Fuel Cell Hybrid Power Research Articles

Research progress on topology and energy management of fuel cell hybrid power ships

Abstract With the increasing awareness of environmental protection, the maritime industry is moving towards green and low-carbon development. Fuel cells, due to their pollution-free and high-efficiency characteristics, are one of the key technologies driving the green transformation of traditional ships. However, fuel cells have relatively soft output characteristics and often require other energy storage components to provide supplementary power. This paper reviews the types, advantages, and disadvantages of the topologies of fuel cell hybrid power ships, analyses the current development status of energy management goals and methods, and finally provides an outlook on the development of fuel cell hybrid power ships.

Performance evaluation and energy management strategy of drone methanol reforming fuel cell hybrid power system: A case study

The performance of hydrogen production by methanol steam reforming and high temperature proton exchange membrane fuel cells on drone lacks the comparison of experimental data, resulting in the overall performance improvement of the system is difficult to evaluate. Therefore, the energy management strategy of methanol reforming high temperature proton exchange membrane fuel cell hybrid power system and state machine is designed and optimized. The performance of this system is analyzed and compared with the flight experiment data of a proton exchange membrane fuel cell hybrid UAV. The results show that the SOC of the system can be stabilized between 70 and 80 during the long cruise phase. The test results show that the maximum hydrogen storage mass density of the hydrogen supply system is increased by 67.6%. The flight time of the system under economic cruise flight of the drone is improved by 29.1%–44.9% with different quality of fuel. Under the maximum flight speed of a certain wind speed, the system can meet the flight requirements and increase the flight time by 31.9% and 17.6% respectively under the wind speed of 1.5 m/s and 4 m/s. Its flight time has been greatly improved, and it has great potential as a drone system.

Multi-Objective Parameter Configuration Optimization of Hydrogen Fuel Cell Hybrid Power System for Locomotives

Conventional methods of parameterizing fuel cell hybrid power systems (FCHPS) often rely on engineering experience, which leads to problems such as increased economic costs and excessive weight of the system. These shortcomings limit the performance of FCHPS in real-world applications. To address these issues, this paper proposes a novel method for optimizing the parameter configuration of FCHPS. First, the power and energy requirements of the vehicle are determined through traction calculations, and a real-time energy management strategy is used to ensure efficient power distribution. On this basis, a multi-objective parameter configuration optimization model is developed, which comprehensively considers economic cost and system weight, and uses a particle swarm optimization (PSO) algorithm to determine the optimal configuration of each power source. The optimization results show that the system economic cost is reduced by 8.76% and 18.05% and the weight is reduced by 11.47% and 9.13%, respectively, compared with the initial configuration. These results verify the effectiveness of the proposed optimization strategy and demonstrate its potential to improve the overall performance of the FCHPS.

A Method of Adaptive Power Allocation for Fuel Cell Hybrid Power Systems Taking into Account Stack Performance

A Method of Adaptive Power Allocation for Fuel Cell Hybrid Power Systems Taking into Account Stack Performance

Self‐Thermostatic Internal Combustion Engine—Proton Exchange Membrane Fuel Cell Hybrid Power Generation System Based on Methanol

Traditional internal combustion engines (ICEs) have garnered considerable attention due to their high emissions and low efficiency issues. In this study, a novel ICE–fuel cell hybrid power system based on a single‐methanol fuel is proposed to address these concerns. The system utilizes methanol as fuel, directly supplying it to the methanol engine, and generates hydrogen for the fuel cell through methanol reforming technology. The structural design of the system fully exploits engine exhaust, first using waste heat for methanol reforming to produce hydrogen and then utilizing exhaust inertial potential energy to drive a dual turbocharging structure for air compression entering the fuel cell, thereby achieving self‐thermal balance. Thermodynamic analysis and cost evaluation indicate that the thermal efficiency of this system is improved by 8.34% compared to traditional diesel engine setups. Compared to engine‐fuel cell hybrid systems that do not utilize waste heat, the thermal efficiency is increased by 5.81%. In terms of economics, the cost of the methanol engine system is ≈.1466$ , which is 44.05% lower than the 0.262 $ fuel cost of traditional diesel engine systems. This study presents an innovative solution that significantly enhances thermal efficiency and offers economic advantages, providing a viable approach to address the low efficiency and high emissions issues of traditional ICEs.

Digital Twin-Enhanced Control for Fuel Cell and Lithium-Ion Battery Hybrid Vehicles

With the development of lithium-ion batteries and fuel cells, the application of hybrid power systems is becoming more and more widespread. To better optimize the energy management problem of fuel cell hybrid systems, the accuracy of system modeling and simulation is very important. The hybrid system is formed by connecting the battery to the fuel cell through an active topology. Digital twin technology is applicable to the mapping of physical entities to each other with high interactivity and fast optimization iterations. In this paper, a relevant model based on mathematical logic is established by collecting actual operational data; subsequently, the accuracy of the model is verified by combining relevant operating conditions and simulating the model. Subsequently, a three-dimensional visualization model of a hybrid power system-based sightseeing vehicle and its operating environment was established using digital twin technology to improve the model simulation of the fuel cell hybrid power system. At low speeds, the simulation results of the hybrid power system-based sightseeing vehicle have a small error compared with the actual running state, and the accuracy of the data related to each internal subcomponent is high. In the simple interaction between the model display vehicle and the environment, the communication state can meet the basic requirements of the digital twin model because the amount of data to be transferred is small. This study makes a preliminary attempt at digital parallelism by combining mathematical logic with visualization models and can be used as a basis for the subsequent development of more mature digital twin models.

