The Estimation Of State Of Charge And Power Prediction Of Lithium-ion Battery Used On H_? Filter

In order to alleviate the energy crisis and environmental pollutions,electric vehicles has been rapidly developed in recent years.Lithium-ion batteries as renewable energy resources have been the mainstream power source of electric vehicles,due to a wide range of advantages,such as environmental protection and higher specific energy.Although the manufacturing techniques of lithium-ion battery are continuing to improve,its lifetime and security are still unable to fully meet the requirements of application needs.State of charge of and the limit the discharge capacity of the batteries play a significant impact on the electric car's performance.Thus,it is necessary to accurately assess the state of charge(SOC)and the state of power(SOP)of the lithium batteries.In view of the hysteresis characteristics of lithium battery presented in the discharge and charge procedure,the second-order RC hysteresis model is proposed in this paper.Then,aimed at the disadvantages of the extended kalman filter algorithm,a H_? filter algorithm is proposed for SOC estimation in this paper.the H_? filter and EKF are used to estimate SOC on the basis of pulse discharge experiments,and the simulation results show that the H_? filter has a higher precision of estimation and a better robustness of the system.On the other hand,we use the estimation of SOC and the constraints of battery voltage,battery current to predict the actual maximum charge power and maximum discharge power of the lithium battery.We evaluate the method through the pulse discharge test and pulse charge test,and make a comparison with the HPPC method(the hybrid pulse power characterization method).The result show that the method proposed in this paper can maintain high accuracy in the estimation process of battery power.In the last part of the paper,the preliminary design of battery management system is introduced,and the whole hardware system is divided into two parts,the control unit and the supervision unit.The supervision unit is mainly responsible for monitoring and displaying the battery state information and uploading state information to the control unit.The control unit is used to estimate the SOC of battery according to state information collected by the supervision unit,and the estimation algorithm is written based on model based design method.