Control of parallel dry methane and steam methane reforming processes for Fischer–Tropsch syngas

The ratio of hydrogen to carbon monoxide in the synthesis gas required for feeding to the gas-to-liquid Fischer–Tropsch (FT) process to produce liquid transportation fuel is about two. The dry methane reforming (DMR) process feeds carbon dioxide and methane and produces a syngas with a H₂/CO ratio of about unity. The steam methane reforming (SMR) process feeds water and methane and produces a syngas with a H₂/CO ratio of about four. This paper studies the plantwide control of a process with DMR and SMR units operating in parallel to produce FT syngas. The total methane fresh feed is split between the two parallel processes in the appropriate fraction so as to produce the desired H₂/CO ratio in the mixed syngas stream from the process.Both the SMR and DMR reactions are highly endothermic and the reactors are fired furnaces with combustion of fuel providing the endothermic heat of the reactions. Reactor exit temperatures are controlled by manipulating the flowrates of fuel to each furnace, with combustion air ratioed to the fuel. Dynamic reactor models assume tubular SMR and DMR reactors in which heat fluxes are determined by the heat generated in their associated fuel/air combustion reactors.The plantwide control structure effectively handles large 20% disturbances in throughput and large setpoint changes in the desired H₂/CO ratio (1.7–2.3).     

Inventory and flow control of the IGCC process with CO2 recycles

We present control strategies for an Integrated Gasification Combined Cycle (IGCC) power plant with CO₂ recycles. One recycle allows for composition control and is useful when the side objective is to produce synthesis gas for chemicals. The second recycle enables temperature control in the gas turbine by using CO₂ as a diluent. The main advantages of the second recycle are that NO_x is not produced and that CO₂/H₂O separation is significantly easier than CO₂/N₂ separation, which reduces cost if the CO₂ is to be sequestered. Models and control systems are developed using process network theory. We introduce a novel method for controlling quality variables and functions of inventories. Dynamic simulations using MATLAB/Simulink models show the response to step changes in setpoints and disturbances. The inventory control method is derived from conservation laws and the second law and it is applicable to process system models of any degree of complexity. A steady-state sensitivity analysis is performed, examining the effect of changing the temperature and C:O ratio within the gasifier on the power production.     

A global perspective of atmospheric carbon dioxide concentrations

A high-resolution (7 km) non-hydrostatic global mesoscale simulation using the Goddard Earth Observing System (GEOS-5) model is used to visualize the flow and fluxes of carbon dioxide throughout the year. Carbon dioxide (CO₂) is the most important greenhouse gas affected by human activity. About half of the CO₂ emitted from fossil fuel combustion remains in the atmosphere, contributing to rising temperatures, while the other half is absorbed by natural land and ocean carbon reservoirs. Despite the importance of CO₂, many questions remain regarding the processes that control these fluxes and how they may change in response to a changing climate. This visualization shows how column CO₂ mixing ratios are strongly affected by local emissions and large-scale weather systems. In order to fully understand carbon flux processes, observations and atmospheric models must work closely together to determine when and where observed CO₂ came from. Together, the combination of high-resolution data and models will guide climate models towards more reliable predictions of future conditions.     

NOX selective catalytic reduction control based on simple models

In the paper, a new approach to the control of the selective catalytic reduction process of NO_X is presented. The reduction process can be efficiently controlled using a combination of feed-forward and feed-back control structures. However, this approach requires expensive measurement equipment. It is shown that measurement of nitric oxide concentration at the input of the catalytic converter and measurement of the flue gas flow rate can be successfully substituted by corresponding “software sensors”. The software sensors are based on simple mathematical models and on measurements of excess oxygen concentration in flue gas and the fuel flow rate which are usually parts of already available standard combustion control system equipment. In the paper the complete derivation of the required mathematical models is given, and the proposed new control structure is described. The structure is tested using simulation and implemented on an industrial pilot plant.     

A six-wafer combustion system for a silicon micro gas turbineengine

As part of a program to develop a micro gas turbine engine capable of producing 10-50 W of electrical power in a package less than one cubic centimeter in volume, we present the design, fabrication, packaging, and experimental test results for the 6-wafer combustion system for a silicon microengine. Comprising the main nonrotating functional components of the engine, the device described measures 2.1 cm×2.1 cm×0.38 cm and is largely fabricated by deep reactive ion etching through a total thickness of 3800 μm. Complete with a set of fuel plenums, pressure ports, fuel injectors, igniters, fluidic interconnects, and compressor and turbine static airfoils, this structure is the first demonstration of the complete hot flow path of a multilevel micro gas turbine engine. The 0.195 cm³ combustion chamber is shown to sustain a stable hydrogen flame over a range of operating mass flows and fuel-air mixture ratios and to produce exit gas temperatures in excess of 1600 K. It also serves as the first experimental demonstration of stable hydrocarbon microcombustion within the structural constraints of silicon. Combined with longevity tests at elevated temperatures for tens of hours, these results demonstrate the viability of a silicon-based combustion system for micro heat engine applications     

