Research on ECMS Based on Segmented Path Braking Energy Recovery in a Fuel Cell Vehicle

Proton exchange membrane fuel cells are widely regarded as having the potential to replace internal combustion engines in vehicles.Since fuel cells cannot recover energy and have a slow dynamic response,they need to be used with different power sources.Developing efficient energy management strategies to achieve excellent fuel economy is the goal of research.This paper proposes an adaptive equivalent fuel minimum consumption strategy(AECMS)to solve the problem of the poor economy of the whole vehicle caused by the wrong selection of equivalent factors(EF)in traditional ECMS.In this method,the kinematics interval is used to update the equivalent factor by considering the penalty term of energy recovery on SOC changes.Finally,the optimized equivalent factor is substituted into the optimization objective function to achieve efficient energy regulation.Simulation results under the New European Driving Cycle show that compared with the traditional ECMS based on fixed SOC benchmarks,the proposed method improves fuel economy by 1.7%while ensuring vehicle power and increases SOC by 30%.

A Novel Method for the Application of the ECMS(Equivalent Consumption Minimization Strategy)to Reduce Hydrogen Consumption in Fuel Cell Hybrid Electric Vehicles

Fuel cell hybrid electric vehicles are currently being considered as ideal means to solve the energy crisis and global warming in today’s society.In this context,this paper proposes a method to solve the problem related to the dependence of the so-called optimal equivalent factor(determined in the framework of the equivalent consumption minimum strategy-ECMS)on the working conditions.The simulation results show that under typical conditions(some representative cities being considered),the proposed strategy can maintain the power balance;for different initial battery’s states of charge(SOC),after the SOC stabilizes,the fuel consumption is 5.25 L/100 km.

Power Conversion System Strategies for Fuel Cell Vehicles

Power electronics is an enabling technology for the development of environmental friendly fuel cell vehicles, and to implement the various vehicle electrical architectures to obtain the best performance. In this paper, power conversion strategies for propulsion and auxiliary power unit applications are described. The power electronics strategies for the successful development of the fuel cell vehicles are presented. The fuel cell systems for propulsion and for auxiliary power unit applications are also discussed.

Interpretation of GB/T 26779-2021,Hydrogen fuel cell electric vehicles refueling receptacle

With the development of fuel cell electric vehicle industry in China,the 70-MPa hydrogen storage cylinders have been widely applied on vehicles in recent years.The revised standard,GB/T 26779-2021,Hydrogen fuel cell electric vehicle refueling receptacle,was released on March 9,2021 with added stipulations for the 70-MPa hydrogen refuelling receptacle.The main technical contents of GB/T 26779-2021 and its similarities and differences with GB/T 26779-2011 are discussed in this paper.

Interpretation of GB/T 24549-2009 Fuel Cell Electric Vehicle—Safety Requirements

The national standard GB/T 24549—2009 Fuel Cell Electric Vehicle—Safety Requirements specifies the general safety requirements for whole vehicle and key parts of Fuel Cell Electric Vehicle (FCEV).It is of great significance for the development of FCEV in china.This paper discusses the main contents and the background of its development.

Theoretical On-Board Hydrogen Redox Electric Power Generator for Infinite Cruising Range Fuel Cell Vehicles

The development of hydrogen redox electric power generators for infinite cruising range electric vehicles represents a true technological breakthrough. Such systems consist of a polymer electrolyte membrane hydrogen electrolytic cell equipped with an electrostatic-induction potential-superposed water electrolytic cell that provides a stoichiometric H2-O2 fuel mixture during operation of the vehicle. This generator functions with zero power input, zero matter input and zero emission due to the so-called ＂zero power input＂ electrostatic-to-chemical energy conversion occurring in the electrolytic cell. Here, theoretical simulations were performed to verify the target performance of such generators, assuming a pair of FC （fuel cell） and electrolytic cell stacks, both of which are commercially available.

Design and Control of a DC Boost Converter for Fuel-Cell-Powered Marine Vehicles

Economic factors along with legislation and policies to counter harmful pollution apply specifically to maritime drive research for improved power generation and energy storage.Proton exchange membrane fuel cells are considered among the most promising options for marine applications.Switching converters are the most common interfaces between fuel cells and all types of load in order to provide a stable regulated voltage.In this paper,a method using artificial neural networks(ANNs)is developed to control the dynamics and response of a fuel cell connected with a DC boost converter.Its capability to adapt to different loading conditions is established.Furthermore,a cycle-mean,black-box model for the switching device is also proposed.The model is centred about an ANN,too,and can achieve considerably faster simulation times making it much more suitable for power management applications.

