Nonlinear predictive control for durability enhancement and efficiency improvement in a fuel cell power system

Abstract

In this work, a nonlinear model predictive control (NMPC) strategy is proposed to improve the efficiency and enhance the durability of a proton exchange membrane fuel cell (PEMFC) power system. The PEMFC controller is based on a distributed parameters model that describes the nonlinear dynamics of the system, considering spatial variations along the gas channels. Parasitic power from different system auxiliaries is considered, including the main parasitic losses which are those of the compressor. A nonlinear observer is implemented, based on the discretised model of the PEMFC, to estimate the internal states. This information is included in the cost function of the controller to enhance the durability of the system by means of avoiding local starvation and inappropriate water vapour concentrations. Simulation results are presented to show the performance of the proposed controller over a given case study in an automotive application (New European Driving Cycle). With the aim of representing the most relevant phenomena that affects the PEMFC voltage, the simulation model includes a two-phase water model and the effects of liquid water on the catalyst active area. The control model is a simplified version that does not consider two-phase water dynamics.

Cost-Optimal Energy Management of Hybrid Electric Vehicles Using Fuel Cell/Battery Health-Aware Predictive Control

“…Typically, noncausal DP and CP can only be implemented offline, as driving cycles must be known beforehand. To explore the possibility of online optimized energy management, causal optimization methods, e.g., equivalent consumption minimization strategy (ECMS) [23], [24], Pontryagin's Minimum Principle (PMP) [25], [26], and model predictive control (MPC) [27], [28], were adopted. These controllers with appropriate design and tuning always produce a satisfactory performance in energy consumption, operating cost, or the total cost of vehicle ownership.…”

Energy management strategy for fuel cell-supercapacitor hybrid vehicles based on prediction of energy demand

“…Currently, it is not entirely clear how to accurately establish the power rate limits to assure non-premature ageing of FCs. Quantifying degradation in FCs is a complex task because the degradation rate strongly depends on the internal conditions [20,21]. Although some authors do not consider power rate constraints in the fuel cell [22,23,24,25], values between 2% and 20% of its maximum power per second are usually adopted [26,27,10,18,28,29,14,30].…”

Control‐oriented LPV Modeling for the Air Supply System of Proton Exchange Membrane Fuel Cells

“…In order to avoid internal oxygen starvation and inappropriate water content, Luno et al. established a stack model with static two‐phase flow and supply air with a single control variable air supply system, and designed a controller based on the nonlinear MRC method for the air supply system. Based on a simplified nonlinear control model and using the differential flatness control theory.…”

“…In order to realize the control of a 150 KW fuel cell engine, Liu et al [8] established a single state quantity air supply system model, and designed a feedback control strategy based on PI control theory. In order to avoid internal oxygen starvation and inappropriate water content, Luno et al [9] established a stack model with static twophase flow and supply air with a single control variable air supply system, and designed a controller based on the nonlinear MRC method for the air supply system. Based on a simplified nonlinear control model and using the differential flatness control theory.…”