Control system design of hybrid fuel cell city bus

This paper introduced the design of the hybrid powertrain of the Fuel Cell City Bus demonstrated in 2008 Beijing Olympic Games. The configuration of the hybrid fuel cell powertrain was introduced. The safety of hydrogen storage and delivery system, the hydrogen leakage alarm system were developed. The real-time distributed control and diagnosis system based on the Time Trigger Controller Area Network （TTCAN） with 10 ms basic control period was developed. The concept and implementation of processor （or controller） monitor and process （or task） monitor technique based on the TYCAN were applied in this paper. The fault tolerant control algorithm of the fuel cell engine and the battery man- agement system were considered. The demonstration experience verified that the fault tolerant control was very important for the fuel cell city bus.

A hybrid fuel cell for water purification and simultaneously electricity generation

The development of highly efficient energy conversion technologies to extract energy from wastewater is urgently needed,especially in facing of increasing energy and environment burdens.Here,we successfully fabricated a novel hybrid fuel cell with BiOCl-NH_(4)PTA as photocatalyst.The polyoxometalate(NH_(4)PTA)act as the acceptor of photoelectrons and could retard the recombination of photogenerated electrons and holes,which lead to superior photocatalytic degradation.By utilizing BiOCl-NH_(4)PTA as photocatalysts and Pt/C air-cathode,we successfully constructed an electron and mass transfer enhanced photocatalytic hybrid fuel cell with flow-through field(F-HFC).In this novel fuel cell,dyes and biomass could be directly degraded and stable power output could be obtained.About 87%of dyes could be degraded in 30 min irradiation and nearly 100%removed within 90 min.The current density could reach up to~267.1μA/cm^(2);with maximum power density(Pmax)of~16.2μW/cm^(2) with Rhodamine B as organic pollutant in F-HFC.The power densities were 9.0μW/cm^(2),12.2μW/cm^(2),and 13.9μW/cm^(2) when using methyl orange(MO),glucose and starch as substrates,respectively.This hybrid fuel cell with BiOCl-NH_(4)PTA composite fulfills the purpose of decontamination of aqueous organic pollutants and synchronous electricity generation.Moreover,the novel design cell with separated photodegradation unit and the electricity generation unit could bring potential practical application in water purification and energy recovery from wastewater.

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.

A comparative study of hybrid electric vehicle fuel consumption over diverse driving cycles

Environmental pollution and declining resources of fossil fuels in recent years,have increased demand for better fuel economy and less pollution for ground transportation.Among the alternative solutions provided by researchers in recent decades,hybrid electric vehicles consisted of an internal combustion engine and an electric motor have been considered as a promising solution in the short-term.In the present study,fuel economy characteristics of a parallel hybrid electric vehicle are investigated by using numerical simulation.The simulation methodology is based on a fast forward facing simulation model of a parallel hybrid and an internal combustion engine powertrains.The objective of this study is to present the main parameters which result in an optimum combination of hybrid powertrain components in order to obtain a better fuel economy of hybrid powertrains regarding different driven cycles and hybridization factors.Then,the fuel consumption of the parallel hybrid electric vehicles are compared considering various driven cycles and hybridization factors.The results showed that the better fuel economy of hybrid powertrains increases by decreasing average load of the test cycle and the point of the best fuel economy for a particular average load of the cycle moves towards higher hybridization factors when the average load of the test cycle is reduced.

A Hybrid Biofuel and Triboelectric Nanogenerator for Bioenergy Harvesting

Various types of energy exist everywhere around us,and these energies can be harvested from multiple sources to power micro-/nanoelectronic system and even personal electronic products.In this work,we proposed a hybrid energy-harvesting system(HEHS)for potential in vivo applications.The HEHS consisted of a triboelectric nanogenerator and a glucose fuel cell for simultaneously harvesting biomechanical energy and biochemical energy in simulated body fluid.These two energy-harvesting units can work individually as a single power source or work simultaneously as an integrated system.This design strengthened the flexibility of harvesting multiple energies and enhanced corresponding electric output.Compared with any individual device,the integrated HEHS outputs a superimposed current and has a faster charging rate.Using the harvested energy,HEHS can power a calculator or a green light-emitting diode pattern.Considering the widely existed biomechanical energy and glucose molecules in the body,the developed HEHS can be a promising candidate for building in vivo self-powered healthcare monitoring system.

