Fuel Cell Hybrid Power System Research Articles

Thermodynamic performance analysis of direct methanol solid oxide fuel cell hybrid power system for ship application

Methanol is a fuel that can be directly supplied to solid oxide fuel cell (SOFC) without carbon deposition. This paper introduces the direct methanol SOFC-Internal combustion engine (ICE) hybrid power and SOFC-Gas turbine (GT) hybrid power systems. Thermodynamic performance analysis of the hybrid power systems and an investigation into the impact of various parameters were conducted. The results indicate that the electric efficiency of the SOFC-ICE system is 56.07 %, which is 3 percentage points higher than the SOFC-GT system but 3–4 percentage points lower than the SOFC-ICE system with pre-reforming. Increasing fuel utilization rate, operation temperature, and excess air ratio is beneficial to the performance of the SOFC, and raising current density helps improve the system's power density. Load-sharing strategy research demonstrates that in a scenario where the power ratio between SOFC and the ICE is 35:65, compared to a methanol engine, the efficiency of the SOFC-ICE hybrid power system increases by 4.3 %. Despite a 1.4-fold increase in weight and a 1.66-fold increase in cost, the fuel consumption rate and carbon emissions decrease by 8.8 %. Therefore, the strategy of combining a high-power engine with a low-power SOFC is currently a suitable load-sharing strategy for ship applications.

Improving Sustainability in Urban and Road Transportation: Dual Battery Block and Fuel Cell Hybrid Power System for Electric Vehicles

Improving Sustainability in Urban and Road Transportation: Dual Battery Block and Fuel Cell Hybrid Power System for Electric Vehicles

Artificial Intelligence-Enabled Techno-Economic Analysis and Optimization of Grid-Tied Solar PV-Fuel Cell Hybrid Power Systems for Enhanced Performance

The incorporation of energy from renewable sources into the power grid is crucial for achieving sustainable and environmentally friendly power generation. This study proposes an artificial intelligence (AI)-enabled methodology for the analysis & optimization of “grid-tied solar photovoltaic (PV)-fuel cell hybrid power systems.” The research aims to demonstrate how AI techniques can assist in decision-making, improve system performance, and achieve higher levels of energy efficiency and financial viability. The study presents the results of a project focusing on a renewable energy system that feeds into the grid and powers a university building. The hybrid power system’s performance and cost were evaluated using unified approaches to modeling, simulation, optimization, and control. The findings indicate that the AI-optimized “solar PV-fuel cell hybrid system connected to the grid” offers excellent performance, meeting 74% of the building’s energy needs through renewable sources. The system also achieved a low levelled price for energy and minimise CO2 emissions, further enhancing its environmental sustainability. The proposed AI-enabled approach proves to be a promising solution for creating grid-connected renewable energy systems with significant benefits for energy efficiency, cost-effectiveness, and environmental impact.

Design, development, integration and evaluation of hybrid fuel cell power systems for an unmanned water surface vehicle

When fuel cells are used to power mobile applications, such a vehicles, hybridization with batteries is normally required. Depending on the electronic coupling between the energy sources the power plants can have passive or active configurations. Hybrid fuel cell-battery power plants with active power control flow have some advantages. For example, they can decrease the total energy losses, while improving the fuel cell performance, extending its lifetime. Power plants with DC/DC converters show low specific energy ratios, but with a superior energy management. In the present research, the hybrid power plant for an unmanned aquatic surface vehicle (USV) based on a PEM fuel cell and a Li-ion battery is developed. Active (with DC–DC converters) or passive architectures are analyzed by numerical simulations and experimental tests. Good results are obtained for the active power plant, where the peak power demands are managed by the battery pack while the fuel cell power remains constant thanks to the DC-converter control. The study shows that a simple control algorithm (no optimal) can help to extend the USV autonomy above 12h in calm waters with a specific energy of 85.6Whkg-1.

