Taking a hydrocarbon zone or a basin group as a unit,this paper analyzed the vertical hydrocarbon generation regularity of onshore and offshore oil and gasfields in China,based on the theory of co-control of source an...Taking a hydrocarbon zone or a basin group as a unit,this paper analyzed the vertical hydrocarbon generation regularity of onshore and offshore oil and gasfields in China,based on the theory of co-control of source and heat.The results demonstrated that the hydrocarbon generation modes of oil and gasfields in China are orderly.First,the hydrocarbon zones in southeastern China offshore area,including the East and South China Sea basins,are dominated by single hydrocarbon generation mode,which displays as either single oil generation in the near shore or single gas generation in the offshore controlled by both source and heat.Second,the eastern hydrocarbon zones,including the Bohai Bay,Songliao and Jianghan basins and the North and South Yellow Sea basins,are dominated by a two-layer hydrocarbon generation mode,which performs as“upper oil and lower gas”.Third,the central hydrocarbon zones,including the Ordos,Sichuan and Chuxiong basins,are also dominated by the“upper oil and lower gas”two-layer hydrocarbon generation mode.In the Ordos Basin,gas is mainly generated in the Triassic,and oil is predominantly generated in the Paleozoic.In the Sichuan Basin,oil was discovered in the Jurassic,and gas was mostly discovered in the Sinian and Triassic.Fourth,the western hydrocarbon zones are dominated by a“sandwich”multi-layer mode,such as the Junggar,Tarim,Qaidam basins.In summary,the theory of co-control of source and heat will be widely applied to oil and gas exploration all over China.Oil targets should be focused on the near shore areas in the southeastern China sea,the upper strata in the eastern and middle hydrocarbon zones,and the Ordovician,Permian and Paleogene strata in the western hydrocarbon zone,while gas targets should be focused on the off-shore areas in the southeastern China sea,the Cambrian,Carboniferous,Jurassic,and Quaternary strata in the western hydrocarbon zone.A pattern of exploring gasfields under or outside oilfields and oilfields under or outside gasfields is presented.Therefore,there is still a great prospect for oil and gas exploration in China.展开更多
精确的轨迹跟踪是智能驾驶汽车实现自主运动控制的关键。针对系统不确定性影响轨迹跟踪控制精度的问题,提出了一种新型鲁棒自适应滑模控制策略。首先,根据车辆运动学原理建立二自由度车辆动力学模型;然后,基于轨迹跟踪误差设计具有自适...精确的轨迹跟踪是智能驾驶汽车实现自主运动控制的关键。针对系统不确定性影响轨迹跟踪控制精度的问题,提出了一种新型鲁棒自适应滑模控制策略。首先,根据车辆运动学原理建立二自由度车辆动力学模型;然后,基于轨迹跟踪误差设计具有自适应性的比例积分微分(proportional integral derivative,PID)型滑模面,通过设计自适应更新律实时在线估计滑模控制增益和系统不确定性的上界,提高了轨迹跟踪控制的精度和鲁棒性。之后,利用粒子群优化算法优化了控制器的控制参数,进一步改善了轨迹跟踪控制性能。最后,在不同路面和车速条件下对所提控制策略进行仿真验证。仿真结果表明,所提控制策略能够保证智能驾驶汽车在系统不确定性影响下跟踪目标轨迹,控制性能优于分数阶PID控制。展开更多
为提升夏季电动汽车驾驶过程中乘员热舒适性与车辆节能续航能力,针对某型电动汽车空调节能制冷控制方法开展了优化研究.根据车辆试验台架建立了AMEsim空调-乘员舱耦合系统,搭建了面向控制的空调-乘员舱系统动态特征预测模型,并结合车速...为提升夏季电动汽车驾驶过程中乘员热舒适性与车辆节能续航能力,针对某型电动汽车空调节能制冷控制方法开展了优化研究.根据车辆试验台架建立了AMEsim空调-乘员舱耦合系统,搭建了面向控制的空调-乘员舱系统动态特征预测模型,并结合车速-制冷能力的耦合关系设计了考虑热舒适的节能模型预测控制器(energy saving model prediction controller,简称MPC-E),最后将Matlab控制模块与AMEsim模型进行了联合仿真.研究表明,搭建的面向控制的预测模型较好地表征了系统动态特征,可作为控制器的内嵌预测模型;相较于传统的比例积分微分(proportional integral derivative,简称PID)控制,MPC-E将空调系统蒸发器风温约束在更合理的范围内,并提供了更佳的乘员舱热舒适性体验,而且实现了12.9%的空调系统总能耗降低.展开更多
基金National Basic Research Program of China(973 Program)“Fundamental research on petroleum resources generation and distribution in deep basins in the South China Sea”(No.2009CB219400)National Science and Technology Major Project“Key technologies of deep sea petroleum exploration”(No.2008ZX05025,2011ZX05025).