Theoretical Propulsion System for Fuel Cell Vehicles with Infinite Cruising Range

The realization of a clean automobile society would require electrically-powered propulsion systems in vehicles.In recent years,electric vehicles have attracted considerable attention from the perspective of utilizing electricity generated from natural sources,such as solar and wind power.The propulsion method considered in the present investigation differs from the conventional off-board energy scheme in a manner such that pure stoichiometric H2/O2 fuels for fuel cells are generated on-board during vehicle operation.In this method,energy conversion occurs by means of ESI-PSE(electrostatic-induction potential-superposed electrolysis).If a quasi-static process is assumed,the theoretical power requirement to produce pure stoichiometric H2/O2 fuels is only 17%of the total energy required owing to a new method for supplying power to the EC(electrolytic cell).If an ESI-PSE EC is combined with a fuel cell(FC)to form an energy cycle,a HREG(hydrogen redox electric power generator)that uses solid PEMs(polymer electrolyte membranes)for the EC as well as the FC can be realized.According to calculations based on data from the operational conditions of commercially available ECs and FCs,more than 70%of the power delivered from the FC can be extracted for driving a motor constantly while a car is in motion.Because of energy self-sustainability on the HREG side,the power control system should not have any power loss.This propulsion system will realize tough vehicles that can continue running at a top speed at long unlimited cruising range.

A Resonant Dual Full-Bridge Class-E Bidirectional DC-DC Converter for Fuel Cell Electric Vehicle

The interests on energy storage schemes, bidirectional dc-dc converter and uninterruptible power supplies have been increasing nowadays as there wide researches are undertaken in the area of electric vehicles. A modified bi directional class-E resonant dc-dc converter is introduced here in this proposed topology for the application in electric vehicles. The advantages of soft switching techniques have been utilized for making analysis simple. The main advantage here in this system is that it can operate in a wide range of frequencies with minimal switching loss in transistors. This paper elaborates a detailed analysis on converter design and the same has been simulated and verified in Matlab/Simulink.

A New Topology of a Variable Output-Voltage DC-DC Converter for Fuel Cell Vehicles

The aim of this paper is to present a new topology of a DC-DC power converter for conditioning the current and voltages behaviors of embarked energy sources used in electrical vehicles. The fuel cells in conjunction with ultra-capacitors have been chosen as the power supply. The originality of the proposed converter is to use a variable voltage of the DC bus of the vehicle. The goal is to allow a better energy management of the embedded sources onboard the vehicle by improving its energy efficiency. After presenting and explaining the topology of the converter, some simulation and experiments results are shown to highlight its different operation modes.

Data-driven modeling and fault diagnosis for fuel cell vehicles using deep learning

The reliability and safety of fuel cell vehicle are crucial for the daily operation. Insulation resistance serves as a crucial index of vehicle reliability, especially when fuel cells operate at high voltages. Low insulation resistance can lead to vehicle malfunctions, exposing the operator to the risk of electric shock. In this study, long-term insulation resistance data from thirteen vehicles equipped with three different types of fuel cell systems are analyzed to diagnose possible low insulation resistance issues. For this purpose, a robust locally weighted scatterplot smoothing method is utilized to filter the original data. In this research, an insulation variation model is developed using a data-driven long short-term memory neural network to identify insulation resistance value anomalies caused by deionizer failure. The results indicate that the coefficient of determination of the failure model is 99.78 %. Moreover, current model efficiently identifies insulation faults resulting from reliability issues, such as conductivity issues of cooling pipes and erosion of vehicle wiring harnesses.

Hydrophobicity gradient optimization of fuel cell gas diffusion media for its application in vehicles

During Fuel Cell Vehicle(FCV)operation,the liquid water in gas diffusion media(GDM)prevents the reaction gas from reaching the reaction zone and lead to output power fluctuation and reduce the lifespan of FCV.In the present research,hydrophobicity gradient settings of micro-porous layer(MPL)and gas diffusion layer(GDL)are optimized to improve the water removal ability of GDM.Computational fluid dynamics(CFD)model is constructed for numerical simulations to analyze the fuel cell power output and the water content in the GDM with different hydrophobicity gradients.Experiments with different hydrophobicity gradients,which are specifically prepared with corresponding concentrations of polytetrafluoroethylene(PTFE)solutions,are conducted for validation of simulation results.It is shown that the positive hydrophobicity gradient of MPL and GDL provides a better capacity for water removal and oxygen transport.The contact angles of MPL and GDL are further optimized as 147.9°-138.6°by genetic algorithm integrated with the CFD simulations.

