The load rejection transient process of bulb turbine units is critical to safety of hydropower stations,and determining appropriate closing laws of guide vanes(GVs)and runner blades(RBs)for this process is of signific...The load rejection transient process of bulb turbine units is critical to safety of hydropower stations,and determining appropriate closing laws of guide vanes(GVs)and runner blades(RBs)for this process is of significance.In this study,we proposed a procedure to optimize the co-closing law of GVs and RBs by using computational fluid dynamics(CFD),combined with the design of experiment(DOE)method,approximation model,and genetic optimization algorithm.The sensitivity of closing law parameters on the histories of head,speed,and thrust was analyzed,and a two-stage GVs’closing law associating with a linear RBs’closing law was proposed.The results show that GVs dominate the transient characteristics by controlling the change of discharge.Speeding GVs’first-stage closing speed while shortening first-stage closing time can not only significantly reduce the maximum rotational speed but also suppress the water hammer pressure;slowing GVs’second-stage closing speed is conducive to controlling the maximum reverse axial force.RBs directly affect the runner force.Slowing RBs’closing speed can further reduce the rotational speed and the maximum reverse axial force.The safety margin of each control parameter,flow patterns,and pressure pulsations of a practical hydropower station were all improved after optimization,demonstrating the effectiveness of this method.展开更多
为快速评价增压器瞬态响应性,以汽油发动机的电磁阀气动式旁通控制的涡轮增压器为例,从发动机标定参数、外围相关零部件及装配、增压器运动机构迟滞三方面分析影响涡轮增压器瞬态响应的主要因素,提出转矩斜率台架快速评价方法。结果表明...为快速评价增压器瞬态响应性,以汽油发动机的电磁阀气动式旁通控制的涡轮增压器为例,从发动机标定参数、外围相关零部件及装配、增压器运动机构迟滞三方面分析影响涡轮增压器瞬态响应的主要因素,提出转矩斜率台架快速评价方法。结果表明:采用比例积分微分(proportional integral differential,PID)预控策略,电磁阀占空比偏置为2.5%~5.0%对增压预控的结果影响较大;增压系统积分时间常数偏差系数大于0,增压压力有欠调趋势;增压系统积分时间常数小于0,增压压力有超调趋势;废气旁通阀关闭裕度比较适宜的区域为-0.05~0.20 mm;转矩斜率方法操作性强,可在发动机台架上快速评价增压器瞬态响应性能。展开更多
In the synthesis of the control algorithm for complex systems, we are often faced with imprecise or unknown mathematical models of the dynamical systems, or even with problems in finding a mathematical model of the sy...In the synthesis of the control algorithm for complex systems, we are often faced with imprecise or unknown mathematical models of the dynamical systems, or even with problems in finding a mathematical model of the system in the open loop. To tackle these difficulties, an approach of data-driven model identification and control algorithm design based on the maximum stability degree criterion is proposed in this paper. The data-driven model identification procedure supposes the finding of the mathematical model of the system based on the undamped transient response of the closed-loop system. The system is approximated with the inertial model, where the coefficients are calculated based on the values of the critical transfer coefficient, oscillation amplitude and period of the underdamped response of the closed-loop system. The data driven control design supposes that the tuning parameters of the controller are calculated based on the parameters obtained from the previous step of system identification and there are presented the expressions for the calculation of the tuning parameters. The obtained results of data-driven model identification and algorithm for synthesis the controller were verified by computer simulation.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant Nos.51839008,51909226).
文摘The load rejection transient process of bulb turbine units is critical to safety of hydropower stations,and determining appropriate closing laws of guide vanes(GVs)and runner blades(RBs)for this process is of significance.In this study,we proposed a procedure to optimize the co-closing law of GVs and RBs by using computational fluid dynamics(CFD),combined with the design of experiment(DOE)method,approximation model,and genetic optimization algorithm.The sensitivity of closing law parameters on the histories of head,speed,and thrust was analyzed,and a two-stage GVs’closing law associating with a linear RBs’closing law was proposed.The results show that GVs dominate the transient characteristics by controlling the change of discharge.Speeding GVs’first-stage closing speed while shortening first-stage closing time can not only significantly reduce the maximum rotational speed but also suppress the water hammer pressure;slowing GVs’second-stage closing speed is conducive to controlling the maximum reverse axial force.RBs directly affect the runner force.Slowing RBs’closing speed can further reduce the rotational speed and the maximum reverse axial force.The safety margin of each control parameter,flow patterns,and pressure pulsations of a practical hydropower station were all improved after optimization,demonstrating the effectiveness of this method.
文摘为快速评价增压器瞬态响应性,以汽油发动机的电磁阀气动式旁通控制的涡轮增压器为例,从发动机标定参数、外围相关零部件及装配、增压器运动机构迟滞三方面分析影响涡轮增压器瞬态响应的主要因素,提出转矩斜率台架快速评价方法。结果表明:采用比例积分微分(proportional integral differential,PID)预控策略,电磁阀占空比偏置为2.5%~5.0%对增压预控的结果影响较大;增压系统积分时间常数偏差系数大于0,增压压力有欠调趋势;增压系统积分时间常数小于0,增压压力有超调趋势;废气旁通阀关闭裕度比较适宜的区域为-0.05~0.20 mm;转矩斜率方法操作性强,可在发动机台架上快速评价增压器瞬态响应性能。
文摘In the synthesis of the control algorithm for complex systems, we are often faced with imprecise or unknown mathematical models of the dynamical systems, or even with problems in finding a mathematical model of the system in the open loop. To tackle these difficulties, an approach of data-driven model identification and control algorithm design based on the maximum stability degree criterion is proposed in this paper. The data-driven model identification procedure supposes the finding of the mathematical model of the system based on the undamped transient response of the closed-loop system. The system is approximated with the inertial model, where the coefficients are calculated based on the values of the critical transfer coefficient, oscillation amplitude and period of the underdamped response of the closed-loop system. The data driven control design supposes that the tuning parameters of the controller are calculated based on the parameters obtained from the previous step of system identification and there are presented the expressions for the calculation of the tuning parameters. The obtained results of data-driven model identification and algorithm for synthesis the controller were verified by computer simulation.
