In order to characterize the voltage behavior of a lithium-ion battery for on-board electric vehicle battery management and control applications,a battery model with a moderate complexity was established.The battery o...In order to characterize the voltage behavior of a lithium-ion battery for on-board electric vehicle battery management and control applications,a battery model with a moderate complexity was established.The battery open circuit voltage (OCV) as a function of state of charge (SOC) was depicted by the Nernst equation.An equivalent circuit network was adopted to describe the polarization effect of the lithium-ion battery.A linear identifiable formulation of the battery model was derived by discretizing the frequent-domain description of the battery model.The recursive least square algorithm with forgetting was applied to implement the on-line parameter calibration.The validation results show that the on-line calibrated model can accurately predict the dynamic voltage behavior of the lithium-ion battery.The maximum and mean relative errors are 1.666% and 0.01%,respectively,in a hybrid pulse test,while 1.933% and 0.062%,respectively,in a transient power test.The on-line parameter calibration method thereby can ensure that the model possesses an acceptable robustness to varied battery loading profiles.展开更多
An electrical equivalent circuit model for lithium-ion batteries used for hybrid electric vehicles （HEV） is presented. The model has two RC networks characterizing battery activation and concentration polarization p...An electrical equivalent circuit model for lithium-ion batteries used for hybrid electric vehicles （HEV） is presented. The model has two RC networks characterizing battery activation and concentration polarization process. The parameters of the model are identified using combined experimental and extended Kalman filter （EKF） recursive methods. The open-circuit voltage and ohmic resistance of the battery are directly measured and calculated from experimental measurements, respectively. The rest of the coupled dynamic parameters, i.e. the RC network parameters, are estimated using the EKF method. Experimental and simulation results are presented to demonstrate the efficacy of the proposed circuit model and parameter identification techniques for simulating battery dynamics.展开更多
This paper reports the results of investigating the permissible amount of battery deterioration. An investigation was carried out using the following two types of vehicles： a BEV （battery electric vehicle） and a H...This paper reports the results of investigating the permissible amount of battery deterioration. An investigation was carried out using the following two types of vehicles： a BEV （battery electric vehicle） and a HEV （hybrid electric vehicle）. First, a detailed evaluation was carried out to identify how the vehicle performance was adversely affected as the lithium-ion batteries installed in the vehicles deteriorated. Next, an attempt was made to determine the permissible amount of deterioration for the vehicle-mounted lithium-ion batteries. In the case of the BEV, the driving distance declined by 20% when the capacity maintenance rate was approximately 80%. Therefore, this was specified as the permissible amount of battery deterioration for the BEV. In the case of the HEV, the fuel consumption increased by 20% when the maximum battery output maintenance rate was approximately 40%. Therefore, this was specified as the permissible amount of battery deterioration for the HEV.展开更多
For safe and reliable operation of lithium-ion batteries in electric vehicles,the real-time monitoring of their internal states is important.The purpose of our study is to find an easily implementable,online identific...For safe and reliable operation of lithium-ion batteries in electric vehicles,the real-time monitoring of their internal states is important.The purpose of our study is to find an easily implementable,online identification method for lithium-ion batteries in electric vehicles.In this article,we propose an equivalent circuit model structure.Based on the model structure we derive the recursive mathematical description.The recursive extended least square algorithm is introduced to estimate the model parameters online.The accuracy and robustness are validated through experiments and simulations.Real-road driving cycle experiment shows that the proposed online identification method can achieve acceptable accuracy with the maximum error of less than 5.52%.In addition,it is proved that the proposed method can also be used to estimate the real-time SOH and SOC of the batteries.展开更多
基金Project(50905015) supported by the National Natural Science Foundation of China
文摘In order to characterize the voltage behavior of a lithium-ion battery for on-board electric vehicle battery management and control applications,a battery model with a moderate complexity was established.The battery open circuit voltage (OCV) as a function of state of charge (SOC) was depicted by the Nernst equation.An equivalent circuit network was adopted to describe the polarization effect of the lithium-ion battery.A linear identifiable formulation of the battery model was derived by discretizing the frequent-domain description of the battery model.The recursive least square algorithm with forgetting was applied to implement the on-line parameter calibration.The validation results show that the on-line calibrated model can accurately predict the dynamic voltage behavior of the lithium-ion battery.The maximum and mean relative errors are 1.666% and 0.01%,respectively,in a hybrid pulse test,while 1.933% and 0.062%,respectively,in a transient power test.The on-line parameter calibration method thereby can ensure that the model possesses an acceptable robustness to varied battery loading profiles.
文摘An electrical equivalent circuit model for lithium-ion batteries used for hybrid electric vehicles （HEV） is presented. The model has two RC networks characterizing battery activation and concentration polarization process. The parameters of the model are identified using combined experimental and extended Kalman filter （EKF） recursive methods. The open-circuit voltage and ohmic resistance of the battery are directly measured and calculated from experimental measurements, respectively. The rest of the coupled dynamic parameters, i.e. the RC network parameters, are estimated using the EKF method. Experimental and simulation results are presented to demonstrate the efficacy of the proposed circuit model and parameter identification techniques for simulating battery dynamics.
文摘This paper reports the results of investigating the permissible amount of battery deterioration. An investigation was carried out using the following two types of vehicles： a BEV （battery electric vehicle） and a HEV （hybrid electric vehicle）. First, a detailed evaluation was carried out to identify how the vehicle performance was adversely affected as the lithium-ion batteries installed in the vehicles deteriorated. Next, an attempt was made to determine the permissible amount of deterioration for the vehicle-mounted lithium-ion batteries. In the case of the BEV, the driving distance declined by 20% when the capacity maintenance rate was approximately 80%. Therefore, this was specified as the permissible amount of battery deterioration for the BEV. In the case of the HEV, the fuel consumption increased by 20% when the maximum battery output maintenance rate was approximately 40%. Therefore, this was specified as the permissible amount of battery deterioration for the HEV.
基金supported by the National High Technology Research and Development Program("863" Project)(Grant No.2011AA05A109)the International Science and Technology Cooperation Program of China(Grant Nos.2011DFA70570,2010DFA72760)the National Natural Science Foundation of China(Grant No.51007088)
文摘For safe and reliable operation of lithium-ion batteries in electric vehicles,the real-time monitoring of their internal states is important.The purpose of our study is to find an easily implementable,online identification method for lithium-ion batteries in electric vehicles.In this article,we propose an equivalent circuit model structure.Based on the model structure we derive the recursive mathematical description.The recursive extended least square algorithm is introduced to estimate the model parameters online.The accuracy and robustness are validated through experiments and simulations.Real-road driving cycle experiment shows that the proposed online identification method can achieve acceptable accuracy with the maximum error of less than 5.52%.In addition,it is proved that the proposed method can also be used to estimate the real-time SOH and SOC of the batteries.
