Experimental investigation on the online fuzzy energy management of hybrid fuel cell/battery power system for UAVs

The hybrid powerplant combining a fuel cell and a battery has become one of the most promising alternative power systems for electric unmanned aerial vehicles (UAVs). To enhance the fuel efficiency and battery service life, highly effective and robust online energy management strategies are needed in real applications.In this work, an energy management system is designed to control the hybrid fuel cell and battery power system for electric UAVs. To reduce the weight, only one programmable direct-current to direct-current (dcdc) converter is used as the critical power split component to implement the power management strategy. The output voltage and current of the dcdc is controlled by an independent energy management controller. An executable process of online fuzzy energy management strategy is proposed and established. According to the demand power and battery state of charge, the online fuzzy energy management strategy produces the current command for the dcdc to directly control the output current of the fuel cell and to indirectly control the charge/discharge current of the battery based on the power balance principle.Another two online strategies, the passive control strategy and the state machine strategy, are also employed to compare with the proposed online fuzzy strategy in terms of the battery management and fuel efficiency. To evaluate and compare the feasibility of the online energy management strategies in application, experiments with three types of missions are carried out using the hybrid power system test-bench, which consists of a commercial fuel cell EOS600, a Lipo battery, a programmable dcdc converter, an energy management controller, and an electric load. The experimental investigation shows that the proposed online fuzzy strategy prefers to use the most power from the battery and consumes the least amount of hydrogen fuel compared with the other two online energy management strategies.     

A mobile renewable house using PV/wind/fuel cell hybrid power system

A photovoltaic/wind/fuel cell hybrid power system for stand-alone applications is proposed and demonstrated with a mobile house. This concept shows that different renewable sources can be used simultaneously to power off-grid applications. The presented mobile house can produce sufficient power to cover the peak load. Photovoltaic and wind energy are used as primary sources and a fuel cell as backup power for the system. The power budgeting of the system is designed based on the local data of solar radiation and wind availability. Further research will focus on the development of the data acquisition system and the implementation of automatic controls for power management.     

Modeling and control of a wind fuel cell hybrid energy system

This paper describes a hybrid energy system consisting of a 5 kW wind turbine and a fuel cell system. Such a system is expected to be a more efficient, zero emission alternative to wind diesel system. Dynamic modeling of various components of this isolated system is presented. Selection of control strategies and design of controllers for the system is described. Simnon is used for the simulation of this highly nonlinear system. Transient responses of the system for a step change in the electrical load and wind speed are presented. System simulation results for a pre-recorded wind speed data indicates the transients expected in such a system. Design, modeling, control and limitations of a wind fuel cell hybrid energy system are discussed.     

Simulation of a small wind fuel cell hybrid energy system

This paper describes simulation results of a small 500 W wind fuel cell hybrid energy system. The system consists of a Southwest Wind Power Inc. AIR 403 wind turbine, a Proton Exchange Membrane Fuel Cell (PEMFC) and an electrolyzer. Dynamic modeling of various components of this small isolated system is presented. Simulink is used for the dynamic simulation of this nonlinear 48 V hybrid energy system. Transient responses of the system to a step change in the load current and wind speed in a number of possible situations are presented. Analysis of simulation results and limitations of a wind fuel cell hybrid energy system are discussed.     

Modeling,control and simulation of an autonomous wind turbine/photovoltaic/fuel cell/ultra-capacitor hybrid power system

This paper focuses on the combination of wind turbine (WT), photovoltaic (PV), fuel cell (FC) and ultra-capacitor (UC) systems for grid-independent applications. The dynamic behavior of the proposed hybrid system is tested under various wind speed, solar radiation and load demand conditions. The developed model and its control strategy exhibit excellent performance for the simulation of a complete day. In the simulation, the solar radiation and power demand data are based on real world measurements, while the wind speed data are quasi-real because it is simulated based on special wind speed generation algorithms.     

A control architecture to coordinate energy management with trajectory tracking control for fuel cell/battery hybrid unmanned aerial vehicles

Fuel cell/battery hybrid energy storage system (HESS) powered unmanned aerial vehicle (UAV) has the outstanding advantage of long endurance time. Trajectory tracking motion is a commonly used task execution mode of UAVs, especially in autonomous UAVs. This study aims at developing a control architecture to coordinate energy management with trajectory tracking control for fuel cell/battery hybrid UAVs. Its position tracking control adopts model predictive control (MPC) and an extended state observer to eliminate the modeling errors and effect of interference. The attitude tracking control adopts an auto-disturbance rejection controller having a quick response. The obtained control parameters are given as an input to the energy management block. Energy management strategies (EMSs) based on online dynamic programming and hierarchical MPC have been proposed. The results obtained from a simulation show that the proposed trajectory tracking control architecture can track the target trajectory stably with a small tracking error. The tracking performance is stable under interference. Experimental results show that dynamic programming is solved online with good control performance. Compared to ordinary EMSs, dynamic programming and hierarchical MPC can increase endurance time by 2.69% and 1.27%, respectively. The proposed control architecture verifies the coordination of energy management and trajectory tracking control, and prospected the advantages of the combination of fuel cell and autonomous driving for long endurance UAVs in the future.     

