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.     

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.     

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.     

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.     

Load sharing using fuzzy logic control in a fuel cell/ultracapacitor hybrid vehicle

Fuel cell (FC) and ultracapacitor (UC) based hybrid power systems appear to be very promising for satisfying high energy and high power requirements of vehicular applications. The improvement in control strategies enhances dynamic response of the FC/UC hybrid vehicular power system under various load conditions. In this study, FC system and UC bank supply power demand using a current-fed full bridge dc–dc converter and a bidirectional dc–dc converter, respectively. We focus on a novel fuzzy logic control algorithm integrated into the power conditioning unit (PCU) for the hybrid system. The control strategy is capable of determining the desired FC power and keeps the dc voltage around its nominal value by supplying propulsion power and recuperating braking energy. Simulation results obtained using MATLAB^® & Simulink^® and ADVISOR^® are presented to verify the effectiveness of the proposed control algorithm.     

Energy management of a fuel cell hybrid ultra-energy efficient vehicle

This paper focuses on energy management in an ultra-energy efficient vehicle powered by a hydrogen fuel cell with rated power of 1 kW. The vehicle is especially developed for the student competition Shell Eco-marathon in the Urban Concept category. In order to minimize the driving energy consumption a simulation model of the vehicle and the electric propulsion is developed. The model is based on vehicle dynamics and real motor efficiency as constant DC/DC, motor controllers and transmission efficiency were considered. Based on that model five propulsion schemes and driving strategies were evaluated. The fuel cell output parameters were experimentally determined. Then, the driving energy demand and hydrogen consumption was estimated for each of the propulsion schemes. Finally, an experimental study on fuel cell output power and hydrogen consumption was conducted for two propulsion schemes in case of hybrid and non-hybrid power source. In the hybrid propulsion scheme, supercapacitors were used as energy storage as they were charged from the fuel cell with constant current of 10 A.     

Economic energy management strategy design and simulation for a dual-stack fuel cell electric vehicle

This paper presents the design and simulation validation of two energy management strategies for dual-stack fuel cell electric vehicles. With growing concerns about environmental issues and the fossil energy crisis, finding alternative methods for vehicle propulsion is necessary. Proton exchange membrane (PEM) fuel cell systems are now considered to be one of the most promising alternative energy sources. In this work, the challenge of further improving the fuel economy and extending the driving range of a fuel cell vehicle is addressed by a dual-stack fuel cell system with specific energy management strategies. An efficiency optimization strategy and an instantaneous optimization strategy are proposed. Simulation validation for each strategy is conducted based on a dual-stack fuel cell electric vehicle model which follows the new European driving cycle (NEDC). Simulation results show that a dual-stack fuel cell system with proposed energy management strategies can significantly improve the fuel economy of a fuel cell vehicle and thus lengthen the driving range while being able to keep the start-stop frequency of the fuel cell stack within a reasonable range.     

A fuzzy logic based supervisory controller for an FC/UC hybrid vehicular power system

Depending on growing concerns on energy crises and environmental issues, fuel cell (FC) powered electrical vehicles are favored for possible substitute to conventional internal combustion engine (ICE) based vehicular systems. However, the typical power profile of an automobile motor consisting of transients is not suitable for the use of a sole FC system for vehicle propulsion. This shortcoming could be partly overcome by hybridization. Two potential benefits of combining an FC system with an energy storage unit, ultra-capacitor (UC) has been presented in this study. Firstly, the durability of the FC system could be improved because the additional energy source can fulfill the transient power demand fluctuations. Secondly, the ability of the energy storage source to recover braking energy enhances the fuel economy greatly. An important aspect in designing a hybrid power structure is to find a suitable control strategy that can manage the active power sharing and take advantage of the inherent scalability and robustness benefits of the hybrid system. An integrated procedure for mathematical modeling and power control strategy design for an FC/UC hybrid vehicle is presented in this paper. A fuzzy logic supervisory controller based power management strategy that secures the power balance in hybrid structure, enhances the FC performance and minimizes the power losses is proposed. The main contribution of this paper apart from the previous studies of the authors is the modeling of the complete FC power system with air supply compressor and the integration of the control of the FC system internal dynamics (especially the oxygen excess ratio) into the overall supervisory control structure to maximize the efficiency and durability. To demonstrate the effectiveness of the proposed power management scheme, simulation studies were performed using MATLAB^®, Simulink^® and SimPowerSystems^® environments by integrating the detailed mathematical and electrical models of the hybrid vehicular system.     

