Accurate vehicle dynamic information plays an important role in vehicle driving safety.However,due to the characteristics of high mobility and multiple controllable degrees of freedom of drive-by-wire chassis vehicles...Accurate vehicle dynamic information plays an important role in vehicle driving safety.However,due to the characteristics of high mobility and multiple controllable degrees of freedom of drive-by-wire chassis vehicles,the current mature application of traditional vehicle state estimation algorithms can not meet the requirements of drive-by-wire chassis vehicle state estimation.This paper proposes a state estimation method for drive-by-wire chassis vehicle based on the dual unscented particle filter algorithm,which make full use of the known advantages of the four-wheel drive torque and steer angle parameters of the drive-by-wire chassis vehicle.In the dual unscented particle filter algorithm,two unscented particle filter transfer information to each other,observe the vehicle state information and the tire force parameter information of the four wheels respectively,which reduce the influence of parameter uncertainty and model parameter changes on the estimation accuracy during driving.The performance with the dual unscented particle filter algorithm,which is analyzed in terms of the time-average square error,is superior of the unscented Kalman filter algorithm.The effectiveness of the algorithm is further verified by driving simulator test.In this paper,a vehicle state estimator based on dual unscented particle filter algorithm was proposed for the first time to improve the estimation accuracy of vehicle parameters and states.展开更多
Distributed drive electric vehicles(DDEVs)possess great advantages in the viewpoint of fuel consumption,environment protection and traffic mobility.Whereas the effects of inertial parameter variation in DDEV control s...Distributed drive electric vehicles(DDEVs)possess great advantages in the viewpoint of fuel consumption,environment protection and traffic mobility.Whereas the effects of inertial parameter variation in DDEV control system become much more pronounced due to the drastic reduction of vehicle weights and body size,and inertial parameter has seldom been tackled and systematically estimated.This paper presents a dual central difference Kalman filter(DCDKF)where two Kalman filters run in parallel to simultaneously estimate vehicle different dynamic states and inertial parameters,such as vehicle sideslip angle,vehicle mass,vehicle yaw moment of inertia,the distance from the front axle to centre of gravity.The proposed estimation method only integrates and utilizes real-time measurements of hub torque information and other in-vehicle sensors from standard DDEVs.The four-wheel nonlinear vehicle dynamics estimation model considering payload variations,Pacejka tire model,wheel and motor dynamics model is developed,the observability of the DCDKF observer is analysed and derived via Lie derivative and differential geometry theory.To address system nonlinearities in vehicle dynamics estimation,the DCDKF and dual extended Kalman filter(DEKF)are also investigated and compared.Simulation with various maneuvers are carried out to verify the effectiveness of the proposed method using Matlab/Simulink-CarsimR.The results show that the proposed DCDKF method can effectively estimate vehicle dynamic states and inertial parameters despite the existence of payload variations and variable driving conditions.This research provides a boot-strapping procedure which can performs optimal estimation to estimate simultaneously vehicle system state and inertial parameter with high accuracy and real-time ability.展开更多
A novel quantum dual signature scheme, which combines two signed messages expected to be sent to two diverse receivers Bob and Charlie, is designed by applying entanglement swapping with coherent states. The signatory...A novel quantum dual signature scheme, which combines two signed messages expected to be sent to two diverse receivers Bob and Charlie, is designed by applying entanglement swapping with coherent states. The signatory Alice signs two different messages with unitary operations(corresponding to the secret keys) and applies entanglement swapping to generate a quantum dual signature. The dual signature is firstly sent to the verifier Bob who extracts and verifies the signature of one message and transmits the rest of the dual signature to the verifier Charlie who verifies the signature of the other message. The transmission of the dual signature is realized with quantum teleportation of coherent states. The analysis shows that the security of secret keys and the security criteria of the signature protocol can be greatly guaranteed.An extensional multi-party quantum dual signature scheme which considers the case with more than three participants is also proposed in this paper and this scheme can remain secure. The proposed schemes are completely suited for the quantum communication network including multiple participants and can be applied to the e-commerce system which requires a secure payment among the customer, business and bank.展开更多