Research on ADHDP energy management strategy for fuel cell hybrid power system

Fuel cell hybrid power system is a prospective power source for electrical vehicles. To reduce hydrogen consumption and enhance dynamic performance of the system, Action Dependent Heuristic Dynamic Programming (ADHDP) energy management strategy for the fuel cell hybrid power system was proposed. Firstly, topology of the system was analyzed and mathematical model was established through mechanism analysis. Secondly, framework of the ADHDP algorithm was presented, and it was followed by training algorithm for evaluating network and executing network of ADHDP based on Back Propagation (BP) algorithm. Finally, hardware-in-the-loop (HIL) simulation of the fuel cell hybrid power system was carried out to demonstrate the proposed ADHDP algorithm under real operating conditions. The results show that evaluating network and executing network of ADHDP have good convergence performance under different operating conditions. Compared with the other algorithms, the proposed ADHDP energy management strategy has better fuel economy and dynamic performance.     

Triple hybrid system coupling fuel cell with wind turbine and thermal solar system

One of the most challenging issues in the domain of renewable energy is the instability of produced power. To put it another way, renewable resources such as solar energy cannot provide continuous energy supply because they rely on natural phenomena that vary randomly. That said, to cover the potential lack of energy that may occur, hybrid renewable energy system can be adopted. In other terms, instead of using single renewable energy source, two different sources can be utilized in order to optimize the output power all over the year. Furthermore, complementary energy system is needed along with renewable sources, to store energy and insure the supply during shortage period. With this in mind, a Green-Green energy system can be constructed by using green storage system such as Fuel Cell to be coupled with the renewable sources. In the light of green-green energy concept, the present paper examines a triple wind-solar-fuel cell combination in the aim of overcoming the energy shortage that occurs during several months of the year. A case study on the region of Dahr Al-Baidar in Lebanon is conducted to present the advantage of the proposed system. Results show that combining wind energy system with thermal solar system allows overcoming the low power produced by solar thermal system especially in winter. For illustration 16 kW are produced by wind turbine during the month of January, by contrast the thermal solar system provides 2 kW during the same period. Nevertheless, in June thermal solar offers 17 kW and wind turbine produces 11 kW.     

Energy control of supercapacitor/fuel cell hybrid power source

This paper deals with a flatness based control principle in a hybrid system utilizing a fuel cell as a main power source and a supercapacitor as an auxiliary power source. The control strategy is based on regulation of the dc bus capacitor energy and, consequently, voltage regulation. The proposed control algorithm does not use a commutation algorithm when the operating mode changes with the load power variation and, thus, avoids chattering effects. Using the flatness based control method, the fuel cell dynamic and its delivered power is perfectly controlled, and the fuel cell can operate in a safe condition. In the hybrid system, the supercapacitor functions during transient energy delivery or during energy recovery situations. To validate the proposed method, the control algorithms are executed in dSPACE hardware, while analogical current loops regulators are employed in the experimental environment. The experimental results prove the validity of the proposed approach.     

Optimized power management based on adaptive-PMP algorithm for a stationary PEM fuel cell/battery hybrid system

This research develops an efficient and robust polymer electrolyte membrane (PEM) fuel cell/battery hybrid operating system. The entire system possesses its own rapid dynamic response benefited from hybrid connection and power split characteristics due to DC/DC buck-boost converter. An indispensable energy management system (EMS) plays a significant role in achieving optimal fuel economy and in a promising running stability. EMS as an indispensable part plays a significant role in achieving optimal fuel economy and promising operation stability. This study aims to develop an adaptive supervisory EMS that comprises computer-aided engineering tools to monitor, control, and optimize the performance of the hybrid power system. A stationary fuel cell/battery hybrid operating system is optimized using adaptive-Pontryagin's minimum principle (A-PMP). The proposed algorithm depends on the adaptation of the control parameter (i.e., fuel cell output power) from the state of charge (SOC) and load power feedback. The integrated model simulated in a Matlab/Simulink environment includes the fuel cell, battery, DC/DC converter, and power requirements models by analyzing the three different load profiles. Real-time experiments are performed to verify the effectiveness of EMS after analyzing the simulated operating principle and control scheme.     

