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.     

Observer-based type-2 fuzzy approach for robust control and energy management strategy of hybrid energy storage systems

In this paper, an observer-based type-2 fuzzy method is proposed for control and energy management strategy (EMS) of the hybrid energy storage system (HESS) which can be composed of the fuel cell (FC), battery (BA), and supercapacitor (SC). The objective and main contribution of the suggested strategy is to provide: 1) Appropriate tracking performance of power sources by an observer-based control method in the presence of noise and signal ripples. 2) An observer-based composite adaptive type-2 fuzzy (OCAT2F) to approximate the voltage of power sources. 3) A dynamical model of DC-bus to guarantee the stability of closed-loop system. 4) An intelligent EMS. To have a high-power supply, the proposed EMS includes two parts; a type-2 fuzzy logic control rule table (T2FLCRT), and an observer-based robust adaptive fuzzy type-2 fuzzy (ORAT2F). Furthermore, stability analyses of the closed-loop system are provided by the input-output linearization (I-OL) approach and based on the Lyapunov theorem. The simulation results of the proposed control scheme under MATLAB/Simulink indicate that the suggested strategy can provide a suitable control performance, and stability of the whole system is achieved.     

Energy management of fuel cell/battery/supercapacitor hybrid power source for vehicle applications

This paper proposes a perfect energy source supplied by a polymer electrolyte membrane fuel cell (PEMFC) as a main power source and storage devices: battery and supercapacitor, for modern distributed generation system, particularly for future fuel cell vehicle applications. The energy in hybrid system is balanced by the dc bus voltage regulation. A supercapacitor module, as a high dynamic and high power density device, functions for supplying energy to regulate a dc bus voltage. A battery module, as a high energy density device, operates for supplying energy to a supercapacitor bank to keep it charged. A FC, as a slowest dynamic source in this system, functions to supply energy to a battery bank in order to keep it charged. Therefore, there are three voltage control loops: dc bus voltage regulated by a supercapacitor bank, supercapacitor voltage regulated by a battery bank, and battery voltage regulated by a FC. To authenticate the proposed control algorithm, a hardware system in our laboratory is realized by analog circuits and numerical calculation by dSPACE. Experimental results with small-scale devices (a PEMFC: 500-W, 50-A; a battery bank: 68-Ah, 24-V; and a supercapacitor bank: 292-F, 30-V, 500-A) corroborate the excellent control principle during motor drive cycle.     

Variable structure battery-based fuel cell hybrid power system and its incremental fuzzy logic energy management strategy

A hybrid power system consists of a fuel cell and an energy storage device like a battery and/or a supercapacitor possessing high energy and power density that beneficially drives electric vehicle motor. The structures of the fuel cell-based power system are complicated and costly, and in energy management strategies (EMSs), the fuel cell's characteristics are usually neglected. In this study, a variable structure battery (VSB) scheme is proposed to enhance the hybrid power system, and an incremental fuzzy logic method is developed by considering the efficiency and power change rate of fuel cell to balance the power system load. The principle of VSB is firstly introduced and validated by discharge and charge experiments. Subsequently, parameters matching of the fuel cell hybrid power system according to the proposed VSB are designed and modeled. To protect the fuel cell as well as ensure the efficiency, a fuzzy logic EMS is formulated via setting the fuel cell operating in a high efficiency and generating an incremental power output within the affordable power slope. The comparison between a traditional deterministic rules-based EMS and the designed fuzzy logic was implemented by numerical simulation in three different operation conditions: NEDC, UDDS, and user-defined driving cycle. The results indicated that the incremental fuzzy logic EMS smoothed the fuel cell power and kept the high efficiency. The proposed VSB and incremental fuzzy logic EMS may have a potential application in fuel cell vehicles.     

Optimized rule-based energy management for a polymer electrolyte membrane fuel cell/battery hybrid power system using a genetic algorithm

The polymer electrolyte membrane fuel cell (PEMFC) coupled with the battery is a promising hybrid power system for future energy supply application. Fuel cell durability, battery charge sustenance, and fuel consumption strongly rely on the energy management strategy (EMS). This paper puts forward an optimized rule-based EMS using genetic algorithm (GA) to optimally allocate the power between the fuel cell and the battery system. Control variables in real-time rule-based EMS are optimally adjusted with single objective of battery charge sustenance considering the fuel cell durability and efficiency. The proposed optimized rule-based EMS is simulated and experimentally verified via MATLAB/Simulink and LabVIEW-based experimental rig, respectively. The conventional rule-based EMS, fuzzy logic EMS, and dynamic programming (DP) EMS are also examined for comparison. The comparison results elucidate that the optimized rule-based EMS realizes a large performance improvement over the conventional rule-based and fuzzy logic EMSs. Near optimal performance is verified compared with DP EMS in terms of fuel economy, battery charge sustenance, fuel cell efficiency, and system durability. The combination of rule-based EMS and GA optimization algorithm has the advantage of having expert experience and global optimization properties, realizing optimal power allocation in real-time application with lower computation burden, which could be applied easily to other EMS system without loss of validity.     

