A computer-implemented battery temperature estimation method, comprising: fitting, when a battery is in an offline state, a first function relationship according to different test temperatures, real parts of corresponding admittances of the battery at the different test temperatures, and an Arrhenius formula; obtaining a temperature distribution model of the battery according to the shape and the size of the battery, wherein the temperature distribution model is used for describing the internal temperatures at different locations inside the battery as a function of a highest internal temperature of the battery, and a surface temperature of the battery; and determining a second function relationship, wherein the second function relationship is derived by substituting the temperature distribution model into the first relationship and integrating the first relationship over the different locations inside the battery, the second function relationship being used for estimating the internal temperature of the battery by using the surface temperature and the real part of the admittance of the battery; wherein the fitting of the first function relationship according to corresponding real parts of the admittances of the battery at different test temperatures comprises: determining a feature test frequency when the battery is in the offline state, wherein the feature test frequency is within a target frequency range, and in the target frequency range, impedance of the battery does not change with a state of charge of the battery; determining the corresponding real parts of the admittances of the battery at the different test temperatures according to the feature test frequency; and fitting the first function relationship according to the different test temperatures and the corresponding real parts of the admittances. fitting, when a battery is in an offline state, a first function relationship according to different test temperatures, real parts of corresponding admittances of the battery at the different test temperatures, and an Arrhenius formula; obtaining a temperature distribution model of the battery according to the shape and the size of the battery, wherein the temperature distribution model is used for describing the internal temperatures at different locations inside the battery as a function of a highest internal temperature of the battery, and a surface temperature of the battery; and determining a second function relationship, wherein the second function relationship is derived by substituting the temperature distribution model into the first relationship and integrating the first relationship over the different locations inside the battery, the second function relationship being used for estimating the internal temperature of the battery by using the surface temperature and the real part of the admittance of the battery; determining a feature test frequency when the battery is in the offline state, wherein the feature test frequency is within a target frequency range, and in the target frequency range, impedance of the battery does not change with a state of charge of the battery; determining the corresponding real parts of the admittances of the battery at the different test temperatures according to the feature test frequency; and fitting the first function relationship according to the different test temperatures and the corresponding real parts of the admittances.