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.     

Energy management strategy based on fuzzy logic for a fuel cell hybrid bus

Fuel cell vehicles, as a substitute for internal-combustion-engine vehicles, have become a research hotspot for most automobile manufacturers all over the world. Fuel cell systems have disadvantages, such as high cost, slow response and no regenerative energy recovery during braking; hybridization can be a solution to these drawbacks. This paper presents a fuel cell hybrid bus which is equipped with a fuel cell system and two energy storage devices, i.e., a battery and an ultracapacitor. An energy management strategy based on fuzzy logic, which is employed to control the power flow of the vehicular power train, is described. This strategy is capable of determining the desired output power of the fuel cell system, battery and ultracapacitor according to the propulsion power and recuperated braking power. Some tests to verify the strategy were developed, and the results of the tests show the effectiveness of the proposed energy management strategy and the good performance of the fuel cell hybrid bus.     

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.     

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.     

Development of new energy management strategy for a household fuel cell/battery hybrid system

This work aims to construct an efficient and robust fuel cell/battery hybrid operating system for a household application. The ability to dispatch the power demands, sustain the state of charge (SOC) of battery, optimize the power consumption, and more importantly, ensure the durability as well as extend the lifetime of a fuel cell system is the basic requirements of the hybrid operating system. New power management strategy based on fuzzy logical combined state machine control is developed, and its effectiveness is compared with various strategies such as dynamic programming (DP), state machine control, and fuzzy logical control with simulation. Experimental results are also presented, except for DP because of difficulties in achieving real‐time implementation and much faster response to load variation. The given current from the energy management system (EMS) as a reference of the fuel cell output current is determined by filtering out various harmful signals. The new power management strategy is applied to a 1‐kW stationary fuel cell/battery hybrid system. Results show that the fuel cell hybrid system can run much smoothly with prolonged lifetime.     

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.     

Power management strategy for vehicular-applied hybrid fuel cell/battery power system

In this paper, a control strategy for a hybrid PEM (proton exchange membrane) fuel cell/BES (battery energy system) vehicular power system is presented. The strategy, based on fuzzy logic control, incorporates the slow dynamics of fuel cells and the state of charge (SOC) of the BES. Fuel cell output power was determined according to the driving load requirement and the SOC, using fuzzy dynamic decision-making and fuzzy self-organizing concepts. An analysis of the simulation results was conducted using Matlab/Simulink/Stateflow software in order to verify the effectiveness of the proposed control strategy. It was confirmed that the control scheme can be used to improve the operational efficiency of the hybrid power system.     

Comparative study of energy management systems for a hybrid fuel cell electric vehicle - A novel mutative fuzzy logic controller to prolong fuel cell lifetime

Hybrid fuel cell battery electric vehicles require complex energy management systems (EMS) in order to operate effectively. Poor EMS can result in a hybrid system that has low efficiency and a high rate of degradation of the fuel cell and battery pack. Many different types of EMS have been reported in the literature, such as equivalent consumption minimisation strategy and fuzzy logic controllers, which typically focus on a single objective optimisations, such as minimisation of H₂ usage. Different vehicle and system specifications make the comparison of EMSs difficult and can often lead to misleading claims about system performance. This paper aims to compare different EMSs, against a range of performance metrics such as charge sustaining ability and fuel cell degradation, using a common modelling framework developed in MATLAB/Simulink - the Electric Vehicle Simulation tool-Kit (EV-SimKit). A novel fuzzy logic controller is also presented which mutates the output membership function depending on fuel cell degradation to prolong fuel cell lifetime – the Mutative Fuzzy Logic Controller (MFLC). It was found that while certain EMSs may perform well at reducing H₂ consumption, this may have a significant impact on fuel cell degradation, dramatically reducing the fuel cell lifetime. How the behaviour of common EMS results in fuel cell degradation is also explored. Finally, by mutating the fuzzy logic membership functions, the MFLC was predicted to extend fuel cell lifetime by up to 32.8%.     

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.     

Fuzzy energy management of hybrid renewable power system with the aim to extend component lifetime

In this paper, a fuzzy energy management algorithm for a hybrid renewable power system based on lifetime extending is presented. When the system contains two storage elements or more, the selection of the suitable element to be charged or discharged becomes of paramount importance. When the storage elements are of different types, the decision will be difficult. Conventional algorithms that make series of tests to select the storage element choose always the first available element. This way of testing affects badly the most used element and may affect the other storage elements too as they rarely operate under hard load scenarios. In this study, and in order to solve this problem, two fuzzy controllers have been used to manage the energy flow for a hybrid renewable power system. It is composed of: a photovoltaic generator as a main source, a fuel cell and batteries as a storage elements. The controllers operate as master and slave. The master controller gives orders to all the system power converters and to the slave controller as well. The latter is activated only when the storage elements are at the same state of charge. It is charged, instead of the master's, to select the suitable element to be charged or discharged. Its orders are given based on lifetime functions for each element. To examine the proposed algorithm, simulations have been performed under Matlab /Simulink (The MathWorks, Inc., Massachusetts, USA). Comparison and statistics have been carried out to give the percentage of the worked hours for each element in each operating mode. The obtained results show the high performance of the proposed algorithm. Copyright © 2017 John Wiley & Sons, Ltd.     