A robust online energy management strategy for fuel cell/battery hybrid electric vehicles

Traditional optimization-based energy management strategies (EMSs) do not consider the uncertainty of driving cycle induced by the change of traffic conditions, this paper proposes a robust online EMS (ROEMS) for fuel cell hybrid electric vehicles (FCHEV) to handle the uncertain driving cycles. The energy consumption model of the FCHEV is built by considering the power loss of fuel cell, battery, electric motor, and brake. An offline linear programming-based method is proposed to produce the benchmark solution. The ROEMS instantaneously minimizes the equivalent power of fuel cell and battery, where an equivalent efficiency of battery is defined as the efficiency of hydrogen energy transforming to battery energy. To control the state of charge of battery, two control coefficients are introduced to adjust the power of battery in objective function. Another penalty coefficient is used to amend the power of fuel cell, which reduces the load change of fuel cell so as to slow the degradation of fuel cell. The simulation results indicate that ROEMS has good performance in both fuel economy and load change control of fuel cell. The most important advantage of ROEMS is its robustness and adaptivity, because it almost produces the optimal solution without changing the control parameters when driving cycles are changed.     

An optimal method of the energy consumption for fuel cell hybrid tram

Energy conservation running for vehicle has been a promising research hotspot in the many universities and research institutions. In order to improve the energy utilization rate in the vehicle running process, an optimization method of the energy consumption and recycle based on fuel cell (FC)/supercapacitor (SC) hybrid tram is proposed in this paper. In the method, a tram operation energy management strategy based on Pontriagin's minimum principle (PMP) can effectively was proposed what adjusts the output power of FC and SC and decreases hydrogen consumption. In addition, a tram breaking velocity curve with maximum energy recovery and the allocation strategy between regenerative force and mechanical braking force be also studied in this paper. According to the simulation results, it could be obtained that the Energy conservation rate is about 5% higher than the un-optimized, it will effectively decrease hydrogen consumption.     

Experimental evaluation of a passive fuel cell/battery hybrid power system for an unmanned ground vehicle

Unmanned vehicles are increasing the performance of monitoring and surveillance in several applications. Endurance is a key issue in these systems, in particular in electric vehicles, powered at present mainly by batteries. Hybrid power systems based on batteries and fuel cells have the potential to achieve high energy density and specific energy, increasing also the life time and safe operating conditions of the power system. The objective of this research is to analyze the performance of a passive hybrid power system, designed and developed to be integrated into an existing Unmanned Ground Vehicle (UGV). The proposed solution is based on six LiPo cells, connected in series, and a 200 W PEM fuel cell stack, directly connected in parallel to the battery without any limitation to its charge. The paper presents the characterization of the system behavior, and shows the main results in terms of performance and energy management.     

Model construction and energy management system of lithium battery,PV generator,hydrogen production unit and fuel cell in islanded AC microgrid

The external electrical characteristics of the lithium battery, PV generator, hydrogen production unit (HPU) and fuel cell in islanded AC microgrid are well analyzed with mathematic models, based on which an energy management system among the abovementioned elements is proposed by using the bus frequency signaling. Specifically, the functions of lithium battery with the variables of the residual capacity and instantaneous working power are well designed to deliver its operation information to other units. The P-f droop control strategy is designed for the PV generator to make it adaptively work off from the maximum power point to the reference power point. The control strategy of HPU can make it work from the maximum efficiency point mode to the allowable maximum power point mode to absorb PV output power as much as possible when the lithium battery is almost getting full charged. Similarly, the fuel cell controller can regulate its power generation from the maximum efficiency point mode to the maximum power point to supply the local load as much as possible when the lithium battery is almost getting full discharged. Finally, the proposed energy management system is verified based on RTLAB experimental platform to show the effectiveness of the proposed coordination control strategy.     

Robust energy management strategy based on non-linear cascade control of fuel cells-super capacitors hybrid power system

The use of super capacitors as secondary sources in fuel cell power systems with adequate energy management strategy strongly contributes to increasing the lifespan of fuel cells by protecting them against sudden variations of the load current and improves the efficiency and the dynamics of the hybrid power system, thus obtained. This paper presents an innovative management strategy of fuel cells-super capacitors hybrid power system, based on a nonlinear control using an integral hysteresis sliding mode controller combined with two cascaded linear controllers. The hybrid power system consists of the fuel cells system, the super capacitors, two power converters, the energy management system and the load. The proposed technique takes into account the physical operating limits of the secondary source such as deep discharges and excessive overloads. Furthermore, the integral effect added to the hysteresis sliding mode controller improves the robustness against disturbances and variations in parameters such as filtering inductances and DC bus capacitors. A detailed model of the system is established and simulated in Matlab/Simulink software, which allows showing its behavior with a very satisfactory accuracy. The simulation results clearly show that the proposed control strategy insures efficient and safe energy transfer. In addition, the control robustness is very satisfactory despite the variation of the system parameters.     

