The authors previous study reported the important role of extratropical intraseasonal oscillation(ISO)on the occurrence of a typical heatwave event over the Yangtze River Valley.Based on the ECMWF subseasonal reforeca...The authors previous study reported the important role of extratropical intraseasonal oscillation(ISO)on the occurrence of a typical heatwave event over the Yangtze River Valley.Based on the ECMWF subseasonal reforecast database,this follow-up study evaluates the extended-range prediction skill of the heatwave event and further unravels the close link between the ISO and extended-range prediction of the event.With a two-week lead time,this heatwave event fails to occur in the reforecast because the predicted surface temperature is signi cantly underesti-mated.More detailed analysis demonstrates that the biases for both the intensity and the location of the warming region are primarily attributable to the inaccurate extratropical intrasea-sonal traveling signals.This work strongly indicates that accurately capturing the extratropical intraseasonal signal from the Eurasian continent is indispensable for extended-range prediction of East Asian extreme heatwave events.展开更多
We examined the characteristic feature and predictability of low frequency variability (LFV) of the atmosphere in the Northern Hemisphere winter (January and February) by using the empirical orthogonal functions (EOFs...We examined the characteristic feature and predictability of low frequency variability (LFV) of the atmosphere in the Northern Hemisphere winter (January and February) by using the empirical orthogonal functions (EOFs) of the geopotential height at 500 hPa. In the discussion, we used the EOFs for geostrophic zonal wind (Uznl) and the height deviation from the zonal mean (Zeddy). The set of EOFs for Uznl and Zeddy was denoted as Uznl-1, Uznl-2, ..., Zeddy-1, Zeddy-2, ..., respectively. We used the data samples of 396 pentads derived from 33 years of NMC, ECMWF and JMA analyses, from January 1963 to 1995. From the calculated scores for Uznl-1, Uznl-2, Zeddy-1, Zeddy-2 and so on we found that Uznl-1 and Zeddy-1 were statistically stable and their scores were more persistent than those of the other EOFs. A close relationship existed between the scores of Uznl-1 and those of Zeddy-1. 30-day forecast experiments were carried out with the medium resolution version of JMA global spectral model for 20 cases in January and February for the period of 1984-1992. Results showed that Zeddy-1 was more predictable than the other EOFs for Zeddy. Considering these results, we argued that prediction of the Zeddy-1 was to be one of the main target of extended-range forecasting.展开更多
Utilizing the Community Atmosphere Model,version 4,the influence of Arctic sea-ice concentration(SIC)on the extended-range prediction of three simulated cold events(CEs)in East Asia is investigated.Numerical results s...Utilizing the Community Atmosphere Model,version 4,the influence of Arctic sea-ice concentration(SIC)on the extended-range prediction of three simulated cold events(CEs)in East Asia is investigated.Numerical results show that the Arctic SIC is crucial for the extended-range prediction of CEs in East Asia.The conditional nonlinear optimal perturbation approach is adopted to identify the optimal Arctic SIC perturbations with the largest influence on CE prediction on the extended-range time scale.It shows that the optimal SIC perturbations are more inclined to weaken the CEs and cause large prediction errors in the fourth pentad,as compared with random SIC perturbations under the same constraint.Further diagnosis reveals that the optimal SIC perturbations first modulate the local temperature through the diabatic process,and then influence the remote temperature by horizontal advection and vertical convection terms.Consequently,the optimal SIC perturbations trigger a warming center in East Asia through the propagation of Rossby wave trains,leading to the largest prediction uncertainty of the CEs in the fourth pentad.These results may provide scientific support for targeted observation of Arctic SIC to improve the extended-range CE prediction skill.展开更多
综合考虑电池和SCR催化器在低温环境下的工作特性,针对低温下温度对Plug-in柴电混合动力汽车性能的影响,提出最短时间控制和燃油消耗最少问题。以SCR起燃温度和电池正常工作温度时间最短为优化目标,以电池温度、电池荷电状态(State of C...综合考虑电池和SCR催化器在低温环境下的工作特性,针对低温下温度对Plug-in柴电混合动力汽车性能的影响,提出最短时间控制和燃油消耗最少问题。以SCR起燃温度和电池正常工作温度时间最短为优化目标,以电池温度、电池荷电状态(State of Charge,SOC)和SCR催化器温度为状态变量,利用极小值原理求得最优控制策略。通过仿真对比规则控制策略,分析了在不同低温条件下基于庞特里亚金极小值原理(Pontryagin’s Minimum Principle,PMP)的最短时间和最少油耗与排放优化控制策略对整车油耗和排放的影响。展开更多