Hamiltonian Energy Control With Energy Management Strategy for Fuel Cell Hybrid Power System

Hamiltonian Energy Control With Energy Management Strategy for Fuel Cell Hybrid Power System

Lifetime-Optimized Energy Management Strategy for Fuel Cell Unmanned Aircraft Vehicle Hybrid Power System

To improve the durability of the fuel cell unmanned aircraft vehicle (UAV) hybrid power system, a model predictive control based energy management strategy (EMS) with minimum energy loss is presented in this paper. The proposed algorithm can effectively reduce the internal loss and power stress of the hybrid power system, which can help to extend fuel cell lifespan. Specifically, a calculation formula with observable parameters is proposed to predict the internal loss of the battery in both the charging and discharging mode. Besides, to increase the hybrid UAV adaptability under complex flying conditions, the fuel cell operating trajectory is also defined in the algorithm to increase the system dynamic performance and efficiency. To verify the effectiveness of the strategy, the hardware-in-the-loop (HIL) experimental test platform is built. Compared to the conventional equivalent consumption minimum strategy (ECMS), the proposed strategy can effectively alleviate the voltage degradation of the fuel cell and decrease the energy loss of the battery. The proposed strategy can help to contribute to the applications of fuel cell hybrid power system in the aviation fields.

A Scalable Segmented-Based PEM Fuel Cell Hybrid Power System Model and Its Simulation Applications

A scalable segmented-based proton-exchange membrane fuel cell (PEMFC) hybrid power system model is developed in this paper. The fuel cell (FC) is developed as a dynamic lumped parameter model to predict the current distributions during dynamic load scenarios. The fuel cell is segmented into 3×3 segments connected with several physical ports and with the variables balanced automatically. Based on the proposed model, a real-time energy management framework is designed to distribute the load current demand during dynamic operations. Simulation results show that the proposed strategy has good performance on both single/segmented fuel cell–battery hybrid systems and the low battery state of charge (SOC) situation. This paper proposes an approach that uses an interconnected ordinary differential equations (ODEs) system model in control problems, which makes the control algorithms readily applicable.

HIERARCHICAL ENERGY MANAGEMENT STRATEGY BASED ON THE MAXIMUM EFFICIENCY RANGE FOR A MULTI-STACK FUEL CELL HYBRID POWER SYSTEM

A multi-stack fuel cell hybrid power system (MFCHS) consists of multiple sources with various characteristics. The power distribution between different sources influences the performance of the system, which involves many factors. To distribute the power effectively and enhance the efficiency and fuel economy of a single-stack fuel cell system, this study proposed a hierarchical energy management strategy (EMS) for MFCHS. An MFCHS configuration that included three fuel cell systems and a battery was presented. An MFCHS model that incorporated the effect of altitude was constructed, and an efficiency analysis of the multi-stack fuel cell system (MFCS) was performed. The hierarchical EMS of MFCHS was composed of a bottom control layer and a top management layer. The bottom control layer utilized a coordinated optimal distribution strategy based on the maximum efficiency range of MFCS to realize optimal power allocation between the different fuel cells in MFCS. The top management layer used EMS under multiple operating conditions to realize the effective distribution of the demand power between MFCS and the battery. Results demonstrate that the proposed strategy improves the average efficiency of MFCS by up to 5.2% and 8.9% compared with those of the equal distribution and daisy chain strategies, respectively. The proposed strategy also displays good performance in terms of the hydrogen consumption of MFCS, which saved 1% and 3% hydrogen compared with the equal distribution and daisy chain strategies, respectively. The proposed strategy results in promising improvements in the overall performance of the system. This study provides a good reference for developing EMS for MFCHS. Keywords: Fuel cell, Multi-stack fuel cell hybrid power system, Energy management strategy, Coordinated optimal distribution, Maximum efficiency range

Coyote Optimization Algorithm-Based Energy Management Strategy for Fuel Cell Hybrid Power Systems

This research proposes an improved energy management strategy (EMS) for a fuel cell hybrid power system for an electric aircraft based on a recently developed coyote optimization algorithm (COA). The suggested hybrid system consists of fuel cells and an energy storage system (ESS) to supply the required load in stable conditions. The distribution and performance of the hybrid electrical power system are determined by various energy sources. Consequently, having the best energy management system is essential for completing this work. The suggested EMS’s main objectives are to reduce hydrogen energy utilization and increase power source longevity. The proposed coyote optimization algorithm with external energy maximization strategy (COA-EEMS) and coyote optimization algorithm with equivalent consumption minimisation strategy (COA-ECMS) are tested with the help of the Opal-RT 5700 real-time HIL simulator and MATLAB/Simulink. The proposed algorithms confirm their robustness and higher efficiency by minimizing hydrogen fuel consumption compared to existing algorithms. The merits of the proposed algorithms are presented in detailed and compared with existing algorithms.

