorithm (GA) and Differential Evolution (DE). The results of the simulation of the storage system using the parameters determined by the algorithms show a remarkably close agreement with the experimental data, with a maximum error of 2.1%. • Innovative proposal for the determination of parameters of a metal hydride hydrogen tank. • Experimental test for the static characterization of a metal hydride tank for hydrogen storage. • An experimentally verified mathematical model for the hydrogen storage system is put forth. • Validation with experimental data and three stochastic optimisation methods: PSO, GA and DE. [ABSTRACT FROM AUTHOR]