Novel neural network IC-based variable step size fuel cell MPPT controller

Harrag, Abdelghani; Bahri, Hamza

doi:10.1016/j.ijhydene.2016.12.079

Cited by 80 publications

(24 citation statements)

References 19 publications

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“…The sFF strategy proposed in [56] will be used as reference with the LFW control implemented in the same manner (see Table 1) for a fair comparison of each strategy RTOk, k = 1 ÷ 7, based on the gaps (18) in the performance indicators:…”

Section: Energy Management Strategies For the Renewable Fuel Cell Hybmentioning

confidence: 99%

“…These strategies can find and track in real-time the optimal solution or a suboptimal solution close to it [7,12]. The RTO strategies usually use optimization algorithms such as the Extremum Seeking (ES) algorithms [13,14], the Equivalent Consumption Minimization Strategy (ECMS) [15,16], the intelligent algorithms [17][18][19], the Model Predictive Control (MPC) schemes [20,21], and so on [22][23][24][25][26]. From these RTO-strategies, the ECMSs based on Pontryagin's Minimum Principle (PMP) [26,27] or Dynamic Programming (DP) are most used for FC-HPS [10].…”

Section: Introductionmentioning

confidence: 99%

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Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/FC-Based Hybrid Power Systems Based on Load-Following Control

Bizon

Oproescu

2018

Energies

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Besides three different real-time optimization strategies analyzed for the Renewable/ Fuel Cell Hybrid Power Systems (REW/FC-HPS) based on load-following (LFW) control, a short but critical assessment of the Real-Time Optimization (RTO) strategies is presented in this paper. The advantage of power flow balance on the DC bus through the FC net power generated using the LFW control instead of using the batteries’ stack is highlighted in this study. As LFW control consequence, the battery operates in charge-sustained mode and many advantages can be exploited in practice such as: reducing the size of the battery and maintenance cost, canceling the monitoring condition of the battery state-of-charge etc. The optimization of three FC-HPSs topologies based on appropriate RTO strategy is performed here using indicators such as fuel economy, fuel consumption efficiency, and FC electrical efficiency. The challenging task to optimize operation of the FC-HPS under unknown profile of the load demand is approached using an optimization function based on linear mix of the FC net power and the fuel consumption through the weighting coefficients knet and kfuel. If optimum values are chosen, then a RTO switching strategy can improve even further the fuel economy over the entire range of load.

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Section: Energy Management Strategies For the Renewable Fuel Cell Hybmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/FC-Based Hybrid Power Systems Based on Load-Following Control

Bizon

Oproescu

2018

Energies

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“…Real-Time Optimization (RTO) strategies for Fuel Cell Hybrid Power Sources (FCHPS) usually use the Extremum Seeking (ES) algorithm [1], Model Predictive Control (MPC) [2], Equivalent Consumption Minimization Strategy (ECMS) [3], robust control [4], intelligent algorithms [5,6] and other techniques [7] to find the optimal point of operation. The ECMS is one of most used RTO strategy, being based on Dynamic Programming (DP) [8] and Pontryagin's Minimum Principle (PMP) [9].…”

Section: Real-time Optimization Strategiesmentioning

confidence: 99%

Real-time strategy to optimize the airflow rate of fuel cell hybrid power source under variable load cycle

Bizon

Culcer

Oproescu

et al. 2017

2017 International Conference on Applied Electronics (AE)

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“…Harrag and Bahri proposed a neural network variable step size IC‐based MPPT controller for the PEMFC power system. The efficiency of the proposed method has been successfully studied using Matlab/Simulink environment.…”

Section: Introductionmentioning

confidence: 99%

A Novel Single Sensor Variable Step Size Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell Power System

Harrag

Bahri

2019

Fuel Cells

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This paper proposes a novel single sensor variable step size maximum power point tracking (MPPT) method for proton exchange membrane (PEM) fuel cell. This paper is a first, if modest, attempt to develop a single sensor MPPT for fuel cell systems. The proposed MPPT algorithm uses only one sensor to track the maximum power of PEM fuel system composed of 7 kW proton exchange membrane fuel cell (PEMFC) powering 50 Ω resistive load via a DC–DC boost converter driven using the proposed MPPT. The performances of the proposed controller have been evaluated using the implemented PEM fuel cell power system Matlab/Simulink model using two test scenarios considering temperature and hydrogen pressure variation. Simulation results show that the proposed controller can effectively track the maximum power point using only one sensor which reduces the cost as well as the complexity of the PEM fuel cell power system. Comparative results with the two sensors MPPT show that the two sensors MPPT outperforms the single sensor MPPT regarding the dynamic performances. However, the proposed single sensor MPPT performs better considering the static performances. In addition, the proposed controller reduces drastically the current ripple increasing by the way the fuel cell efficiency and lifetime by reducing the frequent trip due to over‐current and even harmonics.

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Novel neural network IC-based variable step size fuel cell MPPT controller

Cited by 80 publications

References 19 publications

Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/FC-Based Hybrid Power Systems Based on Load-Following Control

Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/FC-Based Hybrid Power Systems Based on Load-Following Control

Real-time strategy to optimize the airflow rate of fuel cell hybrid power source under variable load cycle

A Novel Single Sensor Variable Step Size Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell Power System

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