Hydrogen Fuel Cell Power System—Development Perspectives for Hybrid Topologies

In recent years, the problem of environmental pollution, especially the emission of greenhouse gases, has attracted people’s attention to energy infrastructure. At present, the fuel consumed by transportation mainly comes from fossil energy, and the strong traffic demand has a great impact on the environment and climate. Fuel cell electric vehicles (FCEVs) use hydrogen energy as a clean alternative to fossil fuels, taking into account the dual needs of transportation and environmental protection. However, due to the low power density and high manufacturing cost of hydrogen fuel cells, their combination with other power supplies is necessary to form a hybrid power system that maximizes the utilization of hydrogen energy and prolongs the service life of hydrogen fuel cells. Therefore, the hybrid power system control mode has become a key technology and a current research hotspot. This paper first briefly introduces hydrogen fuel cells, then summarizes the existing hybrid power circuit topology, categorizes the existing technical solutions, and finally looks forward to the future for different scenarios of hydrogen fuel cell hybrid power systems. This paper provides reference and guidance for the future development of renewable hydrogen energy and hydrogen fuel cell hybrid electric vehicles.

Analysis of solid oxide fuel cell hybrid power system in marine application for CO2 reduction

The usefulness of a solid oxide fuel cell (SOFC) for a large vessel is evaluated by estimating the amount of CO2 emitted by a crude oil tanker. Conventional and two SOFC hybrid power generation systems are proposed and analyzed. The traditional system consists of five generators and a steam boiler, whereas two SOFC hybrid systems are made up of five smaller generators with additional SOFC power and a steam boiler. The performance of the SOFC is calculated through a zero-dimensional model developed, including electrochemical stack model. The CO2 emission of the SOFC hybrid system is estimated depending on the SOFC capacity, 2.5 MW and 5.0 MW. CO2 emissions in the SOFC hybrid system are 5.4% ∼8.8% lower than in the traditional structure for one round trip sail. The reduction of CO2 comes from two factors; the high efficiency of SOFC and the operations of DF generators at a relatively high load rate. The SOFC hybrid system can be an eco-friendly technology to reduce the CO2 emissions of the large ships.

Adaptive energy management for fuel cell hybrid power system with power slope constraint and variable horizon speed prediction

An adaptive energy management strategy (EMS) is proposed to improve the economy and reliability of the fuel cell vehicle. Firstly, a variable horizon speed prediction method based on the principal component analysis and the K-means clustering is constructed. Then, an adaptive equivalent consumption minimization strategy (AECMS) with power slope constraints was designed to minimize the hydrogen consumption while ensuring reliability. Finally, a proportional-integral controller is used to track the air flow and pressure of the fuel cell engine (FCE) under energy distribution. Simulation results under West Virginia University Suburban (WVUSUB) show that the proposed strategy can improve the speed prediction accuracy by 2.80% and 25.57%, and reduce the hydrogen consumption by 2.79% and 2.66%, respectively, compared with the fixed 12 s and 15 s horizon. Moreover, the control error of oxygen excess ratio and the cathode pressure under energy distribution are 0.0102 (0.51%) and 189.4 Pa (0.0935%), respectively, indicating better reliability than the strategy without constraint.

Feasibility analysis of hydrogen production potential from rooftop solar power plant for industrial zones in Vietnam

Currently, global energy transformation and the promotion of renewable energy use are being taken care of to minimize the harm to the environment. However, the disadvantage of renewable energy is the random change, which leads to the regulation of grid operations, which is very difficult when the capacity of renewable energy sources accounts for a large proportion. The hydrogen production technology from wind and solar energy sources is one of the possible methods to minimize adverse impacts on the utility grid and serve the load demand of industrial zones. In this study, the photovoltaic (PV) hydrogen production potential for industrial zones in Vietnam is analyzed. The Homer was used to simulate and calculate power output. The results showed that the Hai Duong province has the lowest solar radiation, so the solar power output is 3600389 kWh/year, and the amount of hydrogen generated is less so it mainly serves the hydrogen load while the fuel cell can only generate very low amounts of electricity of about 4150 kWh/year for direct current (DC) load. The hybrid power systems in the typical industrial plant in Quang Nam province, Binh Thuan province, Can Tho city can generate about 17386 kg/year to 17422 kg/year to supply the operation of fuel cells based on the value of solar radiation of each province. The better the area with solar potential, the lower the net present cost (NPC), cost of energy (COE), and operation cost, so the economical and technical efficiency of the PV–Fuel cell hybrid power system will increase.