Multi-objective comprehensive optimization of fuel consumption and emission for hybrid electric vehicles

Aiming to reduce fuel consumption and emissions of a dual-clutch hybrid electric vehicle during cold start, multiobjective optimization for fuel consumption and HC/CO emission from a TWC(three-way catalytic converter) outlet is presented in this paper. DP(dynamic programming) considering dual-state variables is proposed based on the Bellman optimality principle. Both the battery SOC(state of charge) and the temperature of TWC monolith are considered in the algorithm simultaneously. In this way the global optimal control strategy and the Pareto optimal solution of multi-objective function are derived. Simulation results show that the proposed method is able to promote the TWC light-off significantly by decreasing the engine's load and improving exhaust temperature from the outlet of the engine, in comparison with original DP considering the single battery SOC. Compared to the results achieved by rule-based control strategy, fuel economy and emission of TWC outlet for cold start are optimized comprehensively. Each indicator of Pareto solution set shows the significant improvement.

A novel supercapacitor-fuel cell hybrid cell

A monolithic hybrid fuel cell (MHFC) with a novel configuration was proposed in an effort to improve the fuel cell performance during instantaneous power changes. A modified direct methanol fuel cell (DMFC) with a layer of hydrous ruthenium dioxide (RuO2·xH2O) sandwiched between the anode catalyst layer and membrane was used to demonstrate the principle of the MHFC. Experimental results indicate that the RuO2·xH2O layer is equivalent to a resistor-capacitor transmission line and functions similar to a capacitor in parallel with the anode electrode. The improvement in dynamic response of the MHFC was experimentally confirmed under step current change and square current pulse operating. The ionic conductivity of the RuO2·xH2O layer was also obtained.

Design and Fuel Consumption Optimization for a Bio-Inspired Semi-floating Hybrid Vehicle

Based on a bionic concept and combing air-cushion techniques and track driving mechanisms, a novel semi-floating hybrid concept vehicle is proposed to meet the transportation requirements on soft terrain. First, the vehicle scheme and its improved duel-spring flexible suspension design are described. Then, its fuel consumption model is proposed accordingly with respect to two vehicle operating parameters. Aiming at minimizing the fuel consumption, two Genetic Algorithms （GAs） are designed and implemented. For the initial one （GA-1）, despite getting an acceptable result, there still existed some problems in its optimiza- tion process. Based on an analysis of the defects of GA-1, an improved algorithm GA-2 was developed whose effectiveness and stability were embodied in the optimization process and results. The proposed design scheme and optimization approaches can provide valuable references for this new kind of vehicle with industry, military or scientific exploitations, etc. promising applications in the areas of agriculture, petroleum industry, military or scientific explaitations, etc.

Realization and Analysis of Good Fuel Economy and Kinetic Performance of a Low-cost Hybrid Electric Vehicle

By using high-power and high-efficiency propulsion systems,current hybrid electric vehicles（HEVs） in market can achieve excellent fuel economy and kinetic performance.However,it is the cost of current HEVs that hinders HEVs coming into widespread use.A novel hybrid electric propulsion system is designed to balance HEV cost and performance for developing markets.A battery/supercapacitor-based hybrid energy storage system（HESS） is used to improve energy conversion efficiency and reduce battery size and cost.An all-in-one-controller（AIOC） which integrates engine electronic control unit（ECU）,motor ECU,and HESS management system is developed to save materials and energy,and reduce the influence of distribution parameters on circuit.As for the powertrain configuration,four schemes are presented：belt-driven starter generator（BSG） scheme,four-wheel drive HEV scheme,full HEV scheme,and ranger-extender electric vehicle（EV） scheme.Component selection and parameter matching for the propulsion system are performed,and an energy management strategy is developed based on powertrain configuration and selected components.Forward-facing simulation models are built,comprehending the control strategy based on the optimal engine torque for the low-cost hybrid electric propulsion system.Co-simulation of AVL CRUISE and Matlab/Simulink is presented and the best scheme is selected.The simulation results indicate that,for the best design,fuel consumption in urban driving condition is 4.11 L/（100 km） and 0-50 km/h accelerating time is 10.95 s.The proposed research can realize low-cost concept for HEV while achieving satisfactory fuel economy and kinetic performance,and help to improve commercialization of HEVs.