This article explores the dynamics of the Diaspora's dual loyalties towards their home countries and host countries by using American Jewry as a case study. It argues that in liberal-democratic states,the shift in...This article explores the dynamics of the Diaspora's dual loyalties towards their home countries and host countries by using American Jewry as a case study. It argues that in liberal-democratic states,the shift in the Diaspora's loyalty towards the homeland vis-à-vis the host land is a result of the change to the host land's perception of where the acceptable boundary of the Diaspora's practice of dual loyalties is, or in other words, to what extent the Diaspora's support of the homeland is perceived to be acceptable by their host land. The reconstruction of this boundary is determined by four factors: the degree of political coordination between home states and host states, the attempt of the home state to mobilize its diasporas, the means advocated and supported by the Diaspora, and the severity of potential consequences due to the Diaspora's action.展开更多
Vehicle state and tire-road adhesion are of great use and importance to vehicle active safety control systems. However, it is always not easy to obtain the information with high accuracy and low expense. Recently, man...Vehicle state and tire-road adhesion are of great use and importance to vehicle active safety control systems. However, it is always not easy to obtain the information with high accuracy and low expense. Recently, many estimation methods have been put forward to solve such problems, in which Kalman filter becomes one of the most popular techniques. Nevertheless, the use of complicated model always leads to poor real-time estimation while the role of road friction coefficient is often ignored. For the purpose of enhancing the real time performance of the algorithm and pursuing precise estimation of vehicle states, a model-based estimator is proposed to conduct combined estimation of vehicle states and road friction coefficients. The estimator is designed based on a three-DOF vehicle model coupled with the Highway Safety Research Institute(HSRI) tire model; the dual extended Kalman filter (DEKF) technique is employed, which can be regarded as two extended Kalman filters operating and communicating simultaneously. Effectiveness of the estimation is firstly examined by comparing the outputs of the estimator with the responses of the vehicle model in CarSim under three typical road adhesion conditions(high-friction, low-friction, and joint-friction). On this basis, driving simulator experiments are carried out to further investigate the practical application of the estimator. Numerical results from CarSim and driving simulator both demonstrate that the estimator designed is capable of estimating the vehicle states and road friction coefficient with reasonable accuracy. The DEKF-based estimator proposed provides the essential information for the vehicle active control system with low expense and decent precision, and offers the possibility of real car application in future.展开更多
Acquisition of real-time and accurate vehicle state and parameter information is critical to the research of vehicle dynamic control system.By studying the defects of the former Kalman filter based estimation method,a...Acquisition of real-time and accurate vehicle state and parameter information is critical to the research of vehicle dynamic control system.By studying the defects of the former Kalman filter based estimation method,a new estimating method is proposed.First the nonlinear vehicle dynamics system,containing inaccurate model parameters and constant noise,is established.Then a dual unscented particle filter(DUPF)algorithm is proposed.In the algorithm two unscented particle filters run in parallel,states estimation and parameters estimation update each other.The results of simulation and vehicle ground testing indicate that the DUPF algorithm has higher state estimation accuracy than unscented Kalman filter(UKF)and dual extended Kalman filter(DEKF),and it also has good capability to revise model parameters.展开更多