Due to soaring fuel prices and environmental concerns, hybrid electric vehicle(HEV) technology attracts more attentions in last decade. Energy management system, configuration of HEV and traffic conditions are the mai...Due to soaring fuel prices and environmental concerns, hybrid electric vehicle(HEV) technology attracts more attentions in last decade. Energy management system, configuration of HEV and traffic conditions are the main factors which affect HEV's fuel consumption, emission and performance. Therefore, optimal management of the energy components is a key element for the success of a HEV. An optimal energy management system is developed for HEV based on genetic algorithm. Then, different powertrain system component combinations effects are investigated in various driving cycles. HEV simulation results are compared for default rule-based, fuzzy and GA-fuzzy controllers by using ADVISOR. The results indicate the effectiveness of proposed optimal controller over real world driving cycles. Also, an optimal powertrain configuration to improve fuel consumption and emission efficiency is proposed for each driving condition. Finally, the effects of batteries in initial state of charge and hybridization factor are investigated on HEV performance to evaluate fuel consumption and emissions. Fuel consumption average reduction of about 14% is obtained for optimal configuration data in contrast to default configuration. Also results indicate that proposed controller has reduced emission of about 10% in various traffic conditions.展开更多
The paper proposes an adoption of slope,elevation,speed and route distance preview to achieve optimal energymanagement of plug-in hybrid electric vehicles(PHEVs).Theapproach is to identify route features from historic...The paper proposes an adoption of slope,elevation,speed and route distance preview to achieve optimal energymanagement of plug-in hybrid electric vehicles(PHEVs).Theapproach is to identify route features from historical and real-time traffic data,in which information fusion model and trafficprediction model are used to improve the information accuracy.Then,dynamic programming combined with equivalent con-sumption minimization strategy is used to compute an optimalsolution for real-time energy management.The solution is thereference for PHEV energy management control along the route.To improve the system's ability of handling changing situation,the study further explores predictive control model in the real-time control of the energy.A simulation is performed to modelPHEV under above energy control strategy with route preview.The results show that the average fuel consumption of PHEValong the previewed route with model predictive control(MPC)strategy can be reduced compared with optimal strategy andbase control strategy.展开更多
In order to achieve the improvement of the driving comfort and energy efficiency,an new e-CVT flexible full hybrid electric system(E2FHS) is proposed,which uses an integrated main drive motor and generator to take the...In order to achieve the improvement of the driving comfort and energy efficiency,an new e-CVT flexible full hybrid electric system(E2FHS) is proposed,which uses an integrated main drive motor and generator to take the place of the original automatic or manual transmission to realize the functions of continuously variable transmission(e-CVT).The design and prototype realization of the E2FHS system for a plug-in hybrid vehicle(PHEV) is performed.In order to analyze and optimize the parameters and the power flux between different parts of the E2FHS,simulation software is developed.Especially,in order to optimize the performance of the energy economy improvement of the E2FHS,the effect of the different energy management controllers is investigated,and an adaptive online-optimal energy management controller for the E2FHS is built and validated by the prototype PHEV.展开更多
A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the princi...A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the principal component analysis(PCA)and the fuzzy c-means clustering(FCM)algorithm is used to construct the comprehensive driving cycle,congestion driving cycle,urban driving cycle and suburban driving cycle of Chinese urban buses.Secondly,an improved particle swarm optimization(IPSO)algorithm is proposed,and is used to optimize the control parameters of PHEB under different driving cycles,respectively.Then,the variable parameter self-adaptive control strategy based on driving condition identification is given.Finally,for an actual running vehicle,the driving condition is identified by relevance vector machine(RVM),and the corresponding control parameters are selected to control the vehicle.The simulation results show that the fuel consumption of using the variable parameter self-adaptive control strategy is reduced by 4.2% compared with that of the fixed parameter control strategy,and the feasibility of the variable parameter self-adaptive control strategy is verified.展开更多
