Research On State Of Power Estimation Of Lithium Battery And Its Applications In Energy Management

Estimating battery state of power(SOP)precisely is essential to ensure the battery operational safety,prolong the battery service life span and maximize the battery performance.As one of the important decision variables of the energy management in electric vehicle,battery SOP is more related to the safety,economy and reliability of the whole vehicle.In this paper,the onboard battery SOP estimation and its application in energy management will be investigated.The detailed work mainly includes:(1)Four 18650-lithium battery cells under different aging degrees are employed to perform the capacity test and driving cycle test,which provides reliable data support for further SOP investigation;for the shortcomings of the traditional data pieces-based parameter identification method,a two-layer optimization parameter identification method is presented to provide accurate model parameters for SOP investigation,and particle swarm optimization(PSO)algorithm is employed to solve the problem,which is based on the Thevenin model to verify the effectiveness and superiority of the proposed method.(2)For the shortcomings of the traditional SOP estimation method,a SOP estimation method based on multi-order Taylor expansion formulas are proposed,and the SOP analytic formulas are derived based on Cardano theory,which enhances the estimation accuracy and weakens the approximation error caused by the first order Tayler expansion of the traditional method,especially for the longer prediction horizon.(3)Based on the idea of optimization,an improved genetic algorithm(GA)-based SOP estimation method is proposed to remedy the lack of consideration about the internal resistance changing and battery power characteristic,which eliminates the residual error of Taylor expansion and enhances the SOP estimation performance for long prediction horizon;an extreme case is given for SOP estimation,and the error composition of the estimated results is analyzed;at the same time,a comprehensive evaluation of several SOP estimation method is completed;based on the reliable estimation,the influence of battery aging on SOP estimation is explored.(4)Taking the series plug-in hybrid electric vehicle(PHEV)as an example,the topology matching and optimization of the battery pack considering SOP is performed;an energy management strategy considering SOP estimation is proposed,and the effectiveness of the application of SOP estimation method is verified;at the same time,the influence of battery aging on energy management are investigated,and the effects of battery aging on the pure electric driving mileage and operational cost are quantitatively analyzed;based on the optimal matching of the battery topology,the equivalent number of the missing cells caused by battery aging is investigated.