The Configuration Optimization And Energy Management For Li-ion Battery/Ultracapacitor Hybrid Energy Storage System

The development of future-oriented electric vehicles(EVs)has become the common choice of major countries in the world.At present,EV with lithium-ion battery(LIB)as the core energy storage often faces the challenge of frequent high-power load during its driving process,which seriously affects the long-term effective operation of LIB.It is an effective solution to choose a hybrid energy storage system(HESS)composed of the ultracapacitor(UC)and LIB to jointly cope with the challenges of complex working conditions of EV.By making the UCs serve the peak or dynamic parts of the load power,the work load of LIB can be significantly reduced,to improve the health and extend the cycle life of the batteries.This is of great significance for the performance improvement and popularization of EVs.In order to make full use of the HESS,this thesis has carried out research on aspects of behavior modeling,configuration optimization and energy management,from both element level and system level.The results provide theoretical innovation and method support for the application and management of the HESS.The main contents and contributions of this thesis are as follows:(1)Aiming at the capacity degradation and health state evaluation for LIB,a short-term and long-term health state prediction method is proposed.In this method,a battery aging model considering the influence of cycle current is established,and a state observer based on particle filter is designed to track the parameters and evaluate the state of the model.The effectiveness of the method is verified by the experimental data.(2)Aiming at the modeling and power state evaluation for UC,a high-precision UC model and power state estimation method are constructed.By improving the equivalent circuit model based on the concept of variable main capacitor,the corresponding calculation of state of charge and power state is realized.The experimental results show that the model is accurate,robust and the method is effective.(3)Aiming at the configuration optimization for HESS,a hybrid configuration design method based on joint optimization is presented,which takes the whole life mileage and the normalized cost per 100 kilometers as the two objectives.The configuration parameters and power splitting parameters of are jointly optimized.A configuration design software and an experimental platform for HESS are provided.(4)Aiming at the energy management for HESS,a load adaptive real-time energy management strategy is designed.By establishing the three-segment power splitting rules,as well as analyzing the relationship between optimal power splitting parameters and load statistical characteristics,a load adaptive parameter adjustment mechanism is realized.