Variable‐Structure Control with Complementarity‐Inputs for a Lean‐Burn IC Engine of a Series Hybrid Vehicle

This paper presents a robust controller for an internal combustion (IC) engine, as the first stage of a project to develop a hybrid light urban vehicle, running on ethanol in lean burn. In particular, this work focuses on the design of a sliding mode control for an IC engine of a series hybrid power train. The controller must allow for optimal speed regulation and high fuel efficiency. To attain the latter, a complementary operation mode is proposed for the system inputs. Simulation results are presented and discussed showing the viability and advantages of the control strategy employed.     

Analysis of data for the carbon dioxide capture domain

To tackle the global concern for adverse impact of greenhouse gas (GHG) emissions, the post combustion carbon dioxide (CO₂) capture technology is commonly adopted for reducing industrial CO₂ emissions, for example, from power generation plants. The research on post combustion CO₂ capture has been ongoing in the last two decade, and its primary objective is to improve efficiency of the CO₂ capture process while reducing specific operating problems such as solvent degradation and corrosion. This objective requires a good understanding of the intricate relationships among parameters involved in the CO₂ capture process. From a review of the relevant literature, we observed that the most significant parameters influencing the CO₂ production rate include: heat duty, circulation rate of the solvent, CO₂ lean loading, and solvent concentration. To study the nature of relationships among the key parameters, we conducted data modeling and analysis based on the amine-based post combustion CO₂ capture process at the International Test Centre for Carbon Dioxide Capture (ITC) located in Regina, Saskatchewan of Canada. In our study, the experimental data collected from ITC from year 2003 to 2006 were analyzed using the combined approach of neural network modeling and sensitivity analysis. The neural network was trained for modeling the relationships among parameters, and the sensitivity analysis method illustrated the order of significance among the parameters. The modeling results were validated by the process experts. This paper describes the procedure of our work, and discusses the results of the analysis.     

基于PMP算法的HEV能量优化控制策略

针对常用混合动力汽车（Hybrid electric vehicle,HEV）中锂离子电池在功率波动较大时难以满足需求,以及单个驱动周期内HEV燃油能耗大且能量不能很好回收等问题,研究采用锂离子电池和超级电容器混合储能系统（Lithium-ion battery and super-capacitor hybrid energy storage system,Li-SC HESS）与内燃机共同驱动HEV运行.结合比例积分粒子群优化算法（Particle swarm optimization-proportion integration,PSO-PI）控制器和Li-SC HESS内部功率限制管理办法,提出一种改进的基于庞特里亚金极小值原理（Pontryagin's minimum principle,PMP）算法的HEV能量优化控制策略,通过ADVISOR软件建立HEV整车仿真模型,验证该方法的有效性与可行性.仿真结果表明,该能量优化控制策略提高了HEV跟踪整车燃油能耗最小轨迹的实时性,节能减排比改进前提高了1.6%~2%,功率波动时减少了锂离子电池的出力,进而改善了混合储能系统性能,对电动汽车关键技术的后续研究意义重大.     

Hardware-in-the-loop simulation for the design and verification of the control system of a series–parallel hybrid electric city-bus

Hybrid electric buses have been a promising technology to dramatically lower fuel consumption and carbon dioxide (CO₂) emission, while energy management strategy (EMS) is a critical technology to the improvements in fuel economy for hybrid electric vehicles (HEVs). In this paper, a suboptimal EMS is developed for the real-time control of a series–parallel hybrid electric bus. It is then investigated and verified in a hardware-in-the-loop (HIL) simulation system constructed on PT-LABCAR, a commercial real-time simulator. First, an optimal EMS is obtained via iterative dynamic programming (IDP) by defining a cost function over a specific drive cycle to minimize fuel consumption, as well as to achieve zero battery state-of-charge (SOC) change and to avoid frequent clutch operation. The IDP method can lower the computational burden and improve the accuracy. Second, the suboptimal EMS for real-time control is developed by constructing an Elman neural network (NN) based on the aforementioned optimal EMS, so the real-time suboptimal EMS can be used in the vehicle control unit (VCU) of the hybrid bus. The real VCU is investigated and verified utilizing a HIL simulator in a virtual forward-facing HEV environment consisting of vehicle, driver and driving environment. The simulation results demonstrate that the proposed real-time suboptimal EMS by the neural network can coordinate the overall hybrid powertrain of the hybrid bus to optimize fuel economy over different drive cycles, and the given drive cycles can be tracked while sustaining the battery SOC level.     