Analysis on carbon emission reduction intensity of fuel cell vehicles from a life-cycle perspective

The hydrogen fuel cell vehicle is rapidly developing in China for carbon reduction and neutrality.This paper evaluated the life-cycle cost and carbon emission of hydrogen energy via lots of field surveys,including hydrogen production and packing in chlor-alkali plants,transport by tube trailers,storage and refueling in hydrogen refueling stations(HRSs),and application for use in two different cities.It also conducted a comparative study for battery electric vehicles(BEVs)and internal combustion engine vehicles(ICEVs).The result indicates that hydrogen fuel cell vehicle(FCV)has the best environmental performance but the highest energy cost.However,a sufficient hydrogen supply can significantly reduce the carbon intensity and FCV energy cost of the current system.The carbon emission for FCV application has the potential to decrease by 73.1%in City A and 43.8%in City B.It only takes 11.0%–20.1%of the BEV emission and 8.2%–9.8%of the ICEV emission.The cost of FCV driving can be reduced by 39.1%in City A.Further improvement can be obtained with an economical and“greener”hydrogen production pathway.

Machine learning modeling for fuel cell-battery hybrid power system dynamics in a Toyota Mirai 2 vehicle under various drive cycles

Electrification is considered essential for the decarbonization of mobility sector, and understanding and modeling the complex behavior of modern fuel cell-battery electric-electric hybrid power systems is challenging, especially for product development and diagnostics requiring quick turnaround and fast computation. In this study, a novel modeling approach is developed, utilizing supervised machine learning algorithms, to replicate the dynamic characteristics of the fuel cell-battery hybrid power system in a 2021 Toyota Mirai 2nd generation (Mirai 2) vehicle under various drive cycles. The entire data for this study is collected by instrumenting the Mirai vehicle with in-house data acquisition devices and tapping into the Mirai controller area network bus during chassis dynamometer tests. A multi-input - multi-output, feed-forward artificial neural network architecture is designed to predict not only the fuel cell attributes, such as average minimum cell voltage, coolant and cathode air outlet temperatures, but also the battery hybrid system attributes, including lithium-ion battery pack voltage and temperature with the help of 15 system operating parameters. Over 21,0000 data points on various drive cycles having combinations of transient and near steady-state driving conditions are collected, out of which around 15,000 points are used for training the network and 6,000 for the evaluation of the model performance. Various data filtration techniques and neural network calibration processes are explored to condition the data and understand the impact on model performance. The calibrated neural network accurately predicts the hybrid power system dynamics with an R-squared value greater than 0.98, demonstrating the potential of machine learning algorithms for system development and diagnostics.

Recent development in degradation mechanisms of proton exchange membrane fuel cells for vehicle applications:problems,progress,and perspectives

Due to its zero emissions,high efficiency and low noise,proton exchange membrane fuel cell(PEMFC)is full of potential for the application of vehicle power source.Nonetheless,its lifespan and durability remain multiple obstacles to be solved before widespread commercialization.Frequent exposure to non-rated operating conditions could considerably accelerate the degradation of the PEMFC in various forms,thus reducing its durability.This paper first analyzes degradation mechanisms of PEMFCs under typical automotive operating conditions,including idling,startup-shutdown,dynamic loads,and cold start.The corresponding accelerated stress testing methods are also discussed.Then,as the impurities existed in the reaction gas source and generated from the degradation of the PEMFC itself may occur under all automotive conditions,the degradation mechanisms caused by impurity contamination are classified and reviewed in detail.After that,the techniques proposed by researchers to enhance the durability of PEMFCs are presented from four aspects:membrane electrode assembly materials,bipolar plates and flow fields design,stack assembly,and cell control strategies.The challenges in the field and the prospects for the future are summarized and analyzed at the end.The aim of this work is to provide guidelines for improving the durability of PEMFCs in vehicle applications.

