Research On Optimal Sizing And Energy Management Strategy Of Electric Vehicle Hybrid Energy Storage System

With the development of renewable energy vehicles,electric vehicles are favored by people for zero-emission.However,electric vehicles driven by lithium batteries are hard to respond to instantaneous high power requirements of charge and discharge changes,and lithium batteries have aging problems.Therefore,hybrid energy storage systems composed of high specific power supercapacitors and lithium batteries have attracted much attention.The sizing of the battery pack and supercapacitor pack in hybrid energy storage systems affects electric vehicles’ range and the operation cost,respectively.In the actual operation of electric vehicles,the energy management strategy needs to allocate power reasonably to cater to the dynamic changes of the load demands and reduce the operation cost.This dissertation researches the sizing and energy management problems of the hybrid energy storage system to minimize the operation cost of electric vehicles.Firstly,an optimal sizing method based on dynamic programming for hybrid energy storage systems is proposed to meet electric vehicles’ driving range and dynamic performance.Based on the analysis of sizing requirements,the battery pack and supercapacitor pack are modeled.Based on the modeling,the sizing of the battery pack is optimized for the driving range of electric vehicles.After determining the battery sizing,the optimization method of the supercapacitor sizing is designed.The quality constraint specifies the search range of the supercapacitor pack.A dynamic programming algorithm is adopted to optimize different supercapacitor pack combinations to minimize electricity and battery degradation costs.The optimal sizing schemes are designed according to operating conditions of vehicle type and operation costs.Compared with existing methods under different operating conditions,the proposed method has been verified its effectiveness.Secondly,a model predictive control energy management strategy based on reference optimization is proposed in this dissertation to give full play to the performance of hybrid energy storage systems in the actual operation of electric vehicles.Under the optimal sizing scheme of the hybrid energy storage system,the cloud calculates the future load power demand based on the speed information in the future period and the electric vehicle mass.The cloud adopts a dynamic programming algorithm to optimize the future load power with the goal of minimizing the operation cost to obtain an optimized voltage reference of the supercapacitor.The energy management controller based on model predictive control takes optimized voltage reference of the supercapacitor as input and the power loss as the optimization objective.The energy management controller optimizes the real-time power distribution of load power to reduce the operation cost of electric vehicles.Finally,the performance evaluation of the operation cost and the working state of the supercapacitor is carried out under different working conditions.The effectiveness of the proposed energy management strategy under the optimal sizing of the hybrid energy storage system is verified.