The construction and characteristics of a microscale long-optical-path electrochemi- cal cell with a plug-in thin-layer electrode are described.Using ferricyanide as the test species,the thermodynamic parameters of el...The construction and characteristics of a microscale long-optical-path electrochemi- cal cell with a plug-in thin-layer electrode are described.Using ferricyanide as the test species,the thermodynamic parameters of electron transfer processes are determined at car- bon,plantinum,and gold electrodes.展开更多
基金supported by the National Key R&D Program of China(Grant No.2018YFC1505903)the National Natural Science Foundation of China(Grant No.41775071)the National Key R&D Program of China(Grant No.2016YFA0602401)
文摘The authors previous study reported the important role of extratropical intraseasonal oscillation(ISO)on the occurrence of a typical heatwave event over the Yangtze River Valley.Based on the ECMWF subseasonal reforecast database,this follow-up study evaluates the extended-range prediction skill of the heatwave event and further unravels the close link between the ISO and extended-range prediction of the event.With a two-week lead time,this heatwave event fails to occur in the reforecast because the predicted surface temperature is signi cantly underesti-mated.More detailed analysis demonstrates that the biases for both the intensity and the location of the warming region are primarily attributable to the inaccurate extratropical intrasea-sonal traveling signals.This work strongly indicates that accurately capturing the extratropical intraseasonal signal from the Eurasian continent is indispensable for extended-range prediction of East Asian extreme heatwave events.
文摘We examined the characteristic feature and predictability of low frequency variability (LFV) of the atmosphere in the Northern Hemisphere winter (January and February) by using the empirical orthogonal functions (EOFs) of the geopotential height at 500 hPa. In the discussion, we used the EOFs for geostrophic zonal wind (Uznl) and the height deviation from the zonal mean (Zeddy). The set of EOFs for Uznl and Zeddy was denoted as Uznl-1, Uznl-2, ..., Zeddy-1, Zeddy-2, ..., respectively. We used the data samples of 396 pentads derived from 33 years of NMC, ECMWF and JMA analyses, from January 1963 to 1995. From the calculated scores for Uznl-1, Uznl-2, Zeddy-1, Zeddy-2 and so on we found that Uznl-1 and Zeddy-1 were statistically stable and their scores were more persistent than those of the other EOFs. A close relationship existed between the scores of Uznl-1 and those of Zeddy-1. 30-day forecast experiments were carried out with the medium resolution version of JMA global spectral model for 20 cases in January and February for the period of 1984-1992. Results showed that Zeddy-1 was more predictable than the other EOFs for Zeddy. Considering these results, we argued that prediction of the Zeddy-1 was to be one of the main target of extended-range forecasting.
基金the National Natural Science Foundation of China(Grant Nos.42288101,41790475,42175051,and 42005046)the State Key Laboratory of Tropical Oceanography(South China Sea Institute of Oceanology,Chinese Academy of Sciences+1 种基金Grant No.LTO2109)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2021A1515011868).
文摘Utilizing the Community Atmosphere Model,version 4,the influence of Arctic sea-ice concentration(SIC)on the extended-range prediction of three simulated cold events(CEs)in East Asia is investigated.Numerical results show that the Arctic SIC is crucial for the extended-range prediction of CEs in East Asia.The conditional nonlinear optimal perturbation approach is adopted to identify the optimal Arctic SIC perturbations with the largest influence on CE prediction on the extended-range time scale.It shows that the optimal SIC perturbations are more inclined to weaken the CEs and cause large prediction errors in the fourth pentad,as compared with random SIC perturbations under the same constraint.Further diagnosis reveals that the optimal SIC perturbations first modulate the local temperature through the diabatic process,and then influence the remote temperature by horizontal advection and vertical convection terms.Consequently,the optimal SIC perturbations trigger a warming center in East Asia through the propagation of Rossby wave trains,leading to the largest prediction uncertainty of the CEs in the fourth pentad.These results may provide scientific support for targeted observation of Arctic SIC to improve the extended-range CE prediction skill.
