Control Algorithm of Fuel Cell and Batteries for Distributed Generation System

This paper intends to propose a novel control algorithm for utilizing a polymer electrolyte membrane fuel cell (PEMFC) as a main power source and batteries as a complementary source, for hybrid power sources for distributed generation system, particularly for future electric vehicle applications. The control, which takes into account the slow dynamics of a fuel cell (FC) in order to avoid fuel (hydrogen and air) starvation problems, is obviously simpler than state machines used for hybrid source control. The control strategy lies in using an FC for supplying energy to battery and load at the dc bus. The structure is an FC current, battery current, and battery state-of-charge (SOC) cascade control. To validate the proposed principle, a hardware system is realized by analogical circuits for the FC current loop and numerical calculation (dSPACE) for the battery current and SOC loops. Experimental results with small-scale devices (a 500 W PEM FC and 33 Ah, 48 V lead-acid battery bank) illustrate the excellent control scheme during motor drive cycles.     

A coupled power-voltage equilibrium strategy based on droop control for fuel cell/battery/supercapacitor hybrid tramway

In order to improve the robustness of the energy management system (EMS) and avoid the influence of demand power on the design of EMS, a coupled power-voltage equilibrium strategy based on droop control (CPVE-DC) is proposed in this paper. Making use of the principal that the DC bus can directly reflect the changes of load power, the proposed strategy couples DC bus voltage with output powers through droop control to achieve self-equilibrium. The proposed EMS is applied into a hybrid tramway model configured with multiple proton exchange membrane fuel cell (PEMFC) systems, batteries and super capacitors (SCs). FC systems and SC systems are responsible for satisfying most of the demand power, therefore the CPVE-DC strategy generates FCs and SCs reference power through power-voltage droop control on the primary control. Then batteries supplement the rest part of load power and generate DC bus voltage reference value of the next sampling time. With the gambling between output power and DC bus voltage, the hybrid system achieves self-equilibrium and steps into steady operation by selecting appropriate droop coefficients. Then the secondary control of the proposed strategy allocates power between every single unit. In addition, a penalty coefficient is introduced to balance SOC of SCs. The proposed strategy is tested under a real drive cycle LF-LRV on RT-LAB platform. The results demonstrate that the proposed strategy can achieve self-equilibrium and is effective to allocate demand power among these power sources,achieve active control for the range of DC bus voltage and SOC consensus of SCs as well. In addition, some faults are simulated to verify the robustness of the proposed strategy and it turns out that the CPVE-DC strategy possesses higher robustness. Finally, the CPVE-DC strategy is compared with equivalent consumption minimization strategy (ECMS) and the results shows that the proposed strategy is able to get higher average efficiency and lower equivalent fuel consumption.     

A power allocation strategy of a hybrid energy storage system for a PV grid-connected system

针对光伏并网系统中光伏微电源出力的波动性和间歇性,将蓄电池和超级电容器构成的混合储能系统HESS（hybrid energy storage system）应用到光伏并网系统中可以实现光伏功率平滑、能量平衡以及提高并网电能质量。在同时考虑蓄电池的功率上限和超级电容的荷电状态（SOC）的情况下,对混合储能系统提出了基于超级电容SOC的功率分配策略;该策略以超级电容的SOC和功率分配单元的输出功率作为参考值,对混合储能系统充放电过程进行设计。超级电容和蓄电池以Bi-direction DC/DC变换器与500 V直流母线连接,其中超级电容通过双闭环控制策略对直流母线电压进行控制。仿真结果表明,所提功率分配策略能对混合储能系统功率合理分配,而且实现了单位功率因数并网,稳定了直流母线电压。     

Lead carbon ultrabatteries for energy storage

储能技术在太阳能、风能等可再生能源发电、智能电网/微网建设等方面有着广阔的应用前景。铅酸电池具有价格低、较高电压、性能稳定、宽工作温度范围等优势,占据着固定储能市场的主导地位。但在智能电网、混合动力车的实际应用中,电池必须在不同的充电状态下操作,特别是在高倍率部分荷电模式。在这种操作模式下,硫酸盐沉积物积聚在电极表面,限制了铅酸电池的容量和循环寿命。铅碳电池是由铅酸电池和超级电容器组合形成的新型储能装置,它抑制了放电过程中负极板表面硫酸盐的不均匀分布和充电时较早的析氢现象,具有铅酸电池高能量和超级电容器高功率的优点,在部分荷电态大功率充放电状态具有较高的循环寿命,适合高倍率循环和瞬间脉冲放电等工作状态。本文介绍了铅碳电池的基本概念及原理,并对铅碳电池储能技术的发展历程和现状进行了总结。     

