The basic theory of the fast charge and several charge methods are introduced. In order to heighten charge efficiency of valve-regulated lead-acid battery and shorten the charge time, five charge methods are investiga...The basic theory of the fast charge and several charge methods are introduced. In order to heighten charge efficiency of valve-regulated lead-acid battery and shorten the charge time, five charge methods are investigated with experiments done on the Digatron BNT 400-050 test bench. Battery current, terminal voltage, capacity, energy and terminal pole temperature during battery experiment were recorded, and corresponding curves were depicted. Battery capacity-time ratio, energy efficiency and energy-temperature ratio are put forward to be the appraising criteria of lead-acid battery on electric vehicle （EV）. According to the appraising criteria and the battery curves, multistage-current/negative-pulse charge method is recommended to charge lead-acid EV battery.展开更多
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
A design for a Li-ion battery charger IC that can operate in a constant current-constant voltage （CC- CV） charge mode is proposed. In the CC-CV charge mode,the charger IC provides a constant charging current at the ...A design for a Li-ion battery charger IC that can operate in a constant current-constant voltage （CC- CV） charge mode is proposed. In the CC-CV charge mode,the charger IC provides a constant charging current at the beginning, and then the charging current begins to decrease before the battery voltage reaches its final value. After the battery voltage reaches its final value and remains constant,the charging current is further reduced. This approach prevents charging the battery with full current near its saturated voltage,which can cause heating. The novel design of the core of the charger IC realizes the proposed CC-CV charge mode. The chip was implemented in a CSMC 0.6μm CMOS mixed signal process. The experimental results verify the realization of the proposed CC- CV charge mode. The voltage of the battery after charging is 4. 1833V.展开更多
A 100Ah@42V lead-acid battery package for electric vehicles are used for study. 1he hybrid pulse test is applied to the battery package to acquire enough data, by which the partnership for a new generation of vehicles...A 100Ah@42V lead-acid battery package for electric vehicles are used for study. 1he hybrid pulse test is applied to the battery package to acquire enough data, by which the partnership for a new generation of vehicles （PNGV） equivalent circuit model parameters are identified by the least square method. Then, the PNGV model is verified under two conditions, i.e., the composite pulse excitation and the constant-current respectively. The corresponding maximum relative errors of output voltage are less than 3 % and 3.5 %. Results show that the present PNGV equivalent circuit model and verification method is effective, which can satisfy requirement of simulation of power system of electric vehicles.展开更多
The current research of state of charge(SoC) online estimation of lithium-ion battery(LiB) in electric vehicles(EVs)mainly focuses on adopting or improving of battery models and estimation filters. However, little att...The current research of state of charge(SoC) online estimation of lithium-ion battery(LiB) in electric vehicles(EVs)mainly focuses on adopting or improving of battery models and estimation filters. However, little attention has been paid to the accuracy of various open circuit voltage(OCV) models for correcting the SoC with aid of the ampere-hour counting method. This paper presents a comprehensive comparison study on eighteen OCV models which cover the majority of models used in literature. The low-current OCV tests are conducted on the typical commercial LiFePO/graphite(LFP) and LiNiMnCoO/graphite(NMC) cells to obtain