This paper describes a tunable dual-wavelength Ti:sapphire laser system with quasi-continuous-wave and high-power outputs. In the design of the laser, it adopts a frequency-doubled Nd:YAG laser as the pumping source...This paper describes a tunable dual-wavelength Ti:sapphire laser system with quasi-continuous-wave and high-power outputs. In the design of the laser, it adopts a frequency-doubled Nd:YAG laser as the pumping source, and the birefringence filter as the tuning element. Tunable dual-wavelength outputs with one wavelength range from 700 nm to 756.5 nm, another from 830 nm to 900mn have been demonstrated. With a pump power of 23 W at 532 nm, a repetition rate of 7 kHz and a pulse width of 47.6 ns, an output power of 5.1 W at 744.8 nm and 860.9 nm with a pulse width of 13.2 ns and a line width of 3 nm has been obtained, it indicates an optical-to-optical conversion efficiency of 22.2%.展开更多
Firstly,this paper reviews and analyzes historic background of urban-rural integration of Chongqing,and the evolution and trend of urban and rural dual economic structure.On the basis of previous researches,it selects...Firstly,this paper reviews and analyzes historic background of urban-rural integration of Chongqing,and the evolution and trend of urban and rural dual economic structure.On the basis of previous researches,it selects factors and variables influencing urban and rural dual economic structure,and establishes an econometric model.By state space Kalman filtering method,it analyzes dynamic influence of factors upon urban-rural dual economic intensity.According to empirical conclusion,it puts forward corresponding policy recommendations for promoting integrated urban and rural economic development of Chongqing.展开更多
In this paper modelling and analysis in autonomous mode of dual three-phase induction generator (DTPIG) with a new algorithm have been done. We develop the steady state model of a dual three-phase self-excited inducti...In this paper modelling and analysis in autonomous mode of dual three-phase induction generator (DTPIG) with a new algorithm have been done. We develop the steady state model of a dual three-phase self-excited induction generator for stand-alone renewable generation dispensing with the segregating real and imaginary components of the complex impedance of the induction generator. The obtained admittance yields the adequate magnetizing reactance and the frequency. These two key parameters are then used to compute the self-excitation process requirements in terms of the prime mover speed, the capacitance and the load impedance on the one hand and to predict the generator steady state performance parameters on the other. Steady state performances and characteristics of different configurations are clearly examined and compared. The analytical results are found to be in good agreement with experimental results.展开更多
针对传统模型在机组负荷预测中无法充分捕获内部多变量演化模式的问题,提出了一种基于时间序列的趋势和数值信息融合的双重回声状态网络Dual-ESN(dual-echo state network)机组负荷动态预测模型。首先,引入最小二乘法,对相关的多元历史...针对传统模型在机组负荷预测中无法充分捕获内部多变量演化模式的问题,提出了一种基于时间序列的趋势和数值信息融合的双重回声状态网络Dual-ESN(dual-echo state network)机组负荷动态预测模型。首先,引入最小二乘法,对相关的多元历史信息按照局部时间跨度进行趋势拟合。进一步,得到有关过程变化的模式序列,并和原本的数值分别被送入两个独立的储备池,以并行的时间维度进行特征学习。其次,将隐层的高维空间状态送入输出层,融合信息,得到所需要的预测结果。最后,基于山西某工厂660 MW机组装置的真实数据集,进行验证。对比已有预测方法,结果表明所提预测模型在多种性能指标上均有提升。展开更多
基金Supported by National Key Research and Development Program of China(Grant No.2021YFB2500703)Science and Technology Department Program of Jilin Province of China(Grant No.20230101121JC).
文摘Accurate vehicle dynamic information plays an important role in vehicle driving safety.However,due to the characteristics of high mobility and multiple controllable degrees of freedom of drive-by-wire chassis vehicles,the current mature application of traditional vehicle state estimation algorithms can not meet the requirements of drive-by-wire chassis vehicle state estimation.This paper proposes a state estimation method for drive-by-wire chassis vehicle based on the dual unscented particle filter algorithm,which make full use of the known advantages of the four-wheel drive torque and steer angle parameters of the drive-by-wire chassis vehicle.In the dual unscented particle filter algorithm,two unscented particle filter transfer information to each other,observe the vehicle state information and the tire force parameter information of the four wheels respectively,which reduce the influence of parameter uncertainty and model parameter changes on the estimation accuracy during driving.The performance with the dual unscented particle filter algorithm,which is analyzed in terms of the time-average square error,is superior of the unscented Kalman filter algorithm.The effectiveness of the algorithm is further verified by driving simulator test.In this paper,a vehicle state estimator based on dual unscented particle filter algorithm was proposed for the first time to improve the estimation accuracy of vehicle parameters and states.
基金Supported by National Natural Science Foundation of China(Grant Nos.51905329,51975118)Foundation of State Key Laboratory of Automotive Simulation and Control of China(Grant No.20181112).
