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.     

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.     

Fuel cell/battery passive hybrid power source for electric powertrains

The concept of passive hybrid, i.e. the direct electrical coupling between a fuel cell system and a battery without using a power converter, is presented as a feasible solution for powertrain applications. As there are no DC/DC converters, the passive hybrid is a cheap and simple solution and the power losses in the electronic hardware are eliminated. In such a powertrain topology where the two devices always have the same voltage, the active power sharing between the two energy sources can not be done in the conventional way. As an alternative, control of the fuel cell power by adjusting its operating pressure is elaborated. Only pure H₂/O₂ fuel cell systems are considered in this approach. Simulation and hardware in the loop (HIL) results for the powertrain show that this hybrid power source is able to satisfy the power demand of an electric vehicle while sustaining the battery state of charge.     

Experimental investigation on the dynamic performance of a hybrid PEM fuel cell/battery system for lightweight electric vehicle application

A hybrid system combining a 2 kW air-blowing proton exchange membrane fuel cell (PEMFC) stack and a lead–acid battery pack is developed for a lightweight cruising vehicle. The dynamic performances of this PEMFC system with and without the assistance of the batteries are systematically investigated in a series of laboratory and road tests. The stack current and voltage have timely dynamic responses to the load variations. Particularly, the current overshoot and voltage undershoot both happen during the step-up load tests. These phenomena are closely related to the charge double-layer effect and the mass transfer mechanisms such as the water and gas transport and distribution in the fuel cell. When the external load is beyond the range of the fuel cell system, the battery immediately participates in power output with a higher transient discharging current especially in the accelerating and climbing processes. The DC–DC converter exhibits a satisfying performance in adaptive modulation. It helps rectify the voltage output in a rigid manner and prevent the fuel cell system from being overloaded. The dynamic responses of other operating parameters such as the anodic operating pressure and the inlet and outlet temperatures are also investigated. The results show that such a hybrid system is able to dynamically satisfy the vehicular power demand.     

Comparison among various energy management strategies for reducing hydrogen consumption in a hybrid fuel cell/supercapacitor/battery system

The aim of this study is to introduce a comprehensive comparison of various energy management strategies of fuel cell/supercapacitor/battery storage systems. These strategies are utilized to manage the energy demand response of hybrid systems, in an optimal way, under highly fluctuating load condition. Two novel strategies based on salp swarm algorithm (SSA) and mine-blast optimization are proposed. The outcomes of these strategies are compared with commonly used strategies like fuzzy logic control, classical proportional integral control, the state machine, equivalent fuel consumption minimization, maximization, external energy maximization, and equivalent consumption minimization. Hydrogen fuel economy and overall efficiency are used for the comparison of these different strategies. Results demonstrate that the proposed SSA management strategy performed best compared with all other used strategies in terms of hydrogen fuel economy and overall efficiency. The minimum consumed hydrogen and maximum efficiency are found 19.4 gm and 85.61%, respectively.     

An innovative optimal power allocation strategy for fuel cell, battery and supercapacitor hybrid electric vehicle

An optimal design of a three-component hybrid fuel cell electric vehicle comprised of fuel cells, battery, and supercapacitors is presented. First, the benefits of using this hybrid combination are analyzed, and then the article describes an active power-flow control strategy from each energy source based on optimal control theory to meet the demand of different vehicle loads while optimizing total energy cost, battery life and other possible objectives at the same time. A cost function that minimizes the square error between the desired variable settings and the current sensed values is developed. A gain sequence developed compels the choice of power drawn from all devices to follow an optimal path, which makes trade-offs among different targets and minimizes the total energy spent. A new method is introduced to make the global optimization into a real-time based control. A model is also presented to simulate the individual energy storage systems and compare this invention to existing control strategies, the simulation results show that the total energy spent is well saved over the long driving cycles, also the fuel cell and batteries are kept operating in a healthy way.     

Modeling,control and power management of hybrid photovoltaic fuel cells with battery bank supplying electric vehicle

In this paper, modeling, control and power management (PM) of hybrid Photovoltaic Fuel cell/Battery bank system supplying electric vehicle is presented. The HPS is used to produce energy without interruption. It consists of a photovoltaic generator (PV), a proton exchange membrane fuel cell (PEMFC), and a battery bank supplying an electric vehicle of 3 kW. In our work, PV and PEMFC systems work in parallel via DC/DC converter and the battery bank is used to store the excess of energy. The mathematical model topology and it power management of HPS with battery bank system supplying electric vehicle (EV) are the significant contribution of this paper. Obtained results under Matlab/Simulink and some experimental ones are presented and discussed.     

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.     

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.     

Health-aware frequency separation method for online energy management of fuel cell hybrid vehicle considering efficient urban utilization

Frequency separation methods (FSMs) are frequently used to implement energy management of fuel cell hybrid vehicle (FCHV), due to their flexible online implementation and resilience under diverse driving environments. However, predefined static rules of FSM generally result in inefficient operation of FCHV and rapid deterioration of sources. Additionally, allocated limits of storage devices are likely to be violated in the conventional FSM. With this inspiration, the paper proposes a novel health-aware FSM (HFSM) to appropriately distribute the traction power among energy sources of FCHV with efficient urban utilization. The power separation rules of HFSM are tuned in an instantaneous manner to concurrently realize the fuel economy, lifespan extension and allocated storage limits. Within HFSM, an online optimizer is formulated, which introduces the concept of soft/hard limitations and rationalized cost structure to adequately quantify the fuel consumption and health degradation of fuel cell. An adaptive droop adjustment is then integrated with HFSM to consistently realize the storage limitations. Compared to conventional FSM, considerable improvements in the fuel economy and fuel cell service life are observed over an extended iterative loop of standard urban driving cycles.     