the experimental OCV-SoC curves at different ambient temperature and aging stages. With selected OCV and SoC points from experimental OCV-SoC curves, the parameters of each OCV model are determined by curve fitting toolbox of MATLAB 2013. Then the fitting OCV-SoC curves based on diversified OCV models are also obtained. The indicator of root-mean-square error(RMSE) between the experimental data and fitted data is selected to evaluate the adaptabilities of these OCV models for their main features, advantages,and limitations. The sensitivities of OCV models to ambient temperatures, aging stages, numbers of data points,and SoC regions are studied for both NMC and LFP cells. Furthermore, the influences of these models on SoC estimation are discussed. Through a comprehensive comparison and analysis on OCV models, some recommendations in selecting OCV models for both NMC and LFP cells are given.展开更多
考虑电池单体老化差异所致的电池组不一致性,针对串联电池组荷电状态(state of charge,SOC)、容量估计问题,提出一种基于自回归等效电路模型(autoregression equivalent circuit model,AR-ECM)的平均差异模型(mean-difference model,MDM...考虑电池单体老化差异所致的电池组不一致性,针对串联电池组荷电状态(state of charge,SOC)、容量估计问题,提出一种基于自回归等效电路模型(autoregression equivalent circuit model,AR-ECM)的平均差异模型(mean-difference model,MDM)。基于此模型,提出串联电池组SOC、容量多尺度联合估计算法。该算法由2个部分组成,一是基于AR-ECM的MDM及差异化模型参数辨识策略:条件辨识策略和定频分组辨识策略;二是基于多时间尺度H无穷滤波(multi-timescale H infinity filter,Mts-HIF)的电池组SOC、容量联合估计算法。通过将所提出MDM中的自回归平均模型(autoregression mean model,AR-MM)与传统MDM中的n阶RC平均模型(nRC mean model,nRC-MM)比较,结果表明所提出的AR-MM在复杂运行工况下具有更优的动态跟随性能。依据最小化信息量准则(akaike information criterion,AIC),AR-MM具有更优的复杂度与精度的权衡。通过与基于多时间尺度扩展卡尔曼滤波(multi-timescale extended Kalman filter,Mts-EKF)联合状态估计算法比较,结果表明所提出的Mts-HIF状态估计算法具有更优的鲁棒性、精度和收敛速度。展开更多
为了提高锂离子电池在运行过程中的内短路故障检测效率,提出基于弛豫电压的锂离子电池内短路分级及检测方法。首先根据内短路电池暂停放电后的弛豫电压曲线特征,基于支持向量机模型对电池内短路等级进行分类。然后根据分类结果,提出相...为了提高锂离子电池在运行过程中的内短路故障检测效率,提出基于弛豫电压的锂离子电池内短路分级及检测方法。首先根据内短路电池暂停放电后的弛豫电压曲线特征,基于支持向量机模型对电池内短路等级进行分类。然后根据分类结果,提出相应的电池内短路故障检测方法。对于中期内短路电池,立即令其退出电池系统;对于早期内短路电池,利用卡尔曼滤波(Kalman filtering,KF)算法实时计算电池荷电状态(state of charge,SOC)偏差;对于无短路电池,保持原检测措施。最后对所提分类及检测方法进行实验验证。实验结果表明该分类方法的正确率受弛豫电压序列的采样总时间长度和采样间隔时间影响,增加恒流恒压充电阶段获取的特征数据能进一步提高内短路分类结果的正确率,实时检测电池SOC偏差的方法能及时发现异常的早期内短路电池。展开更多
基金the National "863" Program Project (2004AA501970)
文摘The basic theory of the fast charge and several charge methods are introduced. In order to heighten charge efficiency of valve-regulated lead-acid battery and shorten the charge time, five charge methods are investigated with experiments done on the Digatron BNT 400-050 test bench. Battery current, terminal voltage, capacity, energy and terminal pole temperature during battery experiment were recorded, and corresponding curves were depicted. Battery capacity-time ratio, energy efficiency and energy-temperature ratio are put forward to be the appraising criteria of lead-acid battery on electric vehicle （EV）. According to the appraising criteria and the battery curves, multistage-current/negative-pulse charge method is recommended to charge lead-acid EV battery.
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.
文摘A design for a Li-ion battery charger IC that can operate in a constant current-constant voltage （CC- CV） charge mode is proposed. In the CC-CV charge mode,the charger IC provides a constant charging current at the beginning, and then the charging current begins to decrease before the battery voltage reaches its final value. After the battery voltage reaches its final value and remains constant,the charging current is further reduced. This approach prevents charging the battery with full current near its saturated voltage,which can cause heating. The novel design of the core of the charger IC realizes the proposed CC-CV charge mode. The chip was implemented in a CSMC 0.6μm CMOS mixed signal process. The experimental results verify the realization of the proposed CC- CV charge mode. The voltage of the battery after charging is 4. 1833V.