Evaluation of In-Use Fuel Economy for Hybrid and Regular Transit Buses

Fuel costs are a significant portion of transit agency budgets. Hybrid technology offers an attractive option and has the potential to significantly reduce operating costs for agencies. The main impetus behind use of hybrid transit vehicles is fuel savings and reduced emissions. Laboratory tests have indicated that hybrid transit buses can have significantly higher fuel economy and lower emissions compared to conventional transit buses. However, the number of studies is limited and laboratory tests may not represent actual driving conditions since in-use vehicle operation differs from laboratory test cycles. Several initial studies have suggested that the fuel economy savings reported in laboratory tests may not be realized on-road. The objective of the project described in this paper was to evaluate the in-use fuel economy differences between hybrid-electric and conventional transit buses for the Ames, Iowa (USA) transit authority. On-road fuel economy was evaluated over a 12-month period for 12 hybrid and 7 control transit buses. Fuel economy comparisons were also provided for several older in-use bus types. Buses other than the control and hybrid buses were grouped by model year corresponding to US diesel emission standards. Average fuel economy in miles per gallon was calculated for each bus group overall and by season. Hybrid buses had the highest fuel economy for all time periods for all bus types. Hybrid buses had a fuel economy that was 11.8% higher than control buses overall and was 12.2% higher than buses with model years 2007 and higher, 23.4% higher than model years 2004 to 2006, 10.2% higher than model years 1998 to 2003, 38.1% higher than for model years 1994 to 1997, 36.8% higher for model years 1991 to 1993, and 36.8% higher for model years pre-1991. Differences between groups of buses also varied by season of the year.

Hybrid dynamic model of polymer electrolyte membrane fuel cell stack using variable neural network

The polymer electrolyte membrane（PEM） fuel cell has been regarded as a potential alternative power source,and a model is necessary for its design,control and power management.A hybrid dynamic model of PEM fuel cell,which combines the advantages of mechanism model and black-box model,is proposed in this paper.To improve the performance,the static neural network and variable neural network are used to build the black-box model.The static neural network can significantly improve the static performance of the hybrid model,and the variable neural network makes the hybrid dynamic model predict the real PEM fuel cell behavior with required accuracy.Finally,the hybrid dynamic model is validated with a 500 W PEM fuel cell.The static and transient experiment results show that the hybrid dynamic model can predict the behavior of the fuel cell stack accurately and therefore can be effectively utilized in practical application.

Simulation of Dynamic Response of Small Wind-Photovoltaic-Fuel Cell Hybrid Energy System

Renewable energy systems are of importance as being modular, nature-friendly and domestic. Among renewable energy systems, a great deal of research has been conducted especially on photovoltaic effect, wind energy and fuel cell in the recent years. This paper describes dynamic modeling and simulation results of a small wind-photovoltaic-fuel cell hybrid energy system. The hybrid system consists of a 500 W wind turbine, a photovoltaic, a proton exchange membrane fuel cell (PEMFC), ultracapacitors, an electrolyzer, a boost converter, controllers and a power converter that simulated using MATLAB solver. This kind of hybrid system is completely stand-alone, reliable and has high efficiency. In order to minimize sudden variations in voltage magnitude ultracapacitors are proposed. Power converter and inverter are used to produce ac output power. Dynamics of fuel-cell component such as double layer capacitance are also taken into account. Control scheme of fuel-cell flow controller and voltage regulators are based on PID controllers. Dynamic responses of the system for a step change in the electrical load and wind speed are presented. Results showed that the ability of the system in adapting itself to sudden changes and new conditions. Combination of PV and wind renewable sources is made the advantage of using this system in regions which have higher wind speeds in the seasons that suffers from less sunny days and vice versa.

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%。

基于近端策略优化算法的燃料电池混合动力系统综合价值损耗最小能量管理方法

为了降低市域动车组燃料电池混合动力系统运行燃料经济成本,提升燃料电池耐久性,该文提出一种基于近端策略优化算法的能量管理方法。该方法将混合动力系统能量管理问题建模为马尔可夫决策过程,以综合考虑燃料经济性和燃料电池耐久性的综合价值损耗最小为优化目标设置奖励函数,采用一种收敛速度较快的深度强化学习算法—近端策略优化算法求解,实现负载功率在燃料电池和锂电池间的合理有效分配,最后,采用市域动车组实际运行工况进行实验验证。实验结果表明,在训练工况下,所提方法相较基于等效氢耗最小能量管理方法和基于Q-learning能量管理方法,综合价值损耗分别降低19.71%和5.87%;在未知工况下,综合价值损耗分别降低18.05%和13.52%。结果表明,所提方法能够有效降低综合价值损耗,并具有较好的工况适应性。

燃料电池船舶混合动力系统能量管理研究综述

在“双碳”目标下,发展燃料电池船舶是实现航运业转型升级和低碳化的重要发展方向之一。面对当前燃料电池上船的诸多问题,混合动力系统成为燃料电池船舶应用的有效解决方案,其能量管理的研究也成为核心研究方向之一。系统梳理燃料电池船舶的发展概况,针对燃料电池船舶多类型能源能量管理中涉及的能量调度问题以及变换器功率分配问题进行综述;分析各类方法的优缺点及其在实船上应用的可能性;探讨燃料电池船舶推广可行性和发展方向,以期能为技术创新和工程应用提供参考。