文摘Distributed drive electric vehicles(DDEVs)possess great advantages in the viewpoint of fuel consumption,environment protection and traffic mobility.Whereas the effects of inertial parameter variation in DDEV control system become much more pronounced due to the drastic reduction of vehicle weights and body size,and inertial parameter has seldom been tackled and systematically estimated.This paper presents a dual central difference Kalman filter(DCDKF)where two Kalman filters run in parallel to simultaneously estimate vehicle different dynamic states and inertial parameters,such as vehicle sideslip angle,vehicle mass,vehicle yaw moment of inertia,the distance from the front axle to centre of gravity.The proposed estimation method only integrates and utilizes real-time measurements of hub torque information and other in-vehicle sensors from standard DDEVs.The four-wheel nonlinear vehicle dynamics estimation model considering payload variations,Pacejka tire model,wheel and motor dynamics model is developed,the observability of the DCDKF observer is analysed and derived via Lie derivative and differential geometry theory.To address system nonlinearities in vehicle dynamics estimation,the DCDKF and dual extended Kalman filter(DEKF)are also investigated and compared.Simulation with various maneuvers are carried out to verify the effectiveness of the proposed method using Matlab/Simulink-CarsimR.The results show that the proposed DCDKF method can effectively estimate vehicle dynamic states and inertial parameters despite the existence of payload variations and variable driving conditions.This research provides a boot-strapping procedure which can performs optimal estimation to estimate simultaneously vehicle system state and inertial parameter with high accuracy and real-time ability.
基金supported by the National Natural Science Foundation of China(Grant Nos.61272495,61379153,and 61401519)the Research Fund for the Doctoral Program of Higher Education of China(Grant No.20130162110012)
文摘A novel quantum dual signature scheme, which combines two signed messages expected to be sent to two diverse receivers Bob and Charlie, is designed by applying entanglement swapping with coherent states. The signatory Alice signs two different messages with unitary operations(corresponding to the secret keys) and applies entanglement swapping to generate a quantum dual signature. The dual signature is firstly sent to the verifier Bob who extracts and verifies the signature of one message and transmits the rest of the dual signature to the verifier Charlie who verifies the signature of the other message. The transmission of the dual signature is realized with quantum teleportation of coherent states. The analysis shows that the security of secret keys and the security criteria of the signature protocol can be greatly guaranteed.An extensional multi-party quantum dual signature scheme which considers the case with more than three participants is also proposed in this paper and this scheme can remain secure. The proposed schemes are completely suited for the quantum communication network including multiple participants and can be applied to the e-commerce system which requires a secure payment among the customer, business and bank.
文摘This article explores the dynamics of the Diaspora's dual loyalties towards their home countries and host countries by using American Jewry as a case study. It argues that in liberal-democratic states,the shift in the Diaspora's loyalty towards the homeland vis-à-vis the host land is a result of the change to the host land's perception of where the acceptable boundary of the Diaspora's practice of dual loyalties is, or in other words, to what extent the Diaspora's support of the homeland is perceived to be acceptable by their host land. The reconstruction of this boundary is determined by four factors: the degree of political coordination between home states and host states, the attempt of the home state to mobilize its diasporas, the means advocated and supported by the Diaspora, and the severity of potential consequences due to the Diaspora's action.
基金supported by National Natural Science Foundation of China(Grant Nos. 51075176, 51105165)
文摘Vehicle state and tire-road adhesion are of great use and importance to vehicle active safety control systems. However, it is always not easy to obtain the information with high accuracy and low expense. Recently, many estimation methods have been put forward to solve such problems, in which Kalman filter becomes one of the most popular techniques. Nevertheless, the use of complicated model always leads to poor real-time estimation while the role of road friction coefficient is often ignored. For the purpose of enhancing the real time performance of the algorithm and pursuing precise estimation of vehicle states, a model-based estimator is proposed to conduct combined estimation of vehicle states and road friction coefficients. The estimator is designed based on a three-DOF vehicle model coupled with the Highway Safety Research Institute(HSRI) tire model; the dual extended Kalman filter (DEKF) technique is employed, which can be regarded as two extended Kalman filters operating and communicating simultaneously. Effectiveness of the estimation is firstly examined by comparing the outputs of the estimator with the responses of the vehicle model in CarSim under three typical road adhesion conditions(high-friction, low-friction, and joint-friction). On this basis, driving simulator experiments are carried out to further investigate the practical application of the estimator. Numerical results from CarSim and driving simulator both demonstrate that the estimator designed is capable of estimating the vehicle states and road friction coefficient with reasonable accuracy. The DEKF-based estimator proposed provides the essential information for the vehicle active control system with low expense and decent precision, and offers the possibility of real car application in future.