文摘A 100Ah@42V lead-acid battery package for electric vehicles are used for study. 1he hybrid pulse test is applied to the battery package to acquire enough data, by which the partnership for a new generation of vehicles （PNGV） equivalent circuit model parameters are identified by the least square method. Then, the PNGV model is verified under two conditions, i.e., the composite pulse excitation and the constant-current respectively. The corresponding maximum relative errors of output voltage are less than 3 % and 3.5 %. Results show that the present PNGV equivalent circuit model and verification method is effective, which can satisfy requirement of simulation of power system of electric vehicles.
基金Supported by National Natural Science Foundation of China(Grant No.51507012)Beijing Municipal Natural Science Foundation of China(Grant No.3182035)
文摘The current research of state of charge(SoC) online estimation of lithium-ion battery(LiB) in electric vehicles(EVs)mainly focuses on adopting or improving of battery models and estimation filters. However, little attention has been paid to the accuracy of various open circuit voltage(OCV) models for correcting the SoC with aid of the ampere-hour counting method. This paper presents a comprehensive comparison study on eighteen OCV models which cover the majority of models used in literature. The low-current OCV tests are conducted on the typical commercial LiFePO/graphite(LFP) and LiNiMnCoO/graphite(NMC) cells to obtain the experimental OCV-SoC curves at different ambient temperature and aging stages. With selected OCV and SoC points from experimental OCV-SoC curves, the parameters of each OCV model are determined by curve fitting toolbox of MATLAB 2013. Then the fitting OCV-SoC curves based on diversified OCV models are also obtained. The indicator of root-mean-square error(RMSE) between the experimental data and fitted data is selected to evaluate the adaptabilities of these OCV models for their main features, advantages,and limitations. The sensitivities of OCV models to ambient temperatures, aging stages, numbers of data points,and SoC regions are studied for both NMC and LFP cells. Furthermore, the influences of these models on SoC estimation are discussed. Through a comprehensive comparison and analysis on OCV models, some recommendations in selecting OCV models for both NMC and LFP cells are given.
文摘考虑电池单体老化差异所致的电池组不一致性,针对串联电池组荷电状态(state of charge,SOC)、容量估计问题,提出一种基于自回归等效电路模型(autoregression equivalent circuit model,AR-ECM)的平均差异模型(mean-difference model,MDM)。基于此模型,提出串联电池组SOC、容量多尺度联合估计算法。该算法由2个部分组成,一是基于AR-ECM的MDM及差异化模型参数辨识策略:条件辨识策略和定频分组辨识策略;二是基于多时间尺度H无穷滤波(multi-timescale H infinity filter,Mts-HIF)的电池组SOC、容量联合估计算法。通过将所提出MDM中的自回归平均模型(autoregression mean model,AR-MM)与传统MDM中的n阶RC平均模型(nRC mean model,nRC-MM)比较,结果表明所提出的AR-MM在复杂运行工况下具有更优的动态跟随性能。依据最小化信息量准则(akaike information criterion,AIC),AR-MM具有更优的复杂度与精度的权衡。通过与基于多时间尺度扩展卡尔曼滤波(multi-timescale extended Kalman filter,Mts-EKF)联合状态估计算法比较,结果表明所提出的Mts-HIF状态估计算法具有更优的鲁棒性、精度和收敛速度。
文摘为了提高锂离子电池在运行过程中的内短路故障检测效率,提出基于弛豫电压的锂离子电池内短路分级及检测方法。首先根据内短路电池暂停放电后的弛豫电压曲线特征,基于支持向量机模型对电池内短路等级进行分类。然后根据分类结果,提出相应的电池内短路故障检测方法。对于中期内短路电池,立即令其退出电池系统;对于早期内短路电池,利用卡尔曼滤波(Kalman filtering,KF)算法实时计算电池荷电状态(state of charge,SOC)偏差;对于无短路电池,保持原检测措施。最后对所提分类及检测方法进行实验验证。实验结果表明该分类方法的正确率受弛豫电压序列的采样总时间长度和采样间隔时间影响,增加恒流恒压充电阶段获取的特征数据能进一步提高内短路分类结果的正确率,实时检测电池SOC偏差的方法能及时发现异常的早期内短路电池。