基于模型预测框架的燃料电池汽车混合动力系统能量管理

混合动力系统作为燃料电池汽车的关键组成部分,系统的能耗与寿命优化是推动其进一步商业化发展的关键,而能量管理策略(EMS)在提高燃料电池汽车混合动力系统的效率和燃料经济性方面发挥着重要作用。为有效降低混合动力系统的内部损耗,进一步提高系统经济性,提出了一种基于模型预测框架的混合动力系统能耗优化能量管理控制方法。首先构建包含动力系统内部损耗与氢气消耗的目标函数,然后利用模型预测架构求解目标函数来控制燃料电池的输出电流,以实现合理的能量分配,最后在Matlab中进行仿真,验证所制定方法的合理性和有效性。与应用较为广泛的等效氢耗最小策略(ECMS)相比,结果表明所提方法可以显著降低动力系统的内部损耗和氢气消耗。此外,该策略还可以有效保持蓄电池的荷电状态(SOC),延长动力系统的使用寿命。

燃料电池船复合储能容量优化与配置经济性分析

复合储能系统可改善由船舶负载功率波动引起的燃料电池寿命损耗问题,但配置成本限制了其在燃料电池船上的广泛应用。为合理配置储能容量,使船舶动力系统设计具备长期的可靠性,提出了一种计及复合储能系统全寿命周期的容量优化配置方法。在构建各电源系统模型的基础上,建立包括购置成本、维护成本、置换成本和能耗成本的复合储能系统全寿命周期成本模型,并采用雨流计数法来评估储能的置换成本。最后依据“Alsterwasser”号燃料电池船的典型功率需求数据,以储能设备的容量参数、燃料电池的输出功率和电源系统的运行参数为优化变量,采用灰狼优化算法进行求解。通过不同储能类型和优化目标下的配置方案对比,验证了所提方法的经济性。

基于计算机软件的燃料电池混合储能系统分析

燃料电池自身特征导致其越来越多出现在混合储能系统中,为了实现能源调配控制,进一步降低能源成本,提高应用范围,本文分析研究了计算机软件下的燃料电池混合储能系统,包括燃料电池混合储能技术的整体脉络,以及其核心技术架构包括燃料电池功率系统和控制系统两大部分。研究结果表明,有效的能量控制系统可以提高储能调配合理性,降低应用成本,而燃料电池混合储能系统也具有较好的应用发展前景。

船舶多堆燃料电池混合动力系统能量管理策略优化

为研究多堆燃料电池系统(MFCS)、锂电池为动力源的船舶混合动力系统的能量管理策略(EMS),本文提出一种基于粒子群优化(PSO)算法的多级功率分配策略。首先,利用一级EMS分析MFCS和锂电池需求功率,其次,构建以MFCS总效率为优化目标的二级MFCS协同控制策略,优化燃料电池之间的功率分配。最后,基于燃料电池混合动力船舶典型工况,分析船舶混合动力系统的功率分布、等效氢耗量及燃料电池系统效率、加减载速率。研究结果表明,与等效氢消耗最小化策略(ECMS)相比,该策略下的燃料电池1和燃料电池2的氢耗量分别降低了15%和23%,MFCS总效率提高了1.15%,且燃料电池的功率变化波动更小。该研究有助于提高混合动力系统中燃料电池的经济性和耐久性。

燃料电池汽车动力系统及能量管理策略研究进展

动力系统是燃料电池汽车(FCV)的核心,可分为单一式系统与混合动力系统两大类,其中,将燃料电池与辅助电源相结合组成“电-电”混合动力系统,已成为业界主流。本文根据辅助电源类型的不同,提出3类FCV混动系统的构建方案,分别为燃料电池+动力电池方案、燃料电池+超级电容方案、燃料电池+动力电池+超级电容方案,并对各方案的优势和劣势进行比较。同时,本文综述了近年来国内外学者提出的面向FCV的代表性能量管理策略,从理论基础与求解方法的差异出发,将现有燃料电池汽车的能量管理策略分为3类:基于规则定义的策略、基于最优化方法的策略以及基于机器学习的策略,并总结了各类策略在最优性与实时性等方面的优势和劣势。其中,基于规则定义的策略最易实现,在工程应用中最为普遍,但无法实现性能最优;基于最优化方法的策略能够接近甚至达到理论最优,但存在计算量过大、计算耗时过长、实时性差等问题;以强化学习为代表的基于机器学习的策略有望在最优性与实时性之间实现理想的平衡,但目前还存在模型训练耗时长、试错代价高等困难,在实车应用层面还存在一定挑战。基于文献研究与分析,本文提出以下观点:1)以大功率燃料电池为核心的功率混合型系统是FCV混动系统的未来发展方向;2)必须进一步提升智能化程度,根据实际使用场景开发具有个性化的能量管理策略;3)亟需建立关于燃料电池汽车能量管理策略的综合评价体系。