文摘综合考虑电池和SCR催化器在低温环境下的工作特性,针对低温下温度对Plug-in柴电混合动力汽车性能的影响,提出最短时间控制和燃油消耗最少问题。以SCR起燃温度和电池正常工作温度时间最短为优化目标,以电池温度、电池荷电状态(State of Charge,SOC)和SCR催化器温度为状态变量,利用极小值原理求得最优控制策略。通过仿真对比规则控制策略,分析了在不同低温条件下基于庞特里亚金极小值原理(Pontryagin’s Minimum Principle,PMP)的最短时间和最少油耗与排放优化控制策略对整车油耗和排放的影响。
文摘Due to soaring fuel prices and environmental concerns, hybrid electric vehicle(HEV) technology attracts more attentions in last decade. Energy management system, configuration of HEV and traffic conditions are the main factors which affect HEV's fuel consumption, emission and performance. Therefore, optimal management of the energy components is a key element for the success of a HEV. An optimal energy management system is developed for HEV based on genetic algorithm. Then, different powertrain system component combinations effects are investigated in various driving cycles. HEV simulation results are compared for default rule-based, fuzzy and GA-fuzzy controllers by using ADVISOR. The results indicate the effectiveness of proposed optimal controller over real world driving cycles. Also, an optimal powertrain configuration to improve fuel consumption and emission efficiency is proposed for each driving condition. Finally, the effects of batteries in initial state of charge and hybridization factor are investigated on HEV performance to evaluate fuel consumption and emissions. Fuel consumption average reduction of about 14% is obtained for optimal configuration data in contrast to default configuration. Also results indicate that proposed controller has reduced emission of about 10% in various traffic conditions.
文摘The paper proposes an adoption of slope,elevation,speed and route distance preview to achieve optimal energymanagement of plug-in hybrid electric vehicles(PHEVs).Theapproach is to identify route features from historical and real-time traffic data,in which information fusion model and trafficprediction model are used to improve the information accuracy.Then,dynamic programming combined with equivalent con-sumption minimization strategy is used to compute an optimalsolution for real-time energy management.The solution is thereference for PHEV energy management control along the route.To improve the system's ability of handling changing situation,the study further explores predictive control model in the real-time control of the energy.A simulation is performed to modelPHEV under above energy control strategy with route preview.The results show that the average fuel consumption of PHEValong the previewed route with model predictive control(MPC)strategy can be reduced compared with optimal strategy andbase control strategy.
基金Project(2007CB209707) supported by the National Basic Research Program of China
文摘In order to achieve the improvement of the driving comfort and energy efficiency,an new e-CVT flexible full hybrid electric system(E2FHS) is proposed,which uses an integrated main drive motor and generator to take the place of the original automatic or manual transmission to realize the functions of continuously variable transmission(e-CVT).The design and prototype realization of the E2FHS system for a plug-in hybrid vehicle(PHEV) is performed.In order to analyze and optimize the parameters and the power flux between different parts of the E2FHS,simulation software is developed.Especially,in order to optimize the performance of the energy economy improvement of the E2FHS,the effect of the different energy management controllers is investigated,and an adaptive online-optimal energy management controller for the E2FHS is built and validated by the prototype PHEV.
基金Supported by China Automobile Test Cycle Development Project(CATC2015)
文摘A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the principal component analysis(PCA)and the fuzzy c-means clustering(FCM)algorithm is used to construct the comprehensive driving cycle,congestion driving cycle,urban driving cycle and suburban driving cycle of Chinese urban buses.Secondly,an improved particle swarm optimization(IPSO)algorithm is proposed,and is used to optimize the control parameters of PHEB under different driving cycles,respectively.Then,the variable parameter self-adaptive control strategy based on driving condition identification is given.Finally,for an actual running vehicle,the driving condition is identified by relevance vector machine(RVM),and the corresponding control parameters are selected to control the vehicle.The simulation results show that the fuel consumption of using the variable parameter self-adaptive control strategy is reduced by 4.2% compared with that of the fixed parameter control strategy,and the feasibility of the variable parameter self-adaptive control strategy is verified.
文摘The construction and characteristics of a microscale long-optical-path electrochemi- cal cell with a plug-in thin-layer electrode are described.Using ferricyanide as the test species,the thermodynamic parameters of electron transfer processes are determined at car- bon,plantinum,and gold electrodes.
