Aim To research and develop a battery management system(BMS)with the state of charge(SOC)indicator for electric vehicles (EVs).Methods On the basis of analyzing the electro-chemical characteristics of lead-acid. batte...Aim To research and develop a battery management system(BMS)with the state of charge(SOC)indicator for electric vehicles (EVs).Methods On the basis of analyzing the electro-chemical characteristics of lead-acid. battery, the state of charge indicator for lead-acid battery was developed by means of an algorithm based on combination of ampere-hour, Peukert's equation and open-voltage method with the compensation of temperature,aging,self- discharging,etc..Results The BMS based on this method can attain an accurate surplus capa- city whose error is less than 5% in static experiments.It is proved by experiments that the BMS is reliable and can give the driver an accurate surplus capacity,precisely monitor the individual battery modules as the same time,even detect and warn the problems early,and so on. Conclusion A BMS can make the energy of the storage batteries used efficiently, develop the batteries cycle life,and increase the driving distance of EVs.展开更多
We evaluated the effect of various error sources in fishery harvest/effort data on the maximum sustainable yield （MSY） and corresponding fishing effort （EMsv） using Monte Carlo simulation analyses. A high coeffici...We evaluated the effect of various error sources in fishery harvest/effort data on the maximum sustainable yield （MSY） and corresponding fishing effort （EMsv） using Monte Carlo simulation analyses. A high coefficient of variation （CV） of the catch and effort values biased the estimates of MSY and EMsv. Thus, the state of the fisheries resource and its exploitation was overestimated. We compared the effect using three surplus production models, Hilborn-Waters （H-W）, Schnute, and Prager models. The estimates generated using the H-W model were significantly affected by the CV. The Schnute model was least affected by errors in the underlying data. The CVof the catch data had a greater impact on the assessment than the CV of the fishing effort. Similarly, the changes in CV had a greater impact on the estimated maximum sustainable yield （MSY） than on the corresponding estimate of fishing effort （EMsY）. We discuss the likely effect of these biases on management efforts and provide suggestions for the improvement of fishery evaluations.展开更多
文摘Aim To research and develop a battery management system(BMS)with the state of charge(SOC)indicator for electric vehicles (EVs).Methods On the basis of analyzing the electro-chemical characteristics of lead-acid. battery, the state of charge indicator for lead-acid battery was developed by means of an algorithm based on combination of ampere-hour, Peukert's equation and open-voltage method with the compensation of temperature,aging,self- discharging,etc..Results The BMS based on this method can attain an accurate surplus capa- city whose error is less than 5% in static experiments.It is proved by experiments that the BMS is reliable and can give the driver an accurate surplus capacity,precisely monitor the individual battery modules as the same time,even detect and warn the problems early,and so on. Conclusion A BMS can make the energy of the storage batteries used efficiently, develop the batteries cycle life,and increase the driving distance of EVs.
基金Supported by the National Natural Science Foundation for Young Scientists of China (No. 40801225)the Natural Science Foundation of Zhejiang Province (No. Y3090038)
文摘We evaluated the effect of various error sources in fishery harvest/effort data on the maximum sustainable yield （MSY） and corresponding fishing effort （EMsv） using Monte Carlo simulation analyses. A high coefficient of variation （CV） of the catch and effort values biased the estimates of MSY and EMsv. Thus, the state of the fisheries resource and its exploitation was overestimated. We compared the effect using three surplus production models, Hilborn-Waters （H-W）, Schnute, and Prager models. The estimates generated using the H-W model were significantly affected by the CV. The Schnute model was least affected by errors in the underlying data. The CVof the catch data had a greater impact on the assessment than the CV of the fishing effort. Similarly, the changes in CV had a greater impact on the estimated maximum sustainable yield （MSY） than on the corresponding estimate of fishing effort （EMsY）. We discuss the likely effect of these biases on management efforts and provide suggestions for the improvement of fishery evaluations.