Prediction-based optimal power management in a fuel cell/battery plug-in hybrid vehicle

A prediction-based power management strategy is proposed for fuel cell/battery plug-in hybrid vehicles with the goal of improving overall system operating efficiency. The main feature of the proposed strategy is that, if the total amount of energy required to complete a particular drive cycle can be reliably predicted, then the energy stored in the onboard electrical storage system can be depleted in an optimal manner that permits the fuel cell to operate in its most efficient regime. The strategy has been implemented in a vehicle power-train simulator called LFM which was developed in MATLAB/SIMULINK software and its effectiveness was evaluated by comparing it with a conventional control strategy. The proposed strategy is shown to provide significant improvement in average fuel cell system efficiency while reducing hydrogen consumption. It has been demonstrated with the LFM simulation that the prediction-based power management strategy can maintain a stable power request to the fuel cell thereby improving fuel cell durability, and that the battery is depleted to the desired state-of-charge at the end of the drive cycle. A sensitivity analysis has also been conducted to study the effects of inaccurate predictions of the remaining portion of the drive cycle on hydrogen consumption and the final battery state-of-charge. Finally, the advantages of the proposed control strategy over the conventional strategy have been validated through implementation in the University of Delaware's fuel cell hybrid bus with operational data acquired from onboard sensors.     

On-line fuzzy energy management for hybrid fuel cell systems

Fuel Cell Hybrid Vehicles (FCHV) can reach near zero emission by removing the conventional internal combustion from the vehicle powertrain. Nevertheless, before seeing competitive and efficient FCHV on the market, at market prices, different technical, economic, and social challenges should be overcome. A typical hybrid fuel cell powertrain combines a fuel cell stack and a dedicated energy storage system along with their necessary power converters. Energy storage systems are used in order to enhance the well-to-wheel efficiency and thus reducing the hydrogen consumption. An efficient management of power flows on the vehicle, allows optimizing the recovery of energy braking. Moreover, working in the fuel cell maximum efficiency leads to reduced thermal losses and thus to the downsizing of the heat exchangers. This paper presents an enhanced control of the power flows on a FCHV in order to reduce the hydrogen consumption, by generating and storing the electrical energy only at the most suitable moments on a given driving cycle. While the off-line optimization-based on dynamic programming algorithm offers the necessary optimal comparison reference on a known demand, the proposed strategy which can be implemented on-line, is based on a fuzzy logic decision system. The fine tuning of the fuzzy system parameters (mainly the membership functions and the gains), is made using a genetic algorithm and the fuzzy supervisor shows performing results for different load profiles.     

Numerical analysis of an energy storage system based on a metal hydride hydrogen tank and a lithium-ion battery pack for a plug-in fuel cell electric scooter

This work investigates on the performance of a hybrid energy storage system made of a metal hydride tank for hydrogen storage and a lithium-ion battery pack, specifically conceived to replace the conventional battery pack in a plug-in fuel cell electric scooter. The concept behind this solution is to take advantage of the endothermic hydrogen desorption in metal hydrides to provide cooling to the battery pack during operation.The analysis is conducted numerically by means of a finite element model developed in order to assess the thermal management capabilities of the proposed solution under realistic operating conditions.The results show that the hybrid energy storage system is effectively capable of passively controlling the temperature of the battery pack, while enhancing at the same time the on-board storage energy density. The maximum temperature rise experienced by the battery pack is around 12 °C when the thermal management is provided by the hydrogen desorption in metal hydrides, against a value above 30 °C obtained for the same case without thermal management. Moreover, the hybrid energy storage system provides the 16% of the total mass of hydrogen requested by the fuel cell stack during operation, which corresponds to a significant enhancement of the hydrogen storage capability on-board of the vehicle.     

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.     

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.     

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.     

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.     

An online prognostics-based health management strategy for fuel cell hybrid electric vehicles

As the energy transformation in the transportation sector is taking place driven by the development of fuel cell technologies, fuel cell hybrid electric vehicles become promising solutions owing to their long driving duration and zero emissions. However, the unsatisfied lifespan of fuel cells is an inevitable obstacle for their massive commercialization. This paper aims to propose an online adaptive prognostics-based health management strategy for fuel cell hybrid electric vehicles, which can improve the durability of the fuel cell thanks to online health monitoring. Here, particle filtering method is adapted for online fuel cell prognostics and the uncertainty of the predicted results is calculated based on the distribution of particles. A health management strategy is developed based on prognostics and a decision-making process is designed by considering the prognostics uncertainty through a decision fusion method. The obtained results show that the developed strategy has effectively improved the durability of the on-board fuel cell by up to 95.4%. Moreover, a sensitivity analysis of the prognostics occurrence frequency and probability calculation has also been conducted in this paper.