Study of the “coup de fouet” of lead-acid cells as a function of their state-of-charge and state-of-health

This paper shows some new results concerning the influence of operating conditions on the phenomenon known as “coup de fouet”, a voltage drop which occurs at the beginning of the discharge of lead-acid batteries (LABs) previously fully charged. Even if this phenomenon is often suggested for diagnosing the state-of-charge (SOC) and the state-of-health (SOH) of LABs, it remains badly understood. Furthermore, this study deals with other transient voltage responses of LABs to galvanostatic polarisations that depend on their SOC, either on discharge or on charge. A special attention is paid to a phenomenon occurring at the beginning of the charge of these batteries after a full discharge, and which can be compared to the “coup de fouet” on many aspects. Without giving a final answer concerning the origin of these two phenomena, our results present some contradictions with the explanation generally accepted today. It is, also, shown that the study of these phenomena constitutes an original means to investigate the full-charge and full-discharge conditions, together with other characterization methods like impedance spectroscopy. On the other hand, results presented show that it is not possible to connect the “coup de fouet” parameters to the battery capacity without taking care of the high-SOC level, the rest time preceding the discharge, and the depth of the latter discharge, which compromises the reliability of this method suggested in several papers and patents, in particular in applications with irregular cyclings.     

State-of-charge prediction of batteries and battery-supercapacitor hybrids using artificial neural networks

The state-of-charge (SOC) of batteries and battery-supercapacitor hybrid systems is predicted using artificial neural networks (ANNs). Our technique is able to predict the SOC of energy storage devices based on a short initial segment (less than 4% of the average lifetime) of the discharge curve. The prediction shows good performance with a correlation coefficient above 0.95. We are able to improve the prediction further by considering readily available measurements of the device and usage. The prediction is further shown to be resilient to changes in operating conditions or physical structure of the devices.     

混合动力摩托车动力电池的监测系统研究

环境和能源问题要求未来的汽车提高效率、降低污染,辅助混合动力电动汽车将成为主要的发展方向。本文以混合动力摩托车为平台,研究设计了动力电池的监测系统,该系统可实时对每块电池的电压、电流、温度进行检测,并估计电池的荷电状态,并可对电池的电压、温度及电池间电压不均衡性进行监测预警,提供能量管理系统的控制参数。     

基于PNGV模型储能锂电池参数辨识及SOC估算研究

锂电池因具有比能量高、循环寿命长、对环境无污染等优点,在储能系统中已逐渐得到应用.准确估算锂电池的荷电状态(SOC)可防止电池过充、过放,保障电池安全、充分地使用.为了精确估算储能锂电池SOC,基于PNGV(partnership for a new generation of vehicles)电池等效模型,利用递推最小二乘法(RLS)对模型参数进行在线辨识和实时修正,增强了系统的适应性.结合安时法、开路电压法和PNGV模型,提出了一种实时在线修正SOC算法.根据实验数据,建立了仿真模型,以验算模型和SOC估算算法的精度.仿真结果表明,PNGV模型能真实地模拟电池特性,且能有效地提高SOC估算精度,适合长时间在线估算储能锂电池的SOC.     

Power management and nonlinear control of a fuel cell–supercapacitor hybrid automotive vehicle with working condition algorithm

This paper deals with the problem of controlling a multi-source system applied in hybrid electrical vehicles. The system consists of a proton exchange membrane fuel cell (PEMFC) and a super capacitor (SC). Fuel cell (FC) provides energy for load as a main power source, and SC helps the system in a load peak or in fast transients. The system is modeled as Port controlled Hamiltonian (PCH), and interconnection and damping assignment passivity based controller (IDA-PBC) is used for a typical hybrid vehicle. The aim is first to support the load power in all circumstances without interruption by combination of FC and SC production, and second to control the DC bus voltage. The purposed system analyzed under standard driving cycle consists of off-load, over-load, and charging conditions of SC. Simulations are accomplished in MATLAB/Simulink software for validation of control strategy and new represented algorithm. The results illustrate that both control method and algorithm can manage power among PEMFC, SC, and the load whereas the DC bus voltage remains near its reference.     

