Application of new parameterizations of gas transfer velocity and their impact on regional and global marine CO2 budgets

One of the dominant sources of uncertainty in the calculation of air–sea flux of carbon dioxide on a global scale originates from the various parameterizations of the gas transfer velocity, k, that are in use. Whilst it is undisputed that most of these parameterizations have shortcomings and neglect processes which influence air–sea gas exchange and do not scale with wind speed alone, there is no general agreement about their relative accuracy.The most widely used parameterizations are based on non-linear functions of wind speed and, to a lesser extent, on sea surface temperature and salinity. Processes such as surface film damping and whitecapping are known to have an effect on air–sea exchange. More recently published parameterizations use friction velocity, sea surface roughness, and significant wave height. These new parameters can account to some extent for processes such as film damping and whitecapping and could potentially explain the spread of wind-speed based transfer velocities published in the literature.We combine some of the principles of two recently published k parameterizations [Glover, D.M., Frew, N.M., McCue, S.J. and Bock, E.J., 2002. A multiyear time series of global gas transfer velocity from the TOPEX dual frequency, normalized radar backscatter algorithm. In: Donelan, M.A., Drennan, W.M., Saltzman, E.S., and Wanninkhof, R. (Eds.), Gas Transfer at Water Surfaces, Geophys. Monograph 127. AGU,Washington, DC, 325–331; Woolf, D.K., 2005. Parameterization of gas transfer velocities and sea-state dependent wave breaking. Tellus, 57B: 87–94] to calculate k as the sum of a linear function of total mean square slope of the sea surface and a wave breaking parameter. This separates contributions from direct and bubble-mediated gas transfer as suggested by Woolf [Woolf, D.K., 2005. Parameterization of gas transfer velocities and sea-state dependent wave breaking. Tellus, 57B: 87–94] and allows us to quantify contributions from these two processes independently.We then apply our parameterization to a monthly TOPEX altimeter gridded 1.5° × 1.5° data set and compare our results to transfer velocities calculated using the popular wind-based k parameterizations by Wanninkhof [Wanninkhof, R., 1992. Relationship between wind speed and gas exchange over the ocean. J. Geophys. Res., 97: 7373–7382.] and Wanninkhof and McGillis [Wanninkhof, R. and McGillis, W., 1999. A cubic relationship between air−sea CO2 exchange and wind speed. Geophys. Res. Lett., 26(13): 1889–1892]. We show that despite good agreement of the globally averaged transfer velocities, global and regional fluxes differ by up to 100%. These discrepancies are a result of different spatio-temporal distributions of the processes involved in the parameterizations of k, indicating the importance of wave field parameters and a need for further validation.     

船舶蓄电池的使用与维护

阐述电解液溢出对船舶蓄电池的危害,分析引起蓄电池电解液溢出的原因,探寻发生电解液溢出蓄电池的分布规律,针对船舶蓄电池的使用及维护提出建议。     

新加坡电力蓄电池双能源工程车方向选择电路的设计

文章介绍新加坡电力蓄电池双能源工程车的方向选择电路的设计原理,重点阐述了机车重联时,不同编组时的方向控制原理。     

轨道交通车载智能应急电源系统

作为在紧急情况下为轨道交通列车辅助系统供电的应急电源,铅酸或镍铬电池被普遍使用;随着技术的不断发展,锂离子电池的应用也越来越广泛.介绍了GJCL-A型锂离子轨道交通车载智能应急电源系统的组成、工作原理、设计方案及试点应用情况.GJCL-A型锂离子轨道交通车载智能应急电源系统的试验应用结果表明,用于车厢的110V应急供电4 300 s后,其剩余电量仍有40％以上.     

电站蓄电池发生爆炸的原因分析及其预防措施

分析了移动电站蓄电池发生爆炸的原因;阐述了预防蓄电池发生爆炸的措施。     

电动汽车电池架的耐撞性仿真设计与优化

电动汽车发生碰撞时可能诱发一系列由电池系统引起的危害,如对人体的电伤害、电解液泄漏等。合理的电池架设计能够保护电池系统,避免由此带来的危害。用计算机仿真方法对新开发的菱形电动汽车电池架进行耐撞性能的设计与优化,提高了电动汽车的碰撞安全性。     

液冷和冷媒直冷动力电池包冷却性能数值分析

采用数值模拟的研究方法，对比分析了某纯电车型在高速超速以及驱动耐久工况下动力电池包采用液冷和冷媒直冷两种方案的冷却性能，研究结果表明，对于高速超速工况，相对于液冷方案，采用冷媒直冷电池包温度降低了约10%；对于驱动耐久工况，采用冷媒直冷方案电池包温度降低了约 16%，与此同时，电池包均温性也有所改善。在相同工况条件下，动力电池包冷媒直冷的冷却性能优于液冷。     

纯电动汽车动力电池降温性能研究

为了更好地优化纯电动汽车动力电池系统的加热策略,以磷酸铁锂电池包为研究对象,测试其在3种不同环境温度下的电池降温性能,结合实际环境的影响,建立电池降温速率计算模型并通过测试验证。     

电动汽车动力电池低温性能研究与应用

电动汽车锂离子动力电池在低温条件下工作时,电池的内阻明显升高、功率和能量急剧下降,导致整车低温下动力性能不足、续驶里程不足、充电受限等问题。通过试验进行了动力电池的低温特性研究,提出了适合整车低温工作的解决方案,通过实车验证,达到了很好的效果。     

纯电动商用车异质队列的多目标控制

队列行驶的研究能有效解决商用车货运安全、能耗浪费和环境污染等问题,但现有研究多基于单一跟车目标控制的匀质队列,这在货运场景中无法达到很好的控制效果。本文中构造了纯电动异质商用车队列,为其设计了分布式非线性模型预测控制器。根据道路环境信息和车辆跟车、安全、舒适和节能等特性,分别建立了领航车和跟随车的控制器模型,实现异质队列的多目标控制。为验证所提出控制方法的有效性,由5辆动力学特性相异的商用车组成队列,并搭建了控制仿真平台进行Trucksim/Simulink联合仿真。结果表明,本文中提出的控制算法能有效实现异质商用车队列的多目标控制,与PID定速巡航控制相比,能耗可降低5.3%以上。