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.     

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.     

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.     

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.     

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.     

Drive-train simulator for a fuel cell hybrid vehicle

The model formulation, development process, and experimental validation of a new vehicle powertrain simulator called LFM (Light, Fast, and Modifiable) are presented. The existing powertrain simulators were reviewed and it was concluded that there is a need for a new, easily modifiable simulation platform that will be flexible and sufficiently robust to address a variety of hybrid vehicle platforms. First, the structure and operating principle of the LFM simulator are presented, followed by a discussion of the subsystems and input/output parameters. Finally, a validation exercise is presented in which the simulator's inputs were specified to represent the University of Delaware's fuel cell hybrid transit vehicle and “driven” using an actual drive cycle acquired from it. Good agreement between the output of the simulator and the physical data acquired by the vehicle's on-board sensors indicates that the simulator constitutes a powerful and reliable design tool.     

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.     

Review on health-conscious energy management strategies for fuel cell hybrid electric vehicles: Degradation models and strategies

Considering the overwhelming pressure on worldwide demand of fossil fuels and the climate change caused by air pollution, hybrid electric vehicles have seen a promising future thanks to the development of renewable energy sources. Among various kinds of energy sources that have been used in hybrid electric vehicles, lithium-ion battery and proton exchange membrane (PEM) fuel cell exist to be the most favorable ones owing to their high energy density and power density. However, the degradation issues of the energy sources tend to be neglected when designing the energy management strategies for the hybrid electric vehicles. Concerning existing literature, degradation modelling methods of lithium-ion batteries and PEM fuel cells are reviewed and the possibility of integrating them into health-conscious energy management is discussed. Besides, a variety of energy management strategies that have taken the influence of degradations into consideration are reviewed and classified. The contribution of this paper is to investigate the possibility of developing a health-conscious energy management strategy based on accurate estimation of degradation to improve the durability of the system.     

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.     

A novel maximum power fuzzy logic controller for photovoltaic solar energy systems

The maximum power tracking problem and efficient energy utilization of a stand-alone photovoltaic array (PVA) feeding voltage controlled linear and nonlinear loads is studied. A novel and simple on-line fuzzy logic-based dynamic search, detection and tracking controller is developed to ensure maximum power point (MPP) operation under excursions in solar insolation, ambient temperature and electric load variations. A computer simulation model of the PVA renewable utilization scheme including the effects of temperature and solar irradiation changes was developed and fully simulated. The load voltage is controlled by a DC chopper and kept constant at the required rated voltage. A permanent magnet DC motor (PMDC) driving a fan-type load was connected in parallel to an RL passive load. A speed control scheme is also used for the PMDC motor drive so that the drive can be operated at specified speeds. Different controllers have been employed in the unified PVA scheme to control three separate loads at MPP tracking condition namely voltage at load bus and speed of the PMDC motor. The main objective of the paper is to present a novel enhanced, cost-effective MPP detector (MPPD) and dynamic MPP tracking (MPPT) controller for a hybrid mix of electric loads.     

Analysis of a fuel cell hybrid commuter railway vehicle

This study presents paper presents an analysis of the potential CO₂ savings that could be gained through the introduction of hydrogen-powered fuel cells on a commuter-style railway route. Vehicle is modelled as a fuel cell series hybrid. The analysis consists of power/energy flow models of a fuel cell stack, battery pack and hybrid drive controller. The models are implemented in a custom C# application and are capable of providing key parametric information of the simulated journey and individual energy drive components. A typical commuter return journey between Stratford Upon Avon and Birmingham is investigated. The fuel cell stack and battery pack behaviour is assessed for different stack sizes, battery sizes and control strategies to evaluate the performance of the overall system with the aim of understanding the optimum component configuration. Finally, the fuel (H₂) requirements are compared with typical diesel and hybrid-diesel powered vehicles with the aim of understanding the potential energy savings gained from such a fuel cell hybrid vehicle.     

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.