Advanced management strategies for remote-area power-supply systems

An operating strategy based on partial-state-of-charge (PSoC) operation has been developed for a remote-area power-supply (RAPS) system in Peru. The facility will power an entire village and comprises a photovoltaic array, a bank of gel valve-regulated lead-acid (VRLA) batteries, a diesel generator, and a sophisticated control system. The PSoC schedule involves operation below a full state-of-charge (SoC) for 28 days, followed by an equalization charge. The schedule has been evaluated by operating a 24 V battery bank under simulated RAPS conditions in the laboratory. It is found that operation between 58 and 83% SoC causes the negative-plate potentials to move to significantly more negative values during charging as the PSoC duty progresses. This behaviour is undesirable, because it can lead to the activation of a preset limit and a subsequent reduction in system efficiency. Lowering the PSoC window to 47–72% SoC or 40–65% SoC during the 28-day cycle is found to stabilize the negative-plate potentials. The behaviour of the negative plates in gel batteries is very similar to that observed for absorptive glass mat (AGM) designs of VRLA batteries operated in hybrid electric vehicles.     

Non-intrusive measurement of the state-of-charge of lead-acid batteries using wire-wound coils

Non-intrusive monitoring of the state-of-charge (SOC) of lead-acid batteries by the use of wire wound coils is described. Coils were attached to the outside case of the battery, adjacent to the negative end plate, and excited using ac current of frequency in the range of 1–40 kHz. The change in inductance of the coils was monitored during battery cycling, as the metallic content of the electrode changed. Following correction for temperature changes, the technique is capable of estimating the SOC of a battery to an accuracy of ±10%. The inductance profiles that were obtained changed shape as the batteries aged and also with the exciting frequency. The origins of these changes are discussed.     

多输入交错并联Boost变换器功率分配控制策略

针对功率分配底层功能提出一种新型控制策略,该控制策略在传统的双闭环平均电流均流法上加以改进。首先电流内环修改为功率内环,将电压外环的输出除以输入电压再乘以功率分配系数作为新的功率给定值来实现功率分配功能。同时将自抗扰技术应用到电压外环提高母线电压的响应速度。最后基于模块化思想并利用氮化镓功率开关器件,搭建一台三输入交错并联Boost实验样机,其额定功率为1500 W,额定工作频率为500 kHz,峰值效率为98.3%。实验验证结果表明,在相同输入电压或不同输入电压的情况下均能实现功率分配功能,并具有良好的动态响应。     

混合动力船舶超级电容制动能量回馈装置

针对混合动力船舶采用制动电阻吸收制动能量不可避免造成能量浪费的问题,借鉴直流推进系统,采用超级电容储能装置作为能量回馈装置,研究混合动力船舶在典型工况下的制动过程,并对超级电容在制动过程中的控制方法、控制效果进行分析.结果 表明:与制动电阻相比,超级电容制动能量回馈装置不仅能够提升直流母线电压的稳定性,还能有效吸收和储...     

Methods for state-of-charge determination and their applications

State-of-charge (SOC) determination becomes an increasingly important issue in all the applications that include a battery. Former operation strategies made use of voltage limits only to protect the battery against deep discharge and overcharge. Currently, battery operation is changing to what could rather be called battery management than simply protection. For this improved battery control, the battery SOC is a key factor.Much research work has been done in recent years to improve SOC determination. Operational conditions differ for batteries in, for example, photovoltaic applications, (hybrid)-electric vehicles or telecommunications. Hence, a given method for SOC calculation will be more suitable for a certain application than for another. The authors introduce commonly used methods for SOC determination and establish a relationship between the advantages of the different methods and the most common applications. As a main illustration, the analysis of Kalman filter technique for lead-acid battery SOC determination are presented and some results for other calculation methods as well.     