Nonlinear control and optimization of hybrid electrical vehicle under sources limitation constraints

This work presents a new contribution on energy management of hybrid electric systems for vehicle applications. The studied hybrid electrical vehicle is composed of fuel cell as a main source and the auxiliary system containing the battery and supercapacitor. A programmable load is used to emulate a vehicle load profile. Two methods are combined to smartly and optimally control the energy flow between the used sources. These methods are the Interconnection and Damping Assignment Passivity Based Control (IDA-PBC) and the Hamilton-Jacobi Bellman (HJB) optimization. The source limitation is considered here in terms of the battery state of charge. The experimental works validate the efficiency of the proposed control where the obtained results demonstrate that the used strategy allows regulating the power flow under a realistic load drive profile. The global stability proof is demonstrated using Lyapunov theory.     

A power allocation strategy of a hybrid energy storage system for a PV grid-connected system

针对光伏并网系统中光伏微电源出力的波动性和间歇性,将蓄电池和超级电容器构成的混合储能系统HESS（hybrid energy storage system）应用到光伏并网系统中可以实现光伏功率平滑、能量平衡以及提高并网电能质量。在同时考虑蓄电池的功率上限和超级电容的荷电状态（SOC）的情况下,对混合储能系统提出了基于超级电容SOC的功率分配策略;该策略以超级电容的SOC和功率分配单元的输出功率作为参考值,对混合储能系统充放电过程进行设计。超级电容和蓄电池以Bi-direction DC/DC变换器与500 V直流母线连接,其中超级电容通过双闭环控制策略对直流母线电压进行控制。仿真结果表明,所提功率分配策略能对混合储能系统功率合理分配,而且实现了单位功率因数并网,稳定了直流母线电压。     

Optimal energy management strategy of fuel-cell battery hybrid electric mining truck to achieve minimum lifecycle operation costs

Proton exchange membrane fuel cell (PEMFC) electric vehicle is an effective solution for improving fuel efficiency and onboard emissions, taking advantage of the high energy density and short refuelling time. However, the higher cost and short life of the PEMFC system and battery in an electric vehicle prohibit the fuel cell electric vehicle (FCEV) from becoming the mainstream transportation solution. The fuel efficiency-oriented energy management strategy (EMS) cannot guarantee the improvement of total operating costs. This paper proposes an EMS to minimize the overall operation costs of FCEVs, including the cost of hydrogen fuel, as well as the cost associated with the degradations of the PEMFC system and battery energy storage system (ESS). Based on the PEMFC and battery performance degradation models, their remaining useful life (RUL) models are introduced. The control parameters of the EMS are then optimized using a meta-model based global optimization algorithm. This study presents a new optimal control method for a large mining truck operating on a real closed-road operation cycle, using the combined energy efficiency and performance degradation cost measures of the PEMFC system and lithium-ion battery ESS. Simulation results showed that the proposed EMS could improve the total operating costs and the life of the FCEV.     

孤网运行微电网中混合储能管理与控制策略研究

对孤网运行风光互补微电网电压频率控制和混合储能功率分配问题提出了混合储能管理控制策略,该策略将混合储能中锂电池设定恒功率和压频电源两种模式,对超级电容器采用电压/频率控制。锂电池作恒功率电源时,根据发电预测和负荷预测结果平复系统波动;超级电容器则依据电压/频率控制补偿系统实时功率缺额,保障微电网稳定运行。为此在MATLAB/SIMULINK中搭建了仿真模型,进行了孤网运行、能量分析、模式切换三次仿真,结果表明该策略正确。     

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.     

The characteristics of regenerative energy for PEMFC hybrid system with additional generator

This study focuses on the use of the Polymer Electrolyte Membrane Fuel Cell (PEMFC) hybrid system, which consists of a generator, a supercapacitor, and a battery, to obtain regenerative energy. The fuel cell is a Nexa™ Power Module of Ballard Power Systems Inc., and the battery is a Ni-MH battery of Global Battery Co., Ltd. The supercapacitor, which features an excellent power density and capacity of 30 V and 100F, can minimize its power consumption via a cell balancing circuit. This study aimed to evaluate the characteristics of regenerative energy and suggest solutions to increase regenerative energy using a vehicle simulation.     