Energy management strategies for parallel hybrid vehicles using fuzzy logic

This paper presents a fuzzy-logic-based energy management and power control strategy for parallel hybrid vehicles (PHV). The main objective is to optimize the fuel economy of the PHV, by optimizing the operational efficiency of all its components. The controller optimizes the power output of the electric motor/generator and the internal combustion engine by using vehicle speed, driver commands from accelerator and braking pedals, state of charge (SOC) of the battery, and the electric motor/generator speed. Separate controllers optimize braking and gear shifting. Simulation results show potential fuel economy improvement relative to other strategies that only maximize the efficiency of the combustion engine.     

Efficient energy management of CO2 capture plant using control-based optimization approach under plant and market uncertainties

This paper employs a control-based optimization algorithm encompassing of an intelligence model predictive control (MPC) scheme and mixed integer non-linear programming (MINLP) for coal-fired power plant retrofitted with flexible solvent-based post combustion CO₂ capture (PCC) plant (integrated plant). The agility and robustness of the developed control algorithm (MPC) is demonstrated through the control response time and efficiency of energy requirement including the financial and operational benefits of the plant subjected to plant and market uncertainties. While, the MINLP is utilized to forecast plant operational modes by ensuring the operational fidelity of integrated plant. This involves utilization of historical (2011) and forecast (2020) market conditions (electricity tariff and carbon price) subject to maximum plant net operating revenue. The outcomes show that the future power plant will operate in mixed operation modes, for instance in unit turndown and load following modes, which contribute to a minimum capture energy penalty at 3.13 MJ_th/tonne CO₂. Moreover, under the same year (2020), MPC exhibits superior control performance by satisfactorily obtain 94% actual CO₂ capture from the ideal cumulative CO₂ capture. Additionally, the integrated plant is capable to resume approximately 96% actual revenue from the ideal net operating revenue projected by the control-based optimization algorithm. The algorithm demonstrates that the installation of control system package (MPC) into the flexible PCC plant associated with coal-power generator could contribute to efficient energy management subjects to unprecedented uncertainties.     

Rapid Load Following of an SOFC Power System via Stable Fuzzy Predictive Tracking Controller

The solid oxide fuel cell (SOFC) is widely accepted for clean and distributed power generation use, but critical operation problems often occur when the stand-alone fuel cell is directly connected to the electricity grid or the dc electric user. In order to address these problems, in this paper, a data-driven fuzzy modeling method is employed to identify the dynamic model of an integrated SOFC/capacitor system. A novel offset-free input-to-state stable fuzzy predictive controller is developed based on the obtained fuzzy model. Both the rapid power load following and safe SOFC operation requirements are taken into account in the design of the closed-loop control system. Simulations are also given to demonstrate the load following control performance of the proposed fuzzy predictive control strategy for the SOFC/capacitor power system.     

Metallo-porphyrin zinc as gas sensitive material for colorimetric gas sensors on planar optical waveguides

The presented work focuses on the investigations of a metallo-porphyrin and its gasochromic behavior to different gases. Gasochromic materials change their color while they are exposed to a certain gas. So they offer the possibility to develop highly selective chemical gas sensors and gas sensing systems. The focus of this work is the characterization of the metallo-porphyrin 5, 10, 15, 20-tetraphenylporphyrin-zinc (ZnTPP). Nonetheless, there is a wide range of other possible metallo-porphyrins. When embedded into a polymeric matrix (PVC) a color change to the toxic gas NO₂ can be detected. To develop a stand-alone gas sensor, the porphyrin/PVC matrix is deposited onto a planar optical waveguide. The color change of the porphyrin dye can be detected in the evanescent field of the optical waveguide. Therefore, the light of a high power LED is coupled into the waveguide. The color change of the porphyrin is detectable with photodiodes as a variation of the out-coupled light intensity. The sensor shows no unwished sensitivities to CO₂ and CO and only low to NH₃. NO₂ is detectable with a resolution of 1?ppm.     

并联式混合动力在金枪鱼钓船上的应用研究

与传统金枪鱼钓船相比,混合动力推进的金枪鱼钓船具有燃油消耗少、污染小等优点.针对延绳钓金枪鱼钓船,设计了并联式混合动力驱动系统.为满足渔船的不同动力需求,通过模糊控制策略合理控制分配动力的输出.通过Matlab/Simulink的仿真研究,金枪鱼钓船的推进效率和燃油经济性均得到提升,有效地验证了混合动力系统和模糊逻辑控制策略的可行性.     

APU过滤系统在烧结脱硫中的研究与应用

莱钢烧结烟气脱硫过滤系统采用微孔过滤技术,该技术是一个专为高含尘和微米级含尘颗粒除尘设计的自动化系统,根据过滤的生产工艺完成对各设备的操作,单机起动和停止,联动和连锁控制,运行周期的设定,在触摸屏上解除连锁,即可完成单机的操作,打到连锁运行模式,过滤各设备就可自动运行.     