Implementation of self-adaptive Harris Hawks Optimization-based energy management scheme of fuel cell-based electric power system

This paper presents a hybrid Fuel Cell-based Power System (FCPS) consisting of fuel cell and hybrid Energy Storage Systems (ESSs), including a battery with high energy density and supercapacitor with high power density to overcome the sudden load demand change and improving the reliability of the delivered power. Any hybrid power system needs Energy Management Strategies (EMS) to balance the power between the different energy sources. In this paper, a comparative analysis of three energy management strategies, including the state machine control method, the classical PI control method and equivalent consumption minimization strategy (ECMS) is performed. The paper's main objective is enhancing the DC-bus voltage profile of a hybrid fuel cell/battery/supercapacitor power system equipped with the developed under-mentioned EMS by using a hybrid modified optimization technique that combines Harris Hawks optimization (HHO) and Sine Cosine Algorithm (SCA). The new hybrid HHO-SCA is employed to determine the optimal control parameters of the DC-bus voltage controller, which significantly assists in enhancing the DC-bus voltage profile as well as the performance of the applicable ESS in terms of improving efficiency and SoC. The effectiveness of the suggested control schemes is simulated using MATLAB/SIMULINK software. The simulation results confirmed that the proposed HHO-SCA is superior and efficient in improving the DC-bus voltage.     

A hierarchical energy management strategy for fuel cell/battery/supercapacitor hybrid electric vehicles

In this paper, a hierarchical energy management strategy (EMS) based on low-pass filter and equivalent consumption minimization strategy (ECMS) is proposed in order to lift energy sources lifespan, power performance and fuel economy for hybrid electrical vehicles equipped with fuel cell, battery and supercapacitor. As for the considered powertrain configuration, fuel cell serves as main energy source, and battery and supercapacitor are regarded as energy support and storage system. Supercapacitor with high power density and dynamic response acts during great power fluctuations, which relives stress on fuel cell and battery. Meanwhile, battery is used to lift the economy of hydrogen fuel. In higher layer strategy of the proposed EMS, supercapacitor is employed to supply peak power and recycle braking energy by using the adaptive low-pass filter method. Meantime, an ECMS is designed to allocate power of fuel cell and battery such that fuel cell can work in a high efficient range to minimize hydrogen consumption in lower layer. The proposed EMS for hybrid electrical vehicles is modeled and verified by advisor-simulink and experiment bench. Simulation and experiment results are given to confirm effectiveness of the proposed EMS of this paper.     

Solid oxide fuel cell-lithium battery hybrid power generation system energy management: A review

The solid oxide fuel cell (SOFC)/lithium battery hybrid energy structure uses lithium batteries as the energy buffer unit to ensure that the SOFC can operate safely and stably when the load power increases suddenly. For the SOFC/lithium battery hybrid power generation system, a real-time energy management strategy based on power prediction is discussed, and an in-depth summary is made from system construction, power prediction, energy distribution, and power tracking. In the hybrid power generation system, the SOFC system and the lithium battery influence each other. Research the appropriate energy management strategies and realize real-time energy distribution and tracking of hybrid power generation systems in order to improve system performance and economy. This has become a key issue in the current SOFC hybrid power generation system research field.     

A wavelet-fuzzy logic based energy management strategy for a fuel cell/battery/ultra-capacitor hybrid vehicular power system

Due to increasing concerns on environmental pollution and depleting fossil fuels, fuel cell (FC) vehicle technology has received considerable attention as an alternative to the conventional vehicular systems. However, a FC system combined with an energy storage system (ESS) can display a preferable performance for vehicle propulsion. As the additional ESS can fulfill the transient power demand fluctuations, the fuel cell can be downsized to fit the average power demand without facing peak loads. Besides, braking energy can be recovered by the ESS. This study focuses on a vehicular system powered by a fuel cell and equipped with two secondary energy storage devices: battery and ultra-capacitor (UC). However, an advanced energy management strategy is quite necessary to split the power demand of a vehicle in a suitable way for the on-board power sources in order to maximize the performance while promoting the fuel economy and endurance of hybrid system components. In this study, a wavelet and fuzzy logic based energy management strategy is proposed for the developed hybrid vehicular system. Wavelet transform has great capability for analyzing signals consisting of instantaneous changes like a hybrid electric vehicle (HEV) power demand. Besides, fuzzy logic has a quite suitable structure for the control of hybrid systems. The mathematical and electrical models of the hybrid vehicular system are developed in detail and simulated using MATLAB^®, Simulink^® and SimPowerSystems^® environments.