Experimental assessment of fuel cell/supercapacitor hybrid system for scooters

This paper presents an experimental assessment of fuel cell hybrid propulsion systems for scooters based on a modular 1.2 kW PEM fuel cell. The tests of the hybrid system are carried out using a programmable electronic load. Different configurations of the fuel cell/battery and the fuel cell/supercapacitor hybrid systems are explored. Both systems demonstrate their ability to deliver the requested load satisfactorily. The distributions of the fuel cell power delivery, although different between the two systems, are within the region where the fuel cell efficiency is approximately constant. As a result, the rates of fuel consumption show no discernable difference between the two systems for all three driving cycles considered. In addition to the fuel consumption, considerations including bus voltage, cost and packaging issues suggest that the supercapacitor has advantages over the battery for the use as secondary energy storage in fuel cell hybrid propulsion system for scooters.     

Optimization based energy management strategy for fuel cell/battery/ultracapacitor hybrid vehicle considering fuel economy and fuel cell lifespan

Optimization of energy management strategy (EMS) for fuel cell/battery/ultracapacitor hybrid electrical vehicle (FCHEV) is primarily aimed on reducing fuel consumption. However, serious power fluctuation has effect on the durability of fuel cell, which still remains one challenging barrier for FCHEVs. In this paper, we propose an optimized frequency decoupling EMS using fuzzy control method to extend fuel cell lifespan and improve fuel economy for FCHEV. In the proposed EMS, fuel cell, battery and ultracapacitor are employed to supply low, middle and high-frequency components of required power, respectively. For accurately adjusting membership functions of proposed fuzzy controllers, genetic algorithm (GA) is adopted to optimize them considering multiple constraints on fuel cell power fluctuation and hydrogen consumption. The proposed EMS is verified by Advisor-Simulink and experiment bench. Simulation and experimental results confirm that the proposed EMS can effectively reduce hydrogen consumption in three typical drive cycles, limit fuel cell power fluctuation within 300 W/s and thus extend fuel cell lifespan.     

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.     

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.     

Design and experimental tests of control strategies for active hybrid fuel cell/battery power sources

Twenty-first century handheld electronic devices and new generations of electric vehicles or electric airplanes have fueled a need for new high-energy, high-power, small-volume, and lightweight power sources. Current battery technology by itself is insufficient to provide the mandatory long-term power these systems require. Fuel cells are also unable to provide the essentially high peak power demanded by these systems. Hybrid systems composed of fuel cells and secondary batteries could combine the high power density of clean fuel cells and the high energy density of convenient batteries. This paper presents an experimental study on control strategies for active power sharing in such a hybrid fuel cell/battery power source. These control strategies limited the fuel cell current to safe values while also regulating the charging current or voltage of the battery. The several tested control strategies were implemented in MATLAB/Simulink and then tested under the pulsed-current load condition through experiments. Experimental tests were conducted with three control objectives: maximum fuel cell power, maximum fuel cell efficiency, and adaptive.     

Energy management of PEM fuel cell/ supercapacitor hybrid power sources for an electric vehicle

This paper presents the utilization of a supercapacitor (SC) as an auxiliary power source in an electric vehicle (EV), composed of a proton electrolyte membrane fuel cell (PEMFC) as the main energy source. The main weak point of PEMFC is slow dynamics because one must limit the fuel cell current slope in order to prevent fuel starvation problems, to improve its performance and lifetime. The very fast power response and high specific power of a supercapacitor can complement the slower power output of the main source to produce the compatibility and performance characteristics needed in a propulsion system. DC-DC converters connected to the hybrid source ensure a constant voltage value in inverters inputs. After an architecture presentation of the hybrid energy source, two parallel-type configurations are explored in more detail. For each of them, the energy flow control and management, validated simulation shows the performance obtained in this configuration. The hybrid source management is based primarily on the intervention of the supercapacitor in fugitives' schemes such as slopes, different speeds and rapid acceleration. Secondly, the PEMFC intervenes to guarantee the power in permanent regime. Finally, simulation results considering energy management are presented and illustrated the hybrid energy source benefits.     

A fuel-cell/battery hybrid DC backup power system via a new high step-up three port converter

In this paper, a fuel-cell (FC)/battery hybrid direct-current (DC) backup power system is proposed for high step-up applications. This system is composed of a newly developed non-isolated three-port converter, which achieves a high voltage gain by taking the advantage of a quasi Z-source network and an energy transfer capacitor. After analyzing the converter, a comprehensive comparison study and a design procedure are provided. Moreover, the controllers regulating the source power levels while smoothing the FC power profile according to the proposed energy management strategy (EMS) are designed based on the developed small-signal model of the proposed converter. Both hardware and controller design procedures are validated through the PSIM model of the whole system. As a result, it is shown that the proposed system can effectively couple FC and battery while transferring their energies to a high voltage DC bus according to the offered EMS.     

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.     

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.