Influence of combustion parameters on NOx production in an industrial boiler

NO_x formation during the combustion process occurs mainly through the oxidation of nitrogen in the combustion air (thermal NO_x) and through oxidation of nitrogen with the fuel (prompt NO_x). The present study aims to investigate numerically the problem of NO_x pollution using a model furnace of an industrial boiler utilizing fuel gas. The importance of this problem is mainly due to its relation to the pollutants produced by large boiler furnaces used widely in thermal industrial plants. Governing conservation equations of mass, momentum and energy, and equations representing the transport of species concentrations, turbulence, combustion and radiation modeling in addition to NO modeling equations were solved together to present temperature and NO distribution inside the radiation and convection sections of the boiler. The boiler under investigation is a 160 MW, water-tube boiler, gas fired with natural gas and having two vertically aligned burners.The simulation study provided the NO distribution in the combustion chamber and in the exhaust gas at various operating conditions of fuel to air ratio with varying either the fuel or air mass flow rate, inlet air temperature and combustion primary air swirl angle. In particular, the simulation provided more insight on the correlation between the maximum furnace temperature and furnace average temperatures and the thermal NO concentration. The results have shown that the furnace average temperature and NO concentration decrease as the excess air factor λ increases for a given air mass flow rate. When considering a fixed value of mass flow rate of fuel, the results show that increasing λ results in a maximum value of thermal NO concentration at the exit of the boiler at λ = 1.2. As the combustion air temperature increases, furnace temperature increases and the thermal NO concentration increases sharply. The results also show that NO concentration at exit of the boiler exhibits a minimum value at around swirl angle of 45°.     

Distributed plantwide control based on differential dissipativity

Modern chemical plants are becoming very complex, often consisting of a number of nonlinear process units (subsystems) with strong interactions due to material recycle and energy integration. The operation setpoint may need to be adjusted from time to time based on the market demand. To address the aforementioned challenges, a plantwide distributed nonlinear control scheme based on differential dissipativity is proposed in this paper, which can ensure plantwide incremental exponential stability and achieve bounded incremental L₂ gain performance. As a non‐unique property, the differential dissipativity of individual subsystem is shaped by a setpoint‐independent control structure – differential state feedback control. The dissipativity properties of subsystems and individual controllers are determined simultaneously as a large‐scale feasibility problem to ensure the plantwide stability and performance. It is converted into an LMI condition for plantwide supply rate planning and small‐scale sum‐of‐squares programming problems for individual subsystem dissipativity shaping, by using the alternating direction method of multipliers method. The proposed approach is illustrated using a chemical reactor network with a recycle stream. Copyright © 2016 John Wiley & Sons, Ltd.     

Design, implementation, and experimental validation of optimal power split control for hybrid electric trucks

Hybrid electric vehicles require an algorithm that controls the power split between the internal combustion engine and electric machine(s), and the opening and closing of the clutch. Optimal control theory is applied to derive a methodology for a real-time optimal-control-based power split algorithm. The presented strategy is adaptive for vehicle mass and road elevation, and is implemented on a standard Electronic Control Unit of a parallel hybrid electric truck. The implemented strategy is experimentally validated on a chassis dynamo meter. The fuel consumption is measured on 12 different trajectories and compared with a heuristic and a non-hybrid strategy. The optimal control strategy has a fuel consumption lower (up to 3%) than the heuristic strategy on all trajectories that are evaluated, except one. Compared to the non-hybrid strategy the fuel consumption reduction ranged from 7% to 16%.     

Control and real-time optimization of an automotive hybrid fuel cell power system

A real-time optimization method is used to find the point of maximum fuel efficiency of a hybrid fuel cell power system, in an automotive application. The controller performs as the master control in cascade with lower level controls. The lower level controls distribute the power between the ultra-capacitor and the fuel cell, during transients, to find the optimum operating point of the power system. The ultra-capacitor is used to protect fuel cell health and improve phase characteristics of the system. In simulations, the controller is able to find the optimum operating point for the hybrid system without requiring previous knowledge of the system dynamics or explicit representation of the optimization function.     

基于LabVIEW的燃料电池电源监控系统设计

本文介绍了LabVIEW串行通信在燃料电池混合电源监控系统中的应用。监控系统通过串口接收混合电源系统采集到的系统运行参数,向混合电源系统发送控制指令,实现燃料电池混合电源硬件故障诊断、实时在线监控,以图形化的方式动态显示燃料电池混合电源系统的工作状态。简要介绍了监控系统的硬件构成,详细说明了监控软件开发流程。该监控系统效率高、功能强、界面友好、操作简单,具有良好的可移植性和可扩展性。