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.     

Experimental investigation of power management and control of a PV/wind/fuel cell/battery hybrid energy system microgrid

This paper presents an experimental study of a standalone hybrid microgrid system. The latter is dedicated to remote area applications. The system is a compound that utilizes renewable sources that are Wind Generator (WG), Solar Array (SA), Fuel Cell (FC) and Energy Storage System (ESS) using a battery. The power electronic converters play a very important role in the system; they optimize the control and energy management techniques of the various sources. For wind and solar subsystem, the speed and Single Input Fuzzy Logic (SIFL) controllers are used respectively to harvest the maximum power point tracking (MPPT). To maintain a balance of energy in the hybrid system, an energy management strategy based on the battery state of charge (SOC) has been developed and implemented experimentally. The AC output voltage regulation was achieved using a Proportional Integral (PI) controller to supply a resistive load with constant amplitude and frequency. According to the obtained performances, it was concluded that the proposed system is very promising for potential applications in hybrid renewable energy management systems.     

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.     

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.     

Improved fuzzy logic control-based energy management strategy for hybrid power system of FC/PV/battery/SC on tourist ship

An improved fuzzy-based energy management strategy (EMS) is proposed for a tourist ship used hybrid power system with multiple power sources consisting of fuel cell(FC)/photovoltaic cell(PV)/battery(BAT)/super-capacitor(SC). The power demand from propeller and user terminal is afforded by the power sources connecting to power converters. To obtain more superior performance of the power system, the maximum power point tracking (MPPT) algorithm is employed to optimize the PV. Meanwhile, the improved fuzzy logic control based on dynamic programming (DP) associated with wavelet analysis and PI control are employed to achieve the output power optimal distribution and online control. In particular, the MPPT algorithm can improve the utilization of solar energy, and the SC can well absorb the high frequency power and reduce the fluctuation of the battery and FC that exhibits the potential of their lifetime extension. The FC outputs the high and stable power satisfying the ship's power demand even under the extreme work conditions. The developed model is able to illustrate well in the operation process of the hybrid power system governed by the proposed EMS. In addition, compared with the rule-based strategy, the improved fuzzy-based EMS can reduce 14.39% hydrogen consumption and keep the consistency of battery SOC.     

An energy management strategy based on dynamic power factor for fuel cell/battery hybrid locomotive

In order to efficiently absorb more regenerative braking energy which sustains much longer compared with the conventional vehicle, and guarantee the safety of the hybrid system under the actual driving cycle of locomotive, an energy management control based on dynamic factor strategy is proposed for a scale-down locomotive system which consists of proton exchange membrane fuel cell (PEMFC) and battery pack. The proposed strategy which has self-adaption function for different driving cycles aims to achieve the less consumption of hydrogen and higher efficiency of the hybrid system. The experimental results demonstrate that the proposed strategy is able to maintain the charge state of battery (SOC) better than Equivalent Consumption Minimization Strategy (ECMS), and the proposed strategy could keep the change trend of SOC, which the final SOC is closed to the target value regardless of the initial SOC of battery. Moreover, the hydrogen consumption has been reduced by 0.86g and the efficiency of overall system has been raised of 2% at least than ECMS under the actual driving cycle through the proposed strategy. Therefore, the proposed strategy could improve the efficiency of system by diminishing the conversion process of energy outputted by fuel cell.     

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.     

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 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.     

A sizing-design methodology for hybrid fuel cell power systems and its application to an unmanned underwater vehicle

Hybridizing a fuel cell with an energy storage unit (battery or supercapacitor) combines the advantages of each device to deliver a system with high efficiency, low emissions, and extended operation compared to a purely fuel cell or battery/supercapacitor system. However, the benefits of such a system can only be realised if the system is properly designed and sized, based on the technologies available and the application involved. In this work we present a sizing-design methodology for hybridisation of a fuel cell with a battery or supercapacitor for applications with a cyclic load profile with two discrete power levels. As an example of the method's application, the design process for selecting the energy storage technology, sizing it for the application, and determining the fuel load/range limitations, is given for an unmanned underwater vehicle (UUV). A system level mass and energy balance shows that hydrogen and oxygen storage systems dominate the mass and volume of the energy system and consequently dictate the size and maximum mission duration of a UUV.