Lead-acid batteries in micro-hybrid applications. Part I. Selected key parameters

Micro-hybrid electric vehicles were launched by BMW in March 2007. These are equipped with brake energy regeneration (BER) and the automatic start and stop function (ASSF) of the internal combustion engine. These functions are based on common 14 V series components and lead-acid (LA) batteries. The novelty is given by the intelligent onboard energy management, which upgrades the conventional electric system to the micro-hybrid power system (MHPS). In part I of this publication the key factors for the operation of LA batteries in the MHPS are discussed. Especially for BER one is high dynamic charge acceptance (DCA) for effective boost charging. Vehicle rest time is identified as a particular negative parameter for DCA. It can be refreshed by regular fully charging at elevated charge voltage. Thus, the batteries have to be outstandingly robust against overcharge and water loss. This can be accomplished for valve-regulated lead-acid (VRLA) batteries at least if they are mounted in the trunk. ASSF goes along with frequent high-rate loads for warm cranking. The internal resistance determines the drop of the power net voltage during cranking and is preferably low for reasons of power net stability even after years of operation. Investigations have to be done with aged 90 Ah VRLA-absorbent glass mat (AGM) batteries. Battery operation at partial state-of-charge gives a higher risk of deep discharging (overdischarging). Subsequent re-charging then is likely to lead to the formation of micro-short circuits in the absorbent glass mat separator.     

可再生能源交流孤网转并网运行中的电压控制策略

柔性直流远距离输送有仅通过直流送出模式和交直流混联送出模式。两种送出模式下,系统的运行点存在较大差异,直接切换会对电网产生较大冲击。文章首先分析了两种送出模式下系统的调压控制特点,指出并网点电压幅值偏差是切换过程的关键点,设计了以可再生能源集群并网点电压偏差最小为主目标,换流站综合无功裕度最大为次目标的柔性切换策略。最后,基于某柔直电网可再生能源送端规划系统进行仿真,验证了所提策略的有效性。     

Design of 48 V automobile start-stop power system based on lithium ion capacitor

在自主开发的锂离子电容器基础上,基于AVL-Cruise建立了48 V启停电源系统汽车模型。结合安时法、开路电压法和扩展卡尔曼滤波法,设计了器件荷电状态（state of charge,SOC）估计模块,实现在线SOC估计。在MATLAB/Simulink中建立基于模糊控制的能量管理模型,实现发动机启停、纯电动驱动起步、制动能量回收以及主动滑行等功能。最后,根据新欧洲驾驶循环（New European Driving Cycle,NEDC）工况对电源系统的SOC以及整车油耗进行评估。研究结果证明了该系统可实现误差10%以内的SOC估计,同时基于锂离子电容器的48 V启停电源系统具有很好燃油经济性。     

Predictive energy management for a wind turbine with hybrid energy storage system

Hybrid energy storage systems (HESSs) help mitigating the fluctuations and variable availability of certain renewable sources, such as wind power, as they can provide support in different time scales. Therefore, regulating their state-of-charge (SOC) becomes crucial to ensure that the hybrid system complies with generation commitments agreed in time-ahead markets despite subsequent unexpected wind speed variations. So far, research has been mainly targeted at avoiding extreme SOC situations in the storage devices, whereas the regulation of this parameter to specific values has often been disregarded. A novel approach is proposed in this work, where model predictive control (MPC) is used to regulate the SOC of a HESS under variable wind and grid demand scenarios. The MPC-based supervisory controller developed for the hybrid system has been implemented and simulated under different situations. This controller monitors the future variation of the SOC with the aim of having the HESS available to develop its assigned functions successfully. The results show that a proper regulation of the SOC in the HESS increases the capacity to manage the active power supplied to the grid by the hybrid system based on wind power, as well as the level of compliance with generation commitments established time ahead.     

Self-learning energy management for plug-in hybrid electric bus considering expert experience and generalization performance

A self-learning energy management is proposed for plug-in hybrid electric bus, by combining Q-Learning (QL) and Pontryagin's minimum principle algorithms. Different from the existing strategies, the expert experience and generalization performance are focused in the proposed strategy. The expert experience is designed as the approximately optimal reference state-of-charge (SOC) trajectories, and the generalization performance is enhanced by a multiply driving cycle training method. In specific, an efficient zone of SOC is firstly designed based on the approximately optimal reference SOC trajectories. Then, the agent of the QL is trained off-line by taking the expert experience as reference SOC trajectories. Finally, an adaptive strategy is proposed based on the well-trained agent. Specially, two different reward functions are defined. That is, the reward function in the off-line training mainly considers the tracking performance between the expert experience and the SOC, while mainly considering the punishment in the adaptive strategy. Simulation results show that the proposed strategy has good generalization performance and can improve the fuel economy by 22.49%, compared to a charge depleting-charge sustaining (CDCS) strategy.