A novel effective nonlinear state observer based robust nonlinear sliding mode controller for a 6 kW Proton Exchange Membrane Fuel Cell voltage regulation

• Published in: Sustainable energy technologies and assessments 2021-04, Vol.44, p.100996, Article 100996
• Main Authors: Dali, Ali, Abdelmalek, Samir, Bakdi, Azzeddine, Bettayeb, Maamar
• Format: Article
• Language: English
• Subjects: Interleaved boost converter; Nonlinear sliding mode control; Nonlinear state observer; PI controller; Proton Exchange Membrane Fuel Cell; PSO algorithm
• ISSN: 2213-1388
• DOI: 10.1016/j.seta.2021.100996

[Display omitted] •A PSO-optimized nonlinear sliding mode controller is designed based on a state observer for fuel cells.•The new strategy is developed for optimal PEMFC voltage regulation through DC-DC interleaved boost converters (IBC).•Practical conditions and nonlinear time-varying behavior were considered to ensure effectiveness.•PSO is used to optimize the design against disturbances, load variations, and parameter uncertainties and variations.•This flexible controller matches the system specifications and has potential applications compared to the conventional techniques. This paper presents an effective strategy for controlling an Interleaved DC/DC Boost Converter (IBC) that is employed for reducing the current fluctuations in a 6 kW Proton Exchange Membrane Fuel Cell (PEMFC). The proposed design incorporates a new nonlinear control law combined with a nonlinear state observer, it aims at enhancing the durability of the Fuel Cells (FCs) and extending their lifetime. In this regard, a Nonlinear State Observer (NSO) is designed to simultaneously estimate current and voltage signals of the Fuel Cell Source (FCS) and a Nonlinear Sliding Mode Controller (NSMC) is constructed based on these estimates. The proposed sensorless control design is advantageous in avoiding current and voltage sensors redundancy to maintain low cost and complexity levels. Accurate output voltage tracking performance, tracking stability, and dynamic errors for a PEMFC-IBC are considered during changes of the internal model parameters in addition to effects of measurement uncertainties. A third advantage of this design is robustness and external disturbance rejection under large load variations. For these objectives, the observer and the controller parameters are optimally tuned using a recent Metaheuristic Particle Swarm Optimization Algorithm (MPSOA) inspired by the swarm intelligence for improving the dynamic performance of the controlled system. Furthermore, stability and tracking analysis properties of the closed-loop overall system are proved through Lyapunov theory for dynamic operating conditions. Finally, numerical simulations of a typical 6 kW PEMFC system validate the effectiveness of the proposed scheme with comparisons to contemporary approaches across the different cases.