Fast Model Predictive Control of PEM Fuel Cell System Using the L1 Norm

Author:

Nebeluk RobertORCID,Ławryńczuk MaciejORCID

Abstract

This work describes the development of a fast Model Predictive Control (MPC) algorithm for a Proton Exchange Membrane (PEM) fuel cell. The MPC cost-function used considers the sum of absolute values of predicted control errors (the L1 norm). Unlike previous approaches to nonlinear MPC-L1, in which quite complicated neural approximators have been used, two analytical approximators of the absolute value function are utilised. An advanced trajectory linearisation is performed on-line. As a result, an easy-to-solve quadratic optimisation task is derived. All implementation details of the discussed algorithm are detailed for two considered approximators. Furthermore, the algorithm is thoroughly compared with the classical MPC-L2 method in which the sum of squared predicted control errors is minimised. A multi-criteria control quality assessment is performed as the MPC-L1 and MPC-L2 algorithms are compared using four control quality indicators. It is shown that the presented MPC-L1 scheme gives better results for the PEM.

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference38 articles.

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3. Modeling, Simulation, and Concept Studies of a Fuel Cell Hybrid Electric Vehicle Powertrain;Özbek,2010

4. Influence of Low Inlet Pressure and Temperature on the Compressor Map Limits of Electrical Turbo Chargers for Airborne Fuel Cell Applications

5. PEM fuel cell cathode-side flow field design optimization based on multi-criteria analysis of liquid-slug dynamics

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