The Research of Energy Management Strategy for Direct Methanol Fuel Cell/Battery Hybrid System

Cao, Lingzhi; Li, Chunwen; Liu, Lefeng

doi:10.1109/appeec.2010.5448352

Cited by 3 publications

(3 citation statements)

References 12 publications

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“…The direct methanol fuel cell (DMFC) hybrid energy storage system using neural network control, combined with photovoltaic (PV) and lithium‐ion batteries, can rapidly compensate for the power demand, and its ability to track voltage changes and resist interference is stronger, which may allow it to be widely used for residential power systems in the future [73]. An energy distribution control strategy based on fuzzy logic can extend the operation of the DMFC hybrid system and increase its efficiency and stability [74]. Owing to the coking problem of ethanol fuel, realization of its stable power generation remains a big challenge.…”

Section: Emergency Scheduling Of Electricity‐hydrogen Coupled Systems...mentioning

confidence: 99%

Hydrogen‐powered smart grid resilience

Han

Wang

et al. 2023

Energy Conversion and Econom

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With an increasing frequency of natural disasters and security attacks, the safe and stable operation of smart grid has been challenged unprecedently. To reduce the economic loss and social impact caused by power outage accidents, it is urgent to develop and improve the smart grid technology, and strengthen the disaster resistance and recovery capability of smart grids when faced with extreme events. As an efficient and flexible secondary energy source, hydrogen is crucial in improving the resilience of smart grid and supporting energy security. To further promote the deep integration of hydrogen systems and smart grid and improve the energy system resilience, the resilience of smart grids supported by hydrogen is assessed in this study. First, a technical framework of hydrogen-powered smart grid resilience is established, and the value of hydrogen-powered smart grid resilience is analysed considering different time frames (before, during and after an extreme event) of smart grids facing extreme events. Then, hydrogen-powered smart grid resilience is investigated from perspectives of pre-prevention regulation, in-process correction regulation, and postrecovery regulation. Finally, future direction for hydrogen-powered smart grid resilience is investigated and related policy suggestions are provided.

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Section: Emergency Scheduling Of Electricity‐hydrogen Coupled Systems...mentioning

confidence: 99%

Hydrogen‐powered smart grid resilience

Han

Wang

et al. 2023

Energy Conversion and Econom

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“…Similarly, using ANFIS and ANN, Hasiloglu et al [44] modeled a DMFC using temperature, methanol solution flow rate and concentration at the anode, airflow at the cathode, and current as the input parameters, while cell voltage was the output. Using fuzzy logic-based control, Cao et al [45] optimized the energy consumption in a hybrid energy system composed of a battery and a DMFC, aiming to maximize the efficiency of the DMFC while keeping a high state of charge in the battery. Still, a lot of work needs to be carried out for the proper modeling and optimization of DMFCs.…”

Section: Introductionmentioning

confidence: 99%

Maximization of Power Density of Direct Methanol Fuel Cell for Greener Energy Generation Using Beetle Antennae Search Algorithm and Fuzzy Modeling

Al Shouny,

Rezk,

Sayed

et al. 2023

Biomimetics

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Direct methanol fuel cells (DMFCs) are promising form of energy conversion technology that have the potential to take the role of lithium-ion batteries in portable electronics and electric cars. To increase the efficiency of DMFCs, many operating conditions ought to be optimized. Developing a reliable fuzzy model to simulate DMFCs is a major objective. To increase the power output of a DMFC, three process variables are considered: temperature, methanol concentration, and oxygen flow rate. First, a fuzzy model of the DMFC was developed using experimental data. The best operational circumstances to increase power density were then determined using the beetle antennae search (BAS) method. The RMSE values for the fuzzy DMFC model are 0.1982 and 1.5460 for the training and testing data. For training and testing, the coefficient of determination (R2) values were 0.9977 and 0.89, respectively. Thanks to fuzzy logic, the RMSE was reduced by 88% compared to ANOVA. It decreased from 7.29 (using ANOVA) to 0.8628 (using fuzzy). The fuzzy model’s low RMSE and high R2 values show that the modeling phase was successful. In comparison with the measured data and RSM, the combination of fuzzy modeling and the BAS algorithm increased the power density of the DMFC by 8.88% and 7.5%, respectively, and 75 °C, 1.2 M, and 400 mL/min were the ideal values for temperature, methanol concentration, and oxygen flow rate, respectively.

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“…These rule-based design methods are widely recognized as the most practical energy management methods due to their simplicity and practicality. State machine-based energy management strategies require information about the previous state of the system as well as the current inputs, and they execute the outputs based on a defined flow chart or decision tree [21,22]. The core of the state machine control strategy is to ensure that the fuel cell has different output powers in different states [23].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Energy Management Strategy of Hydrogen Fuel Cell Hybrid Electric Vehicles Based on Power Following Strategy–Fuzzy Logic Control Strategy Hybrid Control

Zou,

Luo,

2023

WEVJ

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Fuel cell hybrid electric vehicles have the advantages of zero emission, high efficiency and fast refuelling, etc. and are one of the key directions for vehicle development. The energy management problem of fuel cell hybrid electric vehicles is the key technology for power distribution. The traditional power following strategy has the advantage of a real-time operation, but the power correction is usually based only on the state of charge of a lithium battery, which causes the operating point of the fuel cell to be in the region of a low efficiency. To solve this problem, this paper proposes a hybrid power-following-fuzzy control strategy, where a fuzzy logic control strategy is used to optimise the correction module based on the power following strategy, which regulates the state of charge while correcting the output power of the fuel cell towards the efficient operating point. The results of the joint simulation with Matlab + Advisor under the Globally Harmonised Light Vehicle Test Cycle Conditions show that the proposed strategy still ensures the advantages of real-time energy management, and for the hydrogen fuel cell, the hydrogen consumption is reduced by 13.5% and 4.1% compared with the power following strategy and the fuzzy logic control strategy, and the average output power variability is reduced by 14.6% and 5.1%, respectively, which is important for improving the economy of the whole vehicle and prolonging the lifetime of fuel cell.

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The Research of Energy Management Strategy for Direct Methanol Fuel Cell/Battery Hybrid System

Cited by 3 publications

References 12 publications

Hydrogen‐powered smart grid resilience

Hydrogen‐powered smart grid resilience

Maximization of Power Density of Direct Methanol Fuel Cell for Greener Energy Generation Using Beetle Antennae Search Algorithm and Fuzzy Modeling

Real-Time Energy Management Strategy of Hydrogen Fuel Cell Hybrid Electric Vehicles Based on Power Following Strategy–Fuzzy Logic Control Strategy Hybrid Control

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