文摘Taking a hydrocarbon zone or a basin group as a unit,this paper analyzed the vertical hydrocarbon generation regularity of onshore and offshore oil and gasfields in China,based on the theory of co-control of source and heat.The results demonstrated that the hydrocarbon generation modes of oil and gasfields in China are orderly.First,the hydrocarbon zones in southeastern China offshore area,including the East and South China Sea basins,are dominated by single hydrocarbon generation mode,which displays as either single oil generation in the near shore or single gas generation in the offshore controlled by both source and heat.Second,the eastern hydrocarbon zones,including the Bohai Bay,Songliao and Jianghan basins and the North and South Yellow Sea basins,are dominated by a two-layer hydrocarbon generation mode,which performs as“upper oil and lower gas”.Third,the central hydrocarbon zones,including the Ordos,Sichuan and Chuxiong basins,are also dominated by the“upper oil and lower gas”two-layer hydrocarbon generation mode.In the Ordos Basin,gas is mainly generated in the Triassic,and oil is predominantly generated in the Paleozoic.In the Sichuan Basin,oil was discovered in the Jurassic,and gas was mostly discovered in the Sinian and Triassic.Fourth,the western hydrocarbon zones are dominated by a“sandwich”multi-layer mode,such as the Junggar,Tarim,Qaidam basins.In summary,the theory of co-control of source and heat will be widely applied to oil and gas exploration all over China.Oil targets should be focused on the near shore areas in the southeastern China sea,the upper strata in the eastern and middle hydrocarbon zones,and the Ordovician,Permian and Paleogene strata in the western hydrocarbon zone,while gas targets should be focused on the off-shore areas in the southeastern China sea,the Cambrian,Carboniferous,Jurassic,and Quaternary strata in the western hydrocarbon zone.A pattern of exploring gasfields under or outside oilfields and oilfields under or outside gasfields is presented.Therefore,there is still a great prospect for oil and gas exploration in China.
文摘精确的轨迹跟踪是智能驾驶汽车实现自主运动控制的关键。针对系统不确定性影响轨迹跟踪控制精度的问题,提出了一种新型鲁棒自适应滑模控制策略。首先,根据车辆运动学原理建立二自由度车辆动力学模型;然后,基于轨迹跟踪误差设计具有自适应性的比例积分微分(proportional integral derivative,PID)型滑模面,通过设计自适应更新律实时在线估计滑模控制增益和系统不确定性的上界,提高了轨迹跟踪控制的精度和鲁棒性。之后,利用粒子群优化算法优化了控制器的控制参数,进一步改善了轨迹跟踪控制性能。最后,在不同路面和车速条件下对所提控制策略进行仿真验证。仿真结果表明,所提控制策略能够保证智能驾驶汽车在系统不确定性影响下跟踪目标轨迹,控制性能优于分数阶PID控制。
文摘为提升夏季电动汽车驾驶过程中乘员热舒适性与车辆节能续航能力,针对某型电动汽车空调节能制冷控制方法开展了优化研究.根据车辆试验台架建立了AMEsim空调-乘员舱耦合系统,搭建了面向控制的空调-乘员舱系统动态特征预测模型,并结合车速-制冷能力的耦合关系设计了考虑热舒适的节能模型预测控制器(energy saving model prediction controller,简称MPC-E),最后将Matlab控制模块与AMEsim模型进行了联合仿真.研究表明,搭建的面向控制的预测模型较好地表征了系统动态特征,可作为控制器的内嵌预测模型;相较于传统的比例积分微分(proportional integral derivative,简称PID)控制,MPC-E将空调系统蒸发器风温约束在更合理的范围内,并提供了更佳的乘员舱热舒适性体验,而且实现了12.9%的空调系统总能耗降低.