Dual Fuzzy Energy Control Study of Automotive Fuel Cell Hybrid Power System with Three Energy Sources

A dual fuzzy control strategy is proposed for the complex energy management problem in a multi-energy-source hybrid power system vehicle with fuel cell + Li-ion battery + super capacitor. According to the efficiency characteristic of each energy source in a fuel cell hybrid power system (referred to as FCHPS), a control scheme with a dual fuzzy control strategy is devised, in which the main fuzzy controller controls the fuel cell to ensure its power output. It is controlled by a sub-fuzzy controller that regulates the power output and braking energy recovery of the Li-ion battery and super capacitor. Simulation verification and comparative analysis were carried out under a world light vehicle test cycle (referred to as WLTC) conditions using MATLAB+ADVISOR. With a dual fuzzy control strategy, fuel cell hybrid vehicles meet dynamics requirements and the fuel economy of these vehicles is generally 6.7% and 6.4% better than power following control and single fuzzy control, respectively. Li-ion batteries are also capable of handling reduced average currents.

Energy Management Strategy for PEM Fuel Cell Hybrid Power System Considering DC Bus Voltage Regulation

Developing an energy management strategy (EMS) is an important requirement to satisfy the load power demand for a proton-exchange membrane fuel cell (PEMFC) hybrid system under different working conditions. For this objective, this paper proposes an EMS to control the power distribution between the PEMFC, battery (BAT), and supercapacitor (SC) and regulate the DC bus voltage for matching the load power demand. In this strategy, fuzzy logic rules (FLRs) and low-pass filters (LPFs) are utilized to determine the reference currents for energy sources based on their dynamic response. In addition, current and voltage control loops are designed to provide the appropriate gains for compensators that can maintain a stable voltage on the DC bus. Finally, simulations are conducted in the MATLAB/Simulink environment to validate and compare the effectiveness of the proposed strategy with others. The simulation results present that the proposed EMS achieves the highest distributed power accuracy with an error of (−2.1→2.6) W, while reducing the DC bus voltage ripple by 1% under various load working conditions in comparison to the other approaches.

A review of energy management optimization based on the equivalent consumption minimization strategy for fuel cell hybrid power systems

AbstractThe high global demand for fossil fuels and resulting climate‐change effects due to air pollution have led to the rapid development of renewable energy sources. Battery and proton exchange membrane fuel cells have high power densities and high energy, and supercapacitors can provide peak power. These devices have the advantages of high thermal efficiencies and no carbon emissions during use, which have far‐reaching applications in the fields of hybrid vehicles and ships. To compensate for the slow dynamic response of fuel cells, batteries or supercapacitors are often used as auxiliary power sources to form hybrid powertrains in practice. Therefore, to take full advantage of the hybrid system, energy coordination between multiple energy sources using an energy management strategy is important. The equivalent consumption minimization strategy has been widely investigated due to its simplicity, small operation, good control, and real‐time optimization. In this paper, the topologies of fuel cell hybrid power systems are first systematically classified and characterized. Then, the calculation of equivalent hydrogen consumption for a battery, fuel cell, and supercapacitor is reviewed. To reduce overall hydrogen consumption and extend the life of fuel cells and batteries, an equivalent hydrogen consumption minimization strategy is applied to the energy management of hydrogen fuel power systems.