基金Supported by the National Natural Science Foundation of China(10902049)the Chinese Postdoctoral Science Foundation(2012M521073)+3 种基金the Fundamental Research Funds for the Central Universitiesthe Jiangsu Planned Projects for Postdoctoral Research Funds(1302020C)the Nanjing University of Aeronautics and Astronautics Student Innovative Training Program(20120119101535)the Fundation of Graduate Innovation Center in Nanjing University of Aeronautics and Astronautics(kfjj201404)
文摘Acquisition of real-time and accurate vehicle state and parameter information is critical to the research of vehicle dynamic control system.By studying the defects of the former Kalman filter based estimation method,a new estimating method is proposed.First the nonlinear vehicle dynamics system,containing inaccurate model parameters and constant noise,is established.Then a dual unscented particle filter(DUPF)algorithm is proposed.In the algorithm two unscented particle filters run in parallel,states estimation and parameters estimation update each other.The results of simulation and vehicle ground testing indicate that the DUPF algorithm has higher state estimation accuracy than unscented Kalman filter(UKF)and dual extended Kalman filter(DEKF),and it also has good capability to revise model parameters.
基金Project supported in part by the National Natural Science Foundation of China (Grant Nos 10474071, 60637010, 60671036 and 60278001) and Tianjin Applied Fundamental Research Project, China (07JCZDJC05900).
文摘This paper describes a tunable dual-wavelength Ti:sapphire laser system with quasi-continuous-wave and high-power outputs. In the design of the laser, it adopts a frequency-doubled Nd:YAG laser as the pumping source, and the birefringence filter as the tuning element. Tunable dual-wavelength outputs with one wavelength range from 700 nm to 756.5 nm, another from 830 nm to 900mn have been demonstrated. With a pump power of 23 W at 532 nm, a repetition rate of 7 kHz and a pulse width of 47.6 ns, an output power of 5.1 W at 744.8 nm and 860.9 nm with a pulse width of 13.2 ns and a line width of 3 nm has been obtained, it indicates an optical-to-optical conversion efficiency of 22.2%.
基金Supported by Social Science Planning Project of Chongqing(2010YBJJ13)the Fundamental Research Funds for the Central Universities(XDJK2010C103)Ph.D Foundation Project of Southwest University(SWU1209303)
文摘Firstly,this paper reviews and analyzes historic background of urban-rural integration of Chongqing,and the evolution and trend of urban and rural dual economic structure.On the basis of previous researches,it selects factors and variables influencing urban and rural dual economic structure,and establishes an econometric model.By state space Kalman filtering method,it analyzes dynamic influence of factors upon urban-rural dual economic intensity.According to empirical conclusion,it puts forward corresponding policy recommendations for promoting integrated urban and rural economic development of Chongqing.
文摘In this paper modelling and analysis in autonomous mode of dual three-phase induction generator (DTPIG) with a new algorithm have been done. We develop the steady state model of a dual three-phase self-excited induction generator for stand-alone renewable generation dispensing with the segregating real and imaginary components of the complex impedance of the induction generator. The obtained admittance yields the adequate magnetizing reactance and the frequency. These two key parameters are then used to compute the self-excitation process requirements in terms of the prime mover speed, the capacitance and the load impedance on the one hand and to predict the generator steady state performance parameters on the other. Steady state performances and characteristics of different configurations are clearly examined and compared. The analytical results are found to be in good agreement with experimental results.
文摘针对传统模型在机组负荷预测中无法充分捕获内部多变量演化模式的问题,提出了一种基于时间序列的趋势和数值信息融合的双重回声状态网络Dual-ESN(dual-echo state network)机组负荷动态预测模型。首先,引入最小二乘法,对相关的多元历史信息按照局部时间跨度进行趋势拟合。进一步,得到有关过程变化的模式序列,并和原本的数值分别被送入两个独立的储备池,以并行的时间维度进行特征学习。其次,将隐层的高维空间状态送入输出层,融合信息,得到所需要的预测结果。最后,基于山西某工厂660 MW机组装置的真实数据集,进行验证。对比已有预测方法,结果表明所提预测模型在多种性能指标上均有提升。