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
面向电动汽车一类宽温度,大幅值、宽频率随机电流应用场景,提出一种基于全新电热耦合模型的锂电池多状态在线联合估计方法。该模型由自回归等效电路模型与单态集总热模型耦合而成,以提高模型电气动态跟随性能。电热耦合模型参数采取“...面向电动汽车一类宽温度,大幅值、宽频率随机电流应用场景,提出一种基于全新电热耦合模型的锂电池多状态在线联合估计方法。该模型由自回归等效电路模型与单态集总热模型耦合而成,以提高模型电气动态跟随性能。电热耦合模型参数采取“先验信息初始化-在线修正”的方式确定,以避免电池一致性问题带来的误差,从而实现电热耦合关系在宽温度内的连续准确表达。基于所提出的ARST(autoregression-single state thermal model)耦合模型,该文采用双滤波算法实现锂电池多状态的在线联合估计,弥补目前电池3种及以上状态联合估计的稀缺问题。最后,在[0,50]℃,基于两个动态工况,将所提出的算法与两类基于模型的多状态联合估计算法进行比较。结果表明:ARST模型具有更好的电气跟随性能;所提出的模型参数在线辨识算法能够有效提高模型精度,从而提高多状态联合估计精度;在宽温度应用中,相较仅基于电模型的多状态联合估计算法,兼顾热状态估计的多状态联合估计算法能够有效提高电池状态的估计精度。展开更多
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.
文摘面向电动汽车一类宽温度,大幅值、宽频率随机电流应用场景,提出一种基于全新电热耦合模型的锂电池多状态在线联合估计方法。该模型由自回归等效电路模型与单态集总热模型耦合而成,以提高模型电气动态跟随性能。电热耦合模型参数采取“先验信息初始化-在线修正”的方式确定,以避免电池一致性问题带来的误差,从而实现电热耦合关系在宽温度内的连续准确表达。基于所提出的ARST(autoregression-single state thermal model)耦合模型,该文采用双滤波算法实现锂电池多状态的在线联合估计,弥补目前电池3种及以上状态联合估计的稀缺问题。最后,在[0,50]℃,基于两个动态工况,将所提出的算法与两类基于模型的多状态联合估计算法进行比较。结果表明:ARST模型具有更好的电气跟随性能;所提出的模型参数在线辨识算法能够有效提高模型精度,从而提高多状态联合估计精度;在宽温度应用中,相较仅基于电模型的多状态联合估计算法,兼顾热状态估计的多状态联合估计算法能够有效提高电池状态的估计精度。