Fuel Cell Hybrid Locomotive with Modified Fuzzy Logic Based Energy Management System

As one of the most environmentally friendly energy sources today, fuel cells have become the focus of research in countries around the world, especially in the electric transportation field. This paper mainly studies the modeling of fuel cell hybrid locomotives (FCHL) including fuel cells, batteries, motors, and energy management systems. To increase the operating efficiency and improve the performance of FCHL, a modified fuzzy logic-based energy management system (MFL-EMS) is proposed and compared with the traditional power flow energy management system (PF-EMS). Meanwhile, a modified fuel cell hybrid power system model for locomotives is proposed, taking into account the traction motor features that, compared with a simplified controlled source load, can directly reflect the status of the locomotive running speed and the output power of the traction motor load. The proposed system parameters and configurations are determined by combining the characteristics of power and energy density, response characteristics, and charging/discharging characteristics of fuel cells and batteries. The precise simulation results revealed that adopting the proposed MFL-EMS in comparison to the traditional PF-EMS, reduced the hydrogen consumption by 2.943%. Comparing the battery output voltage, it is confirmed that with MFL-EMS it tends to be steeper than the one with PF-EMS, showing the proposed strategy’s robustness. Overall, the obtained results revealed an improved performance in terms of power distribution as well as SOC, which means less hydrogen consumption and therefore a more economical solution.

Novel extraction method of working condition spectrum for the lifetime prediction and energy management strategy evaluation of automotive fuel cells

Lifetime is a major bottleneck for the commercialization of fuel cells. A quick evaluating method for fuel cell lifetime can assist in immediately assessing technology progress, predicting lifetime in real-time, and extending durability. Among the existing methods, the lifetime prediction method based on working conditions is a cost-effective, time-saving, and realistic method. However, there are no methods and clear standards for extracting the time and frequency of working conditions in test protocols used in this method. In this study, the working condition spectrum extraction method is proposed and used to extract the working condition spectra of commonly used durability test protocols. The lifetime prediction of fuel cells operating under different specific test protocols based on the working condition spectrum extraction method is performed and verified to demonstrate its reliability. Furthermore, the proposed method is used to extract the working condition spectra and predict the lifetime of fuel cells in hybrid power systems with different energy management strategies (EMSs). The results show that the extraction method can provide an evaluation method for developing EMSs of fuel cell hybrid power systems from the lifetime perspective, which is useful for fuel cell durability research.

Energy economy optimization and comprehensive performance improvement for PEMFC/LIB hybrid system based on hierarchical optimization

In order to improve the motion range of mobile welding robot, energy management strategy of fuel cell hybrid power system were studied, which involves energy economy optimization and comprehensive performance improvement. The energy management strategy adopts hierarchical optimization control. Inner layer realizes power distribution and energy optimization, using the maximum power point tracking control (MPPT) based on hybrid algorithm and an improved equivalent consumption minimization strategy (ECMS) to optimize the output power distribution. MPPT allows fuel cell to output maximum power stably and maximize the fuel cell utilization. The improved ECMS optimizes the equivalence factor by fuzzy logic control to increase the calculation accuracy. This strategy improves the economy of system energy consumption. The outer layer uses state machine control to switch the control strategy according to the operating state of the system. When the SOC of the battery is lower than the set threshold, MPPT control is used. And when the SOC is higher than the set threshold, ECMS is used. Experimental results show that the rationality of PEMFC output power and battery charge-discharge has been improved, and the economy of hybrid power system has also been improved.

An Improved Energy Management Strategy for Fuel Cell Hybrid Vehicles Based on Pontryagin's Minimum Principle

For finding a balance between fuel economy and durability of fuel cell hybrid power systems, this article proposes an improved real-time energy management strategy (EMS) based on Pontryagin's minimum principle (IM-PMP). We introduce the fuel cell output change rate with weighted coefficient into the Hamiltonian function to limit frequent power fluctuations so as to improve the durability of the fuel cell. In addition, a real-time costate updating method is proposed for unknown driving conditions. This method determines the optimal value of costate according to the real-time state of charge (SOC), which can ensure the online implementation of the EMS and control the SOC of the lithium battery within a certain range. By constructing the hardware-in-the-loop experimental platform, the proposed strategy is compared with the finite state machine (FSM) strategy. Compared with FSM, the hydrogen consumption of the IM-PMP strategy is reduced by 10.1%, and the fuel cell operating stress is reduced by 38.3%. The SOC of the lithium battery is maintained at around 0.6. The experimental results verify the superiority of the proposed EMS.