A comparative study of AI-driven techno-economic analysis for grid-tied solar PV-fuel cell hybrid power systems

The increasing global demand for clean and sustainable energy solutions has led to the integration of “renewable energy sources” and innovative technologies in power generation systems. In this context, “grid-tied solar photovoltaic (PV)-fuel cell hybrid power systems” have drawn considerable interest because of their potential to provide reliable and efficient energy generation. However, the complex interaction between solar PV and fuel cell components and the fluctuating nature of renewable energy sources necessitates a comprehensive techno-economic analysis. This research paper presents a comparative study of AI-driven approaches for conducting techno-economic analysis of “grid-tied solar PV-fuel cell hybrid power systems.” The study uses various AI techniques to analyze these hybrid systems' performance, economic viability, and environmental impact.

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

Research on energy management strategy of fuel cell hybrid power via an improved TD3 deep reinforcement learning

Fuel cell hybrid electric vehicles (FCHEV) are helping to advance the cause of environmental protection as a sustainable form of transportation. An effective energy management strategy (EMS) is crucial to reduce the usage cost of FCHEV and enhance SOC maintenance ability. This study establishes separate degradation models for fuel cells and lithium batteries, incorporating the decay factor of energy sources’ lifetime into the EMS. To address the sparse reward problem during training, a novel energy management strategy algorithm based on deep reinforcement learning is proposed, which combines the twin delayed deep deterministic policy gradient (TD3) algorithm framework with learning rate annealing (AL) and hindsight prioritized experience replay (HPER) optimization methods, resulting in strong training performance. Experimental results demonstrate significant advantages of the EMS based on the HPER_AL_TD3 algorithm over traditional TD3-based approaches. The proposed EMS exhibits superior adaptability to various driving cycles, ensuring stable SOC levels and reducing the overall usage cost. This research aims to enhance the learning capability of EMS based on deep reinforcement learning and contribute to the promotion of FCHEV.

Energy, exergy, economic, and life cycle environmental analysis of a novel biogas-fueled solid oxide fuel cell hybrid power generation system assisted with solar thermal energy storage unit

Biogas production and its derived hydrogen production technology have broad application prospects. In this paper, an integrated biogas power generation system with solid oxide fuel cells is proposed, which mainly consists of four units: a solar thermal energy storage unit, a biogas production and hydrogen generation unit, a SOFC-MGT unit, and a waste heat utilization unit. The presented system is first studied using energy, exergy, economic, and life cycle environmental analyses and the survey results are contrasted with those of renewable energy systems discussed in the references. Besides, a parametric study is conducted to explore the effect of thermodynamic parameters of solar irradiance, ambient temperature, work fluid temperature, reforming temperature, inlet H2O/CH4 ratio of the reformer, and the current density of SOFC. Results indicate that the proposed system's energy efficiency, exergy efficiency, electric power output and exergy destruction are 43.29%, 37.4%, 414.16 kW (net power generation is 351.43 kW) and 1434.59 kW, respectivily. Moreover, the system's levelized cost of electricity and carbon emission factor are $0.076/kWh and 335.6gCO2eq/kWh, having good economic and environmental benefits simultaneously. The parametric study shows that PTSC can be designed shorter with more solar irradiance and high ambient temperature. Besides, the increase of inlet H2O/CH4 ratio and reforming temperature make the system's energy efficiency fall by 2.5% and 20%. For every 300 A/m2 increase in the current density of SOFC, the system efficiency rises by 1.01%.

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.

Research on the Control Strategy of Urban Integrated Energy Systems Containing the Fuel Cell

As a new type of energy with the advantages of high efficiency, clean and pollution-free, fuel cells have attracted the attention of many experts and scholars. The efficient utilization of fuel cells will certainly become the mainstay of energy transformation and environmental protection. However, fuel cells have low power density, soft electrical output characteristics, and significantly delayed response to sudden load changes. When fuel cells are used as power supply energy alone, the output voltage fluctuates greatly, and the power supply reliability could be higher. To increase the fuel cell’s service life in real world applications, a DC converter and an appropriate auxiliary energy storage power supply are combined to form a fuel cell hybrid power supply system that makes efficient use of the auxiliary energy storage system’s availability, enhances the power supply system’s adaptability through dynamic reconfiguration, and provides better flexibility overall. This work proposes a method for managing the energy produced by an urban integrated power supply system that includes fuel cells, supercapacitors, and solar cells. Applying the IF-THEN rule of load power and the state of charge of the supercapacitors, the power balance is adjusted between the su-percapacitors, photovoltaic cells, and fuel cells according to the defined fuzzy logic control. The intermittent nature of solar power production and the erratic nature of fuel cell output may both be mitigated using this technique, allowing the load power to operate more reliably. The simulation results show that the control strategy adopted in this paper is able to not only meet the load requirements but also reasonably allocate the functional requirements and improve the working efficiency of the system, resulting in a clear optimization effect on the system’s control. In this paper, we focus on the fuel cell hybrid power supply system design, and then we use the idea of fuzzy logic control energy management to build the structure of the fuzzy logic control system, design the fuzzy controller, determine the functions, and verify the solutions through simulation and experimentation.

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.