Polymer Electrolyte Membrane Fuel Cells (PEMFC) in Automotive Applications: Environmental Relevance of the Manufacturing Stage

This study presents a state of the art of several studies dealing with the environmental impact assessment of fuel cell (FC) vehicles and the comparison with their conventional fossil-fuelled counterparts, by means of the Life Cycle As-sessment (LCA) methodology. Results declare that, depending on the systems characteristics, there are numerous envi-ronmental advantages, but also some disadvantages can be expected. In addition, the significance of the manufac-turing process of the FC, more specifically the Polymer Electrolyte Membrane Fuel Cell (PEMFC) type, in terms of environmental impact is presented. Finally, CIEMAT’s role in HYCHAIN European project, consisting of supporting early adopters for hydrogen FCs in the transport sector, is

Atomic-scale engineering of advanced catalytic and energy materials via atomic layer deposition for eco-friendly vehicles

Zero-emission eco-friendly vehicles with partly or fully electric powertrains have exhibited rapidly increased demand for reducing the emissions of air pollutants and improving the energy efficiency. Advanced catalytic and energy materials are essential as the significant portions in the key technologies of eco-friendly vehicles, such as the exhaust emission control system,power lithium ion battery and hydrogen fuel cell. Precise synthesis and surface modification of the functional materials and electrodes are required to satisfy the efficient surface and interface catalysis, as well as rapid electron/ion transport. Atomic layer deposition(ALD), an atomic and close-to-atomic scale manufacturing method, shows unique characteristics of precise thickness control, uniformity and conformality for film deposition, which has emerged as an important technique to design and engineer advanced catalytic and energy materials. This review has summarized recent process of ALD on the controllable preparation and modification of metal and oxide catalysts, as well as lithium ion battery and fuel cell electrodes. The enhanced catalytic and electrochemical performances are discussed with the unique nanostructures prepared by ALD. Recent works on ALD reactors for mass production are highlighted. The challenges involved in the research and development of ALD on the future practical applications are presented, including precursor and deposition process investigation, practical device performance evaluation, large-scale and efficient production, etc.

融合工况预测的燃料电池汽车里程自适应等效氢耗最小控制策略

为有效地提高插电式燃料电池汽车的经济性,实现燃料电池和动力电池的功率最优分配,考虑到行驶工况、电池荷电状态(State of charge,SOC)、等效因子与氢气消耗之间的密切联系,制定融合工况预测的里程自适应等效氢耗最小策略.通过基于误差反向传播的神经网络来实现未来短期车速的预测,分析未来车辆需求功率变化,同时借助全球定位系统规划一条通往目的地的路径,智能交通系统便可获取整个行程的交通流量信息,利用行驶里程和SOC实时动态修正等效消耗最小策略中的等效因子,实现能量管理策略的自适应性.基于MATLAB/Simulink软件,搭建整车仿真模型与传统的能量管理策略进行仿真对比验证.仿真结果表明,采用基于神经网络的工况预测算法能够较好地预测未来短期工况,其预测精度相较于马尔可夫方法提高12.5%,所提出的能量管理策略在城市道路循环工况(UDDS)下的氢气消耗比电量消耗维持(CD/CS)策略下降55.6%.硬件在环试验表明,在市郊循环工况(EUDC)下的氢气消耗比CD/CS策略下降26.8%,仿真验证结果表明了所提出的策略相比于CD/CS策略在氢气消耗方面的优越性能,并通过硬件在环实验验证了所提策略的有效性.

基于TD3-PER的氢燃料电池混合动力汽车能量管理策略研究

为优化氢燃料电池混合动力汽车的燃料经济性及辅助动力电池性能,提出了一种基于优先经验采样的双延迟深度确定性策略梯度(TD3-PER)能量管理策略。采用双延迟深度确定性策略梯度(TD3)算法,在防止训练过优估计的同时实现了更精准的连续控制;同时结合优先经验采样(PER)算法,在获得更好优化性能的基础上加速了策略的训练。仿真结果表明:相较于深度确定性策略梯度(DDPG)算法,所提出的TD3-PER能量管理策略的百公里氢耗量降低了7.56%,平均功率波动降低了6.49%。

车用氢能发展难点与对策

“双碳”目标背景下,国内加快能源转型步伐,交通运输业作为第三大碳排放行业,加快向电、氢转型。分析了国内氢燃料电池汽车和加氢站的发展现状,从产业链的角度深入剖析了国内车用氢能发展的“车贵”“氢贵”“站贵”等三大痛点,认为深层次的原因是燃料电池、车辆生产和加氢站设备生产存在技术瓶颈,关键零部件仍然依赖进口,加氢站建设及运营成本高,电解水等制氢成本高等。最后,从行业发展的角度,分别提出了降低车用氢能成本的突破路径,指导行业良性发展。