功率量化固体氧化物燃料电池混合动力系统控制策略:在移动机器人中的应用

SAE International Journal of Alternative Powertrains Pub Date : 2016-04-05 DOI:10.4271/2016-01-0317

Yuan-zhan Wang, Jason B. Siegel, A. Stefanopoulou

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引用次数: 5

摘要

本文研究了用于履带式移动机器人的丙烷驱动固体氧化物燃料电池(SOFC)与锂离子电池混合的量化功率水平调度(包括部分负载运行和启动/关闭周期)。军方要求安静运行和长时间任务，但由于能量密度低，单独使用电池或由于噪音而使用内燃机无法满足这些要求。为了满足这一需求，我们考虑在几个离散功率水平下工作的SOFC，这样可以实现最大的系统效率。燃油效率在瞬变过程中下降，由此产生的热梯度导致堆的应力和退化;因此，开关功率水平应最小化。多余的能量被用来给电池充电，但是当它充满电时，SOFC应该关闭以节省燃料。然而，启动和关闭阶段会消耗电池和燃料能量，并导致堆栈退化，因此应该尽可能少地安排。利用电池和SOFC的简单模型，采用动态规划方法对最优调度策略进行评估。代表性周期是由对特定任务的测量功率数据的随机抽样产生的。最后，考虑电池退化、燃油效率和设计鲁棒性，建立了基于规则的控制策略，并与最优控制策略进行了比较。应用于军用履带式机器人的监视作为一个例子，使用功率配置文件从仪器PackBot;然而，该方法可以广泛应用于具有较大开/关罚金的交通混合动力系统。引用本文:Wang, Y.， Siegel, J.， and Stefanopoulou, A.，“功率量化固体氧化物燃料电池混合动力系统的控制策略:在移动机器人中的应用”，SAE Int。能源工程学报，5(1):2016,doi:10.4271/2016-01-0317。版权所有©2016 SAE International doi:10.4271/2016-01-0317 saealtpow.saejournals.org 58密歇根大学下载自SAE International, 2017年11月8日(星期三)

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Control Strategies for Power Quantized Solid Oxide Fuel Cell Hybrid Powertrains: In Mobile Robot Applications

This paper addresses scheduling of quantized power levels (including part load operation and startup/shutdown periods) for a propane powered solid oxide fuel cell (SOFC) hybridized with a lithium-ion battery for a tracked mobile robot. The military requires silent operation and long duration missions, which cannot be met by batteries alone due to low energy density or with combustion engines due to noise. To meet this need we consider an SOFC operated at a few discrete power levels where maximum system efficiency can be achieved. The fuel efficiency decreases during transients and resulting thermal gradients lead to stress and degradation of the stack; therefore switching power levels should be minimized. Excess generated energy is used to charge the battery, but when it’s fully charged the SOFC should be turned off to conserve fuel. However, startup and shutdown phases consume both battery and fuel energy and induce stack degradation, and therefore should be scheduled as infrequently as possible. Simple models of the battery and SOFC are used to evaluate the optimal scheduling strategy using Dynamic Programming. Representative cycles are generated from random sampling of measured power data for specific tasks. Finally a rule-based control strategy is developed and compared with the optimal one, considering battery degradation, fuel efficiency as well as design robustness. The application to military tracked robots for surveillance is considered as an example using power profiles from an instrumented PackBot; however the methodology can be applied broadly to hybrid power systems for transportation which have large turn on/off penalties. CITATION: Wang, Y., Siegel, J., and Stefanopoulou, A., "Control Strategies for Power Quantized Solid Oxide Fuel Cell Hybrid Powertrains: In Mobile Robot Applications," SAE Int. J. Alt. Power. 5(1):2016, doi:10.4271/2016-01-0317. 2016-01-0317 Published 04/05/2016 Copyright © 2016 SAE International doi:10.4271/2016-01-0317 saealtpow.saejournals.org 58 Downloaded from SAE International by University of Michigan, Wednesday, November 08, 2017

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来源期刊

SAE International Journal of Alternative Powertrains TRANSPORTATION SCIENCE & TECHNOLOGY-

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期刊介绍： The SAE International Journal of Alternative Powertrains provides a forum for peer-reviewed scholarly publication of original research and review papers that address challenges and present opportunities in alternative and electric powertrains and propulsion technology. The Journal strives to facilitate discussion between researchers, engineers, academic faculty and students, and industry practitioners working with systems as well as components, and the technological aspects and functions of powertrains and propulsion systems alternative to the traditional combination of internal combustion engine and mechanical transmission. The editorial scope of the Journal includes all technical aspects of alternative propulsion technologies, including, but not limited to, electric drives and electromobility systems, hybrid technology, battery and super-capacitor technology, power electronics, hydraulic drives, energy storage systems for automotive applications, fuel cell technology, and charging and smart grid infrastructures.