The Point Probing Method For Measurement Of Thermal Conductivity And Estimation Of Thermal Conductivity Of Lithium-ion Batteries

With the emergence of the energy and environmental crisis,the automotive industry is gradually moving towards the development path ofelectrification.Lithium-ion batteries have become the first choice for the automotive industry on the road to electrification due to their high energy density,high power,and strong environmental adaptability.However,due to the close arrangement of batteries in electric vehicles,heat is easily accumulated inside the battery pack,causing frequent accidents.Therefore,thermal management of lithium-ion batteries is extremely important to ensure that the battery's performance and safety are optimal.As one of the important physical parameters to characterize the thermal conductivity of materials,thermal conductivity measures the ability of the material's heat transfer.Therefore,thermal conductivity is an indispensable research object in the thermal management analysis of lithium-ion batteries.Aiming at breaking the limitations of steady-state thermal conductivity measurement techniques,including a long measuring time,a complicated experimental setup,and the high requirement for sample preparation,a new method named point heating method for thermal conductivity measurement is proposed in this work.A corresponding 3D thermal transport model has been built to correlate the surface temperature rise with the incident heat flux,sample's thermal conductivity,and the location for temperature probing.A focused continuous wave laser beam is employed as a point heating source to shorten the time span for the sample reaching the thermally steady state,and further the control optical path is used to eliminate the influence of the fluctuation of the incident power on the measured results.The surface temperature rise is recorded by an infrared camera,based on which the thermal conductivity could be determined according the model.A variety of standard materials with known thermal conductivity and linear methods were used to verify the point heating method,and the method was used to measure the thermal conductivity of diatomite from 0.49 to 0.60 W?m^-1?K^-1 with an error of 6.06%.Analyzing the source of the error,it is found that the temperature rise of the heating surface in the thermal conductivity point heating measurement method is monitored by an infrared camera,and the temperature data obtained by the infrared temperature measurement will be affected by the ambient temperature and humidity.Therefore,based on the BP neural network model,this paper predicts the influence of ambient temperature and humidity on the system constant of the thermal conductivity point heating method and further validates the BP neural network model by comparing with the linear and non-linear fitting results Generalization and robustness.The system constant prediction model based on BP neural network has good accuracy,and the error is between±0.17.This model improves the speed and accuracy of the thermal conductivity point heating measurement method.In this thesis,the thermal conductivity of the lithium-ion battery measured by this methodis 10.4 W?m^-1?K^-1,and the overall model and detailed model of the battery are established.The thermal conductivity value of the lithium-ion battery is simulated by using the simulation software FLUENT.It is found that the overall model of the battery has a high accuracy,with an error of 8%compared with the experiment,and the number of grids is reduced by two orders of magnitude.The temperature rise in thermal steady state is7.256°C,which is slightly higher than the experimental temperature rise value of 5.0°C.Therefore,the simulation results of the two models are in good agreement with the experiments.The new method proposed in this paper is quick and non-contact